Biology subjects

Levey, D. F.

Publications and source records attributed to Levey, D. F..

4 recordsLinked to original sources

bioRxiv2025

Robust inference and widespread genetic correlates from a large-scale genetic association study of human personality

Personality traits describe stable differences in how individuals think, feel, and behave and how they interact with and experience their social and physical environments. We assemble data from 46 cohorts including 611K-1.14M participants with European-like and African-like genomes for genome-wide association studies (GWAS) of the Big Five personality traits (extraversion, agreeableness, conscientiousness, neuroticism, and openness to experience), and data from 51K participants for within-family GWAS. We identify 1,257 lead genetic variants associated with personality, including 823 novel variants. Common genetic variants explain 4.8%-9.3% of the variance in each trait, and 10.5%-16.2% accounting for measurement unreliability. Genetic effects on personality are highly consistent across geography, reporter (self vs. close other), age group, and measurement instrument, and we find minimal spousal assortment for personality in recent history. In stark contrast to many other social and behavioral traits, within-family GWAS and polygenic index analyses indicate little to no shared environmental confounding in genetic associations with personality. Polygenic prediction, genetic correlation, and Mendelian randomization analyses indicate that personality genetics have widespread, potentially causal associations with a wide range of consequential behaviors and life outcomes. The genetic architecture of personality is robust and fundamental to being a human.

genomics↗

bioRxiv2022

Modeling the longitudinal changes of ancestry diversity in the Million Veteran Program

The Million Veteran Program (MVP) participants represent 100 years of US history, including significant social and demographic change over time. Our study assessed two aspects of the MVP: (i) longitudinal changes in population diversity and (ii) how these changes can be accounted for in genome-wide association studies (GWAS). The MVP was divided into five birth cohorts (N-range=123,888 [born from 1943-1947] to 136,699 [born from 1948-1953]). Groups of participants were defined by (i) HARE (harmonized ancestry and race/ethnicity) and (ii) a random-forest clustering approach using the 1000 Genomes Project and the Human Genome Diversity Project (1kGP+HGDP) reference panels (77 world populations representing six continental groups). In these groups, we performed GWASs of height, a trait potentially affected by population stratification. Birth cohorts demonstrate important trends in ancestry diversity over time. More recent HARE-assigned Europeans, Africans, and Hispanics had lower European ancestry proportions than older birth cohorts (0.010<Cohens d<0.259, p<7.80x10-4). Conversely, HARE-assigned East Asians showed an increase in European ancestry proportion over time. In GWAS of height using HARE assignments, genomic inflation due to population stratification was prevalent across all birth cohorts (linkage disequilibrium score regression intercept=1.08{+/-}0.042). The 1kGP+HGDP-based ancestry assignment significantly reduced the population stratification (mean intercept reduction=0.045{+/-}0.007, p<0.05) confounding in the GWAS statistics. This study provides a comprehensive characterization of ancestry diversity of the MVP cohort over time and highlights that more refined modeling of genetic diversity (e.g., the 1kGP+HGDP-based ancestry assignment) can more accurately capture the polygenic architecture of traits and diseases that could be affected by population stratification.

genomics↗

bioRxiv2019

Genomic Characterization of Posttraumatic Stress Disorder in a Large US Military Veteran Sample

Individuals vary in their liability to develop Posttraumatic Stress Disorder (PTSD), the symptoms of which are highly heterogeneous, following exposure to life-threatening trauma. Understanding genetic factors that contribute to the biology of PTSD is critical for refining diagnosis and developing new treatments. Using genetic data from more than 250,000 participants in the Million Veteran Program, genomewide association analyses were conducted using a validated electronic health record-based algorithmically-defined PTSD diagnosis phenotype (48,221 cases and 217,223 controls), and PTSD quantitative symptom phenotypes (212,007 individuals). We identified several genome-wide significant loci in the case-control analyses, and numerous such loci in the quantitative trait analyses, including some (e.g., MAD1L1; TCF4; CRHR1) that were associated with multiple symptom sub-domains and total symptom score, and others that were more specific to certain symptom sub-domains (e.g., CAMKV to re-experiencing; SOX6 to hyperarousal). Genetic correlations between all pairs of symptom sub-domains and their total were very high (rg 0.93 - 0.98) supporting validity of the PTSD diagnostic construct. We also demonstrate strong shared heritability with a range of traits, show that heritability persists when conditioned on other major psychiatric disorders, present independent replication results, provide support for one of the implicated genes in postmortem brain of individuals with PTSD, and use this information to identify potential drug repositioning candidates. These results point to the utility of genetics to inform and validate the biological coherence of the PTSD syndrome despite considerable heterogeneity at the symptom level, and to provide new directions for treatment development.

genetics↗

bioRxiv2019

Reproducible Risk Loci and Psychiatric Comorbidities in Anxiety: Results from ~200,000 Million Veteran Program Participants

We used GWAS in the Million Veteran Program sample (nearly 200,000 informative individuals) using a continuous trait for anxiety (GAD-2) to identify 5 genome-wide significant (GWS) signals for European Americans (EA) and 1 for African Americans. The strongest findings were on chromosome 3 (rs4603973, p=7.40x10-11) near the SATB1 locus, a global regulator of gene expression and on chromosome 6 (rs6557168, p=1.04x10-9) near ESR1 which encodes estrogen receptor . A locus identified on chromosome 7 near MADIL1 (p=1.62x10-8) has been previously identified in GWAS of bipolar disorder and of schizophrenia and may represent a risk factor for psychiatric disorders broadly. SNP-based heritability was estimated to be ~6% for GAD-2. We also GWASed for self-reported anxiety disorder diagnoses (N=224,330) and identified two GWS loci, one (rs35546597, MAF=0.42, p=1.88x10-8) near the AURKB locus, and the other (rsl0534613, MAF=0.41, p=4.92x10-8) near the IQCHE and MADIL1 locus identified in the GAD-2 analysis. We demonstrate reproducibility by replicating our top findings in the summary statistics from the Anxiety NeuroGenetics Study (ANGST) and a UK Biobank neuroticism GWAS. We also replicated top findings from a large UK Biobank preprint, demonstrating stability of GWAS findings in complex traits once sufficient power is attained. Finally, we found evidence of significant genetic overlap between anxiety and major depression using polygenic risk scores, but also found that the main anxiety signals are independent of those for MDD. This work presents novel insights into the neurobiological risk underpinning anxiety and related psychiatric disorders. SignificanceAnxiety disorders are common and often disabling. They are also frequently co-morbid with other mental disorders such as major depressive disorder (MDD); these disorders may share commonalities in their underlying genetic architecture. Using one of the largest homogenously phenotyped cohorts available, the Million Veteran Program sample, we investigated common variants associated with anxiety in genome-wide association studies (GWASes), using survey results from the GAD-2 anxiety scale (as a continuous trait, n=199,611), and self-reported anxiety disorder diagnosis (as a binary trait, n=224,330). This largest GWAS to date for anxiety and related traits identified numerous novel significant associations, several of which are replicated in other datasets, and allows inference of underlying biology.

genetics↗