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dc.contributor.authorHill, W. David
dc.contributor.authorDavies, Neil M.
dc.contributor.authorRitchie, Stuart J.
dc.contributor.authorSkene, Nathan G.
dc.contributor.authorBryois, Julien
dc.contributor.authorBell, Steven
dc.contributor.authorDi Angelantonio, Emanuele
dc.contributor.authorRoberts, David J.
dc.contributor.authorXueyi, Shen
dc.contributor.authorDavies, Gail
dc.contributor.authorLiewald, David C. M.
dc.contributor.authorPorteous, David J.
dc.contributor.authorHayward, Caroline
dc.contributor.authorButterworth, Adam S.
dc.contributor.authorMcIntosh, Andrew M.
dc.contributor.authorGale, Catharine R.
dc.contributor.authorDeary, Ian J.
dc.date.accessioned2020-12-22T18:54:29Z
dc.date.available2020-12-22T18:54:29Z
dc.date.issued2019-12-16
dc.date.submitted2019-03-12
dc.identifier.others41467-019-13585-5
dc.identifier.other13585
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/315404
dc.description.abstractAbstract: 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.
dc.languageen
dc.publisherNature Publishing Group UK
dc.rightsAttribution 4.0 International (CC BY 4.0)en
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subjectArticle
dc.subject/631/208/205/2138
dc.subject/706/689/159
dc.subject/706/689/477/2811
dc.subject/706/689/522
dc.subject/45/43
dc.subject/38
dc.subject/38/43
dc.subjectarticle
dc.titleGenome-wide analysis identifies molecular systems and 149 genetic loci associated with income
dc.typeArticle
dc.date.updated2020-12-22T18:54:28Z
prism.issueIdentifier1
prism.publicationNameNature Communications
prism.volume10
dc.identifier.doi10.17863/CAM.62511
dcterms.dateAccepted2019-11-11
rioxxterms.versionofrecord10.1038/s41467-019-13585-5
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/
dc.contributor.orcidDavies, Neil M. [0000-0002-2460-0508]
dc.contributor.orcidSkene, Nathan G. [0000-0002-6807-3180]
dc.contributor.orcidBryois, Julien [0000-0002-4747-2166]
dc.contributor.orcidBell, Steven [0000-0001-6774-3149]
dc.contributor.orcidXueyi, Shen [0000-0002-0538-4774]
dc.contributor.orcidLiewald, David C. M. [0000-0002-0544-7368]
dc.contributor.orcidPorteous, David J. [0000-0003-1249-6106]
dc.contributor.orcidHayward, Caroline [0000-0002-9405-9550]
dc.contributor.orcidButterworth, Adam S. [0000-0002-6915-9015]
dc.contributor.orcidMcIntosh, Andrew M. [0000-0002-0198-4588]
dc.contributor.orcidGale, Catharine R. [0000-0002-3361-8638]
dc.identifier.eissn2041-1723


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Attribution 4.0 International (CC BY 4.0)
Except where otherwise noted, this item's licence is described as Attribution 4.0 International (CC BY 4.0)