TY - JOUR
T1 - Genome-wide analysis identifies molecular systems and 149 genetic loci associated with income
AU - Hill, W. David
AU - Davies, Neil M.
AU - Ritchie, Stuart J.
AU - Skene, Nathan G.
AU - Bryois, Julien
AU - Bell, Steven
AU - Di Angelantonio, Emanuele
AU - Roberts, David J.
AU - Xueyi, Shen
AU - Davies, Gail
AU - Liewald, David C.M.
AU - Porteous, David J.
AU - Hayward, Caroline
AU - Butterworth, Adam S.
AU - McIntosh, Andrew M.
AU - Gale, Catharine R.
AU - Deary, Ian J.
N1 - Publisher Copyright:
© 2019, The Author(s).
PY - 2019/12/1
Y1 - 2019/12/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85076619342&partnerID=8YFLogxK
U2 - 10.1038/s41467-019-13585-5
DO - 10.1038/s41467-019-13585-5
M3 - Article
C2 - 31844048
AN - SCOPUS:85076619342
SN - 2041-1723
VL - 10
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 5741
ER -