Background: Creativity is known to be heritable and exhibits familial aggregation with psychiatric disorders; however, previous epidemiological and genetic studies have not shown the complex nature of the relationship between creativity and various psychiatric disorders. Here, we demonstrate that using an expanded and validated machine learning-based phenotyping of occupational creativity (OC) can allow us to further understand the trait of creativity, which was previously difficult to define and study. We present the largest genome-wide association study (GWAS) on OC to reveal the relationship between creativity and psychiatric disorders.Methods: Using a machine learning-based phenotyping of OC, we conducted a GWAS on 241,736 participants of European ancestry from the UK Biobank. We applied genetic correlation analysis, polygenic risk score analysis, and the bivariate causal mixture model (MiXeR) to investigate the genetic relationship between OC and psychiatric disorders. False discovery rate (FDR) analysis was used to identify additional and shared loci for OC and psychiatric disorders.Findings: This GWAS identified 25 loci associated with OC which have not yet been reported. We found extensive genetic overlap with psychiatric disorders, including schizophrenia, major depression, bipolar I disorder, attention deficit/hyperactivity disorder, and anorexia nervosa in genetic correlation and polygenic risk score analyses. The MiXeR analyses found mixed direction of effects in the association between OC and psychiatric disorders. Conditional and conjunctional FDR analyses identified additional and shared loci for OC and psychiatric disorders.Interpretation: There is extensive genetic overlap between OC and psychiatric disorders with mixed effect direction. Our GWAS analysis via machine learning-based phenotyping contributes to the understanding of the genetic architecture of creativity, which may inform genetic discovery, biological mechanisms, and genetic prediction in human cognition and psychiatric disorders.Funding: This study was supported by a National Research Foundation of Korea grant funded by the Ministry of Science and Information and Communication Technologies, South Korea (grant numbers NRF- 2021R1A2C4001779 to W.M. and NRF-2022R1A2C2009998 to H.H.W.), and a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (HU22C0042 to H.H.W.).Declaration of Interest: Woong-Yang Park was previously employed at GENINUS. Ole A. Andreassen is a consultant for HealthLytix. All other authors state that they have no competing interests to declare.Ethical Approval: This research was conducted using the UKB Resource under Application Number 33002. The UKB (https://www.ukbiobank.ac.uk/about-biobank-uk) was approved by the National Research Ethics Committee (REC reference 11/NW/0382).
Abstract Creativity is heritable and exhibits familial aggregation with psychiatric disorders, but its genomic basis and genetic relationship with psychiatric disorders remain largely unknown. Here, we conducted a genome-wide association study (GWAS) using an expanded, machine learning-based definition of creativity in individuals of European ancestry from the UK Biobank ( n = 241,736) and identified 25 creativity-associated loci. Extensive genetic overlap with psychiatric disorders, including schizophrenia, major depression, bipolar I disorder, attention deficit/hyperactivity disorder, and anorexia nervosa, was demonstrated by the genetic correlation, polygenic risk score, and MiXeR analyses. The condFDR and conjFDR analyses identified additional loci for creativity and psychiatric disorders, as well as shared genetic loci between creativity and psychiatric disorders. This GWAS showed significant correlations with GWASs using traditional definitions of creativity and GWASs adjusted for educational attainment. Our findings contribute to the understanding of the genetic architecture of creativity and reveal its polygenic relationships with psychiatric disorders.
Abstract Irritability is a heritable core mental trait associated with several psychiatric illnesses. However, the genomic basis of irritability is unclear. Therefore, this study aimed to 1) identify the genetic variants associated with irritability and investigate the associated biological pathways, genes, and tissues as well as single-nucleotide polymorphism (SNP)-based heritability; 2) explore the relationships between irritability and various traits, including psychiatric disorders; and 3) identify additional and shared genetic variants for irritability and psychiatric disorders. We conducted a genome-wide association study (GWAS) using 379,506 European samples (105,975 cases and 273,531 controls) from the UK Biobank. We utilized various post-GWAS analyses, including linkage disequilibrium score regression, the bivariate causal mixture model (MiXeR), and conditional and conjunctional false discovery rate approaches. This GWAS identified 15 independent loci associated with irritability; the total SNP heritability estimate was 4.19%. Genetic correlations with psychiatric disorders were most pronounced for major depressive disorder (MDD) and bipolar II disorder (BD II). MiXeR analysis revealed polygenic overlap with schizophrenia (SCZ), bipolar I disorder (BD I), and MDD. Conditional false discovery rate analyses identified additional loci associated with SCZ (number [ n ] of additional SNPs = 105), BD I ( n = 54), MDD ( n = 107), and irritability ( n = 157). Conjunctional false discovery rate analyses identified 85, 41, and 198 shared loci between irritability and SCZ, BD I, and MDD, respectively. Multiple genetic loci were associated with irritability and three main psychiatric disorders. Given that irritability is a cross-disorder trait, these findings may help to elucidate the genomics of psychiatric disorders.
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