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- Title
Genome-wide analysis identifies molecular systems and 149 genetic loci associated with income.
- Authors
Hill, W. David; Davies, Neil M.; Ritchie, Stuart J.; Skene, Nathan G.; Bryois, Julien; Bell, Steven; Di Angelantonio, Emanuele; Roberts, David J.; Xueyi, Shen; Davies, Gail; Liewald, David C. M.; Porteous, David J.; Hayward, Caroline; Butterworth, Adam S.; McIntosh, Andrew M.; Gale, Catharine R.; Deary, Ian J.
- Abstract
Socioeconomic position (SEP) is a multi-dimensional construct reflecting (and influencing) multiple socio-cultural, physical, and environmental factors. In a sample of 286,301 participants from UK Biobank, we identify 30 (29 previously unreported) independent-loci associated with income. Using a method to meta-analyze data from genetically-correlated traits, we identify an additional 120 income-associated loci. These loci show clear evidence of functionality, with transcriptional differences identified across multiple cortical tissues, and links to GABAergic and serotonergic neurotransmission. By combining our genome wide association study on income with data from eQTL studies and chromatin interactions, 24 genes are prioritized for follow up, 18 of which were previously associated with intelligence. We identify intelligence as one of the likely causal, partly-heritable phenotypes that might bridge the gap between molecular genetic inheritance and phenotypic consequence in terms of income differences. These results indicate that, in modern era Great Britain, genetic effects contribute towards some of the observed socioeconomic inequalities. Household income is used as a marker of socioeconomic position, a trait that is associated with better physical and mental health. Here, Hill et al. report a genome-wide association study for household income in the UK and explore its relationship with intelligence in post-GWAS analyses including Mendelian randomization.
- Subjects
GENOMES; SOCIOECONOMICS; SEROTONINERGIC mechanisms; NEURAL transmission; MOLECULAR structure of chromatin
- Publication
Nature Communications, 2019, Vol 10, Issue 1, p1
- ISSN
2041-1723
- Publication type
Article
- DOI
10.1038/s41467-019-13585-5