Associations Between Genetic Risk for Adult Suicide Attempt and Suicidal Behaviors in Young Children in the US.

Importance: Suicide rates have been increasing among youth in the US. While the heritability of suicide risk is well established, there is limited understanding of how genetic risk is associated with suicidal thoughts and behaviors in young children. Objective: To examine whether genetic susceptibility to suicide attempts (SAs) is associated with suicidal thoughts and behaviors in children. Design, Setting, and Participants: This case-control study examined data from the Adolescent Brain Cognitive Development (ABCD) study, a population-based longitudinal study of 11 878 US children enrolled at age 9 and 10 years from September 2016 to November 2018. Youth reports of suicidal ideation (SI) and SAs were obtained from the Kiddie Schedule for Affective Disorder and Schizophrenia at baseline and 2 subsequent years. After conservative quality control of genotype data, this analysis focused on 4344 unrelated individuals of European ancestry. Data analysis was conducted from November 2020 to February 2022. Main Outcomes and Measures: Children's lifetime experiences of SI and SAs were assessed each year from ages 9 to 10 years to ages 11 to 12 years. Polygenic risk scores (PRSs) for SAs were calculated for ABCD study participants based on the largest genome-wide association study of SA cases and controls of European ancestry (total sample n = 518 612). Results: Of 4344 children of European ancestry (2045 [47.08%] female; mean [SD] age, 9.93 [0.62] years), significant associations were found between children's SA PRSs and their lifetime SAs with the most robust association in the follow-up year 2 (odds ratio, 1.43 [95% CI, 1.18-1.75]; corrected P = 1.85 × 10-3; Nagelkerke pseudo R2 = 1.51%). These associations remained significant after accounting for children's sociodemographic backgrounds, psychopathology symptoms, parental histories of suicide and mental health, and PRSs for major depression and attention-deficit/hyperactivity disorder (likelihood ratio test P < .05). Children's depressive mood and aggressive behavior were the most significant partial mediators of SA genetic risk on SAs (mediation analysis P < 1 × 10-16). Children's behavioral problems, such as attention problems, rule-breaking behavior, and social problems, also partially mediated the association of SA PRSs with SAs (mediation analysis false discover rate < 0.05). Conclusions and Relevance: This study's findings indicate that there may be genetic factors associated with SA risk across the life span and suggest behaviors and conditions through which the risk could be mediated in childhood. Further research is warranted to examine whether incorporating genetic data could improve the identification of children at risk for suicide.

Genetic Association of Attention-Deficit/Hyperactivity Disorder and Major Depression With Suicidal Ideation and Attempts in Children: The Adolescent Brain Cognitive Development Study.

BACKGROUND: Suicide is among the leading causes of death in children and adolescents. There are well-known risk factors of suicide, including childhood abuse, family conflicts, social adversity, and psychopathology. While suicide risk is also known to be heritable, few studies have investigated genetic risk in younger individuals. METHODS: Using polygenic risk score analysis, we examined whether genetic susceptibility to major psychiatric disorders is associated with suicidal behaviors among 11,878 children enrolled in the ABCD (Adolescent Brain Cognitive Development) Study. Suicidal ideation and suicide attempt data were assessed using the youth report of the Kiddie Schedule for Affective Disorders and Schizophrenia for DSM-5. After performing robust quality control of genotype data, unrelated individuals of European descent were included in analyses (n = 4344). RESULTS: Among 8 psychiatric disorders we examined, depression polygenic risk scores were associated with lifetime suicide attempts both in the baseline (odds ratio = 1.55, 95% CI = 1.10-2.18, p = 1.27 × 10-2) and in the follow-up year (odds ratio = 1.38, 95% CI = 1.08-1.77, p = 1.05 × 10-2), after adjusting for children's age, sex, socioeconomic backgrounds, family history of suicide, and psychopathology. In contrast, attention-deficit/hyperactivity disorder polygenic risk scores were associated with lifetime suicidal ideation (odds ratio = 1.15, 95% CI = 1.05-1.26, p = 3.71 × 10-3), suggesting a distinct contribution of the genetic risk underlying attention-deficit/hyperactivity disorder and depression on suicidal behaviors of children. CONCLUSIONS: The largest genetic sample of suicide risk data in U.S. children suggests a significant genetic basis of suicide risk related to attention-deficit/hyperactivity disorder and depression. Further research is warranted to examine whether incorporation of genomic risk may facilitate more targeted screening and intervention efforts.

Cross-Disorder Genomics Data Analysis Elucidates a Shared Genetic Basis Between Major Depression and Osteoarthritis Pain.

Osteoarthritis (OA) and major depression (MD) are two debilitating disorders that frequently co-occur and affect millions of the elderly each year. Despite the greater symptom severity, poorer clinical outcomes, and increased mortality of the comorbid conditions, we have a limited understanding of their etiologic relationships. In this study, we conducted the first cross-disorder investigations of OA and MD, using genome-wide association data representing over 247K cases and 475K controls. Along with significant positive genome-wide genetic correlations (r g = 0.299 ± 0.026, p = 9.10 × 10-31), Mendelian randomization (MR) analysis identified a bidirectional causal effect between OA and MD (ßOA → MD = 0.09, SE = 0.02, z-score p-value < 1.02 × 10-5; ßMD → OA = 0.19, SE = 0.026, p < 2.67 × 10-13), indicating genetic variants affecting OA risk are, in part, shared with those influencing MD risk. Cross-disorder meta-analysis of OA and MD identified 56 genomic risk loci (P meta ≤ 5 × 10-8), which show heightened expression of the associated genes in the brain and pituitary. Gene-set enrichment analysis highlighted "mechanosensory behavior" genes (GO:0007638; P gene_set = 2.45 × 10-8) as potential biological mechanisms that simultaneously increase susceptibility to these mental and physical health conditions. Taken together, these findings show that OA and MD share common genetic risk mechanisms, one of which centers on the neural response to the sensation of mechanical stimulus. Further investigation is warranted to elaborate the etiologic mechanisms of the pleiotropic risk genes, as well as to develop early intervention and integrative clinical care of these serious conditions that disproportionally affect the aging population.

Genomewide alteration of histone H3K4 methylation underlies genetic vulnerability to psychopathology.

Dysregulated histone methylation has emerged as a recurring theme in multiple neuropsychiatric disorders. However, it is yet unclear whether the altered histone methylation is associated with aetiologic mechanisms or an outcome of disease manifestation. In this study, we examined the genomewide association studies datasets of three major psychiatric disorders, schizophrenia (SCZ), bipolar disorder (BIP), and major depression disorder (MDD), which represents a total of 231,783 cases and 425,444 controls, to clarify the relationship. Our gene-set enrichment analysis results identified statistically significant association of genes involved in three histone methylation biological processes with the three adult-onset psychiatric disorders, which is mainly driven by the histone H3K4 methylation pathway (GO: 0051568). Further analysis of histone H3K4 methylation pathway genes revealed a widespread role of the genes in brain function and disease; 29 (52%) and 41 genes (73.2%) were associated with at least one brain-related trait or brain disorder, respectively. Spatiotemporal gene expression analysis suggests that these pathway genes play a critical role during the prenatal period and are consistent regulators in the cerebral cortex throughout an individual's life. AUTS2, DNMT1 and TET2 are genes of particular interest due to their pervasive role in various aspects of brain function. Our findings support a critical aetiologic role of H3K4 methylation genes shared across SCZ, BIP and MDD, providing new direction for the development of epigenetically-focussed drugs targeting common causal factors of these devastating disorders.

Pathway analysis for genome-wide genetic variation data: Analytic principles, latest developments, and new opportunities.

Pathway analysis, also known as gene-set enrichment analysis, is a multilocus analytic strategy that integrates a priori, biological knowledge into the statistical analysis of high-throughput genetics data. Originally developed for the studies of gene expression data, it has become a powerful analytic procedure for in-depth mining of genome-wide genetic variation data. Astonishing discoveries were made in the past years, uncovering genes and biological mechanisms underlying common and complex disorders. However, as massive amounts of diverse functional genomics data accrue, there is a pressing need for newer generations of pathway analysis methods that can utilize multiple layers of high-throughput genomics data. In this review, we provide an intellectual foundation of this powerful analytic strategy, as well as an update of the state-of-the-art in recent method developments. The goal of this review is threefold: (1) introduce the motivation and basic steps of pathway analysis for genome-wide genetic variation data; (2) review the merits and the shortcomings of classic and newly emerging integrative pathway analysis tools; and (3) discuss remaining challenges and future directions for further method developments.