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

Evelina T Akimova; Tobias Wolfram; Xuejie Ding; Felix C Tropf; Melinda C Mills

doi:10.1038/s41562-024-02076-3

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

Nat Hum Behav. 2024 Dec 23. doi: 10.1038/s41562-024-02076-3. Online ahead of print.

Authors

Evelina T Akimova^#^{1

2}, Tobias Wolfram^#³, Xuejie Ding^{4

5

6}, Felix C Tropf^{7

8

9}, Melinda C Mills^{4

10

11}

Affiliations

¹ Department of Sociology, Purdue University, West Lafayette, IN, USA. [email protected].
² Leverhulme Centre for Demographic Science, Nuffield Department of Population Health and Nuffield College, University of Oxford, Oxford, UK. [email protected].
³ Department of Sociology, University of Bielefeld, Bielefeld, Germany. [email protected].
⁴ Leverhulme Centre for Demographic Science, Nuffield Department of Population Health and Nuffield College, University of Oxford, Oxford, UK.
⁵ WZB Berlin Social Science Center, Berlin, Germany.
⁶ Einstein Center Population Diversity, Berlin, Germany.
⁷ Department of Sociology, Purdue University, West Lafayette, IN, USA.
⁸ Centre for Longitudinal Studies, University College London, London, UK.
⁹ AnalytiXIN, Indianapolis, IN, USA.
¹⁰ Department of Genetics, University Medical Centre Groningen, Groningen, the Netherlands.
¹¹ Department of Economics, Econometrics and Finance, University of Groningen, Groningen, the Netherlands.

^# Contributed equally.

PMID: 39715877
DOI: 10.1038/s41562-024-02076-3

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_g = 0.96-0.97) and income (r_g = 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 R² = 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.

Grants and funding

RC-2018-003/Leverhulme Trust