Polygenic prediction of occupational status GWAS elucidates genetic and environmental interplay in intergenerational transmission, careers and health in UK Biobank

Socioeconomic status (SES) impacts health and life-course outcomes. This genome-wide association study (GWAS) of sociologically informed occupational status measures (ISEI, SIOPS, CAMSIS) using the UK Biobank (N = 273,157) identified 106 independent single-nucleotide polymorphisms of which 8 are novel to the study of SES. Genetic correlations with educational attainment (r<sub>g</sub> = 0.96-0.97) and income (r<sub>g</sub> = 0.81-0.91) point to a common genetic factor for SES. We observed a 54-57% reduction in within-family predictions compared with population-based predictions, attributed to indirect parental effects (22-27% attenuation) and assortative mating (21-27%) following our calculations. Using polygenic scores from population predictions of 5-10% (incremental R<sup>2</sup> = 0.023-0.097 across different approaches and occupational status measures), we showed that (1) cognitive and non-cognitive traits, including scholastic and occupational motivation and aspiration, link polygenic scores to occupational status and (2) 62% of the intergenerational transmission of occupational status cannot be ascribed to genetic inheritance of common variants but other factors such as family environments. Finally, links between genetics, occupation, career trajectory and health are interrelated with parental occupational status.

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Publication Details

Journal
Nature Human Behaviour
Published
2024-12-23
DOI
https://doi.org/10.1038/s41562-024-02076-3
Citations
15
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
8.25

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article

Polygenic prediction of occupational status GWAS elucidates genetic and environmental interplay in intergenerational transmission, careers and health in UK Biobank

Xuejie Ding, Melinda Mills, Tobias Wolfram, Felix C. Tropf et al.
15 citations
Nature Human Behaviour
Genetic Associations and Epidemiology
8.25
article

Polygenic prediction of occupational status GWAS elucidates genetic and environmental interplay in intergenerational transmission, careers and health in UK Biobank

Xuejie Ding, Melinda Mills, Tobias Wolfram, Felix C. Tropf, Evelina T. Akimova
article en
15 citations

Abstract

Socioeconomic status (SES) impacts health and life-course outcomes. This genome-wide association study (GWAS) of sociologically informed occupational status measures (ISEI, SIOPS, CAMSIS) using the UK Biobank (N = 273,157) identified 106 independent single-nucleotide polymorphisms of which 8 are novel to the study of SES. Genetic correlations with educational attainment (r<sub>g</sub> = 0.96-0.97) and income (r<sub>g</sub> = 0.81-0.91) point to a common genetic factor for SES. We observed a 54-57% reduction in within-family predictions compared with population-based predictions, attributed to indirect parental effects (22-27% attenuation) and assortative mating (21-27%) following our calculations. Using polygenic scores from population predictions of 5-10% (incremental R<sup>2</sup> = 0.023-0.097 across different approaches and occupational status measures), we showed that (1) cognitive and non-cognitive traits, including scholastic and occupational motivation and aspiration, link polygenic scores to occupational status and (2) 62% of the intergenerational transmission of occupational status cannot be ascribed to genetic inheritance of common variants but other factors such as family environments. Finally, links between genetics, occupation, career trajectory and health are interrelated with parental occupational status.

Nature Human BehaviourVol. 9(2)
University Medical Center Groningen (NL), University of Groningen (NL), Bielefeld University (DE), Hochschule Bielefeld (DE), Purdue University West Lafayette (US), WZB Berlin Social Science Center (DE), University of Oxford (GB), Einstein Center Digital Future (DE), Nuffield Health (GB), University College London (GB)
Eli Lilly and Company, Lilly Endowment, UK Research and Innovation, Leverhulme Trust, University of Oxford, European Commission, HORIZON EUROPE Framework Programme, Economic and Social Research Council
Openalex Percentile: Top 2%
Genetic Associations and Epidemiology
8.25
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