Suicide: Genetics and Heritability

Evidence for the biopsychosocial model of suicide: a review of whole person modeling studies using machine learning

Background

Traditional approaches to modeling suicide-related thoughts and behaviors focus on few data types from often-siloed disciplines. While psychosocial aspects of risk for these phenotypes are frequently studied, there is a lack of research assessing their impact in the context of biological factors, which are important in determining an individual's fulsome risk profile. To directly test this biopsychosocial model of suicide and identify the relative importance of predictive measures when considered together, a transdisciplinary, multivariate approach is needed. Here, we systematically review the emerging literature on large-scale studies using machine learning to integrate measures of psychological, social, and biological factors simultaneously in the study of suicide.

Methods

We conducted a systematic review of studies that used machine learning to model suicide-related outcomes in human populations including at least one predictor from each of biological, psychological, and sociological data domains. Electronic databases MEDLINE, EMBASE, PsychINFO, PubMed, and Web of Science were searched for reports published between August 2013 and August 30, 2023. We evaluated populations studied, features emerging most consistently as risk or resilience factors, methods used, and strength of evidence for or against the biopsychosocial model of suicide.

Results

Out of 518 full-text articles screened, we identified a total of 20 studies meeting our inclusion criteria, including eight studies conducted in general population samples and 12 in clinical populations. Common important features identified included depressive and anxious symptoms, comorbid psychiatric disorders, social behaviors, lifestyle factors such as exercise, alcohol intake, smoking exposure, and marital and vocational status, and biological factors such as hypothalamic-pituitary-thyroid axis activity markers, sleep-related measures, and selected genetic markers. A minority of studies conducted iterative modeling testing each data type for contribution to model performance, instead of reporting basic measures of relative feature importance.

Conclusion

Studies combining biopsychosocial measures to predict suicide-related phenotypes are beginning to proliferate. This literature provides some early empirical evidence for the biopsychosocial model of suicide, though it is marred by harmonization challenges. For future studies, more specific definitions of suicide-related outcomes, inclusion of a greater breadth of biological data, and more diversity in study populations will be needed.

The combination of autism and exceptional cognitive ability is associated with suicidal ideation

Autism with co-occurring exceptional cognitive ability is often accompanied by severe internalizing symptoms and feelings of inadequacy. Whether cognitive ability also translates into greater risk for suicidal ideation is unclear. To investigate this urgent question, we examined two samples of high-ability autistic individuals for factors that were predictive of suicidal ideation. In the first sample (N = 1,074 individuals seen at a clinic specializing in gifted/talented youth), we observed a striking excess of parent-reported suicidal ideation in autistic individuals with IQ ≥ 120 (Odds Ratio = 5.9, p=0.0007). In a separate sample of SPARK participants, we confirmed higher rates of suicidal thoughts compared to non-autistic children from the ABCD cohort (combined N = 16,049, Odds Ratio = 6.8, p<2.2e-16), and further that autistic children with suicidal thoughts had significantly higher cognitive ability (p<2.2e-16) than those without. Elevated polygenic scores (PGS) for cognitive performance were associated with increased suicidal thoughts (N = 1,983, Z=2.16,p=0.03), with PGS for educational attainment trending in the same direction (Z=1.4,p=0.17). Notably, similar results were found in parents of these autistic youth, where higher PGS for educational attainment was associated with increasing thoughts of suicide (N = 736, Z=2.28,p=0.02). Taken together, these results suggest that on a phenotypic and genetic level, increasing cognitive ability is an unexpected risk factor for suicidal ideation in individuals diagnosed with, or at risk for autism.

Genome-wide association study meta-analysis of suicide death and suicidal behavior

Suicide is a worldwide health crisis. We aimed to identify genetic risk variants associated with suicide death and suicidal behavior. Meta-analysis for suicide death was performed using 3765 cases from Utah and matching 6572 controls of European ancestry. Meta-analysis for suicidal behavior using data across five cohorts (n = 8315 cases and 256,478 psychiatric or populational controls of European ancestry) was also performed. One locus in neuroligin 1 (NLGN1) passing the genome-wide significance threshold for suicide death was identified (top SNP rs73182688, with p = 5.48 × 10^-8 before and p = 4.55 × 10^-8 after mtCOJO analysis conditioning on MDD to remove genetic effects on suicide mediated by MDD). Conditioning on suicidal attempts did not significantly change the association strength (p = 6.02 × 10^-8), suggesting suicide death specificity. NLGN1 encodes a member of a family of neuronal cell surface proteins. Members of this family act as splice site-specific ligands for beta-neurexins and may be involved in synaptogenesis. The NRXN-NLGN pathway was previously implicated in suicide, autism, and schizophrenia. We additionally identified ROBO2 and ZNF28 associations with suicidal behavior in the meta-analysis across five cohorts in gene-based association analysis using MAGMA. Lastly, we replicated two loci including variants near SOX5 and LOC101928519 associated with suicidal attempts identified in the ISGC and MVP meta-analysis using the independent FinnGen samples. Suicide death and suicidal behavior showed positive genetic correlations with depression, schizophrenia, pain, and suicidal attempt, and negative genetic correlation with educational attainment. These correlations remained significant after conditioning on depression, suggesting pleiotropic effects among these traits. Bidirectional generalized summary-data-based Mendelian randomization analysis suggests that genetic risk for the suicidal attempt and suicide death are both bi-directionally causal for MDD.

Association of parental death and illness with offspring suicidal ideation: cross-sectional study in a large cohort of university students

PURPOSE

The aim of this study was to (1) investigate the association of parental death and illness with suicidal ideation using a large sample of university students and (2) test whether associations were moderated by perceived family support.

METHODS

We used data from N = 15,008 French university students enrolled in the i-Share cohort (mean age, 20.5 years; 77% women). Students self-reported information on parental death, including the cause, parental illness (cardiovascular, stroke, cancer, depression/anxiety, alcohol abuse), and perceived family support during childhood/adolescence. Twelve-month suicidal ideation was self-reported and categorized into no, occasional, and frequent ideation.

RESULTS

Occasional and frequent suicidal ideation were, respectively, reported by 2692 (17.5%) and 699 (4.6%) students. After adjustment for age, gender, and parental education, we found associations between parental death and risk of occasional and frequent suicidal ideation (respectively, RR = 1.98 [1.81-2.17] and RR = 2.73 [2.30-3.24]). Parental deaths from illness, accidents, and suicides had the strongest associations. We also found associations for parental depression/anxiety (occasional, RR = 1.98 [1.81-2.17]; frequent, RR = 2.73 [2.30-3.24]), alcohol use problems (occasional, RR = 1.71 [1.5-1.94]; frequent, RR = 2.33 [1.89-2.87]), and cardiovascular diseases (occasional, RR = 1.22 [1.06-1.40]; frequent, RR = 1.83 [1.47-2.27]). For participants who experienced parental death and stroke, associations with occasional and frequent suicidal ideation (respectively) increased as perceived family support increased (Ps_interaction ≤ 0.005).

CONCLUSIONS

Students who experienced parental death and common parental illnesses were at risk of reporting suicidal ideation, especially if their family were perceived as an important source of support. As information on parental death or illness can be routinely collected during health visits, attention should be paid to students reporting such experiences.

Suicide Biomarkers to Predict Risk, Classify Diagnostic Subtypes, and Identify Novel Therapeutic Targets: 5 Years of Promising Research

BACKGROUND

Suicide is a global health crisis. However, no objective biomarkers of suicide risk currently exist, and self-reported data can be unreliable, which limits prediction, diagnostic, and treatment efforts. Reliable biomarkers that can differentiate between diagnostic subgroups, predict worsening symptoms, or suggest novel therapeutic targets would be extremely valuable for patients, researchers, and clinicians.

METHODS

MEDLINE was searched for reports published between 2016 and 2021 using search terms (suicid*) AND (biomarker*) OR (indicat*). Reports that compared biomarkers between suicidal ideation, suicide attempt, death from suicide, or any suicide subgroup against other neuropsychiatric disorders were included. Studies exclusively comparing suicidal behavior or death from suicide with healthy controls were not included to ensure that biomarkers were specific to suicide and not other psychopathology.

RESULTS

This review summarizes the last 5 years of research into suicide-associated biomarkers and provides a comprehensive guide for promising and novel biomarkers that encompass varying presentations of suicidal ideation, suicide attempt, and death by suicide. The serotonergic system, inflammation, hypothalamic-pituitary-adrenal axis, lipids, and endocannabinoids emerged as the most promising diagnostic, predictive, and therapeutic indicators.

CONCLUSIONS

The utility of diagnostic and predictive biomarkers is evident, particularly for suicide prevention. While larger-scale studies and further in-depth research are required, the last 5 years of research has uncovered essential biomarkers that could ultimately improve predictive strategies, aid diagnostics, and help develop future therapeutic targets.

[Suicide, a separate entity in psychiatry]

Since ancient times, the subject of suicide has been recurrently discussed in societies. Whether it is a selfish or altruistic act, the ethical debate has always been intense. Today, the suicidal act is at the center of the public debate with the subject of euthanasia and assisted suicide. Philosophers, theologians, sociologists, doctors and jurists share their thoughts on this subject, which is still considered "taboo". Between suicide, suicidal ideas or suicidal crisis, the stakeholders are involved in the field of prevention and are mobilizing to propose innovative treatments.