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Interaction between Social/Psychosocial Factors and Genetic Variants on Body Mass Index: A Gene-Environment Interaction Analysis in a Longitudinal Setting

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Listed:
  • Wei Zhao

    (Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA)

  • Erin B. Ware

    (Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI 48104, USA)

  • Zihuai He

    (Department of Biostatistics, Columbia University, New York, NY 10032, USA)

  • Sharon L. R. Kardia

    (Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA)

  • Jessica D. Faul

    (Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI 48104, USA)

  • Jennifer A. Smith

    (Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
    Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI 48104, USA)

Abstract

Obesity, which develops over time, is one of the leading causes of chronic diseases such as cardiovascular disease. However, hundreds of BMI (body mass index)-associated genetic loci identified through large-scale genome-wide association studies (GWAS) only explain about 2.7% of BMI variation. Most common human traits are believed to be influenced by both genetic and environmental factors. Past studies suggest a variety of environmental features that are associated with obesity, including socioeconomic status and psychosocial factors. This study combines both gene/regions and environmental factors to explore whether social/psychosocial factors (childhood and adult socioeconomic status, social support, anger, chronic burden, stressful life events, and depressive symptoms) modify the effect of sets of genetic variants on BMI in European American and African American participants in the Health and Retirement Study (HRS). In order to incorporate longitudinal phenotype data collected in the HRS and investigate entire sets of single nucleotide polymorphisms (SNPs) within gene/region simultaneously, we applied a novel set-based test for gene-environment interaction in longitudinal studies (LGEWIS). Childhood socioeconomic status (parental education) was found to modify the genetic effect in the gene/region around SNP rs9540493 on BMI in European Americans in the HRS. The most significant SNP (rs9540488) by childhood socioeconomic status interaction within the rs9540493 gene/region was suggestively replicated in the Multi-Ethnic Study of Atherosclerosis (MESA) ( p = 0.07).

Suggested Citation

  • Wei Zhao & Erin B. Ware & Zihuai He & Sharon L. R. Kardia & Jessica D. Faul & Jennifer A. Smith, 2017. "Interaction between Social/Psychosocial Factors and Genetic Variants on Body Mass Index: A Gene-Environment Interaction Analysis in a Longitudinal Setting," IJERPH, MDPI, vol. 14(10), pages 1-17, September.
    • Handle: RePEc:gam:jijerp:v:14:y:2017:i:10:p:1153-:d:113705
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    1. David E. Reich & Michele Cargill & Stacey Bolk & James Ireland & Pardis C. Sabeti & Daniel J. Richter & Thomas Lavery & Rose Kouyoumjian & Shelli F. Farhadian & Ryk Ward & Eric S. Lander, 2001. "Linkage disequilibrium in the human genome," Nature, Nature, vol. 411(6834), pages 199-204, May.
    2. Leonard I. Pearlin, 2010. "The Life Course and the Stress Process: Some Conceptual Comparisons," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 65(2), pages 207-215.
    3. Adam E. Locke & Bratati Kahali & Sonja I. Berndt & Anne E. Justice & Tune H. Pers & Felix R. Day & Corey Powell & Sailaja Vedantam & Martin L. Buchkovich & Jian Yang & Damien C. Croteau-Chonka & Tonu , 2015. "Genetic studies of body mass index yield new insights for obesity biology," Nature, Nature, vol. 518(7538), pages 197-206, February.
    4. Arend Voorman & Thomas Lumley & Barbara McKnight & Kenneth Rice, 2011. "Behavior of QQ-Plots and Genomic Control in Studies of Gene-Environment Interaction," PLOS ONE, Public Library of Science, vol. 6(5), pages 1-7, May.
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