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Is the Gene-Environment Interaction Paradigm Relevant to Genome-Wide Studies? The Case of Education and Body Mass Index

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  • Jason Boardman
  • Benjamin Domingue
  • Casey Blalock
  • Brett Haberstick
  • Kathleen Harris
  • Matthew McQueen

Abstract

This study uses data from the Framingham Heart Study to examine the relevance of the gene-environment interaction paradigm for genome-wide association studies (GWAS). We use completed college education as our environmental measure and estimate the interactive effect of genotype and education on body mass index (BMI) using 260,402 single-nucleotide polymorphisms (SNPs). Our results highlight the sensitivity of parameter estimates obtained from GWAS models and the difficulty of framing genome-wide results using the existing gene-environment interaction typology. We argue that SNP-environment interactions across the human genome are not likely to provide consistent evidence regarding genetic influences on health that differ by environment. Nevertheless, genome-wide data contain rich information about individual respondents, and we demonstrate the utility of this type of data. We highlight the fact that GWAS is just one use of genome-wide data, and we encourage demographers to develop methods that incorporate this vast amount of information from respondents into their analyses. Copyright Population Association of America 2014

Suggested Citation

  • Jason Boardman & Benjamin Domingue & Casey Blalock & Brett Haberstick & Kathleen Harris & Matthew McQueen, 2014. "Is the Gene-Environment Interaction Paradigm Relevant to Genome-Wide Studies? The Case of Education and Body Mass Index," Demography, Springer;Population Association of America (PAA), vol. 51(1), pages 119-139, February.
    • Handle: RePEc:spr:demogr:v:51:y:2014:i:1:p:119-139
    DOI: 10.1007/s13524-013-0259-4
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    Cited by:

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    2. Owen, Gwilym & Jones, Kelvyn & Harris, Richard, 2017. "Does neighbourhood deprivation affect the genetic influence on body mass?," Social Science & Medicine, Elsevier, vol. 185(C), pages 38-45.
    3. Guang Guo & Hexuan Liu & Ling Wang & Haipeng Shen & Wen Hu, 2015. "The Genome-Wide Influence on Human BMI Depends on Physical Activity, Life Course, and Historical Period," Demography, Springer;Population Association of America (PAA), vol. 52(5), pages 1651-1670, October.
    4. Trejo, Sam, 2020. "Exploring Genetic Influences on Birth Weight," SocArXiv 7j59q, Center for Open Science.
    5. Rosalind B. King & Regina M. Bures, 2017. "How the Social Environment Gets Under the Skin," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 36(5), pages 631-637, October.
    6. Sanz-de-Galdeano, Anna & Terskaya, Anastasia & Upegui, Angie, 2020. "Association of a Genetic Risk Score with BMI along the Life-Cycle: Evidence from Several US Cohorts," IZA Discussion Papers 13671, Institute of Labor Economics (IZA).
    7. Amin, Vikesh & Fletcher, Jason M & Lu, Qiongshi & Song, Jie, 2023. "Re-examining the relationship between education and adult mental health in the UK: A research note," Economics of Education Review, Elsevier, vol. 93(C).

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