My primary research question aims to uncover the specific genetic variants and molecular pathways that underlie individual differences in innovation, as proxied by entrepreneurial and scientific research occupations, in UK Biobank whole genome sequence data.
The objectives of my research are listed below:
Aim 1: Identify innovation-associated loci
– Obj 1.1: Conduct a GWAS of self-employment & scientific research occupational phenotypes
– Obj 1.2: Fine-map top loci to single variants and annotate regulatory function (e.g. eQTL overlap)
Aim 2: Characterize genetic effects independent of socioeconomic confounding
– Obj 2.1: Compare genetic profiles of entrepreneurs/researchers versus high!income non!innovators matched on household income
– Obj 2.2: Use within!family (sibling) GWAS to control for shared environment and estimate direct genetic effects
Aim 3: Map trait pathways & neural correlates
– Obj 3.1: Perform mediation analyses to test whether PGS effects on innovation are mediated via cognitive ability, stress resilience or social!functions
– Obj 3.2: Cross!reference significant loci with neuroimaging data (e.g. left!insula volume) to infer brain pathways
Innovation critically drives economic growth, yet its biological underpinnings remain opaque. Twin & SNP!based heritability estimates (~40% for entrepreneurship; ~4% SNP!h² for STEM careers) suggest a substantial genetic component. Polygenic scores for ADHD, cognition and educational attainment have predicted self!employment, & imaging genetics links entrepreneurs to left!insula volume. However, these studies relied on genotyping arrays and limited phenotypes. UKB’s new WGS & deep phenotyping (income, cognition, resilience, social!function scales) vastly expand discovery power. Integrating GWAS, PGS, within!family designs and neurogenetic annotation will yield the first comprehensive map of innovation’s genetic architecture, inform economic surveys, & guide policy on fostering creativity.