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Personality is influenced by both genetic and environmental factors and is associated with other psychiatric traits such as anxiety and depression. The "Big Five" personality traits, which include neuroticism, extraversion, agreeableness, conscientiousness, and openness, are a widely accepted and influential framework for understanding and describing human personality. Of the big five personality traits, neuroticism has most often been the focus of genetic studies and is linked to various mental illnesses including depression, anxiety, and schizophrenia. Our knowledge of the genetic architecture of the other four personality traits is more limited. Utilizing the Million Veteran Program (MVP) cohort we conducted a genome-wide association study (GWAS) in individuals of European and African ancestry. Adding other published data, we performed GWAS meta-analysis for each of the five personality traits with sample sizes ranging from 237,390 to 682,688. We identified 158, 14, 3, 2, and 7 independent genome-wide significant (GWS) loci associated with neuroticism, extraversion, agreeableness, conscientiousness, and openness, respectively. These findings represent 55 novel loci for neuroticism, as well as the first GWS loci discovered for extraversion and agreeableness. Gene-based association testing revealed 254 genes showing significant association with at least one of the five personality traits. Transcriptome-wide and proteome-wide analysis identified altered expression of genes and proteins such as CRHR1, SLC12A5, MAPT , and STX4 . Pathway enrichment and drug perturbation analyses identified complex biology underlying human personality traits. We also studied the inter-relationship of personality traits with 1,437 other traits in a phenome-wide genetic correlation analysis, identifying new associations. Mendelian randomization showed positive bidirectional effects between neuroticism and depression and anxiety while a negative bidirectional effect was observed for agreeableness and these psychiatric traits. This study improves our comprehensive understanding of the genetic architecture underlying personality traits and their relationship to other complex human traits.

There is a high prevalence of antisocial personality disorder (ASPD) in individuals affected by substance use disorders (SUD). However, there is limited information on the specific patterns of association of ASPD with SUD severity and specific SUD diagnostic criteria. We investigated the association of alcohol, cannabis, cocaine, opioid, and tobacco use disorders (AUD, CanUD, CocUD, OUD, and TUD, respectively) in 1,660 individuals with ASPD and 6,640 controls matched by sex (24% female), age, and racial/ethnic background in a sample ascertained for addiction-related traits. Generalized linear regressions were used to test the association of ASPD with the five DSM-5 SUD diagnoses, their severity (i.e., mild, moderate, severe), and their individual diagnostic criteria. We found that ASPD is associated with the diagnosis and severity of AUD (Odds Ratio, ORs=1.89 and 1.25), CanUD (ORs=2.13 and 1.32), and TUD (ORs=1.50 and 1.21) ( ps <.003). Of the specific diagnostic criteria, the "hazardous use" criterion showed the strongest association with ASPD across the five SUDs investigated (from OR TUD =1.88 to OR CanUD =1.37). However, when criteria of different SUDs were included in the same model, ASPD was independently associated only with TUD "hazardous use" and CocUD "attempts to quit". Attempting to quit cocaine was inversely related to the presence of ASPD and remained significant (OR=0.57, 95% confidence interval = 0.36-0.89) after controlling for interactive effects with sex. The current work provides novel insights into how different SUDs, their severity, and their diagnostic criteria associate with ASPD, potentially furthering our understanding of the impact of polysubstance addiction on mental health.

Aims: We performed a latent class analysis (LCA) in a sample ascertained for addiction phenotypes to investigate cocaine use disorder (CoUD) subgroups related to polysubstance addiction (PSA) patterns and characterized their differences with respect to psychiatric and somatic comorbidities., Design: Cross-sectional study., Setting: United States., Participants: Adult participants aged 18-76, 39% female, 47% African American, 36% European American with a lifetime DSM-5 diagnosis of CoUD (N=7,989) enrolled in the Yale-Penn cohort. The control group included 2,952 Yale-Penn participants who did not meet for alcohol, cannabis, cocaine, opioid, or tobacco use disorders., Measurements: Psychiatric disorders and related traits were assessed via the Semi-structured Assessment for Drug Dependence and Alcoholism. These features included substance use disorders (SUD), family history of substance use, sociodemographic information, traumatic events, suicidal behaviors, psychopathology, and medical history. LCA was conducted using diagnoses and diagnostic criteria of alcohol, cannabis, opioid, and tobacco use disorders., Findings: Our LCA identified three subgroups of PSA (i.e., low, 17%; intermediate, 38%; high, 45%) among 7,989 CoUD participants. While these subgroups varied by age, sex, and racial-ethnic distribution (p<0.001), there was no difference on education or income (p>0.05). After accounting for sex, age, and race-ethnicity, the CoUD subgroup with high PSA had higher odds of antisocial personality disorder (OR=21.96 vs. 6.39, difference-p=8.08×10 -6 ), agoraphobia (OR=4.58 vs. 2.05, difference-p=7.04×10 -4 ), mixed bipolar episode (OR=10.36 vs. 2.61, difference-p=7.04×10 -4 ), posttraumatic stress disorder (OR=11.54 vs. 5.86, difference-p=2.67×10 -4 ), antidepressant medication use (OR=13.49 vs. 8.02, difference-p=1.42×10 -4 ), and sexually transmitted diseases (OR=5.92 vs. 3.38, difference-p=1.81×10 -5 ) than the low-PSA CoUD subgroup., Conclusions: We found different patterns of PSA in association with psychiatric and somatic comorbidities among CoUD cases within the Yale-Penn cohort. These findings underscore the importance of modeling PSA severity and comorbidities when examining the clinical, molecular, and neuroimaging correlates of CoUD.