Association of a Genetic Risk Score With Body Mass Index Across Different Birth Cohorts.

TitleAssociation of a Genetic Risk Score With Body Mass Index Across Different Birth Cohorts.
Publication TypeJournal Article
Year of Publication2016
AuthorsWalter, S, Mejía-Guevara, I, Estrada, K, Liu, SY, M. Glymour, M
JournalJAMA
Volume316
Issue1
Start Page63
Pagination63-9
Date Published2016 Jul 05
ISSN Number1538-3598
KeywordsAfrican Continental Ancestry Group, Age Factors, Aged, Aged, 80 and over, Alleles, Body Mass Index, Cohort Studies, European Continental Ancestry Group, Female, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Humans, Male, Middle Aged, Multilocus Sequence Typing, Obesity, Polymorphism, Single Nucleotide, Risk Factors, United States
Abstract

IMPORTANCE: Many genetic variants are associated with body mass index (BMI). Associations may have changed with the 20th century obesity epidemic and may differ for black vs white individuals.

OBJECTIVE: Using birth cohort as an indicator for exposure to obesogenic environment, to evaluate whether genetic predisposition to higher BMI has a larger magnitude of association among adults from more recent birth cohorts, who were exposed to the obesity epidemic at younger ages.

DESIGN, SETTING, AND PARTICIPANTS: Observational study of 8788 adults in the US national Health and Retirement Study who were aged 50 years and older, born between 1900 and 1958, with as many as 12 BMI assessments from 1992 to 2014.

EXPOSURES: A multilocus genetic risk score for BMI (GRS-BMI), calculated as the weighted sum of alleles of 29 single nucleotide polymorphisms associated with BMI, with weights equal to the published per-allele effects. The GRS-BMI represents how much each person's BMI is expected to differ, based on genetic background (with respect to these 29 loci), from the BMI of a sample member with median genetic risk. The median-centered GRS-BMI ranged from -1.68 to 2.01.

MAIN OUTCOMES AND MEASURES: BMI based on self-reported height and weight.

RESULTS: GRS-BMI was significantly associated with BMI among white participants (n = 7482; mean age at first assessment, 59 years; 3373 [45%] were men; P <.001) and among black participants (n = 1306; mean age at first assessment, 57 years; 505 [39%] were men; P <.001) but accounted for 0.99% of variation in BMI among white participants and 1.37% among black participants. In multilevel models accounting for age, the magnitude of associations of GRS-BMI with BMI were larger for more recent birth cohorts. For example, among white participants, each unit higher GRS-BMI was associated with a difference in BMI of 1.37 (95% CI, 0.93 to 1.80) if born after 1943, and 0.17 (95% CI, -0.55 to 0.89) if born before 1924 (P = .006). For black participants, each unit higher GRS-BMI was associated with a difference in BMI of 3.70 (95% CI, 2.42 to 4.97) if born after 1943, and 1.44 (95% CI, -1.40 to 4.29) if born before 1924.

CONCLUSIONS AND RELEVANCE: For participants born between 1900 and 1958, the magnitude of association between BMI and a genetic risk score for BMI was larger among persons born in later cohorts. This suggests that associations of known genetic variants with BMI may be modified by obesogenic environments.

URLhttp://www.ncbi.nlm.nih.gov/pubmed/27380344
DOI10.1001/jama.2016.8729
User Guide Notes

http://www.ncbi.nlm.nih.gov/pubmed/27380344?dopt=Abstract

Alternate JournalJAMA
Citation Key8512
PubMed ID27380344
Grant ListRC2AG036495 / AG / NIA NIH HHS / United States
RC4AG039029 / AG / NIA NIH HHS / United States
U01AG009740 / AG / NIA NIH HHS / United States