Oxytocin Dysfunction in Severe Mental Illnesses following Adverse Childhood Experiences: a systematic review

Oxytocin Dysfunction in Severe Mental Illnesses following Adverse Childhood Experiences: a systematic review | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Oxytocin Dysfunction in Severe Mental Illnesses following Adverse Childhood Experiences: a systematic review Guo Guo, Syeda Naqvi, Naresh Hanchate This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6628062/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Adverse childhood experiences (ACEs) are recognized as a transdiagnostic risk factor for developing severe mental illnesses (SMIs), including schizophrenia (SCZ), major depressive disorder (MDD), or bipolar disorder (BPD). However, the specific associations and underlying mechanisms linking ACEs and SMIs remain unclear. In recent years, oxytocin (OT), a neuropeptide known for its role in social bonding and stress regulation, has emerged as a crucial pathway linking SMIs and ACEs. This study aimed to investigate the relationship between SMIs among individuals with a history of childhood adversity and oxytocin dysregulation both at biochemical and genetic levels. We aimed to identify the mechanisms through which OT dysfunction may contribute to the onset, progression, and symptomatology of SMIs. A comprehensive search of PsycINFO, MEDLINE, Web of Science, and PubMed was undertaken to identify studies reporting the impact of ACEs with or without SMIs and measurements of OT or single nucleotide polymorphisms (SNPs) in the gene encoding oxytocin receptor ( OXTR ). Comparisons were made between SMI groups and healthy controls (HCs). We excluded non-English studies, animal research, and extreme trauma contexts. Data were extracted and appraised independently by two reviewers using the Mixed Methods Appraisal Tool (MMAT). Primary outcomes included group differences in ACE scores, a measure that reflects the type, quantity, and severity of childhood trauma. We also compared group differences in OT levels, genotype frequencies of OXTR SNPs, and pathways linking ACEs, OT dysregulation, and SMIs. This systematic review protocol was registered in PROSPERO: CRD42024555819. Of 513 reports identified by the search, 14 studies with 5,624 participants met the inclusion criteria. Most studies (n = 13; 92.86%) reported individuals with SMIs exhibited significantly higher ACE scores than HCs. Among the fourteen studies that measured OT levels, 66% (n = 6) reported lower OT levels in SMIs irrespective of the subgroups, including in SCZ and borderline personality disorder (BoPD). Several polymorphisms in OXTR were found to have a modulatory effect on SMI outcomes. A subset of SNPs conferred susceptibility, whereas others served as protective factors. This review highlights a strong association between ACEs, OT system dysregulation, and SMI susceptibility, particularly in SCZ and BoPD. However, methodological inconsistencies, gender biases, and reliance on peripheral OT measurements require further investigation. Future longitudinal studies are needed to clarify pathways and inform clinical interventions aimed at mitigating the impact of ACEs on mental health. Biological sciences/Neuroscience Biological sciences/Neuroscience/Stress and resilience Severe mental illness Adverse childhood experiences Oxytocin Oxytocin receptor gene variations Single nucleotide polymorphisms Figures Figure 1 Introduction Severe mental illnesses (SMIs) are psychiatric conditions that significantly affect an individual’s mental, behavioural, physical, and emotional well-being, leading to substantial impairments in daily functioning 1 , 2 . These include bipolar disorder (BPD), borderline personality disorder (BoPD), posttraumatic stress disorder (PTSD), major depressive disorders (MDD), anxiety disorders (AD), and schizophrenia (SCZ). Individuals with SMIs are at greater risk of poor physical health and experience premature mortality at a significantly higher rate, often 10–20 years earlier than the general population 3 . SMIs are complex conditions that can be caused and manifested by a combination of biological, psychological, and environmental factors 4 . Among numerous factors, adverse childhood experiences (ACEs) have been identified as a key environmental risk factor for SMIs 5 . ACEs refer to traumatic events occurring before the age of 18, which include abuse (physical, emotional, and sexual), neglect (physical and emotional), and various forms of household dysfunction 6 . These early-life adversities have been shown to disrupt neurobiological and psychological development, increasing vulnerability to SMIs later in life 7 . However, identifying the underlying causal mechanisms that mediate ACE-linked development of SMIs later in adulthood has been challenging. Emerging evidence suggests that disruptions in the neurobiological pathways regulating the oxytocin (OT) system may serve as a critical mechanism linking ACEs to the onset of SMIs. OT, often referred to as the “love hormone” or “bonding hormone”, is a neuropeptide produced in the brain and acts via the oxytocin receptor (encoded by OXTR ), expressed on target cells. The OT-OXTR signalling plays a crucial role in social bonding, attachment, stress regulation, reproduction, and emotional processing 8 . It is released into the bloodstream at the posterior pituitary to regulate neuroendocrine functions (parturition 9 and milk production 10 ), and OT is also released in the brain to regulate neurobiological pathways associated with social bonding and social behaviours 11 . Given its central role in governing social wellbeing, dysregulation of the OT has been associated with psychiatric disorders 12 . For instance, exposure to childhood adversity is inversely correlated with OT levels measured in plasma 13 and cerebrospinal fluid (CSF) 14 , 15 . These studies suggest that the OT pathway could be a potential link between ACEs and SMIs 16 . In addition to OT dysregulation, a growing body of evidence suggests that the oxytocin receptor gene ( OXTR) plays a role in regulating social behaviour 17 . Furthermore, variations in the OXTR have also been linked to the development of psychiatric disorders 18 . Genetic interactions across development are thought to collectively influence SMI outcomes. In addition to genetic predisposition or resilience associated with OXTR single nucleotide polymorphisms (SNPs), gene-environment (GxE) interactions arising from environmental stressors during adolescence, such as ACEs, also contribute to increased susceptibility 19 . Several SNPs across the OXTR gene and their associations in a variety of mental health disorders and their implications in specific socio-emotional regulation and behaviours have been previously reported 20 . Despite growing interest in the role of OT system in mental health, to our knowledge, no systematic review has comprehensively synthesized evidence on the interplay between ACEs, OT system and SMIs. This study aims to address this gap by investigating whether 1) individuals with SMIs exhibit greater ACE exposure, 2) ACE-linked SMIs exhibit dysregulated OT levels, and 3) OXTR variations exacerbate or protect ACE-linked development of specific SMIs compared to healthy controls (HCs). Additionally, it seeks to identify the potential mechanisms involving the OT system that underlie the association between ACEs and SMIs. Methods Overview The study aimed to systematically review the literature to identify reports investigating circulating levels of OT or OXTR polymorphisms in individuals exposed to adverse childhood experiences (ACEs) with or without a diagnosis of SMIs. This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and is registered with PROSPERO (CRD42024555819). Search strategy and selection criteria A comprehensive search strategy was developed to identify relevant studies published in peer-reviewed journals between 2004 and July 2024. Four electronic databases—PsycINFO, MEDLINE, Web of Science, and PubMed—were searched between February and July 2024. Search terms were constructed around three main concepts: ACE, OT (OT levels and OXTR variations), and SMIs (Supplementary Table 1). To ensure the inclusion of all relevant studies, reference lists of included articles were manually screened, and the searches were re-run in July 2024 before the final analysis. Studies were eligible for inclusion if they met the following specific criteria. First, they needed to include individuals with a history of ACEs, irrespective of a diagnosis of SMI. Eligible studies must have also measured OT levels or analyzed OXTR polymorphisms, with comparisons made between individuals exposed to ACEs and diagnosed with SMI and healthy controls (HCs with a history of ACEs, but no diagnosis of SMI. The primary outcomes of interest included differences in OT levels, OXTR variations, and potential pathways linking OT system dysregulation with ACEs and SMIs. There were no restrictions on study design due to the absence of randomized controlled trials addressing these variables. Therefore, cross-sectional and cohort studies were included. Studies were excluded if they did not include individuals exposed to ACEs or if a suitable control group without SMI was absent. Studies that failed to measure OT levels, analyze OXTR polymorphisms, or perform group comparisons based on ACE exposure were also excluded. Research with outcomes unrelated to ACEs, OT levels, or OXTR variations was deemed ineligible. Additionally, reviews, dissertations, grey literature, conference abstracts, preprints, commentaries, non-academic papers, and books or book chapters were excluded. Non-English studies, animal studies, and research focusing on extreme childhood trauma, such as wartime experiences, were also excluded. After removing duplicates, two independent reviewers (GG and SN) screened titles and abstracts for eligibility. Articles that passed this initial screening were then assessed for full-text eligibility. Any disagreements at either stage were resolved through discussion, or an additional reviewing author (NKH) was consulted if needed. Outcomes The primary outcome of this review was to examine the associations between ACEs, OT system dysregulation (including OT levels and OXTR polymorphisms), and susceptibility to SMIs. Specifically, the review investigated differences in OT levels and OXTR variations between individuals with SMIs and HCs. Additionally, this review explored potential pathways through which ACEs influence OT system dysregulation and mediate the risk of developing SMIs. Data extraction Data extraction was conducted systematically to ensure consistency and comprehensiveness. Extracted information included study characteristics such as the first author, year of publication, and country of origin. Data on the study population included sample size, mean age with standard deviation (M ± SD ), and gender ratio (% female). Information regarding the type of SMI diagnosis was also recorded. Exposure details, including the history of ACEs, OT levels, and OXTR polymorphisms, and sample types used for OT measurements (e.g., blood or serum) were extracted. The associations between ACEs, OT levels, OXTR variations, and potential mediating pathways were documented. Data extraction was performed independently by GG and reviewed by SN to ensure accuracy. Any discrepancies were resolved through discussion and, if necessary, through consultation with an additional reviewing author (NKH). Data analysis The extracted data were synthesized to compare OT levels, OXTR polymorphisms, and ACE exposures between individuals with SMIs and HCs. For continuous variables such as OT levels, t -tests were conducted to evaluate group differences. Categorical data, including genotypic frequencies of specific OXTR polymorphisms, were analysed using chi-squared tests. Effect sizes were reported alongside p -values to highlight the strength and statistical significance of the observed associations. Mediation analyses were conducted in studies exploring pathways linking ACEs and SMIs to test whether OT levels acted as mediators. Path coefficients, b -values, and confidence intervals were reported to demonstrate the significance and magnitude of these mediation effects. Subgroup analyses were performed based on the type of SMI diagnosis, including SCZ and BoPD, to explore variations in OT levels and OXTR polymorphisms. SNPs, such as rs2254298 and rs53576, were examined as potential risk or protective factors. The methodological quality of the included studies was evaluated using the Mixed Methods Appraisal Tool (MMAT) 21 . The tool assessed five domains related to study design, measurement validity, and confounding variables. Each domain was rated as “Yes,” “No,” or “Can’t tell,” with an overall percentage score calculated for each study. There is no strict cutoff in MMAT for defining poor-quality studies. However, for this review, studies that met only two or fewer criteria were deemed poor and were excluded from the final synthesis. Quality evaluations were performed independently by GG and reviewed by SN to ensure accuracy. Any discrepancies were resolved through discussion and, if necessary, consultation with the third reviewer (NKH). Results Literature searches and characteristics of included studies Our search identified 513 articles, of which 14 studies met the inclusion criteria and were included in this systematic review (Fig. 1 ). These studies collectively involved 5,624 participants aged 12 to 54 years and were conducted in seven countries across Asia, Europe, and North America. Most studies employed a cross-sectional design (n = 13; 92.86%), while one used a cohort design. Participants varied in gender representation, with five studies including males and females, eight focusing on females, and one on males only. The SMIs examined comprised SCZ (n = 3; 21%), BoPD (n = 7; 50%), AD (n = 2; 14%), and one each (7%) on depressive disorders (DEP), PTSD (Table 1 ). Although BPD is one of the most widely studied SMI, our search strategy did not yield any studies investigating the associations between OT and ACE-linked BPD. Table 1 Summary characteristics of included studies ID (Author, Year) Country SMI type Sample size Age (years) (M ± SD ) Gender ratio (% female) OT / OXTR specimen SMI HCs SMI HCs SMI HCs OT levels (n = 8) 1 (Chen et al., 2024) China SCZ 160 80 42.40 ± 9.40 43.45 ± 9.99 40% 42.50% Blood 2 (Mielke et al., 2023) Germany BoPD 131 124 24.21 ± 9.29 14.67 ± 1.53 100% 100% Blood 3 (Uzun et al., 2022) Turkey AD 56 28 14.27 ± 1.77 11.60 ± 5.78 57.14% 53.57% Blood 4 (Kartal et al., 2022) Turkey BoPD 31 31 23.06 ± 5.42 25.45 ± 3.74 100% 100% Blood 5 (Speck et al., 2019) Germany SCZ 35 35 40.40 ± 8.80 36.00 ± 10.40 34.29% 34.29% Blood 6 (Bomann et al., 2017) Denmark BoPD 18 20 29.70 ± 9.50 29.50 ± 9.20 100% 100% Serum 7 (Jobst et al., 2016) Germany BoPD 21 20 29.85 ± 7.46 30.42 ± 10.55 100% 100% Blood 8 (Bertsch et al., 2013) Germany BoPD 34 40 24.30 ± 5.60 24.60 ± 4.10 100% 100% Blood OXTR variations (n = 5) 9 (Lee et al., 2022) United States PTSD 135 93 30.80 ± 6.50 31.0 ± 5.60 100% 100% Saliva 10 (Zhang et al., 2020) China BoPD 342 423 33.86 ± 9.03 33.22 ± 8.81 0% 0% Blood 11 (Flasbeck et al., 2018) Germany BoPD 148 154 27.70 ± 7.90 24.6 ± 5.40 100% 100% Saliva 12 (Tollenaar et al., 2017) Netherlands DEP, AD 2180 387 23.06 ± 5.42 25.45 ± 3.74 100% 100% Blood 13 (Cristobal-Narvaez et al., 2017) Spain Early-psychosis 96 242 40.40 ± 8.80 36.00 ± 10.40 34.29% 34.29% Buccal and blood OT levels + OXTR variations (n = 1) 14 (Goh et al., 2024) China SCZ 382 178 43.87 ± 9.51 42.84 ± 10.07 42.41% 48.31% Blood Note*: SCZ = Schizophrenia, BoPD = Borderline personality disorder, AD = Anxiety disorders, PTSD = Posttraumatic stress disorder, DEP = Depressive disorder/ Depression Fourteen studies reviewed were appraised using the MMAT 21 , and the qualities were rated from 3–5 out of 5 points; 4 studies scored 5, 7 scored 4, and 3 studies scored 3, demonstrating fair-to-good quality (Table 2 ). Across the 14 studies, ACEs were predominantly measured using the Childhood Trauma Questionnaire (CTQ) and its short form (CTQ-SF). Other tools, such as the Childhood Experiences of Care and Abuse Questionnaire (CECA-Q) and the Life Stressor Checklist (LSC), were also used. These instruments effectively captured aggregate ACE scores. However, most studies did not explore the impact of specific ACE types, such as emotional or physical abuse, on SMI risk. This lack of granularity limits deeper insights into the nuanced relationships between individual ACEs and different SMIs. Table 2 Quality assessment of the included studies using the MMAT checklist (3. Quantitative non-randomized studies) ID Study designs (Author, year) S1. S2. 1. 2. 3. 4. 5. Level of evidence OT levels (n = 8) 1 Cross-sectional (Chen et al., 2024) Yes Yes Yes Yes Can’t tell Yes Yes 4 (80%) 2 Cross-sectional (Mielke et al., 2023) Yes Yes Yes Yes Yes No Yes 4 (80%) 3 Cross-sectional (Uzun et al., 2022) Yes Yes Yes Yes No No Yes 3 (60%) 4 Cross-sectional (Kartal et al., 2022) Yes Yes Yes Yes No No Yes 3 (60%) 5 Cross-sectional (Speck et al., 2019) Yes Yes Yes Yes No Yes Yes 4 (80%) 6 Cross-sectional (Bomann et al., 2017) Yes Yes Yes Yes No Yes Yes 4 (80%) 7 Cross-sectional (Jobst et al., 2016) Yes Yes Yes Yes Yes Yes Yes 5 (100%) 8 Cross-sectional (Bertsch et al., 2013) Yes Yes Yes Yes No Yes Yes 4 (80%) OXTR variations (n = 5) 9 Cross-sectional (Lee et al., 2022) Yes Yes Yes Yes No Yes Yes 4 (80%) 10 Cross-sectional (Zhang et al., 2020) Yes Yes Yes Yes Yes Yes Yes 5 (100%) 11 Cross-sectional (Flasbeck et al., 2018) Yes Yes Yes Yes No No Yes 3 (60%) 12 Cohort (Tollenaar et al., 2017) Yes Yes Yes Yes Yes Yes Yes 5 (100%) 13 Cross-sectional (Cristobal-Narvaez et al., 2017) Yes Yes Yes Yes Yes No Yes 4 (80%) OT levels + OXTR variations (n = 1) 14 Cross-sectional (Goh et al., 2024) Yes Yes Yes Yes Yes Yes Yes 5 (100%) Note* S1. Are there clear research questions? S2. Do the collected data allow to address the research questions? 1. Are the participants representative of the target population? 2. Are measurements appropriate regarding both the outcome and intervention (or exposure)? 3. Are there complete outcome data? 4. Are the confounders accounted for in the design and analysis? 5. During the study period, is the intervention administered (or exposure occurred) as intended? Association between ACEs and increased risk of SMIs Most studies (n = 13; 92.86%) reported that individuals with SMIs had significantly higher ACE scores than HCs (Table 3 ), consistent with the widely acknowledged associations between childhood adversity and SMI susceptibility. Only one study, conducted by Uzun et al. (2022), found no significant difference between the SMI group and HCs ( t = 1.32, p = 0.19). However, this may be attributed to the use of younger participants. (average of 14.27 years compared to an average of 31.49 years in the other 13 studies). It is possible that adolescence represents a critical period for OT system maturation, and the immediate effects of ACEs may differ compared to adult populations. ACE-linked SMIs predominantly include female participants, with an average of 72.01% female and 27.99% male representation. The gender imbalance observed in ACE-linked SMI research may stem from higher exposure of females to multiple ACEs, more complex patterns of ACEs 22 , and increased susceptibility to psychiatric symptoms following ACEs 23 . These factors likely contribute to the predominance of female participants in such studies. Future studies should aim for a more balanced gender distribution to clarify whether gender plays a moderating role in the relationship between ACEs and SMIs. Table 3 The association between ACE and SMI ACE total scores (M ± SD ) Results of difference tests ID (Author, Year) ACE measurement SMI HCs M SD M SD t p OT levels (n = 8) 1 (Chen et al., 2024) CTQ-SF, structured interviews 60.59 14.18 38.00 4.32 13.92 *** < 0.001 2 (Mielke et al., 2023) CTQ, CECA. Q 0.65 0.97 − 0.68 0.58 13.38 *** < 0.001 3 (Uzun et al., 2022) CTQ 61.48 16.21 56.85 14.69 1.32 0.19 4 (Kartal et al., 2022) CTQ-SF 55.29 17.07 7.60 4.03 6.51 *** < 0.001 5 (Speck et al., 2019) CTQ-SF 9.20 4.11 7.14 3.07 2.38 * 0.02 6 (Bomann et al., 2017) CTQ 12.60 2.70 6.00 1.30 9.43 *** < 0.001 7 (Jobst et al., 2016) CTQ 15.00 4.86 6.76 2.35 6.76 *** < 0.001 8 (Bertsch et al., 2013) CTQ 57.30 17.30 32.20 12.70 6.95 *** < 0.001 OXTR variations (n = 5) 9 (Lee et al., 2022) LSC 50.00 53.80 28.00 20.70 26.68 *** < 0.001 10 (Zhang et al., 2020) CTQ-SF 51.79 17.53 42.92 15.55 7.32 *** < 0.001 11 (Flasbeck et al., 2018) CTQ-SF 63.70 19.50 33.90 10.80 14.36 *** < 0.001 12 (Tollenaar et al., 2017) CTQ-SF, semi-structured CT interview 42.27 14.32 33.40 9.70 15.29 *** < 0.001 13 (Cristobal-Narvaez et al., 2017) CTQ 41.38 12.91 33.46 8.24 6.48 *** < 0.001 OT levels + OXTR variations (n = 1) 14 (Goh et al., 2024) CTQ-SF 64.75 24.40 44.63 13.42 12.55 *** < 0.001 Note: * p < 0.05, ** p < 0.01, *** p < 0.001. Oxytocin dysfunction in individuals with SMIs We next examined the studies that measured and compared OT levels between individuals with SMIs and HCs. 64% (n = 9) of studies compared OT concentrations between SMI groups and HCs. Among these, 77% (n = 7) of studies reported dysregulated OT levels in ACE-linked SMI patients compared to HCs, of which 66.6% (n = 6) and 11.1% (n = 1) studies found lower or higher OT levels, respectively (Table 4). Two studies that reported no differences between the groups. Importantly, lower OT levels were found in patients with different SMIs. For instance, out of the six studies that showed lower OT levels, 3 (50%) were with SCZ and BoPD participants (Table 4), suggesting ACE-linked downregulation of OT could be a common mechanism leading to SMI pathophysiology. The singular study that reported elevated OT levels was in patients with AD, but this may be due to differences in the younger age group in this study. Overall, these studies suggest OT dysregulation is common across many SMIs. Several studies also investigated the relationship between the impact of ACEs on OT levels in male and female SMI patients. Of the six studies that reported lower OT levels in SMI patients, three focused on female patients with BoPD, and the three others had a mix of both male and female patients, suggesting ACEs can impact both boys and girls during adolescence, increasing their susceptibility to SMIs. Association of OXTR polymorphisms with SMIs Next, we explored the role of OXTR polymorphisms and their association with SMI pathologies. Six of fourteen studies (42%) reported eight single nucleotide polymorphisms (SNPs) in OXTR and their associations with ACE-linked SMIs (Table 5 ). The gene encoding OXTR, a G-protein-coupled receptor spanning about 25 kilobases with four exons and three introns, is located on chromosome 3 in humans at the cytogenetic band 3p25.3 20 . The findings indicate that specific genotypes at these eight loci conferred either risk or protection against SMIs (shown in red or green, respectively; Table 5 ). For instance, the GG genotype of two OXTR SNPs (rs237885 and rs53576) appears to increase susceptibility to SMIs, whereas the TT or AA genotype of these variants served as protective factor, respectively. Similarly, different genotypes at other loci served as either a risk or protective factors, suggesting these variants could play a crucial role and impact the expression levels of OXTR in specific brain areas, or binding affinity to OXT or downstream signalling pathways. Table 4. Comparison of OT levels between SMI group and HCs OT levels (ng/mL) (M ± SD ) Results of difference tests ID (Author, Year) SMI HCs M SD M SD t p 1 (Goh et al., 2024) 11.60 3.58 13.48 3.90 - 5.45 *** < 0.001 2 (Chen et al., 2024) 14.34 3.07 17.26 4.49 -5.54 *** < 0.001 3 (Mielke et al., 2023) 201.94 148.05 255.26 143.12 - 2.92 ** < 0.01 4 (Uzun et al., 2022) 213.71 72.45 166.2 52.70 3.42 *** < 0.001 5 (Kartal et al., 2022) 797.38 22.72 835.00 21.98 - 6.63 *** < 0.001 6 (Speck et al., 2019) 4.59 3.35 5.48 4.50 - 22.02 *** < 0.001 7 (Bomann et al., 2017) 499.00 224.00 411.00 187.00 1.31 0.19 8 (Jobst et al., 2016) 421.67 390.97 399.19 403.58 127.70 130.70 142.60 128.54 450.26 471.46 468.19 454.22 204.42 240.63 252.68 233.85 -0.54 -1.34 -1.08 -0.86 0.59 0.29 0.39 9 (Bertsch et al., 2013) 13.90 15.10 30.70 19.80 - 3.93 *** < 0.001 Note: * p < 0.05, ** p < 0.01, *** p < 0.001. Table 5. Comparison of OXTR variations between SMI group and HCs ID (Author, year) SMI SNP Risk alleles Genotype Genotypic frequencies (n (%)) Group differences in genotype frequencies SMI HCs c 2 p 1 (Goh et al., 2024) SCZ rs1042778 G/T GG GT TT 220 (57.6) 128 (33.5) 34 (8.9) 123 (69.1) 50 (28.1) 5 (2.8) 10.217 ** 0.006 rs2254298 G/A GG GA AA 130 (34.0) 168 (44.0) 84 (22.0) 76 (42.7) 84 (47.2) 18 (10.1) 12.161 ** 0.002 rs237885 G/T GG GT TT 30 (7.9) 155 (40.6) 197 (51.6) 6 (3.4) 56 (31.5) 116 (65.2) 10.490 ** 0.005 rs237887 G/A GG GA AA 127 (33.2) 186 (48.7) 69 (18.1) 89 (50.0) 71 (39.9) 18 (10.1) 15.827 *** < 0.001 rs237895 C/T CC CT TT 33 (8.6) 160 (41.9) 189 (49.5) 13 (7.3) 49 (27.5) 116 (65.2) 12.459 ** 0.002 rs237899 G/A GG GA AA 187 (49.0) 151 (39.5) 44 (11.5) 111 (62.4) 56 (31.5) 11 (6.2) 9.763 ** 0.008 rs53576 G/A GG GA AA 67 (17.5) 155 (40.6) 160 (41.9) 13 (7.3) 75 (42.1) 90 (50.6) 11.025 ** 0.004 2 (Zhang et al., 2020) BoPD rs53576 G/A GG GA AA 125 (38.0) 20 (6.1) 184 (55.9) 177 (43.2) 38 (9.3) 195 (47.6) 6.054 * 0.048 rs237897 G/A GG GA AA 121 (37.6) 14 (4.3) 187 (58.1) 165 (40.8) 34 (8.4) 205 (50.7) 6.754 * 0.034 3 (Tollenaar et al., 2017) DEP, AD rs2254298 G/A GG GA AA 1912 (87.7) 259 (11.9) 9 (0.4) 352 (91.0) 31 (8.0) 4 (1.0) 7.252* 0.027 Note: * p < 0.05, ** p < 0.01, *** p < 0.001. Genotypes that serve as a risk factor are present in red, while genotypes that serve as a protective factor are present in green. These analyses also indicate that specific SNPs in the OXTR are associated with susceptibility to various SMIs. For instance, two studies (Goh et al. (2024) and Tollenaar et al. (2017)) investigated the same SNP, rs2254298. Goh et al. (2024) found that the AA genotype was significantly more prevalent in the SCZ group (22.0%) compared to HCs (10.1%) ( χ² = 12.161, p = 0.002) and Tollenaar et al. (2017) discovered that the GA genotype of rs2254298 was more frequent in the DEP + AD group (11.9%) compared to HCs (8.0%) ( χ² = 7.252, p = 0.027). Similarly, the OXTR SNP rs53576 was also reported in two studies. Goh et al. (2024) found that the GG genotype frequency was higher in the SCZ group (17.5%) compared to HCs (7.3%) ( χ² = 11.025, p = 0.004). Zhang et al. (2020) reported that the AA genotype was significantly more common in the BoPD group (55.9%) compared to HCs (47.6%) ( χ² = 6.054, p = 0.048). We next focused on three studies that examined G×E interactions, demonstrating that OXTR variations moderate the relationship between ACEs and SMIs. Of these, one study highlighted that high additive genetic risk scores (AGRS), calculated across multiple SNPs, amplified the impact of ACEs on schizophrenia symptoms ( β = 0.226, SE = 0.031, 95% CI = [0.169, 0.290], p < 0.001) Goh et al. (2024). Similarly, other studies identified significant ACE × OXTR interactions predicting psychotic symptoms ( p < 0.001) Cristobal-Narvaez et al. (2017), and individuals carrying the A allele of rs53576 (AA or GA genotypes) demonstrated heightened empathy for psychological pain when exposed to ACEs, whereas GG carriers were less affected ( p = 0.037) 24 . Discussion The present systematic review revealed associations between ACEs, OT system dysregulation, and susceptibility to SMIs. ACEs are critical environmental factors predisposing individuals to several neuropsychiatric conditions and SMIs. Consistent with this notion, our findings revealed that individuals with SMIs had a significantly higher prevalence of ACEs than healthy controls (HCs). Additionally, reduced OT levels were observed in approximately 65% of studies in different SMIs, indicating that dysregulation of the oxytocinergic system may play a role in the pathophysiology of SMIs. Finally, subsets of oxytocin receptor ( OXTR ) polymorphisms conferred resilience or susceptibility to SMIs, indicating that gene-environment interactions play a crucial role in the development of SMIs. ACEs are now widely acknowledged and well-established leading causes of adult morbidity and mortality 25 . ACEs have been associated with higher prevalence rates of both mental illnesses, including depression 26 , anxiety 27 , and PTSD 28 , and physical illnesses, such as higher risk of cardiovascular disorders 26 , 29 , diabetes 29 , and weakened immune function 30 . Consistent with a large body of evidence, our study identified strong associations between ACE exposure and the prevalence of SMIs. Importantly, these associations were observed across all the SMI types reported in our study, including SCZ, BoPD, AD, PTSD, DEP, and early psychosis. This indicates that ACEs have a profound impact on adult mental health and serve as a common underlying factor that increases susceptibility to various SMIs. However, the specific SMI outcomes vary among individuals depending on the ACE type, duration, severity, genetic predispositions, and environmental influences. One key mechanism underlying these variations is the prolonged activation of stress response systems following ACE exposure. Chronic stress can lead to heightened cortisol levels, which negatively impact brain development and neurobiological pathways involved in social bonding and social behaviours 31 . In recent decades, the oxytocinergic system has emerged as a crucial neurobiological pathway for its role in social behaviours and social bonding 11 . Several studies have shown its dysregulation is associated with several neuropsychiatric conditions (e.g., depression 32 ) and neurodevelopmental disorders, such as autism spectrum disorder 33 . Our systematic review revealed that most studies reported reduced oxytocin levels in SMI patients compared to healthy controls. Intriguingly, multiple studies in our review reported reduced OT levels were different SMI types (SCZ and BoPD), suggesting OT dysfunction is a possible mediator of SMIs. These studies also suggest OT downregulation could result ACE-induced brain circuit dysfunction regulating emotional and social behaviours that modulate oxytocin neurons and OT in the brain and the periphery. These findings are consistent with previous research highlighting the role of OT in emotional regulation, social behaviour, and stress response 34 . For instance, prior studies have demonstrated that lower OT levels are linked to impaired social cognition in SCZ 35 and increased interpersonal dysfunction in BoPD 36 . While ACE is a common underlying factor of SMIs in these studies, the genetic makeup of these patients is unknown whether these patients harbor variants or mutations in genes associated with social behaviours or brain circuit function. This information could have provided deeper insights into the susceptibility of individuals to ACEs and their outcomes in different SMIs. Instead, we focused on data available on the variants associated with the oxytocinergic system. In particular, identifying OXTR variations as mediators of susceptibility to SMIs adds to the growing body of evidence on gene-environment (G×E) interactions. However, our findings also underscore the complexity of these relationships, as the protective effects of the GG genotype appear to vary depending on the type of ACE, timing, and chronicity. This aligns with prior studies, which reported increased sensitivity to negative parenting among GG carriers, further complicating the role of OXTR polymorphisms 37 . Despite the significant associations identified, several limitations must be acknowledged. First, the reliance on retrospective self-report tools, such as the Childhood Trauma Questionnaire (CTQ), introduces the risk of recall bias and underreporting of ACEs. While some studies incorporated structured interviews, the lack of multi-method assessments limits the accuracy and reliability of ACE measurements. Second, most studies measured peripheral OT levels using plasma, which may not accurately reflect central OT concentrations due to their unstable nature 38 . A recent systematic review of the literature suggests a positive correlation between central and peripheral levels of OT during stressful conditions or intranasal OT delivery but not in baseline conditions 38 . Furthermore, variability in OT specimen types and processing methods (e.g., plasma vs serum) will likely contribute to discrepancies in the reported OT levels. Our systematic review is composed mostly of cross-sectional designs, which contain data obtained at a single time point and thus often hinder causal inferences (cause-and-effect relationships) between ACEs, OT system dysregulation, and SMIs. Longitudinal studies are necessary to establish temporal relationships and assess how OT levels or OXTR variations evolve over time in response to ACEs. Additionally, the overrepresentation of female participants in studies of BPD introduces gender bias, reducing the generalizability of findings to other populations. The small sample sizes in many studies further limit statistical power, particularly in analyses of OXTR polymorphisms. Publication bias may have influenced the findings, as studies with null results are less likely to be published. Additionally, the relationship between ACEs and OT dysregulation in other major SMIs, such as bipolar disorder, remains understudied. The inconsistencies observed in this review reflect the challenges inherent in studying the OT system. For instance, Uzun et al. (2022) reported higher OT levels in adolescents with AD compared to HCs, which contrasts with the trends observed in adult populations 39 . This discrepancy may reflect developmental differences in OT system maturation, highlighting the need for age-specific investigations. Future research should also prioritize longitudinal studies to explore the temporal dynamics of OT dysregulation following ACEs and its role in SMI susceptibility. Improved methodologies, including culturally sensitive, multi-method assessments of ACEs and standardized OT measurement protocols, are essential for enhancing the reliability of findings. It would also be interesting to examine if the OT system is dysregulated in SMI patients who experienced certain extreme ACEs excluded in our current studies. Further exploration of OXTR polymorphisms is needed to clarify their role as risk or protective factors, particularly about specific ACE subtypes. Large-scale studies with diverse and representative populations will be critical for addressing gender biases and improving the generalizability of results. From a clinical and policy perspective, this review highlights the importance of early identification and prevention of childhood adversity to reduce the risk of SMIs. Strategies aimed at promoting safe, stable, and nurturing environments for children, as recommended by the Centers for Disease Control and Prevention (CDC) 40 , should be prioritized in public health initiatives. Moreover, OT-related biomarkers, such as peripheral OT levels and OXTR genotypes, hold promise as tools for identifying individuals at heightened risk of SMIs, potentially informing targeted interventions. While therapies such as intranasal OT administration have shown promise in reducing stress-related symptoms 35 , careful consideration of context-dependent effects and potential risks is essential to ensure safety and efficacy. In conclusion, this review highlights the interplay between ACEs, OT system dysregulation, and susceptibility to SMIs, shedding light on the biological mechanisms underlying ACE's long-term impact on mental health. However, the inconsistencies in the data emphasize the need for rigorous, standardized research to better understand these complex relationships. By addressing methodological limitations and focusing on specific pathways, such as OXTR polymorphisms, future studies can provide more precise insights into the role of genetic, biological, and environmental factors in SMI development. These findings underscore the clinical significance of early intervention and the potential for OT-related biomarkers to inform prevention and treatment strategies, ultimately improving mental health outcomes. Declarations Author Contribution G.G. and N.K.H. conceptualized and designed study; G.G., S.C.F.N., and N.K.H. performed searches, data acquisition, analysis, and interpretation; G.G. and N.K.H. drafted and wrote the manuscript. All authors read and critically revised the manuscript, and approved the final manuscript. ACKNOWLEDGEMENTS We would like to thank the members of the Hanchate lab for their critical reading of the manuscript and for providing feedback. N.K.H is supported by a UCL Excellence Fellowship (funded by the Great Ormond Street Hospital Children’s Charity (VS0321), the Stoneygate Trust, and the Rosetrees Trust (UCL2021/1)) and a New Investigator Research Grant funded by UKRI MRC (MR/X003957/1). The funders had no role in study design, data collection, data analysis, data interpretation, or writing of the report. References NIMH NIoMH. Mental Illness. (2023). https://www.nimh.nih.gov/health/statistics/mental-illness#part_2555 WHO. Management of physical health conditions in adults with severe mental disorders (World Health Organisation Geneva, 2018). Dickerson, F. et al. Natural cause mortality in persons with serious mental illness. Acta Psychiatry. Scand. 137 (5), 371–379 (2018). De Hert, M. et al. Physical illness in patients with severe mental disorders. I. Prevalence, impact of medications and disparities in health care. World Psychiatry . 10 (1), 52–77 (2011). Solmi, M. et al. Age at onset of mental disorders worldwide: large-scale meta-analysis of 192 epidemiological studies. Mol. Psychiatry . 27 (1), 281–295 (2022). Felitti, V. J. et al. Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults. The Adverse Childhood Experiences (ACE) Study. Am. J. Prev. Med. 14 (4), 245–258 (1998). Struck, N. et al. Childhood maltreatment and adult mental disorders–the prevalence of different types of maltreatment and associations with age of onset and severity of symptoms. Psychiatry Res. 293 , 113398 (2020). Florea, T. et al. Oxytocin: Narrative Expert Review of Current Perspectives on the Relationship with Other Neurotransmitters and the Impact on the Main Psychiatric Disorders. Med. (Lithuania) ; 58 (7). (2022). Walter, M. H., Abele, H. & Plappert, C. F. The Role of Oxytocin and the Effect of Stress During Childbirth: Neurobiological Basics and Implications for Mother and Child. Front. Endocrinol. (Lausanne) . 12 , 742236 (2021). UvnäsMoberg, K. et al. Maternal plasma levels of oxytocin during breastfeeding—A systematic review. PloS one . 15 (8), e0235806 (2020). Olff, M. et al. The role of oxytocin in social bonding, stress regulation and mental health: an update on the moderating effects of context and interindividual differences. Psychoneuroendocrinology 38 (9), 1883–1894 (2013). McLaughlin, K. A., Sheridan, M. A. & Lambert, H. K. Childhood adversity and neural development: deprivation and threat as distinct dimensions of early experience. Neurosci. Biobehav Rev. 47 , 578–591 (2014). Opacka-Juffry, J. & Mohiyeddini, C. Experience of stress in childhood negatively correlates with plasma oxytocin concentration in adult men. STRESS-THE Int. J. BIOLOGY STRESS . 15 (1), 1–10 (2012). Ellis, B. J., Horn, A. J., Carter, C. S., van Ijzendoorn, M. H. & Bakermans-Kranenburg, M. J. Developmental programming of oxytocin through variation in early-life stress: Four meta-analyses and a theoretical reinterpretation. Clin. Psychol. Rev. ; 86. (2021). Heim, C. et al. Lower CSF oxytocin concentrations in women with a history of childhood abuse. Mol. Psychiatry . 14 (10), 954–958 (2009). Belsky, J. & Pluess, M. Beyond diathesis stress: differential susceptibility to environmental influences. Psychol. Bull. 135 (6), 885–908 (2009). Kumsta, R., Hummel, E., Chen, F. S. & Heinrichs, M. Epigenetic regulation of the oxytocin receptor gene: implications for behavioral neuroscience. Front. NeuroSci. ; 7 . (2013). Gimpl, G. & Fahrenholz, F. The oxytocin receptor system: structure, function, and regulation. Physiol. Rev. 81 (2), 629–683 (2001). Uher, R. & Zwicker, A. Etiology in psychiatry: embracing the reality of poly-gene-environmental causation of mental illness. World Psychiatry . 16 (2), 121–129 (2017). Kohlhoff, J., Cibralic, S., Hawes, D. J. & Eapen, V. Oxytocin receptor gene (OXTR) polymorphisms and social, emotional and behavioral functioning in children and adolescents: A systematic narrative review. Neurosci. Biobehav. Rev. ; 135. (2022). Hong, Q. N. et al. The Mixed Methods Appraisal Tool (MMAT) version 2018 for information professionals and researchers. Educ. Inform. 34 (4), 285–291 (2018). Haahr-Pedersen, I. et al. Females have more complex patterns of childhood adversity: implications for mental, social, and emotional outcomes in adulthood. Eur. J. Psychotraumatol . 11 (1), 1708618 (2020). Prachason, T. et al. Gender differences in the associations between childhood adversity and psychopathology in the general population. Soc. Psychiatry Psychiatr Epidemiol. 59 (5), 847–858 (2024). Flasbeck, V., Moser, D., Kumsta, R. & Brune, M. The OXTR single-nucleotide polymorphism rs53576 moderates the impact of childhood maltreatment on empathy for social pain in female participants: Evidence for differential susceptibility. Front. Psychiatry ; 9. (2018). Senaratne, D. N. S. et al. The impact of adverse childhood experiences on multimorbidity: a systematic review and meta-analysis. BMC Med. 22 (1), 315 (2024). Merrick, M. T. Vital signs: estimated proportion of adult health problems attributable to adverse childhood experiences and implications for prevention—25 states, 2015–2017. MMWR Morbidity Mortal. Wkly. Rep. ; 68. (2019). Kessler, R. C. et al. Childhood adversities and adult psychopathology in the WHO World Mental Health Surveys. Br. J. Psychiatry . 197 (5), 378–385 (2010). McLaughlin, K. A. et al. Childhood adversities and post-traumatic stress disorder: evidence for stress sensitisation in the World Mental Health Surveys. Br. J. Psychiatry . 211 (5), 280–288 (2017). Hughes, K. et al. The effect of multiple adverse childhood experiences on health: a systematic review and meta-analysis. Lancet Public. Health . 2 (8), e356–e66 (2017). Jonker, I., Rosmalen, J. G. M. & Schoevers, R. A. Childhood life events, immune activation and the development of mood and anxiety disorders: the TRAILS study. Translational Psychiatry . 7 (5), e1112–e (2017). McLaughlin, K. A., Sheridan, M. A. & Nelson, C. Adverse childhood experiences and brain development: Neurobiological mechanisms linking the social environment to psychiatric disorders. life course approach mental disorders ; 249. (2013). Myers, A. J. et al. Variation in the oxytocin receptor gene is associated with increased risk for anxiety, stress and depression in individuals with a history of exposure to early life stress. J. Psychiatr Res. 59 , 93–100 (2014). John, S. & Jaeggi, A. V. Oxytocin levels tend to be lower in autistic children: A meta-analysis of 31 studies. Autism 25 (8), 2152–2161 (2021). Pierzynowska, K. et al. Roles of the Oxytocin Receptor (OXTR) in Human Diseases. Int. J. Mol. Sci. ; 24 (4). (2023). Londono Tobon, A., Newport, D. J. & Nemeroff, C. B. The Role of Oxytocin in Early Life Adversity and Later Psychopathology: a Review of Preclinical and Clinical Studies. Curr. Treat. Options Psychiatry . 5 (4), 401–415 (2018). Jawad, M. Y., Ahmad, B. & Hashmi, A. M. Role of Oxytocin in the Pathogenesis and Modulation of Borderline Personality Disorder: A Review. CUREUS J. Med. Sci. ; 13 (2). (2021). McQuaid, R. J., McInnis, O. A., Stead, J. D., Matheson, K. & Anisman, H. A paradoxical association of an oxytocin receptor gene polymorphism: early-life adversity and vulnerability to depression. Front. NeuroSci. 7 , 128 (2013). Valstad, M. et al. The correlation between central and peripheral oxytocin concentrations: A systematic review and meta-analysis. Neurosci. Biobehavioral Reviews . 78 , 117–124 (2017). Uzun, N., Akca, O. F., Kilinc, I. & Balci, T. Oxytocin and vasopressin levels and related factors in adolescents with social phobia and other anxiety disorders. Clin. Psychopharmacol. Neurosci. 20 (2), 330–342 (2022). CDC & CfDCaP Adverse Childhood Experiences Prevention Strategy. Atlanta, GA: National Center for Injury Prevention and Control . Centers Disease Control Prev. , (2021). Chen, Y-J. et al. Linking childhood trauma to the psychopathology of schizophrenia: the role of oxytocin. Schizophrenia (Heidelberg Germany) . 10 (1), 24 (2024). Mielke, E. L. et al. Adverse childhood experiences mediate the negative association between borderline personality disorder symptoms and plasma oxytocin. Prog Neuropsychopharmacol. Biol. Psychiatry . 125 , 110749 (2023). Kartal, F., Uğur, K., Mete, B., Demirkol, M. E. & Tamam, L. The Relationship Between the Oxytocin Level and Rejection Sensitivity, Childhood Traumas, and Attachment Styles in Borderline Personality Disorder. Psychiatry Investig . 19 (3), 239–246 (2022). Speck, L. G. et al. Endogenous oxytocin response to film scenes of attachment and loss is pronounced in schizophrenia. Soc. Cognit. Affect. Neurosci. 14 (1), 109–117 (2019). Bomann, A. C. et al. The neurobiology of social deficits in female patients with borderline personality disorder: The importance of oxytocin. Personality mental health . 11 (2), 91–100 (2017). Jobst, A. et al. Lower Oxytocin Plasma Levels in Borderline Patients with Unresolved Attachment Representations. Front. Hum. Neurosci. ; 10. (2016). Bertsch, K., Schmidinger, I., Neumann, I. D. & Herpertz, S. C. Reduced plasma oxytocin levels in female patients with borderline personality disorder. Horm. Behav. 63 (3), 424–429 (2013). Lee, H., King, A. P., Li, Y. & Seng, J. S. Oxytocin receptor gene, post-traumatic stress disorder and dissociation in a community sample of European American women. BJPsych Open. ; 8. (2022). Zhang, M., Liu, N., Chen, H. & Zhang, N. Oxytocin receptor gene, childhood maltreatment and borderline personality disorder features among male inmates in China. BMC Psychiatry ; 20. (2020). Tollenaar, M. S., Molendijk, M. L., Penninx, B. W. J. H., Milaneschi, Y. & Antypa, N. The association of childhood maltreatment with depression and anxiety is not moderated by the oxytocin receptor gene. Eur. Arch. Psychiatry Clin. NeuroSci. 267 (6), 517–526 (2017). Cristobal-Narvaez, P. et al. The role of stress-regulation genes in moderating the association of stress and daily-life psychotic experiences. Acta Psychiatry. Scand. 136 (4), 389–399 (2017). Goh, K. K., Kanahara, N., Chiu, Y-H. & Lu, M-L. The impact of childhood trauma exposure on social functioning in schizophrenia: the moderated mediation role of oxytocin and oxytocin receptor gene polymorphisms. Psychol. Med. 54 (5), 980–992 (2024). Additional Declarations No competing interests reported. Supplementary Files Supplementaryinformation.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6628062","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":454284840,"identity":"8bfc5bdc-b742-4648-88c5-fc654b563e5d","order_by":0,"name":"Guo Guo","email":"","orcid":"","institution":"University College London","correspondingAuthor":false,"prefix":"","firstName":"Guo","middleName":"","lastName":"Guo","suffix":""},{"id":454284841,"identity":"4ec1f508-f9d9-4b52-84ed-59a99bf04a96","order_by":1,"name":"Syeda Naqvi","email":"","orcid":"","institution":"University College London","correspondingAuthor":false,"prefix":"","firstName":"Syeda","middleName":"","lastName":"Naqvi","suffix":""},{"id":454284842,"identity":"3f673eac-ef3b-4095-a030-208eacfde1ac","order_by":2,"name":"Naresh Hanchate","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2UlEQVRIiWNgGAWjYFACHhBxAIiZgUQBWIiZOC08DGwJDAwGpGnhMSBOizkD78HPBTV35O3Ze75J/DBgkOdv4DE2wKfFsoEvWXrGsWeGPTxnt0n2GDAYzjjAY5yAT4vBAR4Dad6Gw4w9ErnbpIEOY9zAwGN8gIAW499ALfY98m+egbTYE6PFDGRLYo8EDxtISyJIC36HHeYxs+Y5dji550yasWWPgUTyjMNsxXi9b3C8x/g2T81h2/b2ww9v/Kiwse1vb94sgU8LehxIEI7IUTAKRsEoGAWEAQAAnT7kKXYciAAAAABJRU5ErkJggg==","orcid":"","institution":"University College London","correspondingAuthor":true,"prefix":"","firstName":"Naresh","middleName":"","lastName":"Hanchate","suffix":""}],"badges":[],"createdAt":"2025-05-09 11:23:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6628062/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6628062/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82615327,"identity":"c786d0ce-025c-475f-ab54-049d0ee9f800","added_by":"auto","created_at":"2025-05-13 11:35:33","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":109275,"visible":true,"origin":"","legend":"\u003cp\u003ePRISMA 2020 flow diagram for new systematic reviews which included searches of databases, adapted from Page et al., (2021).\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6628062/v1/86d5abeaafba893701ba0a03.jpg"},{"id":83599812,"identity":"22999470-2d0d-4a8d-969d-1eea65af16c6","added_by":"auto","created_at":"2025-05-29 08:53:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1473679,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6628062/v1/daeb8682-974f-4fc5-81e7-738dd7684f8b.pdf"},{"id":82615315,"identity":"cd122396-42a9-4d17-b181-4296aac23a48","added_by":"auto","created_at":"2025-05-13 11:35:33","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":15245,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryinformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-6628062/v1/f0549b894f8084e36ff70d7b.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Oxytocin Dysfunction in Severe Mental Illnesses following Adverse Childhood Experiences: a systematic review","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSevere mental illnesses (SMIs) are psychiatric conditions that significantly affect an individual\u0026rsquo;s mental, behavioural, physical, and emotional well-being, leading to substantial impairments in daily functioning\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. These include bipolar disorder (BPD), borderline personality disorder (BoPD), posttraumatic stress disorder (PTSD), major depressive disorders (MDD), anxiety disorders (AD), and schizophrenia (SCZ). Individuals with SMIs are at greater risk of poor physical health and experience premature mortality at a significantly higher rate, often 10\u0026ndash;20 years earlier than the general population\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. SMIs are complex conditions that can be caused and manifested by a combination of biological, psychological, and environmental factors\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAmong numerous factors, adverse childhood experiences (ACEs) have been identified as a key environmental risk factor for SMIs\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. ACEs refer to traumatic events occurring before the age of 18, which include abuse (physical, emotional, and sexual), neglect (physical and emotional), and various forms of household dysfunction\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. These early-life adversities have been shown to disrupt neurobiological and psychological development, increasing vulnerability to SMIs later in life\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. However, identifying the underlying causal mechanisms that mediate ACE-linked development of SMIs later in adulthood has been challenging.\u003c/p\u003e \u003cp\u003eEmerging evidence suggests that disruptions in the neurobiological pathways regulating the oxytocin (OT) system may serve as a critical mechanism linking ACEs to the onset of SMIs. OT, often referred to as the \u0026ldquo;love hormone\u0026rdquo; or \u0026ldquo;bonding hormone\u0026rdquo;, is a neuropeptide produced in the brain and acts via the oxytocin receptor (encoded by \u003cem\u003eOXTR\u003c/em\u003e), expressed on target cells. The OT-OXTR signalling plays a crucial role in social bonding, attachment, stress regulation, reproduction, and emotional processing\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. It is released into the bloodstream at the posterior pituitary to regulate neuroendocrine functions (parturition\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e and milk production\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e), and OT is also released in the brain to regulate neurobiological pathways associated with social bonding and social behaviours\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eGiven its central role in governing social wellbeing, dysregulation of the OT has been associated with psychiatric disorders\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. For instance, exposure to childhood adversity is inversely correlated with OT levels measured in plasma\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e and cerebrospinal fluid (CSF)\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. These studies suggest that the OT pathway could be a potential link between ACEs and SMIs\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn addition to OT dysregulation, a growing body of evidence suggests that the oxytocin receptor gene (\u003cem\u003eOXTR)\u003c/em\u003e plays a role in regulating social behaviour\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Furthermore, variations in the \u003cem\u003eOXTR\u003c/em\u003e have also been linked to the development of psychiatric disorders\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Genetic interactions across development are thought to collectively influence SMI outcomes. In addition to genetic predisposition or resilience associated with \u003cem\u003eOXTR\u003c/em\u003e single nucleotide polymorphisms (SNPs), gene-environment (GxE) interactions arising from environmental stressors during adolescence, such as ACEs, also contribute to increased susceptibility\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Several SNPs across the \u003cem\u003eOXTR\u003c/em\u003e gene and their associations in a variety of mental health disorders and their implications in specific socio-emotional regulation and behaviours have been previously reported\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e Despite growing interest in the role of OT system in mental health, to our knowledge, no systematic review has comprehensively synthesized evidence on the interplay between ACEs, OT system and SMIs. This study aims to address this gap by investigating whether 1) individuals with SMIs exhibit greater ACE exposure, 2) ACE-linked SMIs exhibit dysregulated OT levels, and 3) \u003cem\u003eOXTR\u003c/em\u003e variations exacerbate or protect ACE-linked development of specific SMIs compared to healthy controls (HCs). Additionally, it seeks to identify the potential mechanisms involving the OT system that underlie the association between ACEs and SMIs.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eOverview\u003c/h2\u003e \u003cp\u003eThe study aimed to systematically review the literature to identify reports investigating circulating levels of OT or \u003cem\u003eOXTR\u003c/em\u003e polymorphisms in individuals exposed to adverse childhood experiences (ACEs) with or without a diagnosis of SMIs. This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and is registered with PROSPERO (CRD42024555819).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSearch strategy and selection criteria\u003c/h3\u003e\n\u003cp\u003eA comprehensive search strategy was developed to identify relevant studies published in peer-reviewed journals between 2004 and July 2024. Four electronic databases\u0026mdash;PsycINFO, MEDLINE, Web of Science, and PubMed\u0026mdash;were searched between February and July 2024. Search terms were constructed around three main concepts: ACE, OT (OT levels and \u003cem\u003eOXTR\u003c/em\u003e variations), and SMIs (Supplementary Table\u0026nbsp;1). To ensure the inclusion of all relevant studies, reference lists of included articles were manually screened, and the searches were re-run in July 2024 before the final analysis.\u003c/p\u003e \u003cp\u003eStudies were eligible for inclusion if they met the following specific criteria. First, they needed to include individuals with a history of ACEs, irrespective of a diagnosis of SMI. Eligible studies must have also measured OT levels or analyzed \u003cem\u003eOXTR\u003c/em\u003e polymorphisms, with comparisons made between individuals exposed to ACEs and diagnosed with SMI and healthy controls (HCs with a history of ACEs, but no diagnosis of SMI. The primary outcomes of interest included differences in OT levels, \u003cem\u003eOXTR\u003c/em\u003e variations, and potential pathways linking OT system dysregulation with ACEs and SMIs. There were no restrictions on study design due to the absence of randomized controlled trials addressing these variables. Therefore, cross-sectional and cohort studies were included.\u003c/p\u003e \u003cp\u003eStudies were excluded if they did not include individuals exposed to ACEs or if a suitable control group without SMI was absent. Studies that failed to measure OT levels, analyze \u003cem\u003eOXTR\u003c/em\u003e polymorphisms, or perform group comparisons based on ACE exposure were also excluded. Research with outcomes unrelated to ACEs, OT levels, or \u003cem\u003eOXTR\u003c/em\u003e variations was deemed ineligible. Additionally, reviews, dissertations, grey literature, conference abstracts, preprints, commentaries, non-academic papers, and books or book chapters were excluded. Non-English studies, animal studies, and research focusing on extreme childhood trauma, such as wartime experiences, were also excluded.\u003c/p\u003e \u003cp\u003eAfter removing duplicates, two independent reviewers (GG and SN) screened titles and abstracts for eligibility. Articles that passed this initial screening were then assessed for full-text eligibility. Any disagreements at either stage were resolved through discussion, or an additional reviewing author (NKH) was consulted if needed.\u003c/p\u003e\n\u003ch3\u003eOutcomes\u003c/h3\u003e\n\u003cp\u003eThe primary outcome of this review was to examine the associations between ACEs, OT system dysregulation (including OT levels and \u003cem\u003eOXTR\u003c/em\u003e polymorphisms), and susceptibility to SMIs. Specifically, the review investigated differences in OT levels and \u003cem\u003eOXTR\u003c/em\u003e variations between individuals with SMIs and HCs. Additionally, this review explored potential pathways through which ACEs influence OT system dysregulation and mediate the risk of developing SMIs.\u003c/p\u003e\n\u003ch3\u003eData extraction\u003c/h3\u003e\n\u003cp\u003eData extraction was conducted systematically to ensure consistency and comprehensiveness. Extracted information included study characteristics such as the first author, year of publication, and country of origin. Data on the study population included sample size, mean age with standard deviation (M\u0026thinsp;\u0026plusmn;\u0026thinsp;\u003cem\u003eSD\u003c/em\u003e), and gender ratio (% female). Information regarding the type of SMI diagnosis was also recorded. Exposure details, including the history of ACEs, OT levels, and \u003cem\u003eOXTR\u003c/em\u003e polymorphisms, and sample types used for OT measurements (e.g., blood or serum) were extracted. The associations between ACEs, OT levels, \u003cem\u003eOXTR\u003c/em\u003e variations, and potential mediating pathways were documented. Data extraction was performed independently by GG and reviewed by SN to ensure accuracy. Any discrepancies were resolved through discussion and, if necessary, through consultation with an additional reviewing author (NKH).\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eThe extracted data were synthesized to compare OT levels, \u003cem\u003eOXTR\u003c/em\u003e polymorphisms, and ACE exposures between individuals with SMIs and HCs. For continuous variables such as OT levels, \u003cem\u003et\u003c/em\u003e-tests were conducted to evaluate group differences. Categorical data, including genotypic frequencies of specific \u003cem\u003eOXTR\u003c/em\u003e polymorphisms, were analysed using chi-squared tests. Effect sizes were reported alongside \u003cem\u003ep\u003c/em\u003e-values to highlight the strength and statistical significance of the observed associations. Mediation analyses were conducted in studies exploring pathways linking ACEs and SMIs to test whether OT levels acted as mediators. Path coefficients, \u003cem\u003eb\u003c/em\u003e-values, and confidence intervals were reported to demonstrate the significance and magnitude of these mediation effects. Subgroup analyses were performed based on the type of SMI diagnosis, including SCZ and BoPD, to explore variations in OT levels and \u003cem\u003eOXTR\u003c/em\u003e polymorphisms. SNPs, such as rs2254298 and rs53576, were examined as potential risk or protective factors.\u003c/p\u003e \u003cp\u003eThe methodological quality of the included studies was evaluated using the Mixed Methods Appraisal Tool (MMAT)\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. The tool assessed five domains related to study design, measurement validity, and confounding variables. Each domain was rated as \u0026ldquo;Yes,\u0026rdquo; \u0026ldquo;No,\u0026rdquo; or \u0026ldquo;Can\u0026rsquo;t tell,\u0026rdquo; with an overall percentage score calculated for each study. There is no strict cutoff in MMAT for defining poor-quality studies. However, for this review, studies that met only two or fewer criteria were deemed poor and were excluded from the final synthesis. Quality evaluations were performed independently by GG and reviewed by SN to ensure accuracy. Any discrepancies were resolved through discussion and, if necessary, consultation with the third reviewer (NKH).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eLiterature searches and characteristics of included studies\u003c/h2\u003e \u003cp\u003eOur search identified 513 articles, of which 14 studies met the inclusion criteria and were included in this systematic review (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). These studies collectively involved 5,624 participants aged 12 to 54 years and were conducted in seven countries across Asia, Europe, and North America. Most studies employed a cross-sectional design (n\u0026thinsp;=\u0026thinsp;13; 92.86%), while one used a cohort design. Participants varied in gender representation, with five studies including males and females, eight focusing on females, and one on males only. The SMIs examined comprised SCZ (n\u0026thinsp;=\u0026thinsp;3; 21%), BoPD (n\u0026thinsp;=\u0026thinsp;7; 50%), AD (n\u0026thinsp;=\u0026thinsp;2; 14%), and one each (7%) on depressive disorders (DEP), PTSD (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Although BPD is one of the most widely studied SMI, our search strategy did not yield any studies investigating the associations between OT and ACE-linked BPD.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary characteristics of included studies\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"16\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e(Author, Year)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCountry\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSMI type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eSample size\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c11\" namest=\"c9\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003cp\u003e(M\u0026thinsp;\u0026plusmn;\u0026thinsp;\u003cem\u003eSD\u003c/em\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c15\" namest=\"c13\"\u003e \u003cp\u003eGender ratio\u003c/p\u003e \u003cp\u003e(% female)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOT / \u003cem\u003eOXTR\u003c/em\u003e\u003c/p\u003e \u003cp\u003especimen\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSMI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHCs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSMI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eHCs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eSMI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003eHCs\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"16\" nameend=\"c16\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOT levels (n\u0026thinsp;=\u0026thinsp;8)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Chen et al., 2024)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSCZ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e42.40\u0026thinsp;\u0026plusmn;\u0026thinsp;9.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e43.45\u0026thinsp;\u0026plusmn;\u0026thinsp;9.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e42.50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eBlood\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Mielke et al., 2023)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGermany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBoPD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e24.21\u0026thinsp;\u0026plusmn;\u0026thinsp;9.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e14.67\u0026thinsp;\u0026plusmn;\u0026thinsp;1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eBlood\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Uzun et al., 2022)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTurkey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e14.27\u0026thinsp;\u0026plusmn;\u0026thinsp;1.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e11.60\u0026thinsp;\u0026plusmn;\u0026thinsp;5.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e57.14%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e53.57%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eBlood\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Kartal et al., 2022)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTurkey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBoPD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e23.06\u0026thinsp;\u0026plusmn;\u0026thinsp;5.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e25.45\u0026thinsp;\u0026plusmn;\u0026thinsp;3.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eBlood\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Speck et al., 2019)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGermany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSCZ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e40.40\u0026thinsp;\u0026plusmn;\u0026thinsp;8.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e36.00\u0026thinsp;\u0026plusmn;\u0026thinsp;10.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e34.29%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e34.29%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eBlood\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Bomann et al., 2017)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDenmark\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBoPD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e29.70\u0026thinsp;\u0026plusmn;\u0026thinsp;9.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e29.50\u0026thinsp;\u0026plusmn;\u0026thinsp;9.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eSerum\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Jobst et al., 2016)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGermany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBoPD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e29.85\u0026thinsp;\u0026plusmn;\u0026thinsp;7.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e30.42\u0026thinsp;\u0026plusmn;\u0026thinsp;10.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eBlood\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Bertsch et al., 2013)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGermany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBoPD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e24.30\u0026thinsp;\u0026plusmn;\u0026thinsp;5.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e24.60\u0026thinsp;\u0026plusmn;\u0026thinsp;4.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eBlood\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"16\" nameend=\"c16\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOXTR variations (n\u0026thinsp;=\u0026thinsp;5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Lee et al., 2022)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnited States\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePTSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e30.80\u0026thinsp;\u0026plusmn;\u0026thinsp;6.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e31.0\u0026thinsp;\u0026plusmn;\u0026thinsp;5.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eSaliva\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Zhang et al., 2020)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBoPD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e33.86\u0026thinsp;\u0026plusmn;\u0026thinsp;9.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e33.22\u0026thinsp;\u0026plusmn;\u0026thinsp;8.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eBlood\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Flasbeck et al., 2018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGermany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBoPD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e27.70\u0026thinsp;\u0026plusmn;\u0026thinsp;7.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e24.6\u0026thinsp;\u0026plusmn;\u0026thinsp;5.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eSaliva\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Tollenaar et al., 2017)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNetherlands\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDEP, AD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e387\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e23.06\u0026thinsp;\u0026plusmn;\u0026thinsp;5.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e25.45\u0026thinsp;\u0026plusmn;\u0026thinsp;3.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eBlood\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Cristobal-Narvaez et al., 2017)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEarly-psychosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e40.40\u0026thinsp;\u0026plusmn;\u0026thinsp;8.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e36.00\u0026thinsp;\u0026plusmn;\u0026thinsp;10.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e34.29%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e34.29%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eBuccal\u003c/p\u003e \u003cp\u003eand blood\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"16\" nameend=\"c16\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOT levels\u0026thinsp;+\u0026thinsp;OXTR variations (n\u0026thinsp;=\u0026thinsp;1)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Goh et al., 2024)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSCZ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e382\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e43.87\u0026thinsp;\u0026plusmn;\u0026thinsp;9.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e42.84\u0026thinsp;\u0026plusmn;\u0026thinsp;10.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e42.41%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e48.31%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eBlood\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"16\" nameend=\"c16\" namest=\"c1\"\u003e \u003cp\u003eNote*: SCZ\u0026thinsp;=\u0026thinsp;Schizophrenia, BoPD\u0026thinsp;=\u0026thinsp;Borderline personality disorder, AD\u0026thinsp;=\u0026thinsp;Anxiety disorders, PTSD\u0026thinsp;=\u0026thinsp;Posttraumatic stress disorder, DEP\u0026thinsp;=\u0026thinsp;Depressive disorder/ Depression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFourteen studies reviewed were appraised using the MMAT\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, and the qualities were rated from 3\u0026ndash;5 out of 5 points; 4 studies scored 5, 7 scored 4, and 3 studies scored 3, demonstrating fair-to-good quality (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Across the 14 studies, ACEs were predominantly measured using the Childhood Trauma Questionnaire (CTQ) and its short form (CTQ-SF). Other tools, such as the Childhood Experiences of Care and Abuse Questionnaire (CECA-Q) and the Life Stressor Checklist (LSC), were also used. These instruments effectively captured aggregate ACE scores. However, most studies did not explore the impact of specific ACE types, such as emotional or physical abuse, on SMI risk. This lack of granularity limits deeper insights into the nuanced relationships between individual ACEs and different SMIs.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eQuality assessment of the included studies using the MMAT checklist (3. Quantitative non-randomized studies)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStudy designs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Author, year)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS1.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eS2.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eLevel of evidence\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOT levels (n\u0026thinsp;=\u0026thinsp;8)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCross-sectional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Chen et al., 2024)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eCan\u0026rsquo;t tell\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4 (80%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCross-sectional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Mielke et al., 2023)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4 (80%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCross-sectional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Uzun et al., 2022)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3 (60%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCross-sectional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Kartal et al., 2022)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3 (60%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCross-sectional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Speck et al., 2019)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4 (80%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCross-sectional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Bomann et al., 2017)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4 (80%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCross-sectional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Jobst et al., 2016)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCross-sectional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Bertsch et al., 2013)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4 (80%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOXTR variations (n\u0026thinsp;=\u0026thinsp;5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCross-sectional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Lee et al., 2022)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4 (80%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCross-sectional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Zhang et al., 2020)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCross-sectional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Flasbeck et al., 2018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3 (60%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Tollenaar et al., 2017)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCross-sectional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Cristobal-Narvaez et al., 2017)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4 (80%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOT levels\u0026thinsp;+\u0026thinsp;OXTR variations (n\u0026thinsp;=\u0026thinsp;1)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCross-sectional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Goh et al., 2024)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003eNote*\u003c/p\u003e \u003cp\u003eS1. Are there clear research questions? S2. Do the collected data allow to address the research questions? 1. Are the participants representative of the target population? 2. Are measurements appropriate regarding both the outcome and intervention (or exposure)? 3. Are there complete outcome data? 4. Are the confounders accounted for in the design and analysis? 5. During the study period, is the intervention administered (or exposure occurred) as intended?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAssociation between ACEs and increased risk of SMIs\u003c/h3\u003e\n\u003cp\u003eMost studies (n\u0026thinsp;=\u0026thinsp;13; 92.86%) reported that individuals with SMIs had significantly higher ACE scores than HCs (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), consistent with the widely acknowledged associations between childhood adversity and SMI susceptibility. Only one study, conducted by Uzun et al. (2022), found no significant difference between the SMI group and HCs (\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.32, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.19). However, this may be attributed to the use of younger participants. (average of 14.27 years compared to an average of 31.49 years in the other 13 studies). It is possible that adolescence represents a critical period for OT system maturation, and the immediate effects of ACEs may differ compared to adult populations. ACE-linked SMIs predominantly include female participants, with an average of \u003cb\u003e72.01% female\u003c/b\u003e and \u003cb\u003e27.99% male\u003c/b\u003e representation. The gender imbalance observed in ACE-linked SMI research may stem from higher exposure of females to multiple ACEs, more complex patterns of ACEs\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, and increased susceptibility to psychiatric symptoms following ACEs\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. These factors likely contribute to the predominance of female participants in such studies. Future studies should aim for a more balanced gender distribution to clarify whether gender plays a moderating role in the relationship between ACEs and SMIs.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe association between ACE and SMI\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"14\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c10\" namest=\"c4\"\u003e \u003cp\u003eACE total scores (M\u0026thinsp;\u0026plusmn;\u0026thinsp;\u003cem\u003eSD\u003c/em\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c14\" namest=\"c12\" rowspan=\"2\"\u003e \u003cp\u003eResults of difference tests\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Author, Year)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eACE measurement\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eSMI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eHCs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"14\" nameend=\"c14\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOT levels (n\u0026thinsp;=\u0026thinsp;8)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Chen et al., 2024)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCTQ-SF, structured interviews\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e38.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e13.92\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Mielke et al., 2023)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCTQ, CECA. Q\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e13.38\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Uzun et al., 2022)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCTQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e56.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e14.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Kartal et al., 2022)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCTQ-SF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e6.51\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Speck et al., 2019)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCTQ-SF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e2.38\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Bomann et al., 2017)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCTQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e9.43\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Jobst et al., 2016)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCTQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e6.76\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Bertsch et al., 2013)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCTQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e32.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e12.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e6.95\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"14\" nameend=\"c14\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOXTR variations (n\u0026thinsp;=\u0026thinsp;5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Lee et al., 2022)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLSC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e53.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e28.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e20.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e26.68\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Zhang et al., 2020)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCTQ-SF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e42.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e15.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e7.32\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Flasbeck et al., 2018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCTQ-SF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e33.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e10.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e14.36\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Tollenaar et al., 2017)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCTQ-SF, semi-structured CT interview\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e33.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e15.29\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Cristobal-Narvaez et al., 2017)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCTQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e33.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e8.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e6.48\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"14\" nameend=\"c14\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOT levels\u0026thinsp;+\u0026thinsp;OXTR variations (n\u0026thinsp;=\u0026thinsp;1)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Goh et al., 2024)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCTQ-SF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e44.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e13.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e12.55\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"14\" nameend=\"c14\" namest=\"c1\"\u003e \u003cp\u003eNote: \u003csup\u003e*\u003c/sup\u003e \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, \u003csup\u003e**\u003c/sup\u003e \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, \u003csup\u003e***\u003c/sup\u003e \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eOxytocin dysfunction in individuals with SMIs\u003c/h2\u003e \u003cp\u003eWe next examined the studies that measured and compared OT levels between individuals with SMIs and HCs. 64% (n\u0026thinsp;=\u0026thinsp;9) of studies compared OT concentrations between SMI groups and HCs. Among these, 77% (n\u0026thinsp;=\u0026thinsp;7) of studies reported dysregulated OT levels in ACE-linked SMI patients compared to HCs, of which 66.6% (n\u0026thinsp;=\u0026thinsp;6) and 11.1% (n\u0026thinsp;=\u0026thinsp;1) studies found lower or higher OT levels, respectively (Table\u0026nbsp;4). Two studies that reported no differences between the groups. Importantly, lower OT levels were found in patients with different SMIs. For instance, out of the six studies that showed lower OT levels, 3 (50%) were with SCZ and BoPD participants (Table\u0026nbsp;4), suggesting ACE-linked downregulation of OT could be a common mechanism leading to SMI pathophysiology. The singular study that reported elevated OT levels was in patients with AD, but this may be due to differences in the younger age group in this study. Overall, these studies suggest OT dysregulation is common across many SMIs. Several studies also investigated the relationship between the impact of ACEs on OT levels in male and female SMI patients. Of the six studies that reported lower OT levels in SMI patients, three focused on female patients with BoPD, and the three others had a mix of both male and female patients, suggesting ACEs can impact both boys and girls during adolescence, increasing their susceptibility to SMIs.\u003c/p\u003e \u003cp\u003e \u003cb\u003eAssociation of\u003c/b\u003e \u003cb\u003eOXTR\u003c/b\u003e \u003cb\u003epolymorphisms with SMIs\u003c/b\u003e\u003c/p\u003e \u003cp\u003eNext, we explored the role of \u003cem\u003eOXTR\u003c/em\u003e polymorphisms and their association with SMI pathologies. Six of fourteen studies (42%) reported eight single nucleotide polymorphisms (SNPs) in \u003cem\u003eOXTR\u003c/em\u003e and their associations with ACE-linked SMIs (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The gene encoding OXTR, a G-protein-coupled receptor spanning about 25 kilobases with four exons and three introns, is located on chromosome 3 in humans at the cytogenetic band 3p25.3\u003csup\u003e20\u003c/sup\u003e. The findings indicate that specific genotypes at these eight loci conferred either risk or protection against SMIs (shown in red or green, respectively; Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e5\u003c/span\u003e). For instance, the GG genotype of two \u003cem\u003eOXTR\u003c/em\u003e SNPs (rs237885 and rs53576) appears to increase susceptibility to SMIs, whereas the TT or AA genotype of these variants served as protective factor, respectively. Similarly, different genotypes at other loci served as either a risk or protective factors, suggesting these variants could play a crucial role and impact the expression levels of OXTR in specific brain areas, or binding affinity to OXT or downstream signalling pathways.\u003c/p\u003e\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003eTable 4. Comparison of OT levels between SMI group and HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"8\" valign=\"top\"\u003e\n \u003cp\u003eOT levels (ng/mL) (M\u0026nbsp;\u0026plusmn;\u0026nbsp;\u003cem\u003eSD\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" rowspan=\"2\"\u003e\n \u003cp\u003eResults of difference tests\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eID\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e(Author, Year)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eSMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eHCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e(Goh et al., 2024)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- 5.45\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e(Chen et al., 2024)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-5.54\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e(Mielke et al., 2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e201.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e148.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e255.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e143.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- 2.92\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e(Uzun et al., 2022)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e213.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e72.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e166.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e52.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.42\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e(Kartal et al., 2022)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e797.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e835.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- 6.63\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e(Speck et al., 2019)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- 22.02\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e(Bomann et al., 2017)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e499.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e224.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e411.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e187.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e(Jobst et al., 2016)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e421.67\u003c/p\u003e\n \u003cp\u003e390.97\u003c/p\u003e\n \u003cp\u003e399.19\u003c/p\u003e\n \u003cp\u003e403.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e127.70\u003c/p\u003e\n \u003cp\u003e130.70\u003c/p\u003e\n \u003cp\u003e142.60\u003c/p\u003e\n \u003cp\u003e128.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e450.26\u003c/p\u003e\n \u003cp\u003e471.46\u003c/p\u003e\n \u003cp\u003e468.19\u003c/p\u003e\n \u003cp\u003e454.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e204.42\u003c/p\u003e\n \u003cp\u003e240.63\u003c/p\u003e\n \u003cp\u003e252.68\u003c/p\u003e\n \u003cp\u003e233.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.54\u003c/p\u003e\n \u003cp\u003e-1.34\u003c/p\u003e\n \u003cp\u003e-1.08\u003c/p\u003e\n \u003cp\u003e-0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e(Bertsch et al., 2013)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- 3.93\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\" valign=\"top\"\u003e\n \u003cp\u003eNote:\u0026nbsp;\u003csup\u003e*\u003c/sup\u003e \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, \u003csup\u003e**\u003c/sup\u003e \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, \u003csup\u003e***\u003c/sup\u003e \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"1027\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"15\" valign=\"top\" style=\"width: 27.8835%;\"\u003e\n \u003cp\u003eTable 5. Comparison of \u003cem\u003eOXTR\u003c/em\u003e variations between SMI group and HCs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 0.7615%;\"\u003e\n \u003cp\u003eID\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 4.7973%;\"\u003e\n \u003cp\u003e(Author, year)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 2.1702%;\"\u003e\n \u003cp\u003eSMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 2.8555%;\"\u003e\n \u003cp\u003eSNP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 2.589%;\"\u003e\n \u003cp\u003eRisk alleles\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 2.6271%;\"\u003e\n \u003cp\u003eGenotype\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.2284%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 6.3202%;\"\u003e\n \u003cp\u003eGenotypic frequencies (n (%))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.2284%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eGroup differences in genotype frequencies\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 0.2284%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.1601%;\"\u003e\n \u003cp\u003eSMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.3046%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.8936%;\"\u003e\n \u003cp\u003eHCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 0.2284%;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.6069%;\"\u003e\n \u003cp\u003e\u003cem\u003ec\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.4188%;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.3124%;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"7\" valign=\"top\" style=\"width: 0.7615%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"7\" valign=\"top\" style=\"width: 4.7973%;\"\u003e\n \u003cp\u003e(Goh et al., 2024)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.1702%;\"\u003e\n \u003cp\u003eSCZ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.8555%;\"\u003e\n \u003cp\u003ers1042778\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.589%;\"\u003e\n \u003cp\u003eG/T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.6271%;\"\u003e\n \u003cp\u003eGG\u003c/p\u003e\n \u003cp\u003eGT\u003c/p\u003e\n \u003cp\u003eTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.2284%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.1601%;\"\u003e\n \u003cp\u003e220 (57.6)\u003c/p\u003e\n \u003cp\u003e128 (33.5)\u003c/p\u003e\n \u003cp\u003e34 (8.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.3046%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.8936%;\"\u003e\n \u003cp\u003e123 (69.1)\u003c/p\u003e\n \u003cp\u003e50 (28.1)\u003c/p\u003e\n \u003cp\u003e5 (2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.2284%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 4.6069%;\"\u003e\n \u003cp\u003e10.217\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.4188%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.3124%;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 2.1702%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.8555%;\"\u003e\n \u003cp\u003ers2254298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.589%;\"\u003e\n \u003cp\u003eG/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.6271%;\"\u003e\n \u003cp\u003eGG\u003c/p\u003e\n \u003cp\u003eGA\u003c/p\u003e\n \u003cp\u003eAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.2284%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.1601%;\"\u003e\n \u003cp\u003e130 (34.0)\u003c/p\u003e\n \u003cp\u003e168 (44.0)\u003c/p\u003e\n \u003cp\u003e84 (22.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.3046%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.8936%;\"\u003e\n \u003cp\u003e76 (42.7)\u003c/p\u003e\n \u003cp\u003e84 (47.2)\u003c/p\u003e\n \u003cp\u003e18 (10.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.2284%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 4.6069%;\"\u003e\n \u003cp\u003e12.161\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.4188%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.3124%;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 2.1702%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.8555%;\"\u003e\n \u003cp\u003ers237885\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.589%;\"\u003e\n \u003cp\u003eG/T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.6271%;\"\u003e\n \u003cp\u003eGG\u003c/p\u003e\n \u003cp\u003eGT\u003c/p\u003e\n \u003cp\u003eTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.2284%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.1601%;\"\u003e\n \u003cp\u003e30 (7.9)\u003c/p\u003e\n \u003cp\u003e155 (40.6)\u003c/p\u003e\n \u003cp\u003e197 (51.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.3046%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.8936%;\"\u003e\n \u003cp\u003e6 (3.4)\u003c/p\u003e\n \u003cp\u003e56 (31.5)\u003c/p\u003e\n \u003cp\u003e116 (65.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.2284%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 4.6069%;\"\u003e\n \u003cp\u003e10.490\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.4188%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.3124%;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 2.1702%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.8555%;\"\u003e\n \u003cp\u003ers237887\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.589%;\"\u003e\n \u003cp\u003eG/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.6271%;\"\u003e\n \u003cp\u003eGG\u003c/p\u003e\n \u003cp\u003eGA\u003c/p\u003e\n \u003cp\u003eAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.2284%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.1601%;\"\u003e\n \u003cp\u003e127 (33.2)\u003c/p\u003e\n \u003cp\u003e186 (48.7)\u003c/p\u003e\n \u003cp\u003e69 (18.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.3046%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.8936%;\"\u003e\n \u003cp\u003e89 (50.0)\u003c/p\u003e\n \u003cp\u003e71 (39.9)\u003c/p\u003e\n \u003cp\u003e18 (10.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.2284%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 4.6069%;\"\u003e\n \u003cp\u003e15.827\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.4188%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.3124%;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 2.1702%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.8555%;\"\u003e\n \u003cp\u003ers237895\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.589%;\"\u003e\n \u003cp\u003eC/T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.6271%;\"\u003e\n \u003cp\u003eCC\u003c/p\u003e\n \u003cp\u003eCT\u003c/p\u003e\n \u003cp\u003eTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.2284%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.1601%;\"\u003e\n \u003cp\u003e33 (8.6)\u003c/p\u003e\n \u003cp\u003e160 (41.9)\u003c/p\u003e\n \u003cp\u003e189 (49.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.3046%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.8936%;\"\u003e\n \u003cp\u003e13 (7.3)\u003c/p\u003e\n \u003cp\u003e49 (27.5)\u003c/p\u003e\n \u003cp\u003e116 (65.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.2284%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 4.6069%;\"\u003e\n \u003cp\u003e12.459\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.4188%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.3124%;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 2.1702%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.8555%;\"\u003e\n \u003cp\u003ers237899\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.589%;\"\u003e\n \u003cp\u003eG/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.6271%;\"\u003e\n \u003cp\u003eGG\u003c/p\u003e\n \u003cp\u003eGA\u003c/p\u003e\n \u003cp\u003eAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.2284%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.1601%;\"\u003e\n \u003cp\u003e187 (49.0)\u003c/p\u003e\n \u003cp\u003e151 (39.5)\u003c/p\u003e\n \u003cp\u003e44 (11.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.3046%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.8936%;\"\u003e\n \u003cp\u003e111 (62.4)\u003c/p\u003e\n \u003cp\u003e56 (31.5)\u003c/p\u003e\n \u003cp\u003e11 (6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.2284%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 4.6069%;\"\u003e\n \u003cp\u003e9.763\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.4188%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.3124%;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 2.1702%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.8555%;\"\u003e\n \u003cp\u003ers53576\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.589%;\"\u003e\n \u003cp\u003eG/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.6271%;\"\u003e\n \u003cp\u003eGG\u003c/p\u003e\n \u003cp\u003eGA\u003c/p\u003e\n \u003cp\u003eAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.2284%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.1601%;\"\u003e\n \u003cp\u003e67 (17.5)\u003c/p\u003e\n \u003cp\u003e155 (40.6)\u003c/p\u003e\n \u003cp\u003e160 (41.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.3046%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.8936%;\"\u003e\n \u003cp\u003e13 (7.3)\u003c/p\u003e\n \u003cp\u003e75 (42.1)\u003c/p\u003e\n \u003cp\u003e90 (50.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.2284%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 4.6069%;\"\u003e\n \u003cp\u003e11.025\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.4188%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.3124%;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 0.7615%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.7973%;\"\u003e\n \u003cp\u003e(Zhang et al., 2020)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.1702%;\"\u003e\n \u003cp\u003eBoPD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.8555%;\"\u003e\n \u003cp\u003ers53576\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.589%;\"\u003e\n \u003cp\u003eG/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.6271%;\"\u003e\n \u003cp\u003eGG\u003c/p\u003e\n \u003cp\u003eGA\u003c/p\u003e\n \u003cp\u003eAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.2284%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.1601%;\"\u003e\n \u003cp\u003e125 (38.0)\u003c/p\u003e\n \u003cp\u003e20 (6.1)\u003c/p\u003e\n \u003cp\u003e184 (55.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.3046%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.8936%;\"\u003e\n \u003cp\u003e177 (43.2)\u003c/p\u003e\n \u003cp\u003e38 (9.3)\u003c/p\u003e\n \u003cp\u003e195 (47.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.2284%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 4.6069%;\"\u003e\n \u003cp\u003e6.054\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.4188%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.3124%;\"\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 0.7615%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.7973%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.1702%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.8555%;\"\u003e\n \u003cp\u003ers237897\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.589%;\"\u003e\n \u003cp\u003eG/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.6271%;\"\u003e\n \u003cp\u003eGG\u003c/p\u003e\n \u003cp\u003eGA\u003c/p\u003e\n \u003cp\u003eAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.2284%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.1601%;\"\u003e\n \u003cp\u003e121 (37.6)\u003c/p\u003e\n \u003cp\u003e14 (4.3)\u003c/p\u003e\n \u003cp\u003e187 (58.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.3046%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.8936%;\"\u003e\n \u003cp\u003e165 (40.8)\u003c/p\u003e\n \u003cp\u003e34 (8.4)\u003c/p\u003e\n \u003cp\u003e205 (50.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.2284%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 4.6069%;\"\u003e\n \u003cp\u003e6.754\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.4188%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.3124%;\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 0.7615%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.7973%;\"\u003e\n \u003cp\u003e(Tollenaar et al., 2017)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.1702%;\"\u003e\n \u003cp\u003eDEP, AD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.8555%;\"\u003e\n \u003cp\u003ers2254298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.589%;\"\u003e\n \u003cp\u003eG/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 2.8936%;\"\u003e\n \u003cp\u003eGG\u003c/p\u003e\n \u003cp\u003eGA\u003c/p\u003e\n \u003cp\u003eAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.1601%;\"\u003e\n \u003cp\u003e1912 (87.7)\u003c/p\u003e\n \u003cp\u003e259 (11.9)\u003c/p\u003e\n \u003cp\u003e9 (0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.3046%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.8936%;\"\u003e\n \u003cp\u003e352 (91.0)\u003c/p\u003e\n \u003cp\u003e31 (8.0)\u003c/p\u003e\n \u003cp\u003e4 (1.0)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.2284%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 4.6069%;\"\u003e\n \u003cp\u003e7.252*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0.4188%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.3124%;\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"15\" valign=\"top\" style=\"width: 31.3345%;\"\u003e\n \u003cp\u003eNote:\u0026nbsp;\u003csup\u003e*\u003c/sup\u003e \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, \u003csup\u003e**\u003c/sup\u003e \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, \u003csup\u003e***\u003c/sup\u003e \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001. Genotypes that serve as a risk factor are present in red, while genotypes that serve as a protective factor are present in green.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\u003cp\u003eThese analyses also indicate that specific SNPs in the \u003cem\u003eOXTR\u003c/em\u003e are associated with susceptibility to various SMIs. For instance, two studies (Goh et al. (2024) and Tollenaar et al. (2017)) investigated the same SNP, rs2254298. Goh et al. (2024) found that the AA genotype was significantly more prevalent in the SCZ group (22.0%) compared to HCs (10.1%) (\u003cem\u003eχ\u0026sup2;\u003c/em\u003e = 12.161, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002) and Tollenaar et al. (2017) discovered that the GA genotype of rs2254298 was more frequent in the DEP\u0026thinsp;+\u0026thinsp;AD group (11.9%) compared to HCs (8.0%) (\u003cem\u003eχ\u0026sup2;\u003c/em\u003e = 7.252, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.027). Similarly, the \u003cem\u003eOXTR\u003c/em\u003e SNP rs53576 was also reported in two studies. Goh et al. (2024) found that the GG genotype frequency was higher in the SCZ group (17.5%) compared to HCs (7.3%) (\u003cem\u003eχ\u0026sup2;\u003c/em\u003e = 11.025, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004). Zhang et al. (2020) reported that the AA genotype was significantly more common in the BoPD group (55.9%) compared to HCs (47.6%) (\u003cem\u003eχ\u0026sup2;\u003c/em\u003e = 6.054, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.048).\u003c/p\u003e \u003cp\u003eWe next focused on three studies that examined G\u0026times;E interactions, demonstrating that \u003cem\u003eOXTR\u003c/em\u003e variations moderate the relationship between ACEs and SMIs. Of these, one study highlighted that high additive genetic risk scores (AGRS), calculated across multiple SNPs, amplified the impact of ACEs on schizophrenia symptoms (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.226, \u003cem\u003eSE\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.031, 95% CI \u003cb\u003e=\u003c/b\u003e [0.169, 0.290], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) Goh et al. (2024). Similarly, other studies identified significant ACE \u0026times; \u003cem\u003eOXTR\u003c/em\u003e interactions predicting psychotic symptoms (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) Cristobal-Narvaez et al. (2017), and individuals carrying the A allele of rs53576 (AA or GA genotypes) demonstrated heightened empathy for psychological pain when exposed to ACEs, whereas GG carriers were less affected (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.037)\u003csup\u003e24\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003e The present systematic review revealed associations between ACEs, OT system dysregulation, and susceptibility to SMIs. ACEs are critical environmental factors predisposing individuals to several neuropsychiatric conditions and SMIs. Consistent with this notion, our findings revealed that individuals with SMIs had a significantly higher prevalence of ACEs than healthy controls (HCs). Additionally, reduced OT levels were observed in approximately 65% of studies in different SMIs, indicating that dysregulation of the oxytocinergic system may play a role in the pathophysiology of SMIs. Finally, subsets of oxytocin receptor (\u003cem\u003eOXTR\u003c/em\u003e) polymorphisms conferred resilience or susceptibility to SMIs, indicating that gene-environment interactions play a crucial role in the development of SMIs.\u003c/p\u003e \u003cp\u003eACEs are now widely acknowledged and well-established leading causes of adult morbidity and mortality\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. ACEs have been associated with higher prevalence rates of both mental illnesses, including depression\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, anxiety\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e, and PTSD\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e, and physical illnesses, such as higher risk of cardiovascular disorders\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, diabetes\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, and weakened immune function\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Consistent with a large body of evidence, our study identified strong associations between ACE exposure and the prevalence of SMIs. Importantly, these associations were observed across all the SMI types reported in our study, including SCZ, BoPD, AD, PTSD, DEP, and early psychosis. This indicates that ACEs have a profound impact on adult mental health and serve as a common underlying factor that increases susceptibility to various SMIs. However, the specific SMI outcomes vary among individuals depending on the ACE type, duration, severity, genetic predispositions, and environmental influences. One key mechanism underlying these variations is the prolonged activation of stress response systems following ACE exposure. Chronic stress can lead to heightened cortisol levels, which negatively impact brain development and neurobiological pathways involved in social bonding and social behaviours \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn recent decades, the oxytocinergic system has emerged as a crucial neurobiological pathway for its role in social behaviours and social bonding\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Several studies have shown its dysregulation is associated with several neuropsychiatric conditions (e.g., depression\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e) and neurodevelopmental disorders, such as autism spectrum disorder\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Our systematic review revealed that most studies reported reduced oxytocin levels in SMI patients compared to healthy controls. Intriguingly, multiple studies in our review reported reduced OT levels were different SMI types (SCZ and BoPD), suggesting OT dysfunction is a possible mediator of SMIs. These studies also suggest OT downregulation could result ACE-induced brain circuit dysfunction regulating emotional and social behaviours that modulate oxytocin neurons and OT in the brain and the periphery. These findings are consistent with previous research highlighting the role of OT in emotional regulation, social behaviour, and stress response\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. For instance, prior studies have demonstrated that lower OT levels are linked to impaired social cognition in SCZ\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e and increased interpersonal dysfunction in BoPD\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. While ACE is a common underlying factor of SMIs in these studies, the genetic makeup of these patients is unknown whether these patients harbor variants or mutations in genes associated with social behaviours or brain circuit function. This information could have provided deeper insights into the susceptibility of individuals to ACEs and their outcomes in different SMIs.\u003c/p\u003e \u003cp\u003eInstead, we focused on data available on the variants associated with the oxytocinergic system. In particular, identifying \u003cem\u003eOXTR\u003c/em\u003e variations as mediators of susceptibility to SMIs adds to the growing body of evidence on gene-environment (G\u0026times;E) interactions. However, our findings also underscore the complexity of these relationships, as the protective effects of the GG genotype appear to vary depending on the type of ACE, timing, and chronicity. This aligns with prior studies, which reported increased sensitivity to negative parenting among GG carriers, further complicating the role of \u003cem\u003eOXTR\u003c/em\u003e polymorphisms\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eDespite the significant associations identified, several limitations must be acknowledged. First, the reliance on retrospective self-report tools, such as the Childhood Trauma Questionnaire (CTQ), introduces the risk of recall bias and underreporting of ACEs. While some studies incorporated structured interviews, the lack of multi-method assessments limits the accuracy and reliability of ACE measurements. Second, most studies measured peripheral OT levels using plasma, which may not accurately reflect central OT concentrations due to their unstable nature\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. A recent systematic review of the literature suggests a positive correlation between central and peripheral levels of OT during stressful conditions or intranasal OT delivery but not in baseline conditions\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. Furthermore, variability in OT specimen types and processing methods (e.g., plasma vs serum) will likely contribute to discrepancies in the reported OT levels.\u003c/p\u003e \u003cp\u003e Our systematic review is composed mostly of cross-sectional designs, which contain data obtained at a single time point and thus often hinder causal inferences (cause-and-effect relationships) between ACEs, OT system dysregulation, and SMIs. Longitudinal studies are necessary to establish temporal relationships and assess how OT levels or \u003cem\u003eOXTR\u003c/em\u003e variations evolve over time in response to ACEs. Additionally, the overrepresentation of female participants in studies of BPD introduces gender bias, reducing the generalizability of findings to other populations. The small sample sizes in many studies further limit statistical power, particularly in analyses of \u003cem\u003eOXTR\u003c/em\u003e polymorphisms. Publication bias may have influenced the findings, as studies with null results are less likely to be published. Additionally, the relationship between ACEs and OT dysregulation in other major SMIs, such as bipolar disorder, remains understudied.\u003c/p\u003e \u003cp\u003e The inconsistencies observed in this review reflect the challenges inherent in studying the OT system. For instance, Uzun et al. (2022) reported higher OT levels in adolescents with AD compared to HCs, which contrasts with the trends observed in adult populations\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. This discrepancy may reflect developmental differences in OT system maturation, highlighting the need for age-specific investigations.\u003c/p\u003e \u003cp\u003eFuture research should also prioritize longitudinal studies to explore the temporal dynamics of OT dysregulation following ACEs and its role in SMI susceptibility. Improved methodologies, including culturally sensitive, multi-method assessments of ACEs and standardized OT measurement protocols, are essential for enhancing the reliability of findings. It would also be interesting to examine if the OT system is dysregulated in SMI patients who experienced certain extreme ACEs excluded in our current studies. Further exploration of \u003cem\u003eOXTR\u003c/em\u003e polymorphisms is needed to clarify their role as risk or protective factors, particularly about specific ACE subtypes. Large-scale studies with diverse and representative populations will be critical for addressing gender biases and improving the generalizability of results.\u003c/p\u003e \u003cp\u003eFrom a clinical and policy perspective, this review highlights the importance of early identification and prevention of childhood adversity to reduce the risk of SMIs. Strategies aimed at promoting safe, stable, and nurturing environments for children, as recommended by the Centers for Disease Control and Prevention (CDC)\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e, should be prioritized in public health initiatives. Moreover, OT-related biomarkers, such as peripheral OT levels and \u003cem\u003eOXTR\u003c/em\u003e genotypes, hold promise as tools for identifying individuals at heightened risk of SMIs, potentially informing targeted interventions. While therapies such as intranasal OT administration have shown promise in reducing stress-related symptoms\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e, careful consideration of context-dependent effects and potential risks is essential to ensure safety and efficacy.\u003c/p\u003e \u003cp\u003e In conclusion, this review highlights the interplay between ACEs, OT system dysregulation, and susceptibility to SMIs, shedding light on the biological mechanisms underlying ACE's long-term impact on mental health. However, the inconsistencies in the data emphasize the need for rigorous, standardized research to better understand these complex relationships. By addressing methodological limitations and focusing on specific pathways, such as \u003cem\u003eOXTR\u003c/em\u003e polymorphisms, future studies can provide more precise insights into the role of genetic, biological, and environmental factors in SMI development. These findings underscore the clinical significance of early intervention and the potential for OT-related biomarkers to inform prevention and treatment strategies, ultimately improving mental health outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eG.G. and N.K.H. conceptualized and designed study; G.G., S.C.F.N., and N.K.H. performed searches, data acquisition, analysis, and interpretation; G.G. and N.K.H. drafted and wrote the manuscript. All authors read and critically revised the manuscript, and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eACKNOWLEDGEMENTS\u003c/h2\u003e \u003cp\u003eWe would like to thank the members of the Hanchate lab for their critical reading of the manuscript and for providing feedback. N.K.H is supported by a UCL Excellence Fellowship (funded by the Great Ormond Street Hospital Children\u0026rsquo;s Charity (VS0321), the Stoneygate Trust, and the Rosetrees Trust (UCL2021/1)) and a New Investigator Research Grant funded by UKRI MRC (MR/X003957/1). The funders had no role in study design, data collection, data analysis, data interpretation, or writing of the report.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eNIMH NIoMH. Mental Illness. (2023). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.nimh.nih.gov/health/statistics/mental-illness#part_2555\u003c/span\u003e\u003cspan address=\"https://www.nimh.nih.gov/health/statistics/mental-illness#part_2555\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWHO. \u003cem\u003eManagement of physical health conditions in adults with severe mental disorders\u003c/em\u003e (World Health Organisation Geneva, 2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDickerson, F. et al. Natural cause mortality in persons with serious mental illness. \u003cem\u003eActa Psychiatry. Scand.\u003c/em\u003e \u003cb\u003e137\u003c/b\u003e (5), 371\u0026ndash;379 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDe Hert, M. et al. Physical illness in patients with severe mental disorders. I. Prevalence, impact of medications and disparities in health care. \u003cem\u003eWorld Psychiatry\u003c/em\u003e. \u003cb\u003e10\u003c/b\u003e (1), 52\u0026ndash;77 (2011).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSolmi, M. et al. Age at onset of mental disorders worldwide: large-scale meta-analysis of 192 epidemiological studies. \u003cem\u003eMol. Psychiatry\u003c/em\u003e. \u003cb\u003e27\u003c/b\u003e (1), 281\u0026ndash;295 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFelitti, V. J. et al. Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults. The Adverse Childhood Experiences (ACE) Study. \u003cem\u003eAm. J. Prev. Med.\u003c/em\u003e \u003cb\u003e14\u003c/b\u003e (4), 245\u0026ndash;258 (1998).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStruck, N. et al. Childhood maltreatment and adult mental disorders\u0026ndash;the prevalence of different types of maltreatment and associations with age of onset and severity of symptoms. \u003cem\u003ePsychiatry Res.\u003c/em\u003e \u003cb\u003e293\u003c/b\u003e, 113398 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFlorea, T. et al. Oxytocin: Narrative Expert Review of Current Perspectives on the Relationship with Other Neurotransmitters and the Impact on the Main Psychiatric Disorders. \u003cem\u003eMed. (Lithuania)\u003c/em\u003e ; \u003cb\u003e58\u003c/b\u003e(7). (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWalter, M. H., Abele, H. \u0026amp; Plappert, C. F. The Role of Oxytocin and the Effect of Stress During Childbirth: Neurobiological Basics and Implications for Mother and Child. \u003cem\u003eFront. Endocrinol. (Lausanne)\u003c/em\u003e. \u003cb\u003e12\u003c/b\u003e, 742236 (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUvn\u0026auml;sMoberg, K. et al. Maternal plasma levels of oxytocin during breastfeeding\u0026mdash;A systematic review. \u003cem\u003ePloS one\u003c/em\u003e. \u003cb\u003e15\u003c/b\u003e (8), e0235806 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOlff, M. et al. The role of oxytocin in social bonding, stress regulation and mental health: an update on the moderating effects of context and interindividual differences. \u003cem\u003ePsychoneuroendocrinology\u003c/em\u003e \u003cb\u003e38\u003c/b\u003e (9), 1883\u0026ndash;1894 (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcLaughlin, K. A., Sheridan, M. A. \u0026amp; Lambert, H. K. Childhood adversity and neural development: deprivation and threat as distinct dimensions of early experience. \u003cem\u003eNeurosci. Biobehav Rev.\u003c/em\u003e \u003cb\u003e47\u003c/b\u003e, 578\u0026ndash;591 (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOpacka-Juffry, J. \u0026amp; Mohiyeddini, C. Experience of stress in childhood negatively correlates with plasma oxytocin concentration in adult men. \u003cem\u003eSTRESS-THE Int. J. BIOLOGY STRESS\u003c/em\u003e. \u003cb\u003e15\u003c/b\u003e (1), 1\u0026ndash;10 (2012).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEllis, B. J., Horn, A. J., Carter, C. S., van Ijzendoorn, M. H. \u0026amp; Bakermans-Kranenburg, M. J. Developmental programming of oxytocin through variation in early-life stress: Four meta-analyses and a theoretical reinterpretation. \u003cem\u003eClin. Psychol. Rev.\u003c/em\u003e ; 86. (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHeim, C. et al. Lower CSF oxytocin concentrations in women with a history of childhood abuse. \u003cem\u003eMol. Psychiatry\u003c/em\u003e. \u003cb\u003e14\u003c/b\u003e (10), 954\u0026ndash;958 (2009).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBelsky, J. \u0026amp; Pluess, M. Beyond diathesis stress: differential susceptibility to environmental influences. \u003cem\u003ePsychol. Bull.\u003c/em\u003e \u003cb\u003e135\u003c/b\u003e (6), 885\u0026ndash;908 (2009).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKumsta, R., Hummel, E., Chen, F. S. \u0026amp; Heinrichs, M. Epigenetic regulation of the oxytocin receptor gene: implications for behavioral neuroscience. \u003cem\u003eFront. NeuroSci.\u003c/em\u003e ; \u003cb\u003e7\u003c/b\u003e. (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGimpl, G. \u0026amp; Fahrenholz, F. The oxytocin receptor system: structure, function, and regulation. \u003cem\u003ePhysiol. Rev.\u003c/em\u003e \u003cb\u003e81\u003c/b\u003e (2), 629\u0026ndash;683 (2001).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUher, R. \u0026amp; Zwicker, A. Etiology in psychiatry: embracing the reality of poly-gene-environmental causation of mental illness. \u003cem\u003eWorld Psychiatry\u003c/em\u003e. \u003cb\u003e16\u003c/b\u003e (2), 121\u0026ndash;129 (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKohlhoff, J., Cibralic, S., Hawes, D. J. \u0026amp; Eapen, V. Oxytocin receptor gene (OXTR) polymorphisms and social, emotional and behavioral functioning in children and adolescents: A systematic narrative review. \u003cem\u003eNeurosci. Biobehav. Rev.\u003c/em\u003e ; 135. (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHong, Q. N. et al. The Mixed Methods Appraisal Tool (MMAT) version 2018 for information professionals and researchers. \u003cem\u003eEduc. Inform.\u003c/em\u003e \u003cb\u003e34\u003c/b\u003e (4), 285\u0026ndash;291 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHaahr-Pedersen, I. et al. Females have more complex patterns of childhood adversity: implications for mental, social, and emotional outcomes in adulthood. \u003cem\u003eEur. J. Psychotraumatol\u003c/em\u003e. \u003cb\u003e11\u003c/b\u003e (1), 1708618 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePrachason, T. et al. Gender differences in the associations between childhood adversity and psychopathology in the general population. \u003cem\u003eSoc. Psychiatry Psychiatr Epidemiol.\u003c/em\u003e \u003cb\u003e59\u003c/b\u003e (5), 847\u0026ndash;858 (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFlasbeck, V., Moser, D., Kumsta, R. \u0026amp; Brune, M. The OXTR single-nucleotide polymorphism rs53576 moderates the impact of childhood maltreatment on empathy for social pain in female participants: Evidence for differential susceptibility. \u003cem\u003eFront. Psychiatry\u003c/em\u003e ; 9. (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSenaratne, D. N. S. et al. The impact of adverse childhood experiences on multimorbidity: a systematic review and meta-analysis. \u003cem\u003eBMC Med.\u003c/em\u003e \u003cb\u003e22\u003c/b\u003e (1), 315 (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMerrick, M. T. Vital signs: estimated proportion of adult health problems attributable to adverse childhood experiences and implications for prevention\u0026mdash;25 states, 2015\u0026ndash;2017. \u003cem\u003eMMWR Morbidity Mortal. Wkly. Rep.\u003c/em\u003e ; 68. (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKessler, R. C. et al. Childhood adversities and adult psychopathology in the WHO World Mental Health Surveys. \u003cem\u003eBr. J. Psychiatry\u003c/em\u003e. \u003cb\u003e197\u003c/b\u003e (5), 378\u0026ndash;385 (2010).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcLaughlin, K. A. et al. Childhood adversities and post-traumatic stress disorder: evidence for stress sensitisation in the World Mental Health Surveys. \u003cem\u003eBr. J. Psychiatry\u003c/em\u003e. \u003cb\u003e211\u003c/b\u003e (5), 280\u0026ndash;288 (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHughes, K. et al. The effect of multiple adverse childhood experiences on health: a systematic review and meta-analysis. \u003cem\u003eLancet Public. Health\u003c/em\u003e. \u003cb\u003e2\u003c/b\u003e (8), e356\u0026ndash;e66 (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJonker, I., Rosmalen, J. G. M. \u0026amp; Schoevers, R. A. Childhood life events, immune activation and the development of mood and anxiety disorders: the TRAILS study. \u003cem\u003eTranslational Psychiatry\u003c/em\u003e. \u003cb\u003e7\u003c/b\u003e (5), e1112\u0026ndash;e (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcLaughlin, K. A., Sheridan, M. A. \u0026amp; Nelson, C. Adverse childhood experiences and brain development: Neurobiological mechanisms linking the social environment to psychiatric disorders. \u003cem\u003elife course approach mental disorders\u003c/em\u003e ; 249. (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMyers, A. J. et al. Variation in the oxytocin receptor gene is associated with increased risk for anxiety, stress and depression in individuals with a history of exposure to early life stress. \u003cem\u003eJ. Psychiatr Res.\u003c/em\u003e \u003cb\u003e59\u003c/b\u003e, 93\u0026ndash;100 (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJohn, S. \u0026amp; Jaeggi, A. V. Oxytocin levels tend to be lower in autistic children: A meta-analysis of 31 studies. \u003cem\u003eAutism\u003c/em\u003e \u003cb\u003e25\u003c/b\u003e (8), 2152\u0026ndash;2161 (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePierzynowska, K. et al. Roles of the Oxytocin Receptor (OXTR) in Human Diseases. \u003cem\u003eInt. J. Mol. Sci.\u003c/em\u003e ; \u003cb\u003e24\u003c/b\u003e(4). (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLondono Tobon, A., Newport, D. J. \u0026amp; Nemeroff, C. B. The Role of Oxytocin in Early Life Adversity and Later Psychopathology: a Review of Preclinical and Clinical Studies. \u003cem\u003eCurr. Treat. Options Psychiatry\u003c/em\u003e. \u003cb\u003e5\u003c/b\u003e (4), 401\u0026ndash;415 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJawad, M. Y., Ahmad, B. \u0026amp; Hashmi, A. M. Role of Oxytocin in the Pathogenesis and Modulation of Borderline Personality Disorder: A Review. \u003cem\u003eCUREUS J. Med. Sci.\u003c/em\u003e ; \u003cb\u003e13\u003c/b\u003e(2). (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcQuaid, R. J., McInnis, O. A., Stead, J. D., Matheson, K. \u0026amp; Anisman, H. A paradoxical association of an oxytocin receptor gene polymorphism: early-life adversity and vulnerability to depression. \u003cem\u003eFront. NeuroSci.\u003c/em\u003e \u003cb\u003e7\u003c/b\u003e, 128 (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eValstad, M. et al. The correlation between central and peripheral oxytocin concentrations: A systematic review and meta-analysis. \u003cem\u003eNeurosci. Biobehavioral Reviews\u003c/em\u003e. \u003cb\u003e78\u003c/b\u003e, 117\u0026ndash;124 (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUzun, N., Akca, O. F., Kilinc, I. \u0026amp; Balci, T. Oxytocin and vasopressin levels and related factors in adolescents with social phobia and other anxiety disorders. \u003cem\u003eClin. Psychopharmacol. Neurosci.\u003c/em\u003e \u003cb\u003e20\u003c/b\u003e (2), 330\u0026ndash;342 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCDC \u0026amp; CfDCaP Adverse Childhood Experiences Prevention Strategy. \u003cem\u003eAtlanta, GA: National Center for Injury Prevention and Control\u003c/em\u003e. \u003cem\u003eCenters Disease Control Prev.\u003c/em\u003e, (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen, Y-J. et al. Linking childhood trauma to the psychopathology of schizophrenia: the role of oxytocin. \u003cem\u003eSchizophrenia (Heidelberg Germany)\u003c/em\u003e. \u003cb\u003e10\u003c/b\u003e (1), 24 (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMielke, E. L. et al. Adverse childhood experiences mediate the negative association between borderline personality disorder symptoms and plasma oxytocin. \u003cem\u003eProg Neuropsychopharmacol. Biol. Psychiatry\u003c/em\u003e. \u003cb\u003e125\u003c/b\u003e, 110749 (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKartal, F., Uğur, K., Mete, B., Demirkol, M. E. \u0026amp; Tamam, L. The Relationship Between the Oxytocin Level and Rejection Sensitivity, Childhood Traumas, and Attachment Styles in Borderline Personality Disorder. \u003cem\u003ePsychiatry Investig\u003c/em\u003e. \u003cb\u003e19\u003c/b\u003e (3), 239\u0026ndash;246 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSpeck, L. G. et al. Endogenous oxytocin response to film scenes of attachment and loss is pronounced in schizophrenia. \u003cem\u003eSoc. Cognit. Affect. Neurosci.\u003c/em\u003e \u003cb\u003e14\u003c/b\u003e (1), 109\u0026ndash;117 (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBomann, A. C. et al. The neurobiology of social deficits in female patients with borderline personality disorder: The importance of oxytocin. \u003cem\u003ePersonality mental health\u003c/em\u003e. \u003cb\u003e11\u003c/b\u003e (2), 91\u0026ndash;100 (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJobst, A. et al. Lower Oxytocin Plasma Levels in Borderline Patients with Unresolved Attachment Representations. \u003cem\u003eFront. Hum. Neurosci.\u003c/em\u003e ; 10. (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBertsch, K., Schmidinger, I., Neumann, I. D. \u0026amp; Herpertz, S. C. Reduced plasma oxytocin levels in female patients with borderline personality disorder. \u003cem\u003eHorm. Behav.\u003c/em\u003e \u003cb\u003e63\u003c/b\u003e (3), 424\u0026ndash;429 (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee, H., King, A. P., Li, Y. \u0026amp; Seng, J. S. Oxytocin receptor gene, post-traumatic stress disorder and dissociation in a community sample of European American women. \u003cem\u003eBJPsych Open.\u003c/em\u003e ; 8. (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang, M., Liu, N., Chen, H. \u0026amp; Zhang, N. Oxytocin receptor gene, childhood maltreatment and borderline personality disorder features among male inmates in China. \u003cem\u003eBMC Psychiatry\u003c/em\u003e ; 20. (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTollenaar, M. S., Molendijk, M. L., Penninx, B. W. J. H., Milaneschi, Y. \u0026amp; Antypa, N. The association of childhood maltreatment with depression and anxiety is not moderated by the oxytocin receptor gene. \u003cem\u003eEur. Arch. Psychiatry Clin. NeuroSci.\u003c/em\u003e \u003cb\u003e267\u003c/b\u003e (6), 517\u0026ndash;526 (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCristobal-Narvaez, P. et al. The role of stress-regulation genes in moderating the association of stress and daily-life psychotic experiences. \u003cem\u003eActa Psychiatry. Scand.\u003c/em\u003e \u003cb\u003e136\u003c/b\u003e (4), 389\u0026ndash;399 (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoh, K. K., Kanahara, N., Chiu, Y-H. \u0026amp; Lu, M-L. The impact of childhood trauma exposure on social functioning in schizophrenia: the moderated mediation role of oxytocin and oxytocin receptor gene polymorphisms. \u003cem\u003ePsychol. Med.\u003c/em\u003e \u003cb\u003e54\u003c/b\u003e (5), 980\u0026ndash;992 (2024).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Severe mental illness, Adverse childhood experiences, Oxytocin, Oxytocin receptor gene variations, Single nucleotide polymorphisms","lastPublishedDoi":"10.21203/rs.3.rs-6628062/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6628062/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAdverse childhood experiences (ACEs) are recognized as a transdiagnostic risk factor for developing severe mental illnesses (SMIs), including schizophrenia (SCZ), major depressive disorder (MDD), or bipolar disorder (BPD). However, the specific associations and underlying mechanisms linking ACEs and SMIs remain unclear. In recent years, oxytocin (OT), a neuropeptide known for its role in social bonding and stress regulation, has emerged as a crucial pathway linking SMIs and ACEs. This study aimed to investigate the relationship between SMIs among individuals with a history of childhood adversity and oxytocin dysregulation both at biochemical and genetic levels. We aimed to identify the mechanisms through which OT dysfunction may contribute to the onset, progression, and symptomatology of SMIs. A comprehensive search of PsycINFO, MEDLINE, Web of Science, and PubMed was undertaken to identify studies reporting the impact of ACEs with or without SMIs and measurements of OT or single nucleotide polymorphisms (SNPs) in the gene encoding oxytocin receptor (\u003cem\u003eOXTR\u003c/em\u003e). Comparisons were made between SMI groups and healthy controls (HCs). We excluded non-English studies, animal research, and extreme trauma contexts. Data were extracted and appraised independently by two reviewers using the Mixed Methods Appraisal Tool (MMAT). Primary outcomes included group differences in ACE scores, a measure that reflects the type, quantity, and severity of childhood trauma. We also compared group differences in OT levels, genotype frequencies of \u003cem\u003eOXTR\u003c/em\u003e SNPs, and pathways linking ACEs, OT dysregulation, and SMIs. This systematic review protocol was registered in PROSPERO: CRD42024555819. Of 513 reports identified by the search, 14 studies with 5,624 participants met the inclusion criteria. Most studies (n\u0026thinsp;=\u0026thinsp;13; 92.86%) reported individuals with SMIs exhibited significantly higher ACE scores than HCs. Among the fourteen studies that measured OT levels, 66% (n\u0026thinsp;=\u0026thinsp;6) reported lower OT levels in SMIs irrespective of the subgroups, including in SCZ and borderline personality disorder (BoPD). Several polymorphisms in \u003cem\u003eOXTR\u003c/em\u003e were found to have a modulatory effect on SMI outcomes. A subset of SNPs conferred susceptibility, whereas others served as protective factors. This review highlights a strong association between ACEs, OT system dysregulation, and SMI susceptibility, particularly in SCZ and BoPD. However, methodological inconsistencies, gender biases, and reliance on peripheral OT measurements require further investigation. Future longitudinal studies are needed to clarify pathways and inform clinical interventions aimed at mitigating the impact of ACEs on mental health.\u003c/p\u003e","manuscriptTitle":"Oxytocin Dysfunction in Severe Mental Illnesses following Adverse Childhood Experiences: a systematic review","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-13 11:35:29","doi":"10.21203/rs.3.rs-6628062/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"25919866-4b1d-44f0-b933-0c8c51c2a972","owner":[],"postedDate":"May 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":48308317,"name":"Biological sciences/Neuroscience"},{"id":48308318,"name":"Biological sciences/Neuroscience/Stress and resilience"}],"tags":[],"updatedAt":"2025-05-29T08:53:17+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-13 11:35:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6628062","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6628062","identity":"rs-6628062","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}