A Multivariate Genome-Wide Association Study Reveals Neural Correlates and Common Biological Mechanisms of Psychopathology Spectra.

There is considerable comorbidity across externalizing and internalizing behavior dimensions of psychopathology. We applied genomic structural equation modeling (gSEM) to genome-wide association study (GWAS) summary statistics to evaluate the factor structure of externalizing and internalizing psychopathology across 16 traits and disorders among European-ancestry individuals (n's = 16,400 to 1,074,629). We conducted GWAS on factors derived from well-fitting models. Downstream analyses served to identify biological mechanisms, explore drug repurposing targets, estimate genetic overlap between the externalizing and internalizing spectra, and evaluate causal effects of psychopathology liability on physical health. Both a correlated factors model, comprising two factors of externalizing and internalizing risk, and a higher-order single-factor model of genetic effects contributing to both spectra demonstrated acceptable fit. GWAS identified 409 lead single nucleotide polymorphisms (SNPs) associated with externalizing and 85 lead SNPs associated with internalizing, while the second-order GWAS identified 256 lead SNPs contributing to broad psychopathology risk. In bivariate causal mixture models, nearly all externalizing and internalizing causal variants overlapped, despite a genetic correlation of only 0.37 (SE = 0.02) between them. Externalizing genes showed cell-type specific expression in GABAergic, cortical, and hippocampal neurons, and internalizing genes were associated with reduced subcallosal cortical volume, providing insight into the neurobiological underpinnings of psychopathology. Genetic liability for externalizing, internalizing, and broad psychopathology exerted causal effects on pain, general health, cardiovascular diseases, and chronic illnesses. These findings underscore the complex genetic architecture of psychopathology, identify potential biological pathways for the externalizing and internalizing spectra, and highlight the physical health burden of psychiatric comorbidity.

A Multivariate Genome-Wide Association Study Reveals Neural Correlates and Common Biological Mechanisms of Psychopathology Spectra.

There is considerable comorbidity across externalizing and internalizing behavior dimensions of psychopathology. We applied genomic structural equation modeling (gSEM) to genome-wide association study (GWAS) summary statistics to evaluate the factor structure of externalizing and internalizing psychopathology across 16 traits and disorders among European-ancestry individuals (n's = 16,400 to 1,074,629). We conducted GWAS on factors derived from well-fitting models. Downstream analyses served to identify biological mechanisms, explore drug repurposing targets, estimate genetic overlap between the externalizing and internalizing spectra, and evaluate causal effects of psychopathology liability on physical health. Both a correlated factors model, comprising two factors of externalizing and internalizing risk, and a higher-order single-factor model of genetic effects contributing to both spectra demonstrated acceptable t. GWAS identified 409 lead single nucleotide polymorphisms (SNPs) associated with externalizing and 85 lead SNPs associated with internalizing, while the second-order GWAS identified 256 lead SNPs contributing to broad psychopathology risk. In bivariate causal mixture models, nearly all externalizing and internalizing causal variants overlapped, despite a genetic correlation of only 0.37 (SE = 0.02) between them. Externalizing genes showed cell-type specific expression in GABAergic, cortical, and hippocampal neurons, and internalizing genes were associated with reduced subcallosal cortical volume, providing insight into the neurobiological underpinnings of psychopathology. Genetic liability for externalizing, internalizing, and broad psychopathology exerted causal effects on pain, general health, cardiovascular diseases, and chronic illnesses. These findings underscore the complex genetic architecture of psychopathology, identify potential biological pathways for the externalizing and internalizing spectra, and highlight the physical health burden of psychiatric comorbidity.

Combining Transdiagnostic and Disorder-Level GWAS Enhances Precision of Psychiatric Genetic Risk Profiles in a Multi-Ancestry Sample.

The etiology of substance use disorders (SUDs) and psychiatric disorders reflects a combination of both transdiagnostic (i.e., common) and disorder-level (i.e., independent) genetic risk factors. We applied genomic structural equation modeling to examine these genetic factors across SUDs, psychotic, mood, and anxiety disorders using genome-wide association studies (GWAS) of European- (EUR) and African-ancestry (AFR) individuals. In EUR individuals, transdiagnostic genetic factors represented SUDs (143 lead single nucleotide polymorphisms [SNPs]), psychotic (162 lead SNPs), and mood/anxiety disorders (112 lead SNPs). We identified two novel SNPs for mood/anxiety disorders that have probable regulatory roles on FOXP1, NECTIN3, and BTLA genes. In AFR individuals, genetic factors represented SUDs (1 lead SNP) and psychiatric disorders (no significant SNPs). The SUD factor lead SNP, although previously significant in EUR- and cross-ancestry GWAS, is a novel finding in AFR individuals. Shared genetic variance accounted for overlap between SUDs and their psychiatric comorbidities, with second-order GWAS identifying up to 12 SNPs not significantly associated with either first-order factor in EUR individuals. Finally, common and independent genetic effects showed different associations with psychiatric, sociodemographic, and medical phenotypes. For example, the independent components of schizophrenia and bipolar disorder had distinct associations with affective and risk-taking behaviors, and phenome-wide association studies identified medical conditions associated with tobacco use disorder independent of the broader SUDs factor. Thus, combining transdiagnostic and disorder-level genetic approaches can improve our understanding of co-occurring conditions and increase the specificity of genetic discovery, which is critical for psychiatric disorders that demonstrate considerable symptom and etiological overlap.

Gene × environment effects and mediation involving adverse childhood events, mood and anxiety disorders, and substance dependence.

Adverse childhood events (ACEs) contribute to the development of mood and anxiety disorders and substance dependence. However, the extent to which these effects are direct or indirect and whether genetic risk moderates them is unclear. We examined associations among ACEs, mood/anxiety disorders and substance dependence in 12,668 individuals (44.9% female, 42.5% African American/Black, 42.1% European American/white). Using latent variables for each phenotype, we modelled direct and indirect associations of ACEs with substance dependence, mediated by mood/anxiety disorders (the forward or 'self-medication' model) and of ACEs with mood/anxiety disorders, mediated by substance dependence (the reverse or 'substance-induced' model). In a subsample, we tested polygenic scores for the substance dependence and mood/anxiety disorder factors as moderators in the mediation models. Although there were significant indirect paths in both directions, mediation by mood/anxiety disorders (the forward model) was greater than that by substance dependence (the reverse model). Greater genetic risk for substance use disorders was associated with a weaker direct association between ACEs and substance dependence in both ancestry groups (reflecting gene × environment interactions) and a weaker indirect association in European-ancestry individuals (reflecting moderated mediation). We found greater evidence that substance dependence reflects self-medication of mood/anxiety disorders than that mood/anxiety disorders are substance induced. Among individuals at higher genetic risk for substance dependence, ACEs were less associated with that outcome. Following exposure to ACEs, multiple pathways appear to underlie the associations between mood/anxiety disorders and substance dependence. Specification of these pathways could inform individually targeted prevention and treatment approaches.

Multivariate, Multi-omic Analysis in 799,429 Individuals Identifies 134 Loci Associated with Somatoform Traits.

Somatoform traits, which manifest as persistent physical symptoms without a clear medical cause, are prevalent and pose challenges to clinical practice. Understanding the genetic basis of these disorders could improve diagnostic and therapeutic approaches. With publicly available summary statistics, we conducted a multivariate genome-wide association study (GWAS) and multi-omic analysis of four somatoform traits-fatigue, irritable bowel syndrome, pain intensity, and health satisfaction-in 799,429 individuals genetically similar to Europeans. Using genomic structural equation modeling, GWAS identified 134 loci significantly associated with a somatoform common factor, including 44 loci not significant in the input GWAS and 8 novel loci for somatoform traits. Gene-property analyses highlighted an enrichment of genes involved in synaptic transmission and enriched gene expression in 12 brain tissues. Six genes, including members of the CD300 family, had putatively causal effects mediated by protein abundance. There was substantial polygenic overlap (76-83%) between the somatoform and externalizing, internalizing, and general psychopathology factors. Somatoform polygenic scores were associated most strongly with obesity, Type 2 diabetes, tobacco use disorder, and mood/anxiety disorders in independent biobanks. Drug repurposing analyses suggested potential therapeutic targets, including MEK inhibitors. Mendelian randomization indicated potentially protective effects of gut microbiota, including Ruminococcus bromii. These biological insights provide promising avenues for treatment development.