Job attainment is an important component of socioeconomic status (SES). There is currently a paucity of genomic research on an individual’s job attainment, as well as how it is related to other SES variables and overall well-being at the whole genome level. By incorporating O*NET occupational information into the UK Biobank database, we performed GWAS analyses of six major job attainment characteristics—job complexity, autonomy, innovation, information demands, emotional demands, and physical demands—on 219,483 individuals of European ancestry. The job attainment characteristics had moderate to high pairwise genetic correlations, manifested by three latent factors: cognitive, emotional, and physical requirements. The latent factor of overall job requirement underlying the job attainment traits represented a critical genetic path from educational attainment to income (P < 0.001). Job attainment characteristics were genetically positively correlated with positive health and well-being outcomes (i.e., subject well-being, overall health rating, number of non-cancer illnesses etc. (|rg|: 0.14–0.51), similar to other SES indices; however, the genetic correlations exhibited opposite directions for physical demands (|rg|: 0.14–0.51) and were largely negligible for emotional demands. By adopting a finer-grained approach to capture specific job attainment phenotypes, our study represents an important step forward in understanding the shared genetic architecture among job attainment characteristics, other SES indices, and potential role in health and well-being outcomes.
Bibliographical noteTis study was supported the Ministry of Education, Singapore, under its Social Science Research Tematic Grant (SSRTG), MOE2017-SSRTG-022, Academic Research Fund (AcRF), R-317-000-162-115 and R-317-000-138-115. Tis research has been conducted using the UK Biobank Resource under application number 37334 and Add Health Study data under application number 11030901. Tis study was approved by the NUS Internal Review Board (IRB #: L09-013E and IRB #: LS-19-075E). All methods used in the study were carried out in accordance with relevant guidelines and regulations. Informed consent was obtained from all subjects and/or their legal guardian(s) by UKB or Add Health. We are grateful to the study’s participants and staff for data collection. The computational work for this study was partially performed on resources of the National Supercomputing Centre, Singapore (https://www.nscc.sg). Add Health is directed by Robert A. Hummer and funded by the National Institute on Aging cooperative agreements U01 AG071448 (Hummer) and U01 AG071450 (Aiello and Hummer) at the University of North Carolina at Chapel Hill. Waves I-V data are from the Add Health Program Project, grant P01 HD31921 (Harris) from Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), with cooperative funding from 23 other federal agencies and foundations. Add Health was designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill.
© 2022. The Author(s).
- Academic Success
- Educational Status
- Social Class