Probing the oral-brain connection: Oral microbiome patterns in a large community cohort with anxiety, depression, and trauma symptoms, and periodontal outcomes

Probing the oral-brain connection: Oral microbiome patterns in a large community cohort with anxiety, depression, and trauma symptoms, and periodontal outcomes | 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 Probing the oral-brain connection: Oral microbiome patterns in a large community cohort with anxiety, depression, and trauma symptoms, and periodontal outcomes Stefanie Malan-Müller, Rebeca Vidal, Esther O'Shea, Eduardo Montero, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4328261/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Oct, 2024 Read the published version in Translational Psychiatry → Version 1 posted 11 You are reading this latest preprint version Abstract The role of the oral microbiome in mental health has recently been appreciated within the proposed oral-brain axis. This study examined the structure and composition of the salivary microbiome in a large-scale population-based cohort of individuals reporting mental health symptoms ( n = 306) compared to mentally healthy controls ( n = 164) using 16S rRNA sequencing. Mental health symptoms were evaluated using validated questionnaires and included depression, anxiety, and posttraumatic stress disorder, with accompanying periodontal outcomes. Participants also indicated current or previous diagnoses of anxiety, depression, periodontitis, and gingivitis. Mental and periodontal health variables influenced the overall composition of the oral microbiome. PTSD symptoms correlated with reduced Haemophilus sputorum and elevated Prevotella histicola levels. Anxiety disorder diagnosis was associated with decreased Neisseria elongate and increased Oribacterium asaccharolyticum . P. histicola abundance was also positively associated with depressive scores and negatively associated with psychological quality of life. A higher abundance of Shuttleworthia and a lower abundance of Capnocytophaga were evident in those who reported a clinical periodontitis diagnosis. Functional prediction analysis revealed a potential role for tryptophan metabolism/degradation in the oral-brain axis, which was confirmed by lower plasma serotonin levels across symptomatic groups. Higher Eggerthia and lower Haemophilus parainfluenzae abundance were associated with reported clinical periodontitis diagnosis and psychotherapeutic efficacy. This study sheds light on the intricate interplay between oral microbiota, periodontal outcomes, and mental health, emphasizing the need for further exploration of the oral-brain axis to pave the way for novel therapeutic interventions and predicting therapeutic response. Biological sciences/Genetics/Genomics/Comparative genomics Health sciences/Diseases/Psychiatric disorders/Depression Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Mental health disorders place a heavy burden on patients, families, societies, and global economies. In 2019, an estimated 418 million disability-adjusted life years (DALYs) could be attributable to mental disorders [ 1 ]. In 2017, depression was the leading cause of disability globally, with an estimated 322 million people living with depression [ 2 ], whilst about 260 million people suffered from anxiety disorders, and many suffered with additional comorbidities [ 3 ]. Mental disorders were the leading cause of the health-related burden of disease, and to worsen the situation, the COVID-19 pandemic has left in its wake a steep rise in the global prevalence of anxiety and depressive disorders [ 4 ]. Several factors, including economic insecurity, work-related stress, collective trauma, inequality, modern lifestyles, global events, and environmental factors, have likely contributed to the increased prevalence of mental health disorders [ 5 ]. Modern lifestyles, characterized by high stress levels, processed diets, excessive sanitation practices, and antibiotic use, alongside environmental changes like increased pollutants, climate change, and urbanization, have shifted human microbiota towards an industrialized state [ 6 ]. These microbiota alterations, coupled with the loss of specific functional attributes, may lead to suboptimal disease-promoting microbial communities, worsening compromised mental health [ 6 ]. The burden of mental health disorders is compounded by treatment limitations such as non-adherence, treatment resistance, and relapse [ 7 – 9 ], highlighting the necessity for innovative treatment modalities. The human holobiont, comprising the human host and its symbiotic microorganisms, plays a crucial role in health and disease [ 10 , 11 , 12 ]. While much attention has been given to the gut-brain axis, emerging evidence suggests that the oral microbiota, a less explored niche, may also influence the central nervous system and behavior [ 13 , 14 ]. The oral cavity hosts a diverse array of bacteria, and dysregulation can lead to disease. Periodontitis, a chronic bacterial infection affecting nearly half the global population [ 15 ], triggers systemic inflammation through pro-inflammatory cytokine release and invasion by periodontal keystone pathogens like Porphyromonas gingivalis ( P. gingivalis ) [ 16 ]. Periodontitis not only contributes to chronic inflammatory conditions like atherosclerosis, diabetes, and cardiovascular diseases [ 17 ] [ 18 ] [ 19 ] but also shows associations with psychiatric disorders [ 20 ], suggesting involvement in the oral-brain axis. A longitudinal study spanning 10 years found a higher incidence of subsequent depression in individuals with periodontitis compared to those without [ 21 ], indicating a potential causal relationship between periodontitis and major depression. Additionally, recent research has identified specific bacterial taxa implicated in periodontal disease as well as anxiety, depressive disorders, and trauma-related disorders [ 22 ]. Pathogenic periodontal bacteria can impact the CNS through various pathways, both directly and indirectly [ 22 ]. Direct routes include bloodstream transmission or areas with compromised blood-brain barrier (BBB) integrity [ 23 ]. Indirectly, they induce pro-inflammatory cytokine production, activating endothelial cells expressing tumor necrosis factor (TNF)-α and interleukin-1 (IL-1) β receptors, which signal perivascular macrophages, leading to neuroinflammation [ 24 ]. Keystone pathogens widen intercellular spaces in periodontal pockets, causing epithelial rupture and a "leaky mouth" [ 25 ], facilitating lipopolysaccharide (LPS) access to circulation, activating the immune system and the hypothalamic pituitary adrenal (HPA) axis, influencing CNS function [ 26 , 24 ]. Other entry points include circumventricular organs, the choroid plexus [ 23 , 27 ], and olfactory/trigeminal nerves [ 28 ]. Brain-resident microglia can be influenced by periodontal bacteria via leptomeninges [ 26 ]. Periodontal pathogens also affect gut microbial composition/function directly via enteral or indirectly via hematogenous transmission [ 29 ]. Clinical data on the oral microbiome's connection to mental health disorders are limited. A study utilizing genetic association analysis and Mendelian randomization to assess links between salivary-tongue dorsum microbiome interactions and anxiety/depression, found significant associations and causal effects [ 30 ], especially, Eggerthia was linked to anxiety and depression across multiple databases. Another study in adolescents ( n = 66) noted a differential abundance of Actinomyces , Spirochaetaceae , Fusobacterium , and Treponema in those with anxiety and depression symptoms [ 31 ]. Wingfield et al. compared oral microbial composition in depressed young adults ( n = 40), discovering 21 bacterial taxa with differing levels compared to controls, including increased Neisseria spp . and Prevotella nigrescens [ 32 ]. To unravel the oral-brain axis's role in anxiety and depression, larger studies across diverse age groups are needed, gathering both microbiome and mechanistic data. Clinical data linking the oral microbiome to mental health disorders are limited. A study employing genetic association analysis and Mendelian randomization found significant associations and causal effects between salivary-tongue dorsum microbiome interactions and anxiety/depression, with Eggerthia notably linked to both conditions across multiple databases [ 30 ]. Another study involving adolescents ( n = 66) observed differing abundances of Actinomyces , Spirochaetaceae , Fusobacterium , and Treponema in individuals with symptoms of anxiety and depression [ 31 ]. Wingfield et al. compared the oral microbial composition in depressed young adults ( n = 40), identifying 21 bacterial taxa with varying levels compared to controls, including increased Neisseria spp . and Prevotella nigrescens [ 32 ]. Larger studies encompassing diverse age groups and gathering microbiome and mechanistic data are needed to elucidate the role of the oral-brain axis in anxiety and depression. This study aimed to contribute to the limited oral microbiome data currently available, and to explore the oral-brain axis, by investigating the salivary microbiome in individuals with symptoms of anxiety, depression, and posttraumatic stress disorder (PTSD) with periodontal outcomes. Methods Study participant evaluation and enrollment This cohort comprised two Spanish study populations from PsicoBioma ( n = 186, March 2021 - Jan 2022) and TRIAD ( n = 284, Nov 2021 - Dec 2022), both based on population-based microbiome projects. PsicoBioma recruited participants from Spain, while TRIAD recruited from Madrid, Barcelona, Vitoria, and Oviedo municipalities (allowing blood collection). Both cohorts provided saliva samples and completed similar online questionnaires. TRIAD also provided blood samples for plasma analysis and completed a more comprehensive periodontal health questionnaire. The research adhered to The Code of Ethics of the World Medical Association (Declaration of Helsinki) for human experiments, and data processing followed Spanish Organic Law 3/2018 on Personal Data Protection and Digital Rights Guarantee (BOE 16673 of 6 Dec 2018) and its 17th Additional Provision. Approval was obtained from the Ethics Committees of Hospital Clínico San Carlos (Madrid), Medical Research Ethics Committee of Asturias, Basque Medicine Research Ethics Committee, and Drug Research Ethics Committee of Hospital de la Santa Creu i Sant Pau (PSQ-19-2 C.I. 196/474-E). All research participants provided online, written informed consent. The study recruited healthy controls, participants with a current/previous diagnosis of anxiety, depressive, or trauma-related disorders, or individuals who were experiencing these symptoms. Spanish residents, 18 years or older, who were proficient in reading and understanding Spanish were included. Individuals who used antibiotics within the previous six months, and those diagnosed with any other major psychiatric disorders including psychotic disorders, personality disorders, or neurodegenerative disorders, were excluded. Demographic and clinical data Demographic, health, and clinical data were collected using a secure online questionnaire. Psychological evaluations relied on standardized self-report questionnaires validated for the Spanish population; this study focused on symptoms rather than formal diagnoses. However, participants also indicated on the questionnaire whether they had a previous/current clinical diagnosis of anxiety or depression (“diagnosis” henceforth refers to clinical diagnoses, and “symptoms” refers to self-report questionnaire data). Depressive symptoms were assessed using the Centre for Epidemiologic Studies Depression (CESD) scale; state and trait anxiety symptoms were evaluated using the state-trait anxiety inventory (STAI). The posttraumatic stress disorder (PTSD) Checklist for the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5, PCL-5), and the Childhood Trauma Questionnaire-Short Form (CTQ-SF) evaluated trauma exposure. Additionally, quality of life was measured using the World Health Organization Quality Of Life Questionnaire (WHOQOL). Psychiatric symptoms were determined based on the following criteria: Depressive symptoms: CESD scores of 16–24 indicated mild and 25–55 severe depressive symptoms [ 33 ]. PTSD symptoms: PCL-5 score > 33 + more than 3 symptom clusters [ 34 ]. State anxiety symptoms: STAI-S scores > 41; trait anxiety symptoms: STAI-T scores > 45; CTQ-SF [ 35 ] total score was used to evaluate the severity of childhood maltreatment. The TRIAD cohort completed a periodontal health questionnaire [ 36 ] (validated for the Spanish population [ 37 ]) to predict severe periodontitis, according to Montero et al., 2020 [ 37 ]. Specifically, severe periodontitis was defined according to three criteria: (i) the Centers for Disease Control/American Academy of Periodontology (CDC/AAP) case definition [ 38 ], henceforth referred to as SeverePerioCDCAAP ; (ii) the presence of ≥ 50% of teeth with clinical attachment level (CAL) ≥ 5 mm, henceforth referred to as TeethCAL5 ; (iii) the presence of ≥ 25% of teeth with probing pocket depth (PPD) ≥ 6 mm, henceforth referred to as TeethPPD6 . In addition, participants also indicated whether they had a previous/current clinical diagnosis of periodontitis and/or gingivitis (“diagnosis” refers to a self-reported clinical diagnosis, and “predicted severe periodontitis” refers to self-reported questionnaire data). Blood collection and processing Whole blood (10ml) was collected using BD Vacutainer® EDTA tubes. Blood was centrifuged at 1800 rpm for 10 minutes at room temperature, and the resulting supernatant (plasma) was transferred into clean 1.5ml Eppendorf tubes for storage at -80°C for later use. Kynurenine, tryptophan, and serotonin quantification in plasma Plasma levels of kynurenine (KYN), tryptophan (TRP), and serotonin (5-HT) were measured using High-performance liquid chromatography (HPLC). TRP and 5-HT were detected fluorometrically at excitation/emission wavelengths of 270/360 nm and 290/398 nm, respectively (Waters 2475, Multi fluorescence Detector; Waters, Milford, MA, USA). The ratios of KYN or 5-HT to TRP concentrations were calculated and used as a measure of TRP degradation (see Supplementary Materials for details). Bacterial DNA extraction, 16S rRNA gene sequencing and analysis Participants self-collected saliva samples in DNA/RNA Shield Safe Collect Saliva Collection tubes (Zymo Research, Irvine, California, USA), from which microbial DNA was extracted (ZymoBIOMICS DNA Miniprep Kit, Zymo Research). Bacterial 16S rRNA gene V3-4 amplicons were generated, using previously described primers [ 39 ] and sequenced (2 x 300bp paired-end) (Centre de Regulació Genòmica, Barcelona, Spain), on the Illumina NextSeq2000 platform (see Supplementary Material for details). Quality control of FASTQ sequencing files was performed using fastqc and multiqc. Raw sequence reads were [ 41 ], de-replicated and de-noised to combine identical reads into amplicon sequence variants (ASVs) and construct consensus quality profiles for each combined set of sequences ( dada2 version 3.11 [ 40 ]). Following chimeras removal, a consensus paired-end reads file was generated for feature construction and downstream analysis. Taxonomic binning of classified sequences was built using a local copy of the Ribosomal Database Project (RDP) Classifier (Train Set 19 [ 42 ]), and normalized data were produced from the relative abundance of taxa present in each sample. A feature table of 54 817 unique ASVs with an average read length of 391 nucleotides in 470 samples was consequently constructed (following pre-processing, the minimum number of reads per sample was 18 868, and the average number of reads per sample was 95 763). Statistical analyses Data was analyzed using bioinformatics and statistical analysis packages in R [ 41 ], including the packages dada2 (version 3.18, [ 40 ]), vegan (version 2.6.4, [ 43 ]), phyloseq (version 1.46.0, [ 44 ]), ggplot2 (version 3.4.4, [ 45 ]), CoDaSeq (version 0.99.7, [ 46 , 47 ]. For clinical and demographic data, continuous variables were summarized as means (M) and standard deviations (SD) if normally distributed or as medians and interquartile ranges (IQRs) if non-normally distributed. To assess differences in the metadata variables between symptomatic and control groups, Student's t -tests and Wilcoxon rank sum tests were used to assess differences between normally and non-normally distributed data (normality tested using Shapiro-Wilk Normality Test), respectively. Categorical data were summarized as counts ( n ) and percentages, and χ 2 or Fisher exact tests were used to assess differences between groups, where appropriate. Significance was defined as p ≤ 0.05. The Simpson index was used to evaluate α-diversity [ 48 ]. Taxa were agglomerated to genus level, assigning species-level where possible. Data was transformed to relative abundance out of 100 to account for differences in total depth per sample. Variance filtering was performed ( genefilter function, version 1.84.0), which removed taxa with the lowest 40% variance. Abundance matrices were centred log-ratio (clr)-transformed, using the minimum proportional abundance detected for each taxon for the imputation of zeros. The ordination of community variation was visualized using multidimensional scaling (MDS) of genus-level Aitchison distances. The capscale function ( vegan package) [ 43 ] was used to determine the contribution of metadata variables to microbiome community variation. The ASV table was filtered to retain taxa observed in at least 15% of participants. Associations between taxonomic abundance and metadata variables were analyzed using a linear modeling approach ( fw_glm function, Tjazi package) [ 49 ]), whilst adjusting for covariates including age, Body mass index (BMI), smoking status, and cholesterol medication use. We performed false discovery rate (FDR) correction using the Benjamini-Hochberg procedure and significance was defined as q ≤ 0.1. We utilized PICRUSt2 [ 50 ] to predict the central nervous system (CNS)-related functional potential of oral taxa, by focusing on gut-brain modules (GBMs) [ 51 ]. Associations between GBMs and mental health outcomes were tested using the same linear modeling approach as previously described, with significance set at q ≤ 0.1. Results Clinical and demographic characteristics Clinical and demographic characteristics of the depressive ( n = 148), state ( n = 256) and trait anxiety ( n = 281), and PTSD ( n = 73) symptomatic cohorts (according to criteria described in the Methods and Materials), and healthy controls (no significant mental health symptoms) ( n = 164) are described in Tables 1–4. In our cohort of 470 individuals, 306 presented with at least one or a combination of the aforementioned symptoms. Females constituted 72% of our cohort, and the median age was 40 years. Comorbidity of these psychiatric symptoms was common; of the 232 individuals who had both state and trait anxiety symptoms, 133 of them also had depressive symptoms (57.3%), 67 had comorbid PTSD symptoms (28.9%), and 52 (22.4%) had PTSD and depressive symptoms. Of the 148 individuals with depressive symptoms, 144 (97.3%) also had trait anxiety symptoms, and 54 (36.5%) had symptoms of PTSD. A total of 34 (7%) individuals had a current clinical diagnosis of periodontitis, and 30 (11%) had a gingivitis diagnosis. The self-reported periodontal health questionnaire administered to most of the TRIAD cohort ( n = 196) (unavailable for the PsicoBioma cohort) showed 81 individuals (41%) had probable severe periodontitis using TeethPPD6 criteria, 93 (47%) had it based on the TeethCAL5 criteria, and 106 (54%) had it based on the Centers for Disease Control (CDC)/American Academy of Periodontology (AAP) criteria (SeverePerioCDCAAP). Periodontal and mental health variables influence oral microbiome community composition The Simpson alpha diversity index showed no significant differences between the mental health symptomatic groups and controls. However, among individuals who completed the self-reported periodontal health questionnaire ( n = 196, 48%), those with receding gums had a lower Simpson alpha diversity index compared to those without (Wilcoxon rank-sum tests, p = 0.005, r = 0.17, n = 284). Several variables influenced the overall oral microbial composition (β-diversity), with smoking status eliciting the largest effect, followed by age, living environment (city, town, or rural setting), and alveolar bone loss. The most significant subset ( R 2 ≥ 0.002 and q ≤ 0.1) of variables is illustrated in Fig. 1 (Supplementary Table 1 contains the full set of significant variables). Oral taxa associated with trauma, mental health outcomes, and psychological quality of life Our symptomatic cohort reported significantly higher levels of childhood trauma compared to controls. Individuals who reported high levels of emotional neglect had significantly lower abundance of Streptococcus mutans (GLM q = 0.07, β = -0.6, n = 470) (Fig. 2 a). Individuals with PTSD symptoms ( n = 73) had significantly lower relative abundance of Haemophilus sputorum ( H. sputorum ) (GLM, q = 0.09, β = -1.2, n = 237) and higher levels of Prevotella histicola ( P. histicola ) (GLM, q = 0.09, β = 1.6, n = 237), compared to controls ( n = 164) (Fig. 2 b). Those with a current anxiety disorder diagnosis ( n = 134) harbored significantly lower levels of Neisseria (GLM, q = 0.001, β = -0.96, n = 470), specifically Neisseria elongate ( N. elongate ) (GLM, q = 0.09, β = -0.94, n = 470) and significantly higher levels of Oribacterium asaccharolyticum ( O. asaccharolyticum ) (GLM q = 0.03, β = 0.53, n = 470) compared to those without a current diagnosis ( n = 336) (Fig. 2 c). Interestingly, higher relative abundance of P. histicola was also evident in individuals with higher CESD depressive scores (GLM q = 0.05, β = 0.04, n = 470) (Fig. 2 d) and those with poor psychological quality of life scores (GLM q = 0.08, β = -0.2, n = 470) (Fig. 2 e). Individuals with higher CESD scores also had a higher relative abundance of Lancefieldella (GLM q = 0.05, β = 0.01, n = 470) and O. asaccharolyticum (GLM q = 0.05, β = 0.02, n = 470), however, the effect sizes were relatively small (Fig. 2 f). Oral microbiome signatures related to periodontal health Several oral taxa were associated with periodontal health variables (Fig. 3 , Supplementary Table 2). The abundance of Shuttleworthia was higher in participants with a self-reported periodontitis diagnosis and those with predicted severe periodontitis based on the TeethCAL5 criteria. The abundance of Capnocytophaga was lower in participants with a self-reported clinical periodontitis diagnosis and those with predicted severe periodontitis based on the TeethPPD6 criteria. Several common taxa were differentially abundant in those with a self-reported clinical periodontitis diagnosis and those who reported loose teeth (a symptom of periodontitis), including a higher relative abundance of Tannerella forsythia , Metaprevotella , Fretibacterium fastidiosum , and lower relative abundance of Prevotellaceae and Haemophilus parainfluenzae . Three taxa had a higher abundance in participants with a self-reported clinical gingivitis diagnosis, Parvimonas , Gallibacter , and Eggerthia ; Eggerthia was the only common taxon between periodontitis and gingivitis diagnosis, whose abundance was altered similarly for both diagnoses. Functional potential of the oral microbiome: possible implications for mental health outcomes Functional prediction revealed lower tryptophan metabolism/degradation in individuals with PTSD symptoms (GLM, q = 0.02, β = -0.8, n = 470), those who experienced higher levels of childhood trauma (GLM, q = 0.09, β = -0.01), and those with lower quality of life (specifically personal relationships) (GLM, q = 0.06, β = 0.06). Interestingly, lower metabolism/degradation of tryptophan was also predicted in individuals with predicted severe periodontitis based on the TeethCAL5 criteria ( n = 93) and TeethPPD6 criteria ( n = 81) (GLM, q = 0.07, β = -0.52, n = 196 and GLM, q = 0.02, β = -0.6, n = 196, respectively). Figure 4 illustrates the full set of predicted gut-brain modules (GBMs) linked to severe periodontitis, mental health, childhood trauma, and quality of life. Plasma measures Analyses to confirm lower TRP metabolism/degradation revealed lower plasma levels of 5-HT and the ratio of 5-HT/TRP in individuals with depressive symptoms (Wilcoxon rank-sum test, p < 0.01, mean difference (MD) = 0.8, and p < 0.01, MD = 0.9, n = 282 respectively), state anxiety symptoms ( p < 0.01, MD = 0.6, and p < 0.01, MD = 0.5, n = 282 respectively), trait anxiety symptoms ( p < 0.01, MD = 0.6, and p < 0.01, MD = 0.6, n = 282 respectively), and PTSD symptoms ( p < 0.01, MD = 1.0, and p < 0.01, MD = 0.9, n = 282 respectively) compared to healthy controls (Fig. 5 ). Oral microbes and therapeutic response Interestingly, two taxa associated with a current self-reported clinical diagnosis of periodontitis and/or gingivitis were also associated with self-reported efficacy of psychotherapy, namely Eggerthia and Haemophilus parainfluenza . Eggerthia was present at a higher relative abundance in those with a current self-reported clinical diagnosis of periodontitis and/or gingivitis and in individuals with poor self-reported psychotherapeutic efficacy (GLM q = 0.12, r = -0.62, n = 322), whereas the abundance of H. parainfluenza was lower in these individuals (GLM q = 0.12, r = 0.60, n = 322), although the association did not reach the threshold for statistical significance of q ≤ 0.1. Discussion This study represents one of the largest oral microbiome investigations in mental health, to date. The composition of the overall oral microbiome was significantly impacted by several mental health variables (including clinical diagnoses of anxiety disorders or depression), as well as periodontal symptoms, predicted severe periodontitis. and self-reported clinical diagnoses of gingivitis and/or periodontitis. These findings correlate with previous research highlighting the significant effects of mental [ 32 ] and periodontal [ 52 , 53 ] health on the oral microbiome beta diversity. Various additional factors shaped the oral microbiome composition, aligning with earlier research emphasizing the impact of factors such as smoking [ 54 ], BMI, [ 55 ], age [ 52 ], arthritis [ 56 ], gout [ 57 ], and geographic location [ 58 ] on the oral microbiome. Although none of the mental health variables or self-reported periodontal outcomes influenced Simpson’s diversity, lower diversity was evident among individuals with self-reported receding gums. Earlier studies also failed to detected differences in alpha diversity between individuals with depression and anxiety compared to controls [ 31 ], and between periodontitis patients and controls [ 53 ]. Several taxa were associated with mental health, trauma, and well-being. P. histicola is of particular interest, with a higher relative abundance in individuals with PTSD symptoms, those with higher CESD scores, and those with poorer interpersonal quality of life. Prevotella is the second most common bacteria dominating the oral cavity and this diverse genus includes several species. P. histicola is a facultative oral pathogen, which can cause pathologies such as caries and periodontitis [ 59 , 60 ]. Previously, lower levels of Prevotella were noted in the oropharyngeal microbiota in schizophrenia and mania cohorts compared to controls [ 61 ], and a negative association was observed between the abundance of Prevotella and distress [ 62 ]. Importantly, Prevotella is a genus strongly associated with waking samples, and the majority of our samples were collected close to waking, which could explain the discrepancies between the findings. Furthermore, the majority of studies report on genus level, whereas our finding is for the species P. histicola , and research has shown that species from the same genus could fulfill vastly different roles [ 63 , 64 ], therefore future studies should aim for higher resolution of taxonomic classification to disentangle taxonomic functions and disease associations. A lower relative abundance of N. elongata in individuals with a clinical diagnosis of anxiety disorders echoes similar observations in patients with schizophrenia and mania [ 61 ]. Conversely, previous research in young adults linked depression with increased levels of Neisseria spp [ 32 ]. Discrepancies in these findings may be attributed to differences in sample size and age of the population, as well as the resolution of microbial analysis (species vs. genus). Neisseria species, integral members of the oropharyngeal flora [ 65 ], play crucial roles in maintaining oral [ 66 ] and cardiovascular health [ 66 , 67 ]. Their presence correlates with good oral health, attributed to their aerobic, nitrite-reducing capabilities essential for gum health [ 66 – 68 ]. Moreover, Neisseria -dominated oral microbiomes exhibit a reduced likelihood of hosting the cariogenic pathogen S. mutans [ 69 ]. Notably, we detected a higher abundance of S. mutans in individuals reporting childhood emotional neglect, a known risk factor for mental health disorders. These findings underscore the intricate interplay between oral microbial composition, mental health outcomes, and early life adversity. The involvement of cross-feeding and interactions among microbial taxa adds complexity to understanding comorbidity and risk factors in mental health conditions. Individuals with an anxiety disorder diagnosis and higher CESD scores harbored a higher abundance of O. asaccharolyticum . This correlates with increased abundance reported in elderly people receiving treatment for anxiety, depression, and insomnia [ 70 ]. Furthermore, an increased abundance of the Odoribacter genus was also noted in the gut microbiomes of patients with depression [ 71 ], a preclinical model of depression [ 72 ], and individuals with periodontal disease [ 73 ]. Elevated levels of the Odoribacter genus were also detected in the oral microbiome of periodontitis patients [ 74 ]. These findings underscore the potential interconnectivity between oral and gut microbiomes and taxa implicated in both oral and periodontal health, with implications for the oral-gut-brain axis. Furthermore, in a randomized, double-blind placebo-controlled trial, synbiotics reduced both systemic inflammation and systemic lupus erythematosus disease activity, whilst simultaneously also depleting O. asaccharolyticum from the microbiome [ 75 ], suggesting pathogenicity and a potential therapeutic target to facilitate anti-inflammatory effects, which warrant further investigation. Participants with PTSD symptoms had a lower abundance of H. sputorum , correlating with findings in young adults with depression [ 32 ]. Haemophilus is a nitrate-reducing genus, and therefore, higher levels are associated with good oral health. This taxon is also depleted in the oral and gut microbiomes of individuals with rheumatoid arthritis (RA), which also correlated with higher levels of serum autoantibodies [ 76 ], suggesting a potential involvement in autoimmunity and inflammation. Interestingly, PTSD is associated with RA, with female PTSD patients having a 76% higher risk of developing RA [ 77 ]. Levels of Haemophilus in the oral and gut microbiomes could therefore be involved in this comorbidity, possibly via its immunomodulatory effects. The abundance of several taxa was associated with periodontal outcomes; Shuttleworthia and Capnocytophaga were associated with a self-reported clinical diagnosis of periodontitis and predicted severe periodontitis. Previous studies reported similar findings in periodontitis [ 74 , 78 ], and gingivitis patients [ 79 ]. Shuttleworthia and Capnocytophaga should therefore be investigated as potential non-invasive, salivary microbiome markers of periodontitis. Eggerthia was more prevalent in those with a periodontitis/gingivitis diagnosis, correlating with previous reports in periodontitis [ 80 ], and gingivitis patients [ 81 ]. These findings suggest that salivary levels of Eggerthia should be investigated as an early, non-invasive indicator of periodontal health problems. We however did not detect differences in the relative abundance of certain keystone periodontitis-associated taxa, including Porphyromonas gingivalis , which could be attributed to analyzing saliva samples and not periodontal pocket samples [ 82 ]. While no shared oral taxa were associated with both mental and periodontal health, we found a common functional pathway: metabolism/degradation of TRP. This pathway was diminished in individuals with PTSD symptoms, those who experienced childhood trauma, those with poor interpersonal quality of life, and those with predicted periodontitis. Decreased degradation of TRP through the 5-HT pathway could result in lower 5-HT levels and higher TRP levels. Our data revealed reduced plasma levels of 5-HT and 5-HT/TRP ratios in all symptomatic groups compared to healthy controls. Decreased 5-HT/TRP ratios may result from lower 5-HT levels and increased TRP levels. Directly measuring 5-HT levels in plasma can be challenging due to factors like its short half-life and difficulties in accurately measuring relatively low 5-HT plasma levels [ 83 ]. Therefore, the 5-HT/TRP ratio allows for an indirect assessment of serotonin synthesis capacity, which may indicate alterations in serotonin function in the CNS [ 84 , 85 ]. Decreased levels of 5-HT align with previous research in depression [ 86 ] and PTSD [ 87 ]. Serotonin-mediated neurotransmission is implicated in anxiety disorders, although its relationship is complex due to the diversity of anxiety disorders [ 88 ]. Serotonin is crucial for CNS development and function [ 89 , 90 ], yet it also affects oral health. Psychotropic drugs like selective serotonin reuptake inhibitors (SSRIs) can reduce salivary flow rate and cause xerostomia (dry mouth) [ 91 ], affecting oral cleansing and tooth decay prevention [ 92 ]. While our study didn't find statistically significant differences in 5-HT levels in those with clinical diagnosis or predicted severe periodontitis, altered serotonin levels could influence oral health. Although serotonin is vital for mental health, most (~ 90%) of its production occurs in the gastrointestinal tract [ 93 ], influencing various physiological processes beyond the CNS, including colonic motility [ 95 ]. While our findings suggest potential oral microbiota involvement in TRP metabolism and systemic serotonin levels, systemic levels don't directly reflect CNS levels due to the blood-brain barrier (BBB). Psychotropic medications, like SSRIs, may have affected CNS serotonin levels in this cohort. Nevertheless, our study underscores the importance of the serotonergic system in mental and oral health, suggesting avenues for further research into oral microbiota, TRP metabolism, and serotonin production interplay. Understanding these relationships could lead to novel therapeutic approaches for mental health disorders associated with serotonin dysregulation. Identifying treatment response markers is crucial to lighten the burden of disease and enhance treatment efficacy. Although oral taxa were not associated with psychoactive medication use, a higher relative abundance of Eggerthia and a lower abundance of H. parainfluenza was evident in individuals with a self-reported periodontitis diagnosis and those reporting poor psychotherapeutic efficacy, hinting at a potential effect of oral health on treatment efficacy. The psychotherapeutic efficacy association narrowly missed statistical significance, and warrants further investigation. Data on oral microbiome and treatment response associations are limited, however, research suggests a causal effect of elevated levels of Eggerthia on anxiety and depression [ 30 ]; links between lower levels of H. parainfluenza and generalized anxiety disorder [ 96 ], and higher levels of this taxon in individuals with periodontitis + IBS [ 97 ]. These taxa are good candidates to explore in future longitudinal treatment outcome studies, especially in patients with periodontal health problems. Limitations of this study include the absence of clinical assessments of anxiety, depression, PTSD, periodontitis, and gingivitis. Instead, validated questionnaires were used to assess symptoms, in addition, participants reported current diagnoses of any of these disorders/conditions. Mental health disorders are complex, with varying symptom presentations even among individuals diagnosed with the same disorder. Understanding these disorders in this context is crucial. Additionally, diagnoses and treatment strategies are informed by symptoms rather than rigid diagnostic criteria, with associations with biological markers often correlating more strongly with symptoms [ 98 ]. Further oral microbiome studies with well-defined clinical samples are warranted to compare findings to self-reported symptom cohorts. Different oral niches harbor distinct microbiomes. This study investigated self-collected saliva samples as a proxy for the oral microbiome. Samples from the periodontal pocket would be ideal for studying the microbiome related to periodontitis. However, the aim of this study was mental health outcomes whilst considering self-reported periodontal health outcomes. Furthermore, studies have shown that saliva samples were the most stable within-subjects (temporal) as well as between-subjects [ 99 ]. Lastly, our cross-sectional study can only report on microbial associations with disease; future longitudinal studies are needed to infer causality between the oral microbiome and mental health symptoms. This study reveals a compelling connection between the composition of oral microbiota, mental health conditions, early life experiences, as well as periodontal outcomes. We highlighted taxa and functional pathways implicated in both mental and oral health, which expands our current knowledge of the newly described oral-brain axis, which encompasses a complex interplay between microbial composition, systemic neuromodulators, and outcomes in mental and oral health. Understanding these relationships offers promising avenues for integrated approaches to promote oral and psychological resilience, emphasizing the importance of considering both oral and mental health within a holistic framework of care. Declarations Acknowledgments This research was supported by a 2018 NARSAD Young Investigator Grant from the Brain and Behaviour Research Foundation (grant number: 27050), Una4Career grant (European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 847635), a Knowledge Generation Grant from the Ministry of Science and Innovation (Spain) (PID2021-126468OA-I00), and Ministry of Health (Spain) research grant (PNSD 2022I033). The authors would like to thank the following groups and individuals: The Genomics Unit at the CRG for assistance with library preparation and 16S rRNA sequencing; the UCM Occupational Medicine Service, María Suárez, Alexandra Becedas López, and Miriam Jubero for assistance with blood collection, Dr. JH Müller for statistical assistance., and the participants of this project. The data that support the findings of this study are available from the corresponding author, [S Malan-Müller], upon reasonable request. 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Additional Declarations The authors have declared there is NO conflict of interest to disclose Supplementary Files Table1.xlsx Table 1: Comparative statistics of continuous and categorical variables for the depressive symptom vs. healthy control cohorts Table2.xlsx Table 2: Comparative statistics of continuous and categorical variables for the trait anxiety symptom vs. healthy control cohorts Table3.xlsx Table 3: Comparative statistics of continuous and categorical variables for the state anxiety symptom vs. healthy control cohorts Table4.xlsx Table 4: Comparative statistics of continuous and categorical variables for the PTSD symptom vs. healthy control cohorts SupplementaryMaterial.docx SupplementaryTable1.xlsx Cite Share Download PDF Status: Published Journal Publication published 05 Oct, 2024 Read the published version in Translational Psychiatry → Version 1 posted Editorial decision: revise 12 Jul, 2024 Review # 1 received at journal 13 Jun, 2024 Review # 3 received at journal 12 Jun, 2024 Reviewer # 3 agreed at journal 30 May, 2024 Reviewer # 2 agreed at journal 30 May, 2024 Reviewer # 1 agreed at journal 29 May, 2024 Reviewers invited by journal 16 May, 2024 Submission checks completed at journal 29 Apr, 2024 First submitted to journal 26 Apr, 2024 Unknown event 26 Apr, 2024 Editor assigned by journal 26 Apr, 2024 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. 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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-4328261","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":303460609,"identity":"c02b8e31-605a-475a-b1ec-5177061d3211","order_by":0,"name":"Stefanie Malan-Müller","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0klEQVRIiWNgGAWjYHACxgMgko+9AUgaWBCnB6yFjQdEGUiQokUiAUQRoUV+2uEHB37u2JbYJvn86oYfBRIM/O3dCXi1GNxOMzjYe+Z2Ypt0TtnNHqDDJM6c3YBfi3SCwQHeNrCWtBs8QC0GErn4tcjPTv9w8C9Ii+SZtJt/iNHCcDvH4DDYFgn2Y7eJssXgdk7BYdm228ZtPDlst2UMJHgI+gXosI0P37bdlu1nP/7s5ps/NnL87b0EHIYAPAZgkljlIMD+gBTVo2AUjIJRMIIAAMLPTEYdw7lcAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0003-0639-0129","institution":"Complutense University of Madrid","correspondingAuthor":true,"prefix":"","firstName":"Stefanie","middleName":"","lastName":"Malan-Müller","suffix":""},{"id":303460610,"identity":"38889ba9-d86f-4bc0-bef7-35b118125c8c","order_by":1,"name":"Rebeca Vidal","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Rebeca","middleName":"","lastName":"Vidal","suffix":""},{"id":303460611,"identity":"776f52ac-9288-4786-8d67-b21fbc571c1e","order_by":2,"name":"Esther O'Shea","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Esther","middleName":"","lastName":"O'Shea","suffix":""},{"id":303460612,"identity":"732a18cf-a0b8-4951-b3ed-76612ccffdde","order_by":3,"name":"Eduardo Montero","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Eduardo","middleName":"","lastName":"Montero","suffix":""},{"id":303460613,"identity":"13537b08-8837-4396-b349-76bc70cda8ce","order_by":4,"name":"Elena Figuero","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Elena","middleName":"","lastName":"Figuero","suffix":""},{"id":303460614,"identity":"9969d3d1-6e7d-40e3-9d69-a0ed6aca5f7c","order_by":5,"name":"Iñaki Zorrilla","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Iñaki","middleName":"","lastName":"Zorrilla","suffix":""},{"id":303460615,"identity":"7f413bd0-5cfa-42d2-8863-7d8eb3901a48","order_by":6,"name":"Javier de Diego-Adeliño","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Javier","middleName":"","lastName":"de Diego-Adeliño","suffix":""},{"id":303460616,"identity":"f68c24c9-cdb9-4c35-aafd-547b535103b1","order_by":7,"name":"Marta Cano","email":"","orcid":"https://orcid.org/0000-0003-0675-9483","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Marta","middleName":"","lastName":"Cano","suffix":""},{"id":303460617,"identity":"5014182a-ccf6-4e34-82d9-b9bb626d848b","order_by":8,"name":"María García-Portilla","email":"","orcid":"https://orcid.org/0000-0003-3643-1622","institution":"Universidad de Oviedo","correspondingAuthor":false,"prefix":"","firstName":"María","middleName":"","lastName":"García-Portilla","suffix":""},{"id":303460618,"identity":"f8d7f65d-4b32-4aaf-a5cd-dc58f56c3b29","order_by":9,"name":"Ana González-Pinto","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Ana","middleName":"","lastName":"González-Pinto","suffix":""},{"id":303460619,"identity":"9d2df2d1-07df-44ab-b88d-fb92cd0db7e2","order_by":10,"name":"Juan Leza","email":"","orcid":"https://orcid.org/0000-0002-9901-0094","institution":"universidad complutense. Fac. medicina","correspondingAuthor":false,"prefix":"","firstName":"Juan","middleName":"","lastName":"Leza","suffix":""}],"badges":[],"createdAt":"2024-04-26 08:25:41","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4328261/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4328261/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41398-024-03122-4","type":"published","date":"2024-10-05T04:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":57519146,"identity":"39b1855f-b922-44c6-bf55-061ebaeba8cb","added_by":"auto","created_at":"2024-05-31 20:38:58","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1331999,"visible":true,"origin":"","legend":"\u003cp\u003eEffect sizes of variables that had a statistically significant effect on the oral microbiome community variation (distance-based redundancy analysis (dbRDA) on genus-level Aitchison distance) in our cohort (\u003cem\u003en\u003c/em\u003e = 470). Color intensity is proportional to the q-values (False Discovery Rate (FDR) corrected p-values); adjusted \u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e effect sizes are indicated on the y-axis. Certain variables were not available for the entire cohort: gingivitis diagnosis (ever), oral bleeding or inflammation, loose teeth, consumption of dietary whole grains (\u003cem\u003en\u003c/em\u003e = 284); alveolar bone loss (\u003cem\u003en\u003c/em\u003e = 184), psychoactive medication use (\u003cem\u003en \u003c/em\u003e= 265), and having arthritis or gout (\u003cem\u003en\u003c/em\u003e = 282). BMI – body mass index, CESD - Centre for Epidemiologic Studies Depression, Whole grains – weekly whole grain consumption, TeetchCAL5 criteria - probable severe periodontitis based on the “≥50% of teeth with clinical attachment level (CAL) ≥5 mm” criteria\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4328261/v1/ea1d1f137834d1c849ab420c.jpg"},{"id":57519147,"identity":"eff6646e-6fb7-4993-9b84-af86ffcb556a","added_by":"auto","created_at":"2024-05-31 20:38:59","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1593388,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Higher relative abundance of \u003cem\u003eS. mutans\u003c/em\u003e in individuals who experienced childhood emotional neglect. (b) Lower relative abundance of \u003cem\u003eH. sputorum\u003c/em\u003e and higher abundance of \u003cem\u003eP. histicola\u003c/em\u003e in individuals with symptoms of PTSD compared to controls. (c) Individuals with a current anxiety disorder diagnosis had lower levels of \u003cem\u003eN. elongata\u003c/em\u003e and higher levels of \u003cem\u003eO. asaccharolyticum\u003c/em\u003e. (d) The relative abundance of \u003cem\u003eP. histicola\u003c/em\u003e was positively associated with CESD depressive scores and (e) negatively associated with World Health Organization Quality Of Life (WHOQOL) scores for domain 2. (f) Summary graphic highlighting common taxa associated with mental health outcomes, trauma, and well-being (positive associations are indicated in yellow tones, negative associations in blue tones, color intensity is proportional to standardized GLM β coefficients, and point size is proportional to the q-values (FDR corrected \u003cem\u003ep\u003c/em\u003e-values)). Horizontal lines on the violin plots indicate the median and the thicker part of the violin around the median represents the interquartile range (IQR). Significance \u003cem\u003eq\u003c/em\u003e ≤ 0.1 (only statistically significant taxa are illustrated). Abundance is the clr-transformed relative abundance values. \u003cem\u003eH. sputorum\u003c/em\u003e - \u003cem\u003eHaemophilus sputorum\u003c/em\u003e, \u003cem\u003eP. histicola\u003c/em\u003e - \u003cem\u003ePrevotella histicola\u003c/em\u003e, \u003cem\u003eN. elongata\u003c/em\u003e - \u003cem\u003eNeisseria elongate\u003c/em\u003e, \u003cem\u003eO. asaccharolyticum\u003c/em\u003e - \u003cem\u003eOribacterium asaccharolyticum\u003c/em\u003e, PTSD - posttraumatic stress disorder, GLM – generalised linear model\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4328261/v1/1ce82e84a0c56ddfa2c428bb.jpg"},{"id":57519153,"identity":"82f001b7-8d6e-417e-a6aa-57bbf6705d91","added_by":"auto","created_at":"2024-05-31 20:39:00","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":652606,"visible":true,"origin":"","legend":"\u003cp\u003eSummary graphic highlighting common taxa associated with periodontal outcomes (self-reported clinical diagnosis of current periodontitis/gingivitis available for all participants, \u003cem\u003en \u003c/em\u003e= 470; questionnaire data to predict severe periodontitis available for \u003cem\u003en\u003c/em\u003e = 196 [48%] of the participants). Positive associations are in shades of yellow, negative associations in shades of blue, and color intensity is proportional to standardized GLM β coefficients, and point size is proportional to the q-values (FDR corrected \u003cem\u003ep\u003c/em\u003e-values). Periodontitis diagnosis (n = 34, 7%) – participants reported having a current clinical diagnosis of periodontitis; Gingivitis diagnosis (\u003cem\u003en\u003c/em\u003e = 30, 11%) – participants reported having a current clinical diagnosis of gingivitis; TeetchCAL5 - probable severe periodontitis based on the “≥50% of teeth with clinical attachment level (CAL) ≥5 mm” criteria (\u003cem\u003en\u003c/em\u003e = 93, 47%); TeethPPD6 - probable severe periodontitis based on the “≥25% of teeth with probing pocket depth (PPD) ≥6 mm” criteria (\u003cem\u003en\u003c/em\u003e = 81, 41.3%)\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4328261/v1/50faf7ff930e0ba8ee69ecde.jpg"},{"id":57519149,"identity":"ad2a7f41-649c-499c-a28c-e458ae73fd78","added_by":"auto","created_at":"2024-05-31 20:39:00","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":788949,"visible":true,"origin":"","legend":"\u003cp\u003eShared (solid line boxes) and unique (dotted line boxes) gut-brain modules (GBMs) associated with predicted severe periodontitis (stages III-IV) as well as mental health, childhood trauma, and quality of life variables. Positive correlations are displayed in yellow tones, and negative correlations in blue tones (white tones indicate values close to zero). Color intensity is proportional to standardized GLM β coefficients, and point size is proportional to the q-values (FDR corrected \u003cem\u003ep\u003c/em\u003e-values)\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4328261/v1/116dbbc5fc28361055a0ae9a.jpg"},{"id":57519148,"identity":"a8981740-cdab-477e-a598-2d67ac295734","added_by":"auto","created_at":"2024-05-31 20:38:59","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1321893,"visible":true,"origin":"","legend":"\u003cp\u003eLog transformed plasma levels (nmol/ml) of serotonin (5-HT) and the ratio of serotonin/tryptophan (5-HT/TRP) in participants with (a) depressive, (b) trait anxiety, (c) state anxiety, and (d) PTSD symptoms compared to healthy controls. Horizontal lines on the violin plots indicate the median, and the thicker part of the violin around the median represents the interquartile range (IQR). Significance \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01. PTSD - posttraumatic stress disorder\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4328261/v1/615113825d2c42f9c8ae59d0.jpg"},{"id":66001954,"identity":"456b3b55-9473-4e12-bcf2-6b29528a3006","added_by":"auto","created_at":"2024-10-06 07:05:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6449233,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4328261/v1/a671e0a6-660a-41d7-b115-989053b952d5.pdf"},{"id":57519156,"identity":"d3295d40-c258-4e3d-8f8c-55dce48e278a","added_by":"auto","created_at":"2024-05-31 20:39:00","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":17157,"visible":true,"origin":"","legend":"\u003cp\u003eTable 1: Comparative statistics of continuous and categorical variables for the depressive symptom vs. healthy control cohorts\u003c/p\u003e","description":"","filename":"Table1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4328261/v1/8008b3a7f7a9792f728e75b2.xlsx"},{"id":57519157,"identity":"b210fd23-77a4-4b6e-bc15-4fdbea8ce1ce","added_by":"auto","created_at":"2024-05-31 20:39:01","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":16312,"visible":true,"origin":"","legend":"\u003cp\u003eTable 2: Comparative statistics of continuous and categorical variables for the trait anxiety symptom vs. healthy control cohorts\u003c/p\u003e","description":"","filename":"Table2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4328261/v1/47d2dabe08a896e465825f59.xlsx"},{"id":57519145,"identity":"06567078-1817-438b-b09b-63b28a18af44","added_by":"auto","created_at":"2024-05-31 20:38:58","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":16344,"visible":true,"origin":"","legend":"\u003cp\u003eTable 3: Comparative statistics of continuous and categorical variables for the state anxiety symptom vs. healthy control cohorts\u003c/p\u003e","description":"","filename":"Table3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4328261/v1/1450bf63e468e69a181db285.xlsx"},{"id":57519158,"identity":"ace5818e-e6b6-4085-a20e-17b615a9829c","added_by":"auto","created_at":"2024-05-31 20:39:01","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":23416,"visible":true,"origin":"","legend":"\u003cp\u003eTable 4: Comparative statistics of continuous and categorical variables for the PTSD symptom vs. healthy control cohorts\u003c/p\u003e","description":"","filename":"Table4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4328261/v1/2a43d4c66d38f915721f46e7.xlsx"},{"id":57519151,"identity":"b4264fa6-8aed-450f-8493-1a910a7049a1","added_by":"auto","created_at":"2024-05-31 20:39:00","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":22441,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-4328261/v1/773f1a888afced3cbe5f5ddc.docx"},{"id":57519159,"identity":"4324e182-2c07-4c58-8a80-8f51fc0f01cf","added_by":"auto","created_at":"2024-05-31 20:39:01","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":15143,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4328261/v1/b534f58b06ab9cb19730661a.xlsx"}],"financialInterests":"The authors have declared there is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose","formattedTitle":"Probing the oral-brain connection: Oral microbiome patterns in a large community cohort with anxiety, depression, and trauma symptoms, and periodontal outcomes","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMental health disorders place a heavy burden on patients, families, societies, and global economies. In 2019, an estimated 418\u0026nbsp;million disability-adjusted life years (DALYs) could be attributable to mental disorders [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In 2017, depression was the leading cause of disability globally, with an estimated 322\u0026nbsp;million people living with depression [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], whilst about 260\u0026nbsp;million people suffered from anxiety disorders, and many suffered with additional comorbidities [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Mental disorders were the leading cause of the health-related burden of disease, and to worsen the situation, the COVID-19 pandemic has left in its wake a steep rise in the global prevalence of anxiety and depressive disorders [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSeveral factors, including economic insecurity, work-related stress, collective trauma, inequality, modern lifestyles, global events, and environmental factors, have likely contributed to the increased prevalence of mental health disorders [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Modern lifestyles, characterized by high stress levels, processed diets, excessive sanitation practices, and antibiotic use, alongside environmental changes like increased pollutants, climate change, and urbanization, have shifted human microbiota towards an industrialized state [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. These microbiota alterations, coupled with the loss of specific functional attributes, may lead to suboptimal disease-promoting microbial communities, worsening compromised mental health [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe burden of mental health disorders is compounded by treatment limitations such as non-adherence, treatment resistance, and relapse [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], highlighting the necessity for innovative treatment modalities. The human holobiont, comprising the human host and its symbiotic microorganisms, plays a crucial role in health and disease [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. While much attention has been given to the gut-brain axis, emerging evidence suggests that the oral microbiota, a less explored niche, may also influence the central nervous system and behavior [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe oral cavity hosts a diverse array of bacteria, and dysregulation can lead to disease. Periodontitis, a chronic bacterial infection affecting nearly half the global population [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], triggers systemic inflammation through pro-inflammatory cytokine release and invasion by periodontal keystone pathogens like \u003cem\u003ePorphyromonas gingivalis\u003c/em\u003e (\u003cem\u003eP. gingivalis\u003c/em\u003e) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Periodontitis not only contributes to chronic inflammatory conditions like atherosclerosis, diabetes, and cardiovascular diseases [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] but also shows associations with psychiatric disorders [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], suggesting involvement in the oral-brain axis. A longitudinal study spanning 10 years found a higher incidence of subsequent depression in individuals with periodontitis compared to those without [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], indicating a potential causal relationship between periodontitis and major depression. Additionally, recent research has identified specific bacterial taxa implicated in periodontal disease as well as anxiety, depressive disorders, and trauma-related disorders [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePathogenic periodontal bacteria can impact the CNS through various pathways, both directly and indirectly [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Direct routes include bloodstream transmission or areas with compromised blood-brain barrier (BBB) integrity [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Indirectly, they induce pro-inflammatory cytokine production, activating endothelial cells expressing tumor necrosis factor (TNF)-α and interleukin-1 (IL-1) β receptors, which signal perivascular macrophages, leading to neuroinflammation [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Keystone pathogens widen intercellular spaces in periodontal pockets, causing epithelial rupture and a \"leaky mouth\" [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], facilitating lipopolysaccharide (LPS) access to circulation, activating the immune system and the hypothalamic pituitary adrenal (HPA) axis, influencing CNS function [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Other entry points include circumventricular organs, the choroid plexus [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], and olfactory/trigeminal nerves [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Brain-resident microglia can be influenced by periodontal bacteria via leptomeninges [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Periodontal pathogens also affect gut microbial composition/function directly via enteral or indirectly via hematogenous transmission [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eClinical data on the oral microbiome's connection to mental health disorders are limited. A study utilizing genetic association analysis and Mendelian randomization to assess links between salivary-tongue dorsum microbiome interactions and anxiety/depression, found significant associations and causal effects [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], especially, \u003cem\u003eEggerthia\u003c/em\u003e was linked to anxiety and depression across multiple databases. Another study in adolescents (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;66) noted a differential abundance of \u003cem\u003eActinomyces\u003c/em\u003e, \u003cem\u003eSpirochaetaceae\u003c/em\u003e, \u003cem\u003eFusobacterium\u003c/em\u003e, and \u003cem\u003eTreponema\u003c/em\u003e in those with anxiety and depression symptoms [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Wingfield et al. compared oral microbial composition in depressed young adults (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;40), discovering 21 bacterial taxa with differing levels compared to controls, including increased \u003cem\u003eNeisseria spp\u003c/em\u003e. and \u003cem\u003ePrevotella nigrescens\u003c/em\u003e [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. To unravel the oral-brain axis's role in anxiety and depression, larger studies across diverse age groups are needed, gathering both microbiome and mechanistic data.\u003c/p\u003e \u003cp\u003eClinical data linking the oral microbiome to mental health disorders are limited. A study employing genetic association analysis and Mendelian randomization found significant associations and causal effects between salivary-tongue dorsum microbiome interactions and anxiety/depression, with \u003cem\u003eEggerthia\u003c/em\u003e notably linked to both conditions across multiple databases [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Another study involving adolescents (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;66) observed differing abundances of \u003cem\u003eActinomyces\u003c/em\u003e, \u003cem\u003eSpirochaetaceae\u003c/em\u003e, \u003cem\u003eFusobacterium\u003c/em\u003e, and \u003cem\u003eTreponema\u003c/em\u003e in individuals with symptoms of anxiety and depression [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Wingfield et al. compared the oral microbial composition in depressed young adults (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;40), identifying 21 bacterial taxa with varying levels compared to controls, including increased \u003cem\u003eNeisseria spp\u003c/em\u003e. and \u003cem\u003ePrevotella nigrescens\u003c/em\u003e [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Larger studies encompassing diverse age groups and gathering microbiome and mechanistic data are needed to elucidate the role of the oral-brain axis in anxiety and depression.\u003c/p\u003e \u003cp\u003eThis study aimed to contribute to the limited oral microbiome data currently available, and to explore the oral-brain axis, by investigating the salivary microbiome in individuals with symptoms of anxiety, depression, and posttraumatic stress disorder (PTSD) with periodontal outcomes.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy participant evaluation and enrollment\u003c/h2\u003e \u003cp\u003eThis cohort comprised two Spanish study populations from PsicoBioma (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;186, March 2021 - Jan 2022) and TRIAD (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;284, Nov 2021 - Dec 2022), both based on population-based microbiome projects. PsicoBioma recruited participants from Spain, while TRIAD recruited from Madrid, Barcelona, Vitoria, and Oviedo municipalities (allowing blood collection). Both cohorts provided saliva samples and completed similar online questionnaires. TRIAD also provided blood samples for plasma analysis and completed a more comprehensive periodontal health questionnaire. The research adhered to The Code of Ethics of the World Medical Association (Declaration of Helsinki) for human experiments, and data processing followed Spanish Organic Law 3/2018 on Personal Data Protection and Digital Rights Guarantee (BOE 16673 of 6 Dec 2018) and its 17th Additional Provision. Approval was obtained from the Ethics Committees of Hospital Cl\u0026iacute;nico San Carlos (Madrid), Medical Research Ethics Committee of Asturias, Basque Medicine Research Ethics Committee, and Drug Research Ethics Committee of Hospital de la Santa Creu i Sant Pau (PSQ-19-2 C.I. 196/474-E). All research participants provided online, written informed consent.\u003c/p\u003e \u003cp\u003eThe study recruited healthy controls, participants with a current/previous diagnosis of anxiety, depressive, or trauma-related disorders, or individuals who were experiencing these symptoms. Spanish residents, 18 years or older, who were proficient in reading and understanding Spanish were included. Individuals who used antibiotics within the previous six months, and those diagnosed with any \u003cem\u003eother\u003c/em\u003e major psychiatric disorders including psychotic disorders, personality disorders, or neurodegenerative disorders, were excluded.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eDemographic and clinical data\u003c/h2\u003e \u003cp\u003eDemographic, health, and clinical data were collected using a secure online questionnaire. Psychological evaluations relied on standardized self-report questionnaires validated for the Spanish population; this study focused on symptoms rather than formal diagnoses. However, participants also indicated on the questionnaire whether they had a previous/current clinical diagnosis of anxiety or depression (\u0026ldquo;diagnosis\u0026rdquo; henceforth refers to clinical diagnoses, and \u0026ldquo;symptoms\u0026rdquo; refers to self-report questionnaire data). Depressive symptoms were assessed using the Centre for Epidemiologic Studies Depression (CESD) scale; state and trait anxiety symptoms were evaluated using the state-trait anxiety inventory (STAI). The posttraumatic stress disorder (PTSD) Checklist for the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5, PCL-5), and the Childhood Trauma Questionnaire-Short Form (CTQ-SF) evaluated trauma exposure. Additionally, quality of life was measured using the World Health Organization Quality Of Life Questionnaire (WHOQOL).\u003c/p\u003e \u003cp\u003ePsychiatric symptoms were determined based on the following criteria:\u003c/p\u003e \u003cp\u003eDepressive symptoms: CESD scores of 16\u0026ndash;24 indicated mild and 25\u0026ndash;55 severe depressive symptoms [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. PTSD symptoms: PCL-5 score\u0026thinsp;\u0026gt;\u0026thinsp;33\u0026thinsp;+\u0026thinsp;more than 3 symptom clusters [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. State anxiety symptoms: STAI-S scores\u0026thinsp;\u0026gt;\u0026thinsp;41; trait anxiety symptoms: STAI-T scores\u0026thinsp;\u0026gt;\u0026thinsp;45; CTQ-SF [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] total score was used to evaluate the severity of childhood maltreatment.\u003c/p\u003e \u003cp\u003eThe TRIAD cohort completed a periodontal health questionnaire [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] (validated for the Spanish population [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]) to predict severe periodontitis, according to Montero et al., 2020 [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Specifically, severe periodontitis was defined according to three criteria: (i) the Centers for Disease Control/American Academy of Periodontology (CDC/AAP) case definition [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], henceforth referred to as \u003cem\u003eSeverePerioCDCAAP\u003c/em\u003e; (ii) the presence of \u0026ge;\u0026thinsp;50% of teeth with clinical attachment level (CAL)\u0026thinsp;\u0026ge;\u0026thinsp;5 mm, henceforth referred to as \u003cem\u003eTeethCAL5\u003c/em\u003e; (iii) the presence of \u0026ge;\u0026thinsp;25% of teeth with probing pocket depth (PPD)\u0026thinsp;\u0026ge;\u0026thinsp;6 mm, henceforth referred to as \u003cem\u003eTeethPPD6\u003c/em\u003e. In addition, participants also indicated whether they had a previous/current clinical diagnosis of periodontitis and/or gingivitis (\u0026ldquo;diagnosis\u0026rdquo; refers to a self-reported clinical diagnosis, and \u0026ldquo;predicted severe periodontitis\u0026rdquo; refers to self-reported questionnaire data).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eBlood collection and processing\u003c/h2\u003e \u003cp\u003eWhole blood (10ml) was collected using BD Vacutainer\u0026reg; EDTA tubes. Blood was centrifuged at 1800 rpm for 10 minutes at room temperature, and the resulting supernatant (plasma) was transferred into clean 1.5ml Eppendorf tubes for storage at -80\u0026deg;C for later use.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eKynurenine, tryptophan, and serotonin quantification in plasma\u003c/h2\u003e \u003cp\u003ePlasma levels of kynurenine (KYN), tryptophan (TRP), and serotonin (5-HT) were measured using High-performance liquid chromatography (HPLC). TRP and 5-HT were detected fluorometrically at excitation/emission wavelengths of 270/360 nm and 290/398 nm, respectively (Waters 2475, Multi fluorescence Detector; Waters, Milford, MA, USA). The ratios of KYN or 5-HT to TRP concentrations were calculated and used as a measure of TRP degradation (see Supplementary Materials for details).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eBacterial DNA extraction, 16S rRNA gene sequencing and analysis\u003c/h2\u003e \u003cp\u003eParticipants self-collected saliva samples in DNA/RNA Shield Safe Collect Saliva Collection tubes (Zymo Research, Irvine, California, USA), from which microbial DNA was extracted (ZymoBIOMICS DNA Miniprep Kit, Zymo Research). Bacterial 16S rRNA gene V3-4 amplicons were generated, using previously described primers [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] and sequenced (2 x 300bp paired-end) (Centre de Regulaci\u0026oacute; Gen\u0026ograve;mica, Barcelona, Spain), on the Illumina NextSeq2000 platform (see Supplementary Material for details).\u003c/p\u003e \u003cp\u003eQuality control of FASTQ sequencing files was performed using fastqc and multiqc. Raw sequence reads were [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], de-replicated and de-noised to combine identical reads into amplicon sequence variants (ASVs) and construct consensus quality profiles for each combined set of sequences (\u003cem\u003edada2\u003c/em\u003e version 3.11 [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]). Following chimeras removal, a consensus paired-end reads file was generated for feature construction and downstream analysis. Taxonomic binning of classified sequences was built using a local copy of the Ribosomal Database Project (RDP) Classifier (Train Set 19 [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]), and normalized data were produced from the relative abundance of taxa present in each sample. A feature table of 54 817 unique ASVs with an average read length of 391 nucleotides in 470 samples was consequently constructed (following pre-processing, the minimum number of reads per sample was 18 868, and the average number of reads per sample was 95 763).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003eData was analyzed using bioinformatics and statistical analysis packages in \u003cem\u003eR\u003c/em\u003e [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], including the packages \u003cem\u003edada2\u003c/em\u003e (version 3.18, [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]), \u003cem\u003evegan\u003c/em\u003e (version 2.6.4, [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]), \u003cem\u003ephyloseq\u003c/em\u003e (version 1.46.0, [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]), \u003cem\u003eggplot2\u003c/em\u003e (version 3.4.4, [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]), \u003cem\u003eCoDaSeq\u003c/em\u003e (version 0.99.7, [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. For clinical and demographic data, continuous variables were summarized as means (M) and standard deviations (SD) if normally distributed or as medians and interquartile ranges (IQRs) if non-normally distributed. To assess differences in the metadata variables between symptomatic and control groups, Student's \u003cem\u003et\u003c/em\u003e-tests and Wilcoxon rank sum tests were used to assess differences between normally and non-normally distributed data (normality tested using Shapiro-Wilk Normality Test), respectively. Categorical data were summarized as counts (\u003cem\u003en\u003c/em\u003e) and percentages, and \u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e or Fisher exact tests were used to assess differences between groups, where appropriate. Significance was defined as \u003cem\u003ep\u003c/em\u003e \u0026le; 0.05.\u003c/p\u003e \u003cp\u003eThe Simpson index was used to evaluate α-diversity [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Taxa were agglomerated to genus level, assigning species-level where possible. Data was transformed to relative abundance out of 100 to account for differences in total depth per sample. Variance filtering was performed (\u003cem\u003egenefilter\u003c/em\u003e function, version 1.84.0), which removed taxa with the lowest 40% variance. Abundance matrices were centred log-ratio (clr)-transformed, using the minimum proportional abundance detected for each taxon for the imputation of zeros. The ordination of community variation was visualized using multidimensional scaling (MDS) of genus-level Aitchison distances. The \u003cem\u003ecapscale\u003c/em\u003e function (\u003cem\u003evegan\u003c/em\u003e package) [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e] was used to determine the contribution of metadata variables to microbiome community variation.\u003c/p\u003e \u003cp\u003eThe ASV table was filtered to retain taxa observed in at least 15% of participants. Associations between taxonomic abundance and metadata variables were analyzed using a linear modeling approach (\u003cem\u003efw_glm\u003c/em\u003e function, \u003cem\u003eTjazi\u003c/em\u003e package) [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]), whilst adjusting for covariates including age, Body mass index (BMI), smoking status, and cholesterol medication use. We performed false discovery rate (FDR) correction using the Benjamini-Hochberg procedure and significance was defined as \u003cem\u003eq\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.1.\u003c/p\u003e \u003cp\u003eWe utilized PICRUSt2 [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e] to predict the central nervous system (CNS)-related functional potential of oral taxa, by focusing on gut-brain modules (GBMs) [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Associations between GBMs and mental health outcomes were tested using the same linear modeling approach as previously described, with significance set at \u003cem\u003eq\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.1.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eClinical and demographic characteristics\u003c/h2\u003e \u003cp\u003eClinical and demographic characteristics of the depressive (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;148), state (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;256) and trait anxiety (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;281), and PTSD (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;73) symptomatic cohorts (according to criteria described in the Methods and Materials), and healthy controls (no significant mental health symptoms) (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;164) are described in Tables\u0026nbsp;1\u0026ndash;4. In our cohort of 470 individuals, 306 presented with at least one or a combination of the aforementioned symptoms. Females constituted 72% of our cohort, and the median age was 40 years. Comorbidity of these psychiatric symptoms was common; of the 232 individuals who had both state and trait anxiety symptoms, 133 of them also had depressive symptoms (57.3%), 67 had comorbid PTSD symptoms (28.9%), and 52 (22.4%) had PTSD and depressive symptoms. Of the 148 individuals with depressive symptoms, 144 (97.3%) also had trait anxiety symptoms, and 54 (36.5%) had symptoms of PTSD.\u003c/p\u003e \u003cp\u003eA total of 34 (7%) individuals had a current clinical diagnosis of periodontitis, and 30 (11%) had a gingivitis diagnosis. The self-reported periodontal health questionnaire administered to most of the TRIAD cohort (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;196) (unavailable for the PsicoBioma cohort) showed 81 individuals (41%) had probable severe periodontitis using TeethPPD6 criteria, 93 (47%) had it based on the TeethCAL5 criteria, and 106 (54%) had it based on the Centers for Disease Control (CDC)/American Academy of Periodontology (AAP) criteria (SeverePerioCDCAAP).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePeriodontal and mental health variables influence oral microbiome community composition\u003c/h2\u003e \u003cp\u003eThe Simpson alpha diversity index showed no significant differences between the mental health symptomatic groups and controls. However, among individuals who completed the self-reported periodontal health questionnaire (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;196, 48%), those with receding gums had a lower Simpson alpha diversity index compared to those without (Wilcoxon rank-sum tests, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.005, \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.17, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;284). Several variables influenced the overall oral microbial composition (β-diversity), with smoking status eliciting the largest effect, followed by age, living environment (city, town, or rural setting), and alveolar bone loss. The most significant subset (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e \u0026ge; 0.002 and \u003cem\u003eq\u003c/em\u003e \u0026le; 0.1) of variables is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e (Supplementary Table\u0026nbsp;1 contains the full set of significant variables).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eOral taxa associated with trauma, mental health outcomes, and psychological quality of life\u003c/h2\u003e \u003cp\u003eOur symptomatic cohort reported significantly higher levels of childhood trauma compared to controls. Individuals who reported high levels of emotional neglect had significantly lower abundance of \u003cem\u003eStreptococcus mutans\u003c/em\u003e (GLM \u003cem\u003eq\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.07, β \u003cem\u003e=\u003c/em\u003e -0.6, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;470) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). Individuals with PTSD symptoms (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;73) had significantly lower relative abundance of \u003cem\u003eHaemophilus sputorum\u003c/em\u003e (\u003cem\u003eH. sputorum\u003c/em\u003e) (GLM, \u003cem\u003eq\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.09, β \u003cem\u003e=\u003c/em\u003e -1.2, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;237) and higher levels of \u003cem\u003ePrevotella histicola\u003c/em\u003e (\u003cem\u003eP. histicola\u003c/em\u003e) (GLM, \u003cem\u003eq\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.09, β\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;1.6, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;237), compared to controls (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;164) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). Those with a current anxiety disorder diagnosis (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;134) harbored significantly lower levels of \u003cem\u003eNeisseria\u003c/em\u003e (GLM, \u003cem\u003eq\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001, β \u003cem\u003e=\u003c/em\u003e -0.96, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;470), specifically \u003cem\u003eNeisseria elongate\u003c/em\u003e (\u003cem\u003eN. elongate\u003c/em\u003e) (GLM, \u003cem\u003eq\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.09, β \u003cem\u003e=\u003c/em\u003e -0.94, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;470) and significantly higher levels of \u003cem\u003eOribacterium asaccharolyticum\u003c/em\u003e (\u003cem\u003eO. asaccharolyticum\u003c/em\u003e) (GLM \u003cem\u003eq\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03, β\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;0.53, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;470) compared to those without a current diagnosis (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;336) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). Interestingly, higher relative abundance of \u003cem\u003eP. histicola\u003c/em\u003e was also evident in individuals with higher CESD depressive scores (GLM \u003cem\u003eq\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.05, β\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;0.04, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;470) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed) and those with poor psychological quality of life scores (GLM \u003cem\u003eq\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.08, β \u003cem\u003e=\u003c/em\u003e -0.2, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;470) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee). Individuals with higher CESD scores also had a higher relative abundance of \u003cem\u003eLancefieldella\u003c/em\u003e (GLM \u003cem\u003eq\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.05, β\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;0.01, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;470) and \u003cem\u003eO. asaccharolyticum\u003c/em\u003e (GLM \u003cem\u003eq\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.05, β\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;0.02, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;470), however, the effect sizes were relatively small (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eOral microbiome signatures related to periodontal health\u003c/h2\u003e \u003cp\u003eSeveral oral taxa were associated with periodontal health variables (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Supplementary Table\u0026nbsp;2). The abundance of \u003cem\u003eShuttleworthia\u003c/em\u003e was higher in participants with a self-reported periodontitis diagnosis and those with predicted severe periodontitis based on the TeethCAL5 criteria. The abundance of \u003cem\u003eCapnocytophaga\u003c/em\u003e was lower in participants with a self-reported clinical periodontitis diagnosis and those with predicted severe periodontitis based on the TeethPPD6 criteria. Several common taxa were differentially abundant in those with a self-reported clinical periodontitis diagnosis and those who reported loose teeth (a symptom of periodontitis), including a higher relative abundance of \u003cem\u003eTannerella forsythia\u003c/em\u003e, \u003cem\u003eMetaprevotella\u003c/em\u003e, \u003cem\u003eFretibacterium fastidiosum\u003c/em\u003e, and lower relative abundance of \u003cem\u003ePrevotellaceae\u003c/em\u003e and \u003cem\u003eHaemophilus parainfluenzae\u003c/em\u003e. Three taxa had a higher abundance in participants with a self-reported clinical gingivitis diagnosis, \u003cem\u003eParvimonas\u003c/em\u003e, \u003cem\u003eGallibacter\u003c/em\u003e, and \u003cem\u003eEggerthia\u003c/em\u003e; \u003cem\u003eEggerthia\u003c/em\u003e was the only common taxon between periodontitis and gingivitis diagnosis, whose abundance was altered similarly for both diagnoses.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eFunctional potential of the oral microbiome: possible implications for mental health outcomes\u003c/h2\u003e \u003cp\u003eFunctional prediction revealed lower tryptophan metabolism/degradation in individuals with PTSD symptoms (GLM, \u003cem\u003eq\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02, β = -0.8, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;470), those who experienced higher levels of childhood trauma (GLM, \u003cem\u003eq\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.09, β = -0.01), and those with lower quality of life (specifically personal relationships) (GLM, \u003cem\u003eq\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.06, β\u0026thinsp;=\u0026thinsp;0.06). Interestingly, lower metabolism/degradation of tryptophan was also predicted in individuals with predicted severe periodontitis based on the TeethCAL5 criteria (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;93) and TeethPPD6 criteria (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;81) (GLM, \u003cem\u003eq\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.07, β = -0.52, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;196 and GLM, \u003cem\u003eq\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02, β = -0.6, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;196, respectively). Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e illustrates the full set of predicted gut-brain modules (GBMs) linked to severe periodontitis, mental health, childhood trauma, and quality of life.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003ePlasma measures\u003c/h2\u003e \u003cp\u003eAnalyses to confirm lower TRP metabolism/degradation revealed lower plasma levels of 5-HT and the ratio of 5-HT/TRP in individuals with depressive symptoms (Wilcoxon rank-sum test, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, mean difference (MD)\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;0.8, and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, MD\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;0.9, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;282 respectively), state anxiety symptoms (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, MD\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;0.6, and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, MD\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;0.5, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;282 respectively), trait anxiety symptoms (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, MD\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;0.6, and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, MD\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;0.6, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;282 respectively), and PTSD symptoms (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, MD\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;1.0, and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, MD\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;0.9, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;282 respectively) compared to healthy controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eOral microbes and therapeutic response\u003c/h2\u003e \u003cp\u003eInterestingly, two taxa associated with a current self-reported clinical diagnosis of periodontitis and/or gingivitis were also associated with self-reported efficacy of psychotherapy, namely \u003cem\u003eEggerthia\u003c/em\u003e and \u003cem\u003eHaemophilus parainfluenza\u003c/em\u003e. \u003cem\u003eEggerthia\u003c/em\u003e was present at a higher relative abundance in those with a current self-reported clinical diagnosis of periodontitis and/or gingivitis and in individuals with poor self-reported psychotherapeutic efficacy (GLM \u003cem\u003eq\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.12, \u003cem\u003er =\u003c/em\u003e -0.62, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;322), whereas the abundance of \u003cem\u003eH. parainfluenza\u003c/em\u003e was lower in these individuals (GLM \u003cem\u003eq\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.12, \u003cem\u003er\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.60, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;322), although the association did not reach the threshold for statistical significance of \u003cem\u003eq\u003c/em\u003e \u0026le; 0.1.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study represents one of the largest oral microbiome investigations in mental health, to date. The composition of the overall oral microbiome was significantly impacted by several mental health variables (including clinical diagnoses of anxiety disorders or depression), as well as periodontal symptoms, predicted severe periodontitis. and self-reported clinical diagnoses of gingivitis and/or periodontitis. These findings correlate with previous research highlighting the significant effects of mental [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] and periodontal [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e] health on the oral microbiome beta diversity. Various additional factors shaped the oral microbiome composition, aligning with earlier research emphasizing the impact of factors such as smoking [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e], BMI, [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e], age [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e], arthritis [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e], gout [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e], and geographic location [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e] on the oral microbiome.\u003c/p\u003e \u003cp\u003eAlthough none of the mental health variables or self-reported periodontal outcomes influenced Simpson\u0026rsquo;s diversity, lower diversity was evident among individuals with self-reported receding gums. Earlier studies also failed to detected differences in alpha diversity between individuals with depression and anxiety compared to controls [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], and between periodontitis patients and controls [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSeveral taxa were associated with mental health, trauma, and well-being. \u003cem\u003eP. histicola\u003c/em\u003e is of particular interest, with a higher relative abundance in individuals with PTSD symptoms, those with higher CESD scores, and those with poorer interpersonal quality of life. \u003cem\u003ePrevotella\u003c/em\u003e is the second most common bacteria dominating the oral cavity and this diverse genus includes several species. \u003cem\u003eP. histicola\u003c/em\u003e is a facultative oral pathogen, which can cause pathologies such as caries and periodontitis [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. Previously, lower levels of \u003cem\u003ePrevotella\u003c/em\u003e were noted in the oropharyngeal microbiota in schizophrenia and mania cohorts compared to controls [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e], and a negative association was observed between the abundance of \u003cem\u003ePrevotella\u003c/em\u003e and distress [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. Importantly, \u003cem\u003ePrevotella\u003c/em\u003e is a genus strongly associated with waking samples, and the majority of our samples were collected close to waking, which could explain the discrepancies between the findings. Furthermore, the majority of studies report on genus level, whereas our finding is for the species \u003cem\u003eP. histicola\u003c/em\u003e, and research has shown that species from the same genus could fulfill vastly different roles [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e], therefore future studies should aim for higher resolution of taxonomic classification to disentangle taxonomic functions and disease associations.\u003c/p\u003e \u003cp\u003eA lower relative abundance of \u003cem\u003eN. elongata\u003c/em\u003e in individuals with a clinical diagnosis of anxiety disorders echoes similar observations in patients with schizophrenia and mania [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Conversely, previous research in young adults linked depression with increased levels of \u003cem\u003eNeisseria spp\u003c/em\u003e [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Discrepancies in these findings may be attributed to differences in sample size and age of the population, as well as the resolution of microbial analysis (species vs. genus). \u003cem\u003eNeisseria\u003c/em\u003e species, integral members of the oropharyngeal flora [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e], play crucial roles in maintaining oral [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e] and cardiovascular health [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. Their presence correlates with good oral health, attributed to their aerobic, nitrite-reducing capabilities essential for gum health [\u003cspan additionalcitationids=\"CR67\" citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. Moreover, \u003cem\u003eNeisseria\u003c/em\u003e-dominated oral microbiomes exhibit a reduced likelihood of hosting the cariogenic pathogen \u003cem\u003eS. mutans\u003c/em\u003e [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. Notably, we detected a higher abundance of \u003cem\u003eS. mutans\u003c/em\u003e in individuals reporting childhood emotional neglect, a known risk factor for mental health disorders. These findings underscore the intricate interplay between oral microbial composition, mental health outcomes, and early life adversity. The involvement of cross-feeding and interactions among microbial taxa adds complexity to understanding comorbidity and risk factors in mental health conditions.\u003c/p\u003e \u003cp\u003eIndividuals with an anxiety disorder diagnosis and higher CESD scores harbored a higher abundance of \u003cem\u003eO. asaccharolyticum\u003c/em\u003e. This correlates with increased abundance reported in elderly people receiving treatment for anxiety, depression, and insomnia [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e]. Furthermore, an increased abundance of the \u003cem\u003eOdoribacter\u003c/em\u003e genus was also noted in the gut microbiomes of patients with depression [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e], a preclinical model of depression [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e], and individuals with periodontal disease [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e]. Elevated levels of the \u003cem\u003eOdoribacter\u003c/em\u003e genus were also detected in the oral microbiome of periodontitis patients [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]. These findings underscore the potential interconnectivity between oral and gut microbiomes and taxa implicated in both oral and periodontal health, with implications for the oral-gut-brain axis. Furthermore, in a randomized, double-blind placebo-controlled trial, synbiotics reduced both systemic inflammation and systemic lupus erythematosus disease activity, whilst simultaneously also depleting \u003cem\u003eO. asaccharolyticum\u003c/em\u003e from the microbiome [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e], suggesting pathogenicity and a potential therapeutic target to facilitate anti-inflammatory effects, which warrant further investigation.\u003c/p\u003e \u003cp\u003eParticipants with PTSD symptoms had a lower abundance of \u003cem\u003eH. sputorum\u003c/em\u003e, correlating with findings in young adults with depression [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. \u003cem\u003eHaemophilus\u003c/em\u003e is a nitrate-reducing genus, and therefore, higher levels are associated with good oral health. This taxon is also depleted in the oral and gut microbiomes of individuals with rheumatoid arthritis (RA), which also correlated with higher levels of serum autoantibodies [\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e], suggesting a potential involvement in autoimmunity and inflammation. Interestingly, PTSD is associated with RA, with female PTSD patients having a 76% higher risk of developing RA [\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e]. Levels of \u003cem\u003eHaemophilus\u003c/em\u003e in the oral and gut microbiomes could therefore be involved in this comorbidity, possibly via its immunomodulatory effects.\u003c/p\u003e \u003cp\u003eThe abundance of several taxa was associated with periodontal outcomes; \u003cem\u003eShuttleworthia\u003c/em\u003e and \u003cem\u003eCapnocytophaga\u003c/em\u003e were associated with a self-reported clinical diagnosis of periodontitis and predicted severe periodontitis. Previous studies reported similar findings in periodontitis [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e], and gingivitis patients [\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e]. \u003cem\u003eShuttleworthia\u003c/em\u003e and \u003cem\u003eCapnocytophaga\u003c/em\u003e should therefore be investigated as potential non-invasive, salivary microbiome markers of periodontitis.\u003c/p\u003e \u003cp\u003e \u003cem\u003eEggerthia\u003c/em\u003e was more prevalent in those with a periodontitis/gingivitis diagnosis, correlating with previous reports in periodontitis [\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e], and gingivitis patients [\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e]. These findings suggest that salivary levels of \u003cem\u003eEggerthia\u003c/em\u003e should be investigated as an early, non-invasive indicator of periodontal health problems. We however did not detect differences in the relative abundance of certain keystone periodontitis-associated taxa, including \u003cem\u003ePorphyromonas gingivalis\u003c/em\u003e, which could be attributed to analyzing saliva samples and not periodontal pocket samples [\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWhile no shared oral taxa were associated with both mental and periodontal health, we found a common functional pathway: metabolism/degradation of TRP. This pathway was diminished in individuals with PTSD symptoms, those who experienced childhood trauma, those with poor interpersonal quality of life, and those with predicted periodontitis. Decreased degradation of TRP through the 5-HT pathway could result in lower 5-HT levels and higher TRP levels. Our data revealed reduced plasma levels of 5-HT and 5-HT/TRP ratios in all symptomatic groups compared to healthy controls. Decreased 5-HT/TRP ratios may result from lower 5-HT levels and increased TRP levels. Directly measuring 5-HT levels in plasma can be challenging due to factors like its short half-life and difficulties in accurately measuring relatively low 5-HT plasma levels [\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e]. Therefore, the 5-HT/TRP ratio allows for an indirect assessment of serotonin synthesis capacity, which may indicate alterations in serotonin function in the CNS [\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e, \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDecreased levels of 5-HT align with previous research in depression [\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e] and PTSD [\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e]. Serotonin-mediated neurotransmission is implicated in anxiety disorders, although its relationship is complex due to the diversity of anxiety disorders [\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e]. Serotonin is crucial for CNS development and function [\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e, \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e], yet it also affects oral health. Psychotropic drugs like selective serotonin reuptake inhibitors (SSRIs) can reduce salivary flow rate and cause xerostomia (dry mouth) [\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e], affecting oral cleansing and tooth decay prevention [\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e]. While our study didn't find statistically significant differences in 5-HT levels in those with clinical diagnosis or predicted severe periodontitis, altered serotonin levels could influence oral health.\u003c/p\u003e \u003cp\u003eAlthough serotonin is vital for mental health, most (~\u0026thinsp;90%) of its production occurs in the gastrointestinal tract [\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e], influencing various physiological processes beyond the CNS, including colonic motility [\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e]. While our findings suggest potential oral microbiota involvement in TRP metabolism and systemic serotonin levels, systemic levels don't directly reflect CNS levels due to the blood-brain barrier (BBB). Psychotropic medications, like SSRIs, may have affected CNS serotonin levels in this cohort. Nevertheless, our study underscores the importance of the serotonergic system in mental and oral health, suggesting avenues for further research into oral microbiota, TRP metabolism, and serotonin production interplay. Understanding these relationships could lead to novel therapeutic approaches for mental health disorders associated with serotonin dysregulation.\u003c/p\u003e \u003cp\u003eIdentifying treatment response markers is crucial to lighten the burden of disease and enhance treatment efficacy. Although oral taxa were not associated with psychoactive medication use, a higher relative abundance of \u003cem\u003eEggerthia\u003c/em\u003e and a lower abundance of \u003cem\u003eH. parainfluenza\u003c/em\u003e was evident in individuals with a self-reported periodontitis diagnosis and those reporting poor psychotherapeutic efficacy, hinting at a potential effect of oral health on treatment efficacy. The psychotherapeutic efficacy association narrowly missed statistical significance, and warrants further investigation. Data on oral microbiome and treatment response associations are limited, however, research suggests a causal effect of elevated levels of \u003cem\u003eEggerthia\u003c/em\u003e on anxiety and depression [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]; links between lower levels of \u003cem\u003eH. parainfluenza\u003c/em\u003e and generalized anxiety disorder [\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e], and higher levels of this taxon in individuals with periodontitis\u0026thinsp;+\u0026thinsp;IBS [\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e]. These taxa are good candidates to explore in future longitudinal treatment outcome studies, especially in patients with periodontal health problems.\u003c/p\u003e \u003cp\u003eLimitations of this study include the absence of clinical assessments of anxiety, depression, PTSD, periodontitis, and gingivitis. Instead, validated questionnaires were used to assess symptoms, in addition, participants reported current diagnoses of any of these disorders/conditions. Mental health disorders are complex, with varying symptom presentations even among individuals diagnosed with the same disorder. Understanding these disorders in this context is crucial. Additionally, diagnoses and treatment strategies are informed by symptoms rather than rigid diagnostic criteria, with associations with biological markers often correlating more strongly with symptoms [\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e]. Further oral microbiome studies with well-defined clinical samples are warranted to compare findings to self-reported symptom cohorts.\u003c/p\u003e \u003cp\u003e Different oral niches harbor distinct microbiomes. This study investigated self-collected saliva samples as a proxy for the oral microbiome. Samples from the periodontal pocket would be ideal for studying the microbiome related to periodontitis. However, the aim of this study was mental health outcomes whilst considering self-reported periodontal health outcomes. Furthermore, studies have shown that saliva samples were the most stable within-subjects (temporal) as well as between-subjects [\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e]. Lastly, our cross-sectional study can only report on microbial associations with disease; future longitudinal studies are needed to infer causality between the oral microbiome and mental health symptoms.\u003c/p\u003e \u003cp\u003eThis study reveals a compelling connection between the composition of oral microbiota, mental health conditions, early life experiences, as well as periodontal outcomes. We highlighted taxa and functional pathways implicated in both mental and oral health, which expands our current knowledge of the newly described oral-brain axis, which encompasses a complex interplay between microbial composition, systemic neuromodulators, and outcomes in mental and oral health. Understanding these relationships offers promising avenues for integrated approaches to promote oral and psychological resilience, emphasizing the importance of considering both oral and mental health within a holistic framework of care.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by a\u0026nbsp;2018 NARSAD Young Investigator Grant from the Brain and Behaviour Research Foundation (grant number: 27050), Una4Career grant (European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 847635), a Knowledge Generation Grant from the Ministry of Science and Innovation (Spain) (PID2021-126468OA-I00), and Ministry of Health (Spain) research grant (PNSD 2022I033).\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the following groups and individuals: The Genomics Unit at the CRG for assistance with library preparation and 16S rRNA sequencing; the UCM\u0026nbsp;Occupational Medicine Service,\u0026nbsp;María Suárez, Alexandra Becedas López, and Miriam Jubero\u003c/p\u003e\n\u003cp\u003efor assistance with blood collection, Dr. JH Müller for statistical assistance., and the participants of this project.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author, [S Malan-Müller], upon reasonable request. Data will be deposited in the National Microbiome Data Collaborative after acceptance of the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors report there are no competing interests to declare.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eArias D, Saxena S, Verguet S (2022). Quantifying the global burden of mental disorders and their economic value. eClinicalMedicine. doi: 10.1016/j.eclinm.2022.101675.\u003c/li\u003e\n\u003cli\u003eFriedrich MJ (2017). Depression Is the Leading Cause of Disability Around the World. JAMA, 317:1517.\u003c/li\u003e\n\u003cli\u003eDepression and Other Common Mental Disorders. https://www.who.int/publications-detail-redirect/depression-global-health-estimates. Accessed 23 Feb 2024.\u003c/li\u003e\n\u003cli\u003eSantomauro DF, Herrera AMM, Shadid J, Zheng P, Ashbaugh C, Pigott DM, et al. (2021). 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Nature, 581:19\u0026ndash;21.\u003c/li\u003e\n\u003cli\u003ePandey D, Szczesniak M, Maclean J, Yim HCH, Zhang F, Graham P, et al. (2022). Dysbiosis in Head and Neck Cancer: Determining Optimal Sampling Site for Oral Microbiome Collection. Pathogens, 11:1550.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1-4 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"translational-psychiatry","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"tp","sideBox":"Learn more about [Translational Psychiatry](http://www.nature.com/tp/)","snPcode":"41398","submissionUrl":"https://mts-tp.nature.com/cgi-bin/main.plex","title":"Translational Psychiatry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4328261/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4328261/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe role of the oral microbiome in mental health has recently been appreciated within the proposed oral-brain axis. This study examined the structure and composition of the salivary microbiome in a large-scale population-based cohort of individuals reporting mental health symptoms (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;306) compared to mentally healthy controls (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;164) using 16S rRNA sequencing. Mental health symptoms were evaluated using validated questionnaires and included depression, anxiety, and posttraumatic stress disorder, with accompanying periodontal outcomes. Participants also indicated current or previous diagnoses of anxiety, depression, periodontitis, and gingivitis. Mental and periodontal health variables influenced the overall composition of the oral microbiome. PTSD symptoms correlated with reduced \u003cem\u003eHaemophilus sputorum\u003c/em\u003e and elevated \u003cem\u003ePrevotella histicola\u003c/em\u003e levels. Anxiety disorder diagnosis was associated with decreased \u003cem\u003eNeisseria elongate\u003c/em\u003e and increased \u003cem\u003eOribacterium asaccharolyticum\u003c/em\u003e. \u003cem\u003eP. histicola\u003c/em\u003e abundance was also positively associated with depressive scores and negatively associated with psychological quality of life. A higher abundance of \u003cem\u003eShuttleworthia\u003c/em\u003e and a lower abundance of \u003cem\u003eCapnocytophaga\u003c/em\u003e were evident in those who reported a clinical periodontitis diagnosis. Functional prediction analysis revealed a potential role for tryptophan metabolism/degradation in the oral-brain axis, which was confirmed by lower plasma serotonin levels across symptomatic groups. Higher \u003cem\u003eEggerthia\u003c/em\u003e and lower \u003cem\u003eHaemophilus parainfluenzae\u003c/em\u003e abundance were associated with reported clinical periodontitis diagnosis and psychotherapeutic efficacy. This study sheds light on the intricate interplay between oral microbiota, periodontal outcomes, and mental health, emphasizing the need for further exploration of the oral-brain axis to pave the way for novel therapeutic interventions and predicting therapeutic response.\u003c/p\u003e","manuscriptTitle":"Probing the oral-brain connection: Oral microbiome patterns in a large community cohort with anxiety, depression, and trauma symptoms, and periodontal outcomes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-31 20:38:50","doi":"10.21203/rs.3.rs-4328261/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2024-07-12T11:00:34+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2024-06-14T03:54:11+00:00","index":1,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2024-06-12T17:48:45+00:00","index":3,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2024-05-30T15:32:59+00:00","index":3,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2024-05-30T10:32:43+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2024-05-29T16:29:00+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2024-05-17T02:05:07+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-04-29T10:22:53+00:00","index":"","fulltext":""},{"type":"submitted","content":"Translational Psychiatry","date":"2024-04-26T10:53:55+00:00","index":"","fulltext":""},{"type":"checksFailed","content":"","date":"2024-04-26T10:38:06+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-04-26T08:21:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"translational-psychiatry","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"tp","sideBox":"Learn more about [Translational Psychiatry](http://www.nature.com/tp/)","snPcode":"41398","submissionUrl":"https://mts-tp.nature.com/cgi-bin/main.plex","title":"Translational Psychiatry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dcbcf727-0405-48ff-89b8-56d5ffefa73e","owner":[],"postedDate":"May 31st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":32033504,"name":"Biological sciences/Genetics/Genomics/Comparative genomics"},{"id":32033505,"name":"Health sciences/Diseases/Psychiatric disorders/Depression"}],"tags":[],"updatedAt":"2024-10-06T07:05:48+00:00","versionOfRecord":{"articleIdentity":"rs-4328261","link":"https://doi.org/10.1038/s41398-024-03122-4","journal":{"identity":"translational-psychiatry","isVorOnly":false,"title":"Translational Psychiatry"},"publishedOn":"2024-10-05 04:00:00","publishedOnDateReadable":"October 5th, 2024"},"versionCreatedAt":"2024-05-31 20:38:50","video":"","vorDoi":"10.1038/s41398-024-03122-4","vorDoiUrl":"https://doi.org/10.1038/s41398-024-03122-4","workflowStages":[]},"version":"v1","identity":"rs-4328261","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4328261","identity":"rs-4328261","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}