Consistent effects of the genetics of happiness across the lifespan and ancestries in multiple cohorts

Ward, J. et al. (2023) Consistent effects of the genetics of happiness across the lifespan and ancestries in multiple cohorts. Scientific Reports, 13, 17262. (doi: 10.1038/s41598-023-43193-9) (PMID:37828061) (PMCID:PMC10570373)

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Happiness is a fundamental human affective trait, but its biological basis is not well understood. Using a novel approach, we construct LDpred-inf polygenic scores of a general happiness measure in 2 cohorts: the Adolescent Brain Cognitive Development (ABCD) cohort (N = 15,924, age range 9.23–11.8 years), the Add Health cohort (N = 9129, age range 24.5–34.7) to determine associations with several well-being and happiness measures. Additionally, we investigated associations between genetic scores for happiness and brain structure in ABCD (N = 9626, age range (8.9–11) and UK Biobank (N = 16,957, age range 45–83). We detected significant (p.FDR < 0.05) associations between higher genetic scores vs. several well-being measures (best r2 = 0.019) in children of multiple ancestries in ABCD and small yet significant correlations with a happiness measure in European participants in Add Health (r2 = 0.004). Additionally, we show significant associations between lower genetic scores for happiness with smaller structural brain phenotypes in a white British subsample of UK Biobank and a white sub-sample group of ABCD. We demonstrate that the genetic basis for general happiness level appears to have a consistent effect on happiness and wellbeing measures throughout the lifespan, across multiple ancestral backgrounds, and multiple brain structures.

Item Type:Articles
Additional Information:UK Biobank was established by the Wellcome Trust medical charity, Medical Research Council, Department of Health, Scottish Government and the Northwest Regional Development Agency. It has also had funding from the Welsh Assembly Government and the British Heart Foundation. Te funders had no role in study design, data collection or management, analyses or interpretation of the data, nor preparation, review or approval of the manuscript. JW is funded by the Aitchison Family bequest. CLN acknowledges funding from the Medical Research Council (MR/R024774/1) and a Lord Kelvin/Adam Smith Fellowship. LML is supported by a Royal College of Physicians of Edinburgh JMAS Sim Fellowship and a Lord Kelvin/Adam Smith Fellowship. RJS is supported by a University of Glasgow LKAS fellowship and a UKRI Innovation-HDR-UK Fellowship (MR/ S003061/1).
Glasgow Author(s) Enlighten ID:Ward, Dr Joey and Cullen, Dr Breda and Aman, Alisha and Zhu, Miss Xingxing and Anderson, Dr Jana and Pell, Professor Jill and Lyall, Dr Laura and Bailey, Dr Mark and Niedzwiedz, Dr Claire and Lyall, Dr Donald and Strawbridge, Dr Rona and Stanciu, Miss Ioana
Authors: Ward, J., Lyall, L. M., Cullen, B., Strawbridge, R. J., Zhu, X., Stanciu, I., Aman, A., Niedzwiedz, C. L., Anderson, J., Bailey, M. E.S., Lyall, D. M., and Pell, J. P.
College/School:College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > Mental Health and Wellbeing
Journal Name:Scientific Reports
Publisher:Nature Publishing Group
ISSN (Online):2045-2322
Copyright Holders:Copyright: © The Author(s) 2023
First Published:First published in Scientific Reports 13: 17262
Publisher Policy:Reproduced under a Creative Commons licence

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
302182A machine learning approach to understanding comorbidity between mental and physical health conditionsClaire NiedzwiedzMedical Research Council (MRC)MR/R024774/1SHW - Public Health
302131Understanding the excess risk of cardiometabolic disease in individuals with serious mental illnessJill PellMedical Research Council (MRC)MR/S003061/1SHW - Public Health