Distinct Clinical Characteristics Correlate Network of Suicide Attempters in Adolescent Major Depressive Disorder with Non-suicidal Self-Injury (Preprint)
Bibliographic record
Abstract
BACKGROUND Major depressive disorder (MDD), the leading cause of disability worldwide, is regarded as the main cause of global burden of disease in youth. MDD is a common multifactorial, recurrent, and chronic psychological illness and one of the major risk factors for suicide attempts (SA) and non-suicidal self-injury (NSSI). NSSI refers to behaviors causing deliberate destruction or damage to one’s body without a conscious suicidal intention, it has a high incidence in both adults and adolescents and is associated with many psychiatric disorders. Suicide is one of the most serious consequences of mental illness and the fourth leading cause of death among adolescence. According to the WHO (2021), more than 700,000 people die by suicide every year globally (Suicide worldwide in 2019: global health estimates). Previous studies have reported that more than 90 percent of suicides occur in the context of depression, such as MDD. The severity of depression was not only positively correlated with the probability of NSSI, but also laid a mediating effect on stressful life events and NSSI. Therefore, MDD with NSSI are considered as potential suicidal population. Notably, NSSI is highly prevalent and frequently co-occur with suicidal attempt in both clinical and non-clinical populations of adolescents, and has been regarded to predict future suicide attempts. Since suicidal behavior usually begins with self-injury, which is common among young patients with depression, it is critical to investigate risk factors for suicide in MDD with self-injury behaviors. Behavioral abnormalities have been studied, such as executive dysfunction in the depressed adolescents with NSSI and patients of bipolar disorder with suicidal ideation, impaired decision making in patients with SA; based on the assessments of various behavioral symptoms, a number of statistical or actuarial scales have emerged to aid clinicians predict and manage suicide risk. Studies of biomarkers and neural markers of suicide risk have been reported including neural connectivity as a predictor of response in NSSI after psychotherapy or biologically-informed approaches; the low level of cholesterol in sera as a potential biomarker of suicide in patients with MDD and suicidal behavior. Blunted HPA axis activity and dysfunctional adaptive immune response are also associated with increased suicide attempts. Elevated inflammation as presented as increased CRP level in sera was found in patients with SA. Evidence also supported the association between dyslipidemia and suicide risk. Massive studies have been conducted regarding the differences of psychological characteristics, immunity, and metabolic properties between patients with NSSI and suicidal ideation, and the correlation between the immune function and psychological properties was found in patients with SA. Previous studies mainly focused on the investigation of clinical differences between suicide and non-suicide patients, however the results were often inconsistent due to the limited reliability of univariate analysis for the sample heterogeneity in clinic. OBJECTIVE In this study, we aim to investigate the differences and correlation network of multiple psychological and biochemical indicators of suicidal and non-suicidal MDD with NSSI in adolescents. The distinct correlation profile may offer cues for prediction of suicide risk in adolescent MDD with NSSI. METHODS This study was approved by the Ethical Committee of Shenzhen Kangning Hospital (Approved No. 2020-K033-01). One hundred and thirty patients with major depression associated with NSSI were recruited from the Department of Depressive Disorders, Shenzhen Kangning Hospital between March 2020 and January 2021. Participants were young adults aged between 12–35 years old with a history of self- injury for at least 1 year. We collected relevant data from the included subjects: i) Ottawa Self-injury Inventory (OSI) ; Beck Depression Inventory-Ⅱ (BDI-Ⅱ) ; State Trait Anxiety Inventory (STAI); Barrat impulsiveness scale (BIS-11); Difficulties in Emotion Regulation Scale (DERS); State-Trait Anger Expression Inventory (STAXI-2); Borderline Symptom List (BSL-23); Childhood Trauma Questionnaire (CTQ); Ethics Position Questionnaire (EPQ); The Defense Style Questionnaire (DSQ) and Copying Style Questionnaire (CSQ); ii) peripheral blood samples for biochemical assessment. Informed written consent was obtained from all the included participants with their knowledge of this study procedures. The detailed information of the included subjects is displayed in Tables 1-3. With education for at least 6 years, participants were assessed by a trained psychiatrist in the Mini-International Neuropsychological Interview (M.I.N.I.) to meet the DSM-5 diagnosis of MDD. All included patients had a history of self- injury for at least 1 year. Eighty of the 130 participants had suicide attempt in the last year, were included in the group of suicide attempters (‘NSSI+SA’). Fifty people were classified in the non-suicidal self-injury group (‘NSSI’). All included participants had no major physical illness (including acute or chronic infectious diseases and heart, liver, kidney, endocrine, and immune system diseases) or other psychological disorder; they did not have significant factors affecting their immune function and hormone secretion (such as taking immunosuppressant and glucocorticoid). None of the patients were using lipid-lowering medication or sugar-lowering medication. Participants were excluded if they had a major physical illness or other psychological disorder or if they had significant factors affecting their immune function and hormone secretion. Written consent was obtained from participants or their family before the start of the study. Determination of biochemical and immunological indicators Blood samples of patients were collected between 7:00 and 8:00 am. After a 12‑hour fasting. 5 mL of venous blood was extracted and centrifuged at 2500 r/min for 10min. The supernatant was obtained as the serum for further analysis. For the serum lipid, cortisol and blood glucose concentration enzyme linked immunosorbent assay (ELISA) methods were used; the levels of CRP and ACTH were measured by immunoturbidimetry. Behavioral Assessment OSI OSI is a scale used to assess non-suicidal NSSI behavior. The scale consists of a series of independent subscales to assess intention and frequency of NSSI behavior, motivation for initial and ongoing NSSI behavior, and addiction and other NSSI behavioral characteristics [28]. In this study, we utilized the first item in the OSI scale to evaluate the frequency of NSSI in the past one year and one month, and the second item to evaluate whether the patient had suicidal behavior. BDI-Ⅱ BDI-II is a commonly-used, well-validated self-report measure of depressive symptoms. The analyses based on scores that rank depression levels. Its Chinese version has been widely used to assess the symptoms and severity of depression in patients with mental illness and the general population [29]. STAI STAI consists of two subscales, one measuring state anxiety (STAI-S) and the other measuring trait anxiety (STAI-T). The total score on each subscale ranged from 20 to 80, with higher scores indicating more anxiety symptoms. STAI has good applicability in Chinese population [30]. BIS-11 BIS-11 is a scale used to measure impulsivity in an individual's behavior. It consists of three subscales (motor, attentional, non-planning) with a total score of 30-120, with higher scores indicating higher levels of impulsivity. BIS-11 showed good psychometrics in Chinese population samples [31]. DERS DERS is an effective instrument to measure the difficulty of emotion regulation - the difficulty of emotion regulation scale. Among them, there are 6 factors: difficulty in emotional response acceptance, difficulty in goal orientation, difficulty in impulse control, difficulty in emotional awareness, difficulty in the use of regulatory strategies and difficulty in emotional understanding. The higher the score, the more serious the difficulty of emotional regulation, the lower the level of emotional regulation ability. Studies have confirmed its applicability in the Chinese population samples [32]. STAXI-2 STAXI-2 is currently the preferred tool for evaluating the experience and expression of anger, which provides a simple and objective scoring method for the experience, expression and control of anger. The scale can measure state anger, trait anger, and anger expression and control respectively. BSL-23 BSL-23 [33] is a self-rating scale for assessing marginal symptoms. The total score is in a range of 0-92. The higher the score, the more severe the marginal symptoms. BSL-23 has good psychometrics in Chinese population samples [34]. CTQ CTQ was developed by Bernstein et al., which is currently recognized as one of the most effective tools for measuring childhood abuse [35]. The scale includes both abuse and neglect. Among them, abuse includes emotional abuse, physical abuse and sexual abuse. Neglect also includes emotional neglect and physical neglect. The Chinese version of CTQ has been shown to have adequate psychometric properties [36]. EPQ The EPQ questionnaire was compiled by the British psychologist Professor Eysenck and others. The children's version and the adult version are applicable to subjects aged 7-15 and over 16 years, respectively. Both versions of the questionnaire included four subscales: internal and external orientation, mental quality, spiritual quality, and concealment. In this study, the children version and the adult version of t
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".