Age and Sex Differences in the Genetic Architecture of Measures of Subjective Health: Relationships With Physical Health, Depressive Symptoms, and Episodic Memory

Author:

Finkel Deborah12,Gatz Margaret1ORCID,Franz Carol E34ORCID,Catts Vibeke S5,Christensen Kaare6ORCID,Kremen William34ORCID,Nygaard Marianne7ORCID,Plassman Brenda L8,Sachdev Perminder S5ORCID,Whitfield Keith9,Pedersen Nancy L10

Affiliation:

1. Center for Economic and Social Research, University of Southern California , Los Angeles, California , USA

2. Institute for Gerontology, College of Health and Welfare, Jönköping University , Jönköping , Sweden

3. Department of Psychiatry, University of California, San Diego , San Diego, California , USA

4. Center for Behavior Genetics of Aging, University of California, San Diego , San Diego, California , USA

5. Centre for Healthy Brain Ageing (CHeBA), Discipline of Psychiatry and Mental Health, School of Clinical Medicine, UNSW , Sydney , Australia

6. Danish Aging Research Center, Department of Public Health, University of Southern Denmark , Odense , Denmark

7. The Danish Twin Registry, University of Southern Denmark , Odense , Denmark

8. Departments of Psychiatry and Neurology, Duke University School of Medicine , Durham, North Carolina , USA

9. Department of Psychology and Brain and Health, University of Nevada, Las Vegas , Las Vegas, Nevada , USA

10. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet , Stockholm , Sweden

Abstract

Abstract Objectives Subjective health (SH) is not just an indicator of physical health, but also reflects active cognitive processing of information about one’s own health and has been associated with emotional health measures, such as neuroticism and depression. Behavior genetic approaches investigate the genetic architecture of SH, that is, genetic and environmental influences on individual differences in SH and associations with potential components such as physical, cognitive, and emotional health. Previous twin analyses have been limited by sex, sample size, age range, and focus on single covariates. Methods The current analysis used data from 24,173 adults ranging in age from 40 to 90 years from the international Interplay of Genes and Environment across Multiple Studies consortium to investigate the genetic architecture of 3 measures of SH: self-rated health, health compared to others, and impact of health on activities. Independent pathways model of SH included physical health, depressive symptoms, and episodic memory, with age, sex, and country included as covariates. Results Most or all of the genetic variance for SH measures were shared with physical health, depressive symptoms, and episodic memory. Genetic architecture of SH differed across measures, age groups (40–65, 66–90), and sexes. Age comparisons indicated stronger correlations with all 3 covariates in older adults, often resulting from greater shared genetic variance. Discussion The predictive value of SH has been amply demonstrated. The higher genetic contributions to associations between SH and its components in older adults support the increasing conceptualization with age of SH as an intuitive summation of one’s vital reserve.

Funder

National Institutes of Health

John D. and Catherine T. MacArthur Foundation Research Network on Successful Aging

Swedish Council for Working Life and Social Research

Swedish Research Council

MacArthur Foundation Research Network on Successful Aging

Axel and Margaret Ax:son Johnson’s Foundation

Vårdalstiftelsen

Danish Agency for Science and Innovation

Velux Foundation

Veteran Affairs (VA) San Diego Center of Excellence for Stress and Mental Health

U.S. Department of Veterans Affairs

John D. and Catherine T. MacArthur Foundation Research Network on Successful Midlife Development

National Health and Medical Research Council

Australian Research Council

Centre for Research Excellence

Carolina African American Twin Study of Aging

Publisher

Oxford University Press (OUP)

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