Inflammatory Indices are Associated with Non-Suicidal Self-Injury in Adolescents with Major Depressive Disorder

Inflammatory Indices are Associated with Non-Suicidal Self-Injury in Adolescents with Major Depressive Disorder | 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 Research Article Inflammatory Indices are Associated with Non-Suicidal Self-Injury in Adolescents with Major Depressive Disorder Wenxuan Zhang, Yuhan Zhang, Tianmei Xu, Ye Wang, Enyan Yu, Jing Yue This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7454157/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 12 Dec, 2025 Read the published version in BMC Psychiatry → Version 1 posted 10 You are reading this latest preprint version Abstract Background . The neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-lymphocyte ratio (PLR), and C-reactive protein (CRP)-albumin ratio (CAR) constitute peripheral inflammatory indices. This study aimed to evaluate the correlation between these inflammatory indices and non-suicidal self-injury (NSSI) behavior in adolescents with major depressive disorder (MDD). Methods. Adolescents diagnosed with MDD were enrolled in this study. All participants underwent psychological and biochemical assessments and were classified into two groups based on the presence or absence of NSSI. NLR, MLR, PLR, and CAR were calculated from complete blood counts. Results. A total of 101 adolescents with MDD were included. No significant differences were observed in the demographic data between the groups. The NSSI group had significantly higher levels of white blood cells, neutrophils, high-sensitivity-CRP, NLR, MLR, and CAR, and lower albumin levels than the non-NSSI group. Multivariate regression analysis revealed that NLR and MLR were independently associated with NSSI. The proposed cut-off values were NLR = 1.23 (sensitivity = 70.2% and specificity = 59.1%) and MLR = 0.14 (sensitivity = 77.2% and specificity = 43.2%). Conclusions. Systemic inflammation may play a role in NSSI among adolescents with MDD. NLR and MLR, as cost-effective and easily accessible indices, are associated with NSSI, but further longitudinal studies are required to determine their predictive value. non-suicidal self-injury major depressive disorder neutrophil-lymphocyte ratio monocyte-lymphocyte ratio platelet-lymphocyte ratio CRP-albumin ratio Figures Figure 1 Background Major depressive disorder (MDD) is a leading contributor to the global burden of disease, profoundly affecting patient daily lives and resulting in significant social dysfunction [ 1 ]. Additionally, MDD is a major risk factor for non-suicidal self-injury (NSSI) [ 2 ], involving deliberate self-infliction of harm without suicidal intent, including behaviors such as cutting, burning, bruising, biting, and scratching [ 3 ]. Numerous studies have shown that NSSI is the strongest predictor of future suicidal behavior, with patients with MDD who engage in NSSI being at particularly high risk for potential suicide [ 4 , 5 ]. Epidemiological research indicates that MDD onset peaks between the ages of 15–29 years, with MDD being the second leading cause of death among adolescents worldwide [ 6 ]. A meta-analysis involving 41 countries reported that approximately 22.9% of adolescents have engaged in NSSI [ 7 ]. The incidence of NSSI is significantly higher among adolescents with MDD than in the general adolescent population [ 8 , 9 ]. MDD and NSSI not only increase the consumption of medical resources but also have a huge impact on the social economy. The annual economic burden of MDD in the United States has been estimated to be 326 billion dollars, with direct medical costs accounting for about 37% and indirect costs (such as lost productivity) accounting for an even larger share [ 10 ]. Therefore, adolescents with MDD who engage in NSSI constitute a high-risk group for suicide and represent a significant public health concern. Recent years have seen an increasing interest in the role of inflammatory responses in mood disorders. The neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), and high-sensitivity C-reactive protein (hs-CRP) have been identified as simple and stable clinical indices of systemic inflammation and have been investigated in various neuropsychiatric disorders [ 11 , 12 ]. In 2017, Kayhan et al. indicated that higher PLR values were associated with depression severity [ 13 ]. Additionally, a meta-analysis in 2018 revealed that NLR and PLR values in patients with MDD or bipolar disorder (BD) were significantly higher than those in healthy individuals in the same age group [ 14 ]. CRP is widely used as a measure of low-grade inflammation. In 2024, Wang et al. reported a positive correlation between CRP levels and the severity of depressive symptoms [ 15 ]. A large meta-analysis of 37 studies found that 27% of patients with depression had low-grade inflammation (CRP > 3.0 mg/L) [ 16 ]. One possible explanation is that low-grade inflammation may contribute to the onset and progression of depression through multiple pathways, including inducing oxidative stress damage, increasing glutamatergic excitotoxicity, and affecting the activity of neuronal serotonin transporters [ 17 , 18 ]. The ratio of CRP to albumin (CAR) is a novel biomarker reflecting systemic inflammation and nutritional status. Studies have shown that CAR is associated with poorer cardiovascular outcomes, increased incidence of diabetic complications, lower survival rates in patients with cancer, higher tumor invasiveness, and poorer treatment responses [ 19 , 20 ]. However, research on the role of CAR in neuropsychiatric disorders remains limited. Studies on the relationship between NSSI and inflammatory responses are sparse and inconsistent. In 2024, Bai et al. discovered a significant association between interleukin-6 (IL-6) and NSSI but a weaker link between CRP and NSSI [ 21 ]. This contrasts with the findings of Russel et al. in 2020, who reported a negative correlation between CRP and NSSI, suggesting that higher CRP levels may have a protective effect against NSSI [ 22 ]. One possible explanation for these counterintuitive findings is that low CRP levels reflect an increased susceptibility to early infection, while elevated CRP levels may reflect a more robust anti-inflammatory response or a compensatory mechanism to reduce stress-related immune disorders [ 23 ]. In addition, the specific mechanisms underlying the relationship between inflammation, emotion, and NSSI remain unclear. Some studies suggest that inflammatory factors can cross the blood-brain barrier and transmit signals to the central nervous system, thereby influencing neurotransmitters such as serotonin levels, ultimately leading to changes in emotion and behavior [ 24 ]. In 2015, Brundin et al. proposed that inflammation activates the kynurenine metabolic pathway, triggering a cascade of enzymatic reactions that affect neuroinflammation, glutamatergic neurotransmission, and serotonin synthesis, thereby playing a role in emotion regulation and the occurrence of NSSI behaviors [ 25 ]. Several studies have explored the relationship between NSSI or MDD and inflammatory indices; however, a strong gap in the literature regarding the specific association between NSSI and inflammatory indices in adolescents with MDD exists. Existing research has primarily focused on adult populations or has examined NSSI and MDD separately, without investigating their interplay in adolescents. To address this gap, our study aimed to examine the differences in NLR, MLR, PLR, hs-CRP, and CAR between adolescents with MDD with and without NSSI. By doing so, we seek to provide novel biological insights that may contribute to the early identification and intervention of MDD in this high-risk group. Methods Participants This was a cross-sectional study. Participants were selected using convenience sampling from adolescents aged 12 to 18 years who were hospitalized in the Clinical Psychology Department of Zhejiang Provincial People's Hospital between September 2024 and March 2025. All participants were first-diagnosed MDD patients who had not previously received treatment. To ensure the ethical inclusion of underage participants, informed consent was obtained from both the adolescents and their legal guardians before participation. The study procedures were fully explained, and participants had the opportunity to ask questions before providing written consent. All participants were required to meet the following inclusion criteria: (1) a diagnosis of MDD according to the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-V) [18]; (2) a history of NSSI meeting DSM-V diagnostic criteria, defined as recurrent, intentional self-inflicted harm, such as scratching, pinching, or gouging, occurring at least five times within the past year, resulting in mild to moderate physical damage without suicidal intent. The motivation for self-injury typically involves alleviating negative emotions, resolving interpersonal conflicts, or eliciting positive emotional responses; (3) a Hamilton Depression Rating Scale-24 (HDRS-24) score of ≥24 and a Self-Rating Depression Scale (SDS) score of ≥60 [26]. Patients with MDD were divided into two groups based on NSSI diagnosis: MDD with NSSI and MDD without NSSI. The study was approved by the Ethics Committee of Zhejiang Provincial People's Hospital, and (Ethical Application Ref: QT2024205). The exclusion criteria were as follows: (1) individuals with organic brain diseases, intellectual disabilities, or inability to perform hematological tests or scale assessments; (2) individuals with comorbid psychiatric diagnoses, acute infections, subclinical infections, active or chronic inflammation, autoimmune diseases, and chronic liver or kidney diseases; (3) those who had used anti-inflammatory drugs, antipyretic analgesics, immunosuppressants, or glucocorticoids within the past 2 weeks. Data collection Clinical and demographic data were obtained through medical records and standardized psychological assessments conducted by trained psychiatrists. Regarding blood collection, Participants were asked to fast early in the morning on the day of blood collection, and 5 mL of fasting venous blood was collected from participants. The samples were centrifuged at 4,000 rpm for 10 min to isolate the supernatant. A fully automated biochemical analyzer (AU5831, Beckman Coulter, USA) was used to measure the complete blood count, including the WBC count, monocyte count, lymphocyte count, neutrophil count, platelet count, CRP, and albumin. NLR, MLR, PLR, and CAR were calculated. Cases with incomplete clinical, psychological, or inflammatory marker data were excluded from the analysis to ensure data integrity. Assessments Hamilton Depression Rating Scale-24 The HDRS-24 is a widely used, clinician-administered questionnaire assessing the severity of depression in individuals already diagnosed with the disorder. The scale was developed by Hamilton in 1960 and constitutes a series of questions covering various symptoms of depression, including mood, feelings of guilt, suicidal ideation, insomnia, work and activities, psychomotor agitation or retardation, anxiety, weight loss, and somatic symptoms [27]. Zhao et al. demonstrated that the scale exhibited high inter-rater reliability, with a Fleiss' kappa value of 0.92, and demonstrated good internal consistency, with a Cronbach's alpha of 0.714 [28]. Each item is scored on a scale ranging from 0–2 or 0–4, with higher scores indicating more severe depression. Depressive symptom severity is subsequently categorized as no depression or within the normal range (≤7 points), mild depression (8–16 points), moderate depression (17–23 points), and severe depression (≥24 points). Self-Rating Depression Scale The SDS, first proposed by Zung in 1965, was used to assess depressive symptoms [29]. This scale quantifies and evaluates the severity of depressive symptoms using patient self-reports. The primary aim of the SDS is to provide a simple yet effective means of assessing depressive symptoms in clinical and research settings, particularly in psychiatric outpatient and inpatient settings. Gabrys et al. reported that the scale demonstrated strong inter-rater agreement, with a Fleiss' kappa of 0.89, and satisfactory internal consistency, as indicated by a Cronbach's alpha of 0.88 [30]. The SDS comprises 20 items, each rated according to the frequency of symptoms, with scores ranging from 1–4. The severity of depressive symptoms is classified as normal (<50 points), mild depression (50–59 points), moderate depression (60–69 points), or severe depression (≥70 points) based on the scoring criteria [31]. Statistical analysis Statistical analysis was performed utilizing SPSS version 25.0. Numerical variables were summarized as mean ± standard deviation (SD) and categorical variables as frequencies and percentages. The Shapiro–Wilk test was employed to ascertain the normality of the variables. Regarding normally distributed data, an independent two-sample t-test was applied to compare groups. Regarding non-normally distributed data, the Mann–Whitney U test was utilized for intergroup comparisons. Categorical variables and frequencies were analyzed using the chi-squared (χ 2 ) test. Furthermore, receiver operating characteristic (ROC) curve analysis was conducted to establish optimal cut-off values for indices in detecting NSSI. All statistical tests were considered significant at a two-tailed P-value threshold of <0.05. Results Overall, 101 patients were included in this study, with 57 in the NSSI group and 44 in non-NSSI group. The mean age of the NSSI group was 15.53 years, comprising 45 females and 12 males, whereas that of non-NSSI group was 15.59 years, comprising 30 females and 14 males. Statistical analyses revealed no significant differences between the two groups regarding age, sex, family history, body mass index (BMI), SDS score, or HDRS-24 score (all P > 0.05). The choice of statistical tests was based on the distribution of data, as assessed by the Shapiro–Wilk test. The demographic characteristics of the study participants are summarized in Table 1 . Table 1 Characteristics of the study participants Variables NSSI (n = 57) Non-NSSI (n = 44) P-value Age (years) 15.53 ± 1.501 15.59 ± 1.56 0.833 Female, n (%) 45 (78.9%) 30 (68.2%) 0.220 Family history 4 (7.0%) 0 (0%) 0.201 BMI (kg/m 2 ) 21.73 ± 4.035 20.94 ± 4.406 0.351 SDS 76.21 ± 7.384 73.35 ± 9.218 0.086 HDRS-24 33.21 ± 5.836 31.07 ± 5.860 0.071 BMI, Body mass index; SDS, Self-Rating Depression Scale; HDRS-24, Hamilton Depression Rating Scale-24; NSSI, non-suicidal self-injury The WBC count ( P = 0.006), neutrophil count ( P = 0.001), hs-CRP ( P = 0.050), NLR( P = 0.001), MLR ( P = 0.023), and CAR ( P = 0.028) were significantly higher in adolescents with NSSI than in those without NSSI. The albumin count was significantly lower in the NSSI group ( P = 0.001) (Table 2 ). Table 2 Comparison of blood count parameters between the MDD with NSSI and MDD without NSSI groups Variables NSSI Non-NSSI T/Z P-value WBC (10 9 /L) 6.49 (4.11–9.88) a 5.77 (2.93–11.70) a -2.767 0.006 c Monocyte (10 9 /L) 0.41 (0.23–0.81) a 0.36 (0.11–0.64) a -1.916 0.055 c Neutrophil (10 9 /L) 3.54 (1.44–6.38) a 2.82 (1.38–6.67) a -3.425 0.001 c Lymphocyte (10 9 /L) 2.32 ± 0.56 2.41 ± 0.64 -0.801 0.425 b Platelet (10 9 /L) 265.20 ± 52.89 254.07 ± 47.47 0.908 0.366 b hs-CRP (mg/L) 0.835 (0–7.1) a 0.686 (0–5.7) a -1.963 0.050 c Albumin (g/dL) 4.31 ± 0.26 4.53 ± 0.32 -3.499 0.001 b NLR 1.64 (0.54–4.90) a 1.21 (0.50–2.89) a -3.216 0.001 c PLR 121.94 (57.14–359.76) a 112.18 (59.49–217.76) a -1.154 0.248 c MLR 0.19 (0.07–0.55) a 0.15 (0.07–0.27) a -2.277 0.023 c CAR 0.19 (0–1.62) a 0.16 (0–1.31) a -2.204 0.028 c a Expressed as median (lower–upper quartiles), b T-test, c Mann–Whitney U test NLR, Neutrophil–lymphocyte ratio; PLR, Platelet-lymphocyte ratio; MLR, Monocyte-lymphocyte ratio; CAR, CRP-Albumin ratio; WBC, white blood cells; MDD, major depressive disorder; NSSI, non-suicidal self-injury We used NSSI (1 = yes, 0 = no) as the dependent variable in the logistic regression model. Multivariate logistic regression analysis showed that only NLR (odds ratio [OR] 4.726, 95% confidence interval [CI]: 1.888–11.830, P = 0.001) and MLR (OR 3.798, 95% CI: 1.544–9.340, P = 0.004) were significantly associated with NSSI, after controlling for confounding variables (age, sex, BMI) (Table 3 ). Table 3 A logistic regression model for the associations between NSSI and inflammatory markers Variables OR(95% CI) P-value NLR 4.726 (1.888–11.830) 0.001 MLR 3.798 (1.544–9.340) 0.004 CAR 1.221 (0.264–5.643) 0.798 NLR, Neutrophil–lymphocyte ratio; MLR, Monocyte-lymphocyte ratio; CAR, CRP-Albumin ratio; NSSI, non-suicidal self-injury; OR, Odds ratio; CI, Confidence interval ROC curve analyses were performed to assess the effectiveness of the NLR and MLR in predicting NSSI in adolescents with MDD. According to the ROC curve analysis, the area under the curve was 0.687 (95% CI: 0.584, 0.790, P = 0.001) for NLR and 0.633 (95% CI: 0.525, 0.740, P = 0.023) for MLR. The optimal cut-off values were as follows: 1.513 for NLR, with a sensitivity of 52.6% and a specificity of 82.8%; and 0.173 for MLR, with a sensitivity of 50.9% and a specificity of 75.0% (Fig. 1 ). Discussion This study is the first to explore the association between NSSI behavior and inflammatory markers such as CAR, PLR, NLR, and MLR in the context of adolescents with MDD, adding novel insights into the inflammatory profiles of adolescents with MDD and NSSI. The results showed that adolescents with MDD who engaged in NSSI had significantly higher CAR, NLR, and MLR values. Notably, NLR and MLR were associated with NSSI, after adjusting for age, sex, and BMI, whereas CAR was not significantly associated with NSSI. This indicates that NLR and MLR are independent factors influencing NSSI in adolescents with MDD and have a potential role in the clinical evaluation of NSSI. Neutrophils are the primary responding cells in inflammation, promoting phagocytosis and apoptosis mainly through enhancing inflammatory mediators, whereas lymphocytes are associated with immune regulation and anti-inflammatory responses [ 26 ]. The NLR reflects the balance between two different but complementary components of the immune system. The NLR has been studied in various fields, including autoimmune diseases, malignancies, cardiovascular diseases, and neuropsychiatric disorders [ 32 , 33 ]. Several studies have confirmed NLR elevation in patients with schizophrenia, MDD, and bipolar disorder [ 14 , 34 , 35 ]. Few recent studies have focused on adolescents, and the results of these studies are similar to those obtained from adult samples [ 36 ]. One recent study found that adolescents with depression had a significantly higher NLR than the control group, whereas no significant difference was observed in PLR [ 37 ]. However, the 2022 study by Zheng et al. found no correlation between NLR and NSSI in adolescents with mood disorders [ 38 ]. Their study analyzed adolescents with various mood disorders as a single group, without distinguishing specific diagnoses, which may obscure the distinct relationships between MDD and inflammatory markers. NSSI is frequently linked to stressful events, wherein the hypothalamic-pituitary-adrenal (HPA) axis plays a pivotal role in mediating responses to these stressors [ 39 ]. Animal studies show that stress leads to sustained neutrophil elevation [ 40 ], suggesting a link between stress, inflammation, and self-injury. This study is the first to specifically examine the association between NLR and NSSI in adolescents with MDD, supporting the hypothesis that stress-induced immune activation may contribute to NSSI in this population. Monocytes play a key role in innate immunity and inflammation [ 41 ]. The MLR has been suggested as a novel marker of low-grade inflammation and has been used as a prognostic score for systemic inflammation in diseases such as cancer, coronary heart disease, and pancreatitis [ 36 ]. Elevated MLR may contribute to neuroinflammation by increasing monocyte-related cytokines, activating microglia, and affecting neuroplasticity, impairing emotional regulation and cognitive function [ 26 , 38 ]. Patients with NSSI also exhibit higher pain tolerance, potentially owing to altered endogenous opioid levels. Lower plasma β-endorphin in adolescents with NSSI may enhance monocyte-driven inflammation, similar to immune dysregulation observed in opioid use disorder [ 42 – 44 ]. The results of this study are generally consistent with previous studies. A 2021 study of 193 subjects by Puangsri et al. found that suicide attempts in patients with MDD were associated with higher monocyte counts and MLR, and compared to NLR and PLR, MLR demonstrated superior predictive ability for suicide attempts in this population and may serve as a potential biomarker [ 45 ]. A 2022 study by Zheng et al. showed that high MLR levels in young individuals appeared to be associated with self-harm [ 38 ]. In addition, Dadouli et al. found similar results in BD patients with significantly elevated levels of neutrophils, which they suggested could be attributed to low-grade inflammation or psychological stress [ 46 ]. These findings suggest that increased MLR may reflect a shared inflammatory pathway underlying both NSSI and suicide risk in adolescents with MDD. Hs-CRP is a widely used marker of low-grade inflammation in mental disorders, while albumin reflects nutritional status and can be suppressed by inflammation, leading to hypoalbuminemia [ 47 ]. CAR integrates both markers and has been used to assess systemic inflammation in cancer, rheumatoid arthritis, and cardiovascular diseases [ 20 , 48 ]. Previous studies have established a link between CRP and depression. A large cohort study by Tayefi et al. (2017) found that hs-CRP levels were increased with depression severity [ 49 ], and Liu et al. (2024) further reported elevated hs-CRP in MDD patients, linked to gut microbiota disturbances [ 50 ]. However, no prior study has examined the relationship between CAR and NSSI. Our results showed significant differences in hs-CRP, albumin, and CAR levels between the NSSI and non-NSSI groups. However, regression analysis indicated that CAR is not an independent predictor of NSSI after controlling for confounders. Nutritional factors, such as irregular eating habits or malnutrition in adolescents with NSSI, may contribute to lower albumin levels beyond inflammation. Given that lower albumin may exacerbate oxidative stress and depressive symptoms [ 51 ], future studies should better account for nutritional status when assessing CAR in MDD and NSSI. Overall, this study provides preliminary evidence for the relationship between CAR and NSSI, highlighting the need for further research to clarify its clinical relevance. A sensitivity-prioritized approach is crucial in public health and preventive medicine, because higher sensitivity enhances early disease detection. Based on our findings, we recommend adjusting the NLR cutoff for NSSI risk assessment to 1.23, increasing sensitivity to 70.2% with a slight reduction in specificity (59.1%). Similarly, adjusting the MLR cutoff to 0.14 improved sensitivity (77.2%) but reduced specificity (43.2%). Notably, Zheng et al. proposed a similar MLR cutoff (0.135) for NSSI diagnosis, with higher sensitivity (90.6%) but lower specificity (33.7%) [ 38 ]. While these inflammatory markers show potential associations with NSSI, their reliability as standalone biomarkers remains uncertain due to their fluctuations from acute stress or transient infections. Longitudinal studies are needed to enhance their predictive utility and clinical applicability. This study had some limitations. First, the small sample size may affect the stability and generalizability of the findings, necessitating larger samples in future research. Second, NLR, MLR, and CAR, although widely used, may not fully capture the complex inflammatory processes in MDD with NSSI. Future studies should incorporate cytokines such as IL-6 and TNF-α for a more comprehensive analysis. Third, the cross-sectional design prevents causal inferences, and NSSI may trigger inflammatory responses, potentially confounding biomarker specificity. Longitudinal studies are needed to determine baseline inflammation levels and track temporal changes in these markers. Fourth, Participants were not systematically evaluated or screened for Borderline Personality Disorder (BPD) or borderline traits. Given that non-suicidal self-injury is commonly associated with BPD, the absence of such assessments represents a potential confounding factor and should be addressed in future research. Finally, lifestyle, social support, psychosocial stress, and genetic factors may influence inflammation and should be accounted for in future research to improve the accuracy of inflammation-NSSI associations. Conclusions This study found that MDD adolescents with NSSI displayed altered markers of inflammation. NLR and MLR are affordable and stable indicators that are closely related to NSSI. While these findings suggest a potential role for inflammatory indices in risk assessment, their clinical utility in identifying high-risk individuals requires further investigation through longitudinal studies. Abbreviations BD, bipolar disorder; BDP, Borderline Personality Disorder; CAR, ratio of CRP to albumin; CRP, C-reactive protein; hs-CRP, high-sensitivity C-reactive protein; MDD, major depressive disorder; MRL, monocyte-to-lymphocyte ratio; NRL, neutrophil-to-lymphocyte ratio; NSSI, non-suicidal self-injury; PLR, platelet-to-lymphocyte ratio; SDS, Self-Rating Depression Scale Declarations Ethics Approval and Consent to Participate The study was approved by the Ethics Committee of Zhejiang Provincial People's Hospital (Ethical Application Ref: QT2024205) and conducted in accordance with the Declaration of Helsinki. The committee reviewed the protocol and granted a waiver of informed consent because all data were de-identified and posed no additional risk to patients. Consent for Publication Not applicable. Clinical Trial Number Not applicable. Availability of Data and Materials The datasets generated and analyzed during the current study are not publicly available but are available from the corresponding author on reasonable request. Competing Interests The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Funding This work was supported by the Key Research and Development Project of Zhejiang Provincial (2021C03106). Author Contributions WZ. conducted the statistical analysis, interpreted the data, and drafted the manuscript. YZ. contributed to data collection and assisted in data analysis. TX. participated in the literature review and provided support in manuscript preparation. YW. critically reviewed the manuscript. EY. supervised the study design, guided data interpretation, and revised the manuscript. 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A Self-Rating Depression Scale. Arch Gen Psychiatry. 1965 Jan;12:63-70. Gabrys JB, Peters K. Reliability, discriminant and predictive validity of the Zung Self-Rating Depression Scale. Psychol Rep. 1985 Dec;57:1091-6. Dunstan DA, Scott N. Clarification of the cut-off score for Zung's Self-Rating Depression Scale. BMC Psychiatry. 2019 Jun 11;19:177. Balta S. Mean platelet volume, neutrophil-lymphocyte ratio, and long-term major cardiovascular events. Angiology. 2019 Apr;70:289-90. Papachristodoulou E, Kakoullis L, Christophi C, Psarelis S, Hajiroussos V, Parperis K. The relationship of neutrophil-to-lymphocyte ratio with health-related quality of life, depression, and disease activity in SLE: A cross-sectional study. Rheumatol Int. 2023 Oct;43:1841-8. Cabello-Rangel H, Basurto-Morales M, Botello-Aceves E, Pazarán-Galicia O. Mean platelet volume, platelet count, and neutrophil/lymphocyte ratio in drug-naïve patients with schizophrenia: A cross-sectional study. Front Psychiatry. 2023;14:1150235. Wei Y, Feng J, Ma J, Chen D, Chen J. Neutrophil/lymphocyte, platelet/lymphocyte and monocyte/lymphocyte ratios in patients with affective disorders. J Affect Disord. 2022 Jul 15;309:221-8. Velasco A, Lengvenyte A, Rodriguez-Revuelta J, Jimenez-Treviño L, Courtet P, Garcia-Portilla MP, et al. Neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and monocyte-to-lymphocyte ratio in depressed patients with suicidal behavior: A systematic review. Eur Psychiatry. 2023;67:1–25. Özyurt G, Binici NC. Increased neutrophil-lymphocyte ratios in depressive adolescents is correlated with the severity of depression. Psychiatry Res. 2018 Oct;268:426-31. Zheng Q, Liu J, Ji Y, Zhang Y, Chen X, Liu B. Elevated levels of monocyte-lymphocyte ratio and platelet-lymphocyte ratio in adolescents with non-suicidal self-injury. BMC Psychiatry. 2022 Sep 19;22:618. Brown RC, Plener PL. Non-suicidal self-injury in adolescence. Curr Psychiatry Rep. 2017 Mar;19:20. Dhabhar FS, Malarkey WB, Neri E, McEwen BS. Stress-induced redistribution of immune cells--From barracks to boulevards to battlefields: A tale of three hormones--Curt Richter Award winner. Psychoneuroendocrinology. 2012 Sep;37:1345-68. Tudurachi BS, Anghel L, Tudurachi A, Sascău RA, Stătescu C. Assessment of inflammatory hematological ratios (NLR, PLR, MLR, LMR and monocyte/HDL-cholesterol ratio) in acute myocardial infarction and particularities in young patients. Int J Mol Sci. 2023 Sep 21;24:14378. van der Venne P, Balint A, Drews E, Parzer P, Resch F, Koenig J, et al. Pain sensitivity and plasma beta-endorphin in adolescent non-suicidal self-injury. J Affect Disord. 2021 Jan 1;278:199-208. Liu RT. Characterizing the course of non-suicidal self-injury: A cognitive neuroscience perspective. Neurosci Biobehav Rev. 2017 Sep;80:159-65. Baykara S, Şirin Berk Ş, Kaya Ş, Ocak D. Evaluation of complete blood cell count parameters and lymphocyte-related ratios in patients with Opioid Use Disorder. J Immunoassay Immunochem. 2022 May 4;43:259-70. Puangsri P, Ninla-aesong P. Potential usefulness of complete blood count parameters and inflammatory ratios as simple biomarkers of depression and suicide risk in drug-naive, adolescents with major depressive disorder. Psychiatry Res. 2021 Nov;305:114216. Dadouli K, Janho MB, Hatziefthimiou A, Voulgaridi I, Piaha K, Anagnostopoulos L, et al. Neutrophil-to-lymphocyte, monocyte-to-lymphocyte, platelet-to-lymphocyte ratio and systemic immune-inflammatory index in different states of bipolar disorder. Brain Sci. 2022 Aug 4;12:1034. Luo B, Sun M, Huo X, Wang Y. Two new inflammatory markers related to the CURB-65 score for disease severity in patients with community-acquired pneumonia: The hypersensitive C-reactive protein to albumin ratio and fibrinogen to albumin ratio. Open Life Sci. 2021;16:84-91. Chen C, Chen X, Chen J, Xing J, Hei Z, Zhang Q, et al. Association between preoperative hs-crp/albumin Ratio and postoperative sirs in Elderly Patients: A Retrospective Observational Cohort Study. J Nutr Health Aging. 2022;26:352-9. Tayefi M, Shafiee M, Kazemi-Bajestani SMR, Esmaeili H, Darroudi S, Khakpouri S, et al. Depression and anxiety both associate with serum level of hs-CRP: A gender-stratified analysis in a population-based study. Psychoneuroendocrinology. 2017 Jul;81:63-9. Liu P, Jing L, Guo F, Xu Y, Cheng J, Liu S, et al. Characteristics of gut microbiota and its correlation with hs-CRP and somatic symptoms in first-episode treatment-naive major depressive disorder. J Affect Disord. 2024 Jul 1;356:664-71. Chen S, Xia HS, Zhu F, Yin GZ, Qian ZK, Jiang CX, et al. Association between decreased serum albumin levels and depressive symptoms in patients with schizophrenia in a Chinese Han population: A pilot study. Psychiatry Res. 2018 Dec;270:438-42 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 12 Dec, 2025 Read the published version in BMC Psychiatry → Version 1 posted Editorial decision: Revision requested 15 Sep, 2025 Reviews received at journal 12 Sep, 2025 Reviews received at journal 06 Sep, 2025 Reviewers agreed at journal 06 Sep, 2025 Reviewers agreed at journal 06 Sep, 2025 Reviewers invited by journal 06 Sep, 2025 Editor invited by journal 29 Aug, 2025 Editor assigned by journal 27 Aug, 2025 Submission checks completed at journal 27 Aug, 2025 First submitted to journal 25 Aug, 2025 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-7454157","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":514309358,"identity":"5b0165d4-639b-4a25-9dbb-81b1b9a3fd53","order_by":0,"name":"Wenxuan Zhang","email":"","orcid":"","institution":"Lishui Second People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Wenxuan","middleName":"","lastName":"Zhang","suffix":""},{"id":514309362,"identity":"bd754e70-9883-4848-bf7e-d7fc33d776bd","order_by":1,"name":"Yuhan Zhang","email":"","orcid":"","institution":"Huzhou Central Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yuhan","middleName":"","lastName":"Zhang","suffix":""},{"id":514309363,"identity":"c89931ec-54a5-4191-ba11-5ba48f9898d5","order_by":2,"name":"Tianmei Xu","email":"","orcid":"","institution":"Zhejiang Provincial People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Tianmei","middleName":"","lastName":"Xu","suffix":""},{"id":514309364,"identity":"d4fdd21b-a754-44f7-a94f-b3f3a8d6eb0f","order_by":3,"name":"Ye Wang","email":"","orcid":"","institution":"Tongde Hospital of Zhejiang Province","correspondingAuthor":false,"prefix":"","firstName":"Ye","middleName":"","lastName":"Wang","suffix":""},{"id":514309365,"identity":"0495e62e-f8b6-4243-b204-b08670a15f2a","order_by":4,"name":"Enyan Yu","email":"","orcid":"","institution":"The Cancer Hospital of the University of Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Enyan","middleName":"","lastName":"Yu","suffix":""},{"id":514309366,"identity":"5f20b8c8-1506-408e-aa31-0809f734bdd5","order_by":5,"name":"Jing Yue","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFElEQVRIiWNgGAWjYJACgwQGBjk2ZuZjYB4/M/PhB8RoMeZnb0sD8yTb2dIMiLEpcWbPGTOIAed5FCTw2nAj+UDBwx21jBtupKU9+LnjTuLmwzwMBgw1NtG4taQlGCSeOc4M1HvcsPfMs8Rth3kPPGA4lpbbgFNLjoFBYtsxNqDeNAnetsNALXwJBowNh/Foyf8A0sID1Gsm+ReoZXMzj4EEfi05DEAtNRKSQO9Lg2zZwExAi+SZZyCHHTAABbK07JlnxjMOAwM5AY9f+I4nPzP82VZX3waMSsm3O+7I9vcfPvzgQ40NTi0KBxjYgBF3GMJjbDjgCFaZgEM5CMg3MDA/YGCog2uxx6N4FIyCUTAKRigAALCkacVEt/WfAAAAAElFTkSuQmCC","orcid":"","institution":"Lishui Second People's Hospital","correspondingAuthor":true,"prefix":"","firstName":"Jing","middleName":"","lastName":"Yue","suffix":""}],"badges":[],"createdAt":"2025-08-25 13:23:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7454157/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7454157/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12888-025-07705-3","type":"published","date":"2025-12-12T15:59:03+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":91817032,"identity":"1c503b89-ecb8-4fe0-8ca2-3e2e399345f3","added_by":"auto","created_at":"2025-09-22 06:53:20","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":185138,"visible":true,"origin":"","legend":"","description":"","filename":"NSSIBMC0825.docx","url":"https://assets-eu.researchsquare.com/files/rs-7454157/v1/94e5f26e21b970b0a6564310.docx"},{"id":91816934,"identity":"4117d03b-2601-425d-971b-aac94557bc04","added_by":"auto","created_at":"2025-09-22 06:53:02","extension":"png","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":42434,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7454157/v1/81840eac6201b402093420c9.png"},{"id":91486900,"identity":"9e2b85f3-cce4-47f0-b76a-90d00bdf6380","added_by":"auto","created_at":"2025-09-17 04:59:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":42434,"visible":true,"origin":"","legend":"\u003cp\u003eROC curves of NLR and MLR for prediction of NSSI. Diagonal dotted line represents the reference line (AUC=0.5), indicating no discriminative ability.\u003c/p\u003e\n\u003cp\u003eROC, receiver operating characteristic; NLR, Neutrophil–lymphocyte ratio; MLR, Monocyte-lymphocyte ratio; NSSI, non-suicidal self-injury\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7454157/v1/9670a8f41e9cfcbe7702e7ce.png"},{"id":98245160,"identity":"44647bf2-d3a4-4ccd-bdcc-8469e878f518","added_by":"auto","created_at":"2025-12-15 16:16:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":694993,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7454157/v1/907de7df-8a55-409f-b45c-6887651879ee.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Inflammatory Indices are Associated with Non-Suicidal Self-Injury in Adolescents with Major Depressive Disorder","fulltext":[{"header":"Background","content":"\u003cp\u003eMajor depressive disorder (MDD) is a leading contributor to the global burden of disease, profoundly affecting patient daily lives and resulting in significant social dysfunction [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Additionally, MDD is a major risk factor for non-suicidal self-injury (NSSI) [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], involving deliberate self-infliction of harm without suicidal intent, including behaviors such as cutting, burning, bruising, biting, and scratching [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Numerous studies have shown that NSSI is the strongest predictor of future suicidal behavior, with patients with MDD who engage in NSSI being at particularly high risk for potential suicide [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Epidemiological research indicates that MDD onset peaks between the ages of 15\u0026ndash;29 years, with MDD being the second leading cause of death among adolescents worldwide [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. A meta-analysis involving 41 countries reported that approximately 22.9% of adolescents have engaged in NSSI [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The incidence of NSSI is significantly higher among adolescents with MDD than in the general adolescent population [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. MDD and NSSI not only increase the consumption of medical resources but also have a huge impact on the social economy. The annual economic burden of MDD in the United States has been estimated to be 326\u0026nbsp;billion dollars, with direct medical costs accounting for about 37% and indirect costs (such as lost productivity) accounting for an even larger share [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Therefore, adolescents with MDD who engage in NSSI constitute a high-risk group for suicide and represent a significant public health concern.\u003c/p\u003e\u003cp\u003eRecent years have seen an increasing interest in the role of inflammatory responses in mood disorders. The neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), and high-sensitivity C-reactive protein (hs-CRP) have been identified as simple and stable clinical indices of systemic inflammation and have been investigated in various neuropsychiatric disorders [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In 2017, Kayhan et al. indicated that higher PLR values were associated with depression severity [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Additionally, a meta-analysis in 2018 revealed that NLR and PLR values in patients with MDD or bipolar disorder (BD) were significantly higher than those in healthy individuals in the same age group [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. CRP is widely used as a measure of low-grade inflammation. In 2024, Wang et al. reported a positive correlation between CRP levels and the severity of depressive symptoms [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. A large meta-analysis of 37 studies found that 27% of patients with depression had low-grade inflammation (CRP\u0026thinsp;\u0026gt;\u0026thinsp;3.0 mg/L) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. One possible explanation is that low-grade inflammation may contribute to the onset and progression of depression through multiple pathways, including inducing oxidative stress damage, increasing glutamatergic excitotoxicity, and affecting the activity of neuronal serotonin transporters [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The ratio of CRP to albumin (CAR) is a novel biomarker reflecting systemic inflammation and nutritional status. Studies have shown that CAR is associated with poorer cardiovascular outcomes, increased incidence of diabetic complications, lower survival rates in patients with cancer, higher tumor invasiveness, and poorer treatment responses [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. However, research on the role of CAR in neuropsychiatric disorders remains limited.\u003c/p\u003e\u003cp\u003eStudies on the relationship between NSSI and inflammatory responses are sparse and inconsistent. In 2024, Bai et al. discovered a significant association between interleukin-6 (IL-6) and NSSI but a weaker link between CRP and NSSI [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. This contrasts with the findings of Russel et al. in 2020, who reported a negative correlation between CRP and NSSI, suggesting that higher CRP levels may have a protective effect against NSSI [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. One possible explanation for these counterintuitive findings is that low CRP levels reflect an increased susceptibility to early infection, while elevated CRP levels may reflect a more robust anti-inflammatory response or a compensatory mechanism to reduce stress-related immune disorders [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In addition, the specific mechanisms underlying the relationship between inflammation, emotion, and NSSI remain unclear. Some studies suggest that inflammatory factors can cross the blood-brain barrier and transmit signals to the central nervous system, thereby influencing neurotransmitters such as serotonin levels, ultimately leading to changes in emotion and behavior [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In 2015, Brundin et al. proposed that inflammation activates the kynurenine metabolic pathway, triggering a cascade of enzymatic reactions that affect neuroinflammation, glutamatergic neurotransmission, and serotonin synthesis, thereby playing a role in emotion regulation and the occurrence of NSSI behaviors [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSeveral studies have explored the relationship between NSSI or MDD and inflammatory indices; however, a strong gap in the literature regarding the specific association between NSSI and inflammatory indices in adolescents with MDD exists. Existing research has primarily focused on adult populations or has examined NSSI and MDD separately, without investigating their interplay in adolescents. To address this gap, our study aimed to examine the differences in NLR, MLR, PLR, hs-CRP, and CAR between adolescents with MDD with and without NSSI. By doing so, we seek to provide novel biological insights that may contribute to the early identification and intervention of MDD in this high-risk group.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eParticipants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis was a cross-sectional study. Participants were selected using convenience sampling from adolescents aged 12 to 18 years who were hospitalized in the Clinical Psychology Department of Zhejiang Provincial People\u0026apos;s Hospital between September 2024 and March 2025. All participants were first-diagnosed MDD patients who had not previously received treatment. To ensure the ethical inclusion of underage participants, informed consent was obtained from both the adolescents and their legal guardians before participation. The study procedures were fully explained, and participants had the opportunity to ask questions before providing written consent.\u003c/p\u003e\n\u003cp\u003eAll participants were required to meet the following inclusion criteria: (1) a diagnosis of MDD according to the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-V) [18]; (2) a history of NSSI meeting DSM-V diagnostic criteria, defined as recurrent, intentional self-inflicted harm, such as scratching, pinching, or gouging, occurring at least five times within the past year, resulting in mild to moderate physical damage without suicidal intent. The motivation for self-injury typically involves alleviating negative emotions, resolving interpersonal conflicts, or eliciting positive emotional responses; (3) a Hamilton Depression Rating Scale-24 (HDRS-24) score of \u0026ge;24 and a Self-Rating Depression Scale (SDS) score of \u0026ge;60 [26]. Patients with MDD were divided into two groups based on NSSI diagnosis: MDD with NSSI and MDD without NSSI. The study was approved by the Ethics Committee of Zhejiang Provincial People\u0026apos;s Hospital, and (Ethical Application Ref: QT2024205).\u003c/p\u003e\n\n\u003cp\u003eThe exclusion criteria were as follows: (1) individuals with organic brain diseases, intellectual disabilities, or inability to perform hematological tests or scale assessments; (2) individuals with comorbid psychiatric diagnoses, acute infections, subclinical infections, active or chronic inflammation, autoimmune diseases, and chronic liver or kidney diseases; (3) those who had used anti-inflammatory drugs, antipyretic analgesics, immunosuppressants, or glucocorticoids within the past 2 weeks.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eData collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eClinical and demographic data were obtained through medical records and standardized psychological assessments conducted by trained psychiatrists. Regarding blood collection, Participants were asked to fast early in the morning on the day of blood collection, and 5 mL of fasting venous blood was collected from participants. The samples were centrifuged at 4,000 rpm for 10 min to isolate the supernatant. A fully automated biochemical analyzer (AU5831, Beckman Coulter, USA) was used to measure the complete blood count, including the WBC count, monocyte count, lymphocyte count, neutrophil count, platelet count, CRP, and albumin. NLR, MLR, PLR, and CAR were calculated. Cases with incomplete clinical, psychological, or inflammatory marker data were excluded from the analysis to ensure data integrity.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAssessments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eHamilton Depression Rating Scale-24 \u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe HDRS-24 is a widely used, clinician-administered questionnaire assessing the severity of depression in individuals already diagnosed with the disorder. The scale was developed by Hamilton in 1960 and constitutes a series of questions covering various symptoms of depression, including mood, feelings of guilt, suicidal ideation, insomnia, work and activities, psychomotor agitation or retardation, anxiety, weight loss, and somatic symptoms [27]. Zhao et al. demonstrated that the scale exhibited high inter-rater reliability, with a Fleiss\u0026apos; kappa value of 0.92, and demonstrated good internal consistency, with a Cronbach\u0026apos;s alpha of 0.714 [28]. Each item is scored on a scale ranging from 0\u0026ndash;2 or 0\u0026ndash;4, with higher scores indicating more severe depression. Depressive symptom severity is subsequently categorized as no depression or within the normal range (\u0026le;7 points), mild depression (8\u0026ndash;16 points), moderate depression (17\u0026ndash;23 points), and severe depression (\u0026ge;24 points). \u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSelf-Rating Depression Scale\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe SDS, first proposed by Zung in 1965, was used to assess depressive symptoms [29]. This scale quantifies and evaluates the severity of depressive symptoms using patient self-reports. The primary aim of the SDS is to provide a simple yet effective means of assessing depressive symptoms in clinical and research settings, particularly in psychiatric outpatient and inpatient settings. Gabrys et al. reported that the scale demonstrated strong inter-rater agreement, with a Fleiss\u0026apos; kappa of 0.89, and satisfactory internal consistency, as indicated by a Cronbach\u0026apos;s alpha of 0.88 [30]. The SDS comprises 20 items, each rated according to the frequency of symptoms, with scores ranging from 1\u0026ndash;4. The severity of depressive symptoms is classified as normal (\u0026lt;50 points), mild depression (50\u0026ndash;59 points), moderate depression (60\u0026ndash;69 points), or severe depression (\u0026ge;70 points) based on the scoring criteria [31].\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analysis was performed utilizing SPSS version 25.0. Numerical variables were summarized as mean \u0026plusmn; standard deviation (SD) and categorical variables as frequencies and percentages. The Shapiro\u0026ndash;Wilk test was employed to ascertain the normality of the variables. Regarding normally distributed data, an independent two-sample t-test was applied to compare groups. Regarding non-normally distributed data, the Mann\u0026ndash;Whitney \u003cem\u003eU\u003c/em\u003e test was utilized for intergroup comparisons. Categorical variables and frequencies were analyzed using the chi-squared (\u0026chi;\u003csup\u003e2\u003c/sup\u003e) test. Furthermore, receiver operating characteristic (ROC) curve analysis was conducted to establish optimal cut-off values for indices in detecting NSSI. All statistical tests were considered significant at a two-tailed P-value threshold of \u0026lt;0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eOverall, 101 patients were included in this study, with 57 in the NSSI group and 44 in non-NSSI group. The mean age of the NSSI group was 15.53 years, comprising 45 females and 12 males, whereas that of non-NSSI group was 15.59 years, comprising 30 females and 14 males. Statistical analyses revealed no significant differences between the two groups regarding age, sex, family history, body mass index (BMI), SDS score, or HDRS-24 score (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The choice of statistical tests was based on the distribution of data, as assessed by the Shapiro\u0026ndash;Wilk test. The demographic characteristics of the study participants are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCharacteristics of the study participants\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNSSI (n\u0026thinsp;=\u0026thinsp;57)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNon-NSSI (n\u0026thinsp;=\u0026thinsp;44)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15.53\u0026thinsp;\u0026plusmn;\u0026thinsp;1.501\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15.59\u0026thinsp;\u0026plusmn;\u0026thinsp;1.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.833\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e45 (78.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30 (68.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.220\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFamily history\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (7.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.201\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21.73\u0026thinsp;\u0026plusmn;\u0026thinsp;4.035\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20.94\u0026thinsp;\u0026plusmn;\u0026thinsp;4.406\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.351\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSDS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e76.21\u0026thinsp;\u0026plusmn;\u0026thinsp;7.384\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e73.35\u0026thinsp;\u0026plusmn;\u0026thinsp;9.218\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.086\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHDRS-24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33.21\u0026thinsp;\u0026plusmn;\u0026thinsp;5.836\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e31.07\u0026thinsp;\u0026plusmn;\u0026thinsp;5.860\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.071\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eBMI, Body mass index; SDS, Self-Rating Depression Scale; HDRS-24, Hamilton Depression Rating Scale-24; NSSI, non-suicidal self-injury\u003c/p\u003e\u003cp\u003eThe WBC count (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006), neutrophil count (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001), hs-CRP (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.050), NLR(\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001), MLR (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.023), and CAR (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.028) were significantly higher in adolescents with NSSI than in those without NSSI. The albumin count was significantly lower in the NSSI group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of blood count parameters between the MDD with NSSI and MDD without NSSI groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNSSI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNon-NSSI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eT/Z\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWBC (10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.49 (4.11\u0026ndash;9.88)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.77 (2.93\u0026ndash;11.70)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-2.767\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003csup\u003e\u003cb\u003ec\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMonocyte (10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.41 (0.23\u0026ndash;0.81)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.36 (0.11\u0026ndash;0.64)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-1.916\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.055\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNeutrophil (10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.54 (1.44\u0026ndash;6.38)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.82 (1.38\u0026ndash;6.67)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-3.425\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003csup\u003e\u003cb\u003ec\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLymphocyte (10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.801\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.425\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePlatelet (10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e265.20\u0026thinsp;\u0026plusmn;\u0026thinsp;52.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e254.07\u0026thinsp;\u0026plusmn;\u0026thinsp;47.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.908\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.366\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ehs-CRP (mg/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.835 (0\u0026ndash;7.1)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.686 (0\u0026ndash;5.7)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-1.963\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.050\u003c/b\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlbumin (g/dL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-3.499\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003csup\u003e\u003cb\u003eb\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNLR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.64 (0.54\u0026ndash;4.90)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.21 (0.50\u0026ndash;2.89)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-3.216\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePLR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e121.94 (57.14\u0026ndash;359.76)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e112.18 (59.49\u0026ndash;217.76)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-1.154\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.248\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMLR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.19 (0.07\u0026ndash;0.55)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.15 (0.07\u0026ndash;0.27)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-2.277\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.023\u003c/b\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCAR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.19 (0\u0026ndash;1.62)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.16 (0\u0026ndash;1.31)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-2.204\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.028\u003c/b\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ea\u003c/sup\u003e Expressed as median (lower\u0026ndash;upper quartiles), \u003csup\u003eb\u003c/sup\u003e T-test, \u003csup\u003ec\u003c/sup\u003e Mann\u0026ndash;Whitney U test\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eNLR, Neutrophil\u0026ndash;lymphocyte ratio; PLR, Platelet-lymphocyte ratio; MLR, Monocyte-lymphocyte ratio; CAR, CRP-Albumin ratio; WBC, white blood cells; MDD, major depressive disorder; NSSI, non-suicidal self-injury\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eWe used NSSI (1\u0026thinsp;=\u0026thinsp;yes, 0\u0026thinsp;=\u0026thinsp;no) as the dependent variable in the logistic regression model. Multivariate logistic regression analysis showed that only NLR (odds ratio [OR] 4.726, 95% confidence interval [CI]: 1.888\u0026ndash;11.830, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) and MLR (OR 3.798, 95% CI: 1.544\u0026ndash;9.340, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004) were significantly associated with NSSI, after controlling for confounding variables (age, sex, BMI) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eA logistic regression model for the associations between NSSI and inflammatory markers\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOR(95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNLR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4.726 (1.888\u0026ndash;11.830)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMLR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.798 (1.544\u0026ndash;9.340)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCAR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.221 (0.264\u0026ndash;5.643)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.798\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003eNLR, Neutrophil\u0026ndash;lymphocyte ratio; MLR, Monocyte-lymphocyte ratio; CAR, CRP-Albumin ratio; NSSI, non-suicidal self-injury; OR, Odds ratio; CI, Confidence interval\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eROC curve analyses were performed to assess the effectiveness of the NLR and MLR in predicting NSSI in adolescents with MDD. According to the ROC curve analysis, the area under the curve was 0.687 (95% CI: 0.584, 0.790, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) for NLR and 0.633 (95% CI: 0.525, 0.740, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.023) for MLR. The optimal cut-off values were as follows: 1.513 for NLR, with a sensitivity of 52.6% and a specificity of 82.8%; and 0.173 for MLR, with a sensitivity of 50.9% and a specificity of 75.0% (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study is the first to explore the association between NSSI behavior and inflammatory markers such as CAR, PLR, NLR, and MLR in the context of adolescents with MDD, adding novel insights into the inflammatory profiles of adolescents with MDD and NSSI. The results showed that adolescents with MDD who engaged in NSSI had significantly higher CAR, NLR, and MLR values. Notably, NLR and MLR were associated with NSSI, after adjusting for age, sex, and BMI, whereas CAR was not significantly associated with NSSI. This indicates that NLR and MLR are independent factors influencing NSSI in adolescents with MDD and have a potential role in the clinical evaluation of NSSI.\u003c/p\u003e\u003cp\u003eNeutrophils are the primary responding cells in inflammation, promoting phagocytosis and apoptosis mainly through enhancing inflammatory mediators, whereas lymphocytes are associated with immune regulation and anti-inflammatory responses [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The NLR reflects the balance between two different but complementary components of the immune system. The NLR has been studied in various fields, including autoimmune diseases, malignancies, cardiovascular diseases, and neuropsychiatric disorders [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Several studies have confirmed NLR elevation in patients with schizophrenia, MDD, and bipolar disorder [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Few recent studies have focused on adolescents, and the results of these studies are similar to those obtained from adult samples [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. One recent study found that adolescents with depression had a significantly higher NLR than the control group, whereas no significant difference was observed in PLR [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. However, the 2022 study by Zheng et al. found no correlation between NLR and NSSI in adolescents with mood disorders [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Their study analyzed adolescents with various mood disorders as a single group, without distinguishing specific diagnoses, which may obscure the distinct relationships between MDD and inflammatory markers. NSSI is frequently linked to stressful events, wherein the hypothalamic-pituitary-adrenal (HPA) axis plays a pivotal role in mediating responses to these stressors [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Animal studies show that stress leads to sustained neutrophil elevation [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], suggesting a link between stress, inflammation, and self-injury. This study is the first to specifically examine the association between NLR and NSSI in adolescents with MDD, supporting the hypothesis that stress-induced immune activation may contribute to NSSI in this population.\u003c/p\u003e\u003cp\u003eMonocytes play a key role in innate immunity and inflammation [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. The MLR has been suggested as a novel marker of low-grade inflammation and has been used as a prognostic score for systemic inflammation in diseases such as cancer, coronary heart disease, and pancreatitis [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Elevated MLR may contribute to neuroinflammation by increasing monocyte-related cytokines, activating microglia, and affecting neuroplasticity, impairing emotional regulation and cognitive function [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Patients with NSSI also exhibit higher pain tolerance, potentially owing to altered endogenous opioid levels. Lower plasma β-endorphin in adolescents with NSSI may enhance monocyte-driven inflammation, similar to immune dysregulation observed in opioid use disorder [\u003cspan additionalcitationids=\"CR43\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. The results of this study are generally consistent with previous studies. A 2021 study of 193 subjects by Puangsri et al. found that suicide attempts in patients with MDD were associated with higher monocyte counts and MLR, and compared to NLR and PLR, MLR demonstrated superior predictive ability for suicide attempts in this population and may serve as a potential biomarker [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. A 2022 study by Zheng et al. showed that high MLR levels in young individuals appeared to be associated with self-harm [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. In addition, Dadouli et al. found similar results in BD patients with significantly elevated levels of neutrophils, which they suggested could be attributed to low-grade inflammation or psychological stress [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. These findings suggest that increased MLR may reflect a shared inflammatory pathway underlying both NSSI and suicide risk in adolescents with MDD.\u003c/p\u003e\u003cp\u003eHs-CRP is a widely used marker of low-grade inflammation in mental disorders, while albumin reflects nutritional status and can be suppressed by inflammation, leading to hypoalbuminemia [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. CAR integrates both markers and has been used to assess systemic inflammation in cancer, rheumatoid arthritis, and cardiovascular diseases [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Previous studies have established a link between CRP and depression. A large cohort study by Tayefi et al. (2017) found that hs-CRP levels were increased with depression severity [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e], and Liu et al. (2024) further reported elevated hs-CRP in MDD patients, linked to gut microbiota disturbances [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. However, no prior study has examined the relationship between CAR and NSSI. Our results showed significant differences in hs-CRP, albumin, and CAR levels between the NSSI and non-NSSI groups. However, regression analysis indicated that CAR is not an independent predictor of NSSI after controlling for confounders. Nutritional factors, such as irregular eating habits or malnutrition in adolescents with NSSI, may contribute to lower albumin levels beyond inflammation. Given that lower albumin may exacerbate oxidative stress and depressive symptoms [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e], future studies should better account for nutritional status when assessing CAR in MDD and NSSI. Overall, this study provides preliminary evidence for the relationship between CAR and NSSI, highlighting the need for further research to clarify its clinical relevance.\u003c/p\u003e\u003cp\u003eA sensitivity-prioritized approach is crucial in public health and preventive medicine, because higher sensitivity enhances early disease detection. Based on our findings, we recommend adjusting the NLR cutoff for NSSI risk assessment to 1.23, increasing sensitivity to 70.2% with a slight reduction in specificity (59.1%). Similarly, adjusting the MLR cutoff to 0.14 improved sensitivity (77.2%) but reduced specificity (43.2%). Notably, Zheng et al. proposed a similar MLR cutoff (0.135) for NSSI diagnosis, with higher sensitivity (90.6%) but lower specificity (33.7%) [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. While these inflammatory markers show potential associations with NSSI, their reliability as standalone biomarkers remains uncertain due to their fluctuations from acute stress or transient infections. Longitudinal studies are needed to enhance their predictive utility and clinical applicability.\u003c/p\u003e\u003cp\u003eThis study had some limitations. First, the small sample size may affect the stability and generalizability of the findings, necessitating larger samples in future research. Second, NLR, MLR, and CAR, although widely used, may not fully capture the complex inflammatory processes in MDD with NSSI. Future studies should incorporate cytokines such as IL-6 and TNF-α for a more comprehensive analysis. Third, the cross-sectional design prevents causal inferences, and NSSI may trigger inflammatory responses, potentially confounding biomarker specificity. Longitudinal studies are needed to determine baseline inflammation levels and track temporal changes in these markers. Fourth, Participants were not systematically evaluated or screened for Borderline Personality Disorder (BPD) or borderline traits. Given that non-suicidal self-injury is commonly associated with BPD, the absence of such assessments represents a potential confounding factor and should be addressed in future research. Finally, lifestyle, social support, psychosocial stress, and genetic factors may influence inflammation and should be accounted for in future research to improve the accuracy of inflammation-NSSI associations.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study found that MDD adolescents with NSSI displayed altered markers of inflammation. NLR and MLR are affordable and stable indicators that are closely related to NSSI. While these findings suggest a potential role for inflammatory indices in risk assessment, their clinical utility in identifying high-risk individuals requires further investigation through longitudinal studies.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eBD, bipolar disorder; BDP, Borderline Personality Disorder; CAR, ratio of CRP to albumin; CRP, C-reactive protein; hs-CRP, high-sensitivity C-reactive protein; MDD, major depressive disorder; MRL, monocyte-to-lymphocyte ratio; NRL, neutrophil-to-lymphocyte ratio; NSSI, non-suicidal self-injury; PLR, platelet-to-lymphocyte ratio; SDS, Self-Rating Depression Scale\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Ethics Committee of Zhejiang Provincial People\u0026apos;s Hospital (Ethical Application Ref: QT2024205) and conducted in accordance with the Declaration of Helsinki. The committee reviewed the protocol and granted a waiver of informed consent because all data were de-identified and posed no additional risk to patients.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial Number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eof Data and Materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed during the current study are not publicly available but are available from the corresponding author on reasonable request.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Key Research and Development Project of Zhejiang Provincial (2021C03106).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWZ. conducted the statistical analysis, interpreted the data, and drafted the manuscript. YZ. contributed to data collection and assisted in data analysis. TX. participated in the literature review and provided support in manuscript preparation. YW. critically reviewed the manuscript. EY. supervised the study design, guided data interpretation, and revised the manuscript. JY. conceived the study, provided overall supervision, and made substantial contributions to manuscript revision. All authors read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank Editage for the English language editing.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKang SG, Cho SE. Neuroimaging biomarkers for predicting treatment response and recurrence of major depressive disorder. Int J Mol Sci. 2020 Mar 20;21:2148.\u003c/li\u003e\n\u003cli\u003ePeng B, Wang R, Zuo W, Liu H, Deng C, Jing X, et al. 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Psychiatry Res. 2018 Dec;270:438-42\u003c/li\u003e\n\u003c/ol\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":"bmc-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bpsy","sideBox":"Learn more about [BMC Psychiatry](http://bmcpsychiatry.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bpsy/default.aspx","title":"BMC Psychiatry","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"non-suicidal self-injury, major depressive disorder, neutrophil-lymphocyte ratio, monocyte-lymphocyte ratio, platelet-lymphocyte ratio, CRP-albumin ratio","lastPublishedDoi":"10.21203/rs.3.rs-7454157/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7454157/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e. The neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-lymphocyte ratio (PLR), and C-reactive protein (CRP)-albumin ratio (CAR) constitute peripheral inflammatory indices. This study aimed to evaluate the correlation between these inflammatory indices and non-suicidal self-injury (NSSI) behavior in adolescents with major depressive disorder (MDD).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods.\u003c/strong\u003e Adolescents diagnosed with MDD were enrolled in this study. All participants underwent psychological and biochemical assessments and were classified into two groups based on the presence or absence of NSSI. NLR, MLR, PLR, and CAR were calculated from complete blood counts.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults.\u003c/strong\u003e A total of 101 adolescents with MDD were included. No significant differences were observed in the demographic data between the groups. The NSSI group had significantly higher levels of white blood cells, neutrophils, high-sensitivity-CRP, NLR, MLR, and CAR, and lower albumin levels than the non-NSSI group. Multivariate regression analysis revealed that NLR and MLR were independently associated with NSSI. The proposed cut-off values were NLR = 1.23 (sensitivity = 70.2% and specificity = 59.1%) and MLR = 0.14 (sensitivity = 77.2% and specificity = 43.2%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions.\u003c/strong\u003e Systemic inflammation may play a role in NSSI among adolescents with MDD. NLR and MLR, as cost-effective and easily accessible indices, are associated with NSSI, but further longitudinal studies are required to determine their predictive value.\u003c/p\u003e","manuscriptTitle":"Inflammatory Indices are Associated with Non-Suicidal Self-Injury in Adolescents with Major Depressive Disorder","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-17 04:59:28","doi":"10.21203/rs.3.rs-7454157/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-15T15:02:14+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-12T09:58:54+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-06T09:26:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"283992786235685778861142657736669357024","date":"2025-09-06T09:24:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"16340381354431932147750120729734129598","date":"2025-09-06T09:22:50+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-06T09:21:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-08-29T05:39:20+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-27T11:01:28+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-27T10:59:56+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychiatry","date":"2025-08-25T13:08:39+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bpsy","sideBox":"Learn more about [BMC Psychiatry](http://bmcpsychiatry.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bpsy/default.aspx","title":"BMC Psychiatry","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9f84b20e-b047-492b-b940-514ec74c7854","owner":[],"postedDate":"September 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-15T16:12:22+00:00","versionOfRecord":{"articleIdentity":"rs-7454157","link":"https://doi.org/10.1186/s12888-025-07705-3","journal":{"identity":"bmc-psychiatry","isVorOnly":false,"title":"BMC Psychiatry"},"publishedOn":"2025-12-12 15:59:03","publishedOnDateReadable":"December 12th, 2025"},"versionCreatedAt":"2025-09-17 04:59:28","video":"","vorDoi":"10.1186/s12888-025-07705-3","vorDoiUrl":"https://doi.org/10.1186/s12888-025-07705-3","workflowStages":[]},"version":"v1","identity":"rs-7454157","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7454157","identity":"rs-7454157","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}