Dataset Information

Gene-obesogenic environment interactions on body mass indices for older black and white men and women from the Health and Retirement Study.

ABSTRACT: BACKGROUND:Gene-obesogenic environment interactions influence body mass index (BMI) across the life course; however, limited research examines how these interactions may differ by race and sex. METHODS:Utilizing mixed-effects models, we examined the interaction effects of a polygenic risk score (PGS) generated from BMI-associated single-nucleotide polymorphisms, and environmental factors, including age, physical activity, alcohol intake, and childhood socioeconomic status on measured longitudinal BMI from the Health and Retirement Study (HRS). HRS is a population representative survey of older adults in the United States. This study used a subsample of genotyped Black (N?=?1796) and White (N?=?4925) men and women (50-70 years) with measured BMI. RESULTS:Higher PGS was associated with higher BMI. The association between PGS and BMI weakened as individuals aged among White men (Pinteraction?=?0.0383) and White women (Pinteraction?=?0.0514). The mean BMI difference between the 90th and 10th PGS percentile was 4.25?kg/m2 among 50-year-old White men, and 3.11?kg/m2 among the 70 years old's, i.e., a 1.14?kg/m2 (95% CI: -0.27, 2.82) difference. The difference among 50- and 70-year-old White women was 1.34?kg/m2 (95% CI: 0.09, 2.60). In addition, the protection effect of physical activity was stronger among White women with higher PGS (Pinteraction?=?0.0546). Vigorous physical activity (compared with never) was associated with 1.66?kg/m2 (95% CI: 1.06, 2.29) lower mean BMI among those in the 90th PGS percentile, compared with 0.83?kg/m2 (95% CI: 0.37, 1.29) lower among those in the 10th PGS percentile. Interactions were also observed between both PGS and alcohol intake among White men (Pinteraction?=?0.0034) and women (Pinteraction?=?0.0664) and Black women (Pinteraction?=?0.0108), and PGS and childhood socioeconomic status among White women (Pinteraction?=?0.0007). CONCLUSIONS:Our findings reinforce the importance of physical activity among those with an elevated genetic risk; additionally, other detected interactions may underscore the influence of broader social environments on obesity-promoting genes.

SUBMITTER: Thompson MD

PROVIDER: S-EPMC7483541 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Gene-obesogenic environment interactions on body mass indices for older black and white men and women from the Health and Retirement Study.

Thompson Mika D MD Pirkle Catherine M CM Youkhana Fadi F Wu Yan Yan YY

International journal of obesity (2005) 20200518 9

<h4>Background</h4>Gene-obesogenic environment interactions influence body mass index (BMI) across the life course; however, limited research examines how these interactions may differ by race and sex.<h4>Methods</h4>Utilizing mixed-effects models, we examined the interaction effects of a polygenic risk score (PGS) generated from BMI-associated single-nucleotide polymorphisms, and environmental factors, including age, physical activity, alcohol intake, and childhood socioeconomic status on measu ...[more]

PMID: 32424267

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Project description:ImportanceThe early obesogenic home environment is consistently identified as a key influence on child weight trajectories, but little research has examined the mechanisms of that influence. Such research is essential for the effective prevention and treatment of overweight and obesity.ObjectiveTo test behavioral susceptibility theory's hypothesis that the heritability of body mass index (BMI) is higher among children who live in more obesogenic home environments.Design, setting, and participantsThis study was a gene-environment interaction twin study that used cross-sectional data from 925 families (1850 twins) in the Gemini cohort (a population-based prospective cohort of twins born in England and Wales between March and December 2007). Data were analyzed from July to October 2013 and in June 2018.ExposuresParents completed the Home Environment Interview, a comprehensive measure of the obesogenic home environment in early childhood. Three standardized composite scores were created to capture food, physical activity, and media-related influences in the home; these were summed to create an overall obesogenic risk score. The 4 composite scores were split on the mean, reflecting higher-risk and lower-risk home environments.Main outcomes and measuresQuantitative genetic model fitting was used to estimate heritability of age-adjusted and sex-adjusted BMI (BMI SD score, estimated using British 1990 growth reference data) for children living in lower-risk and higher-risk home environments.ResultsAmong 1850 twins (915 [49.5%] male and 935 [50.5%] female; mean [SD] age, 4.1 [0.4] years), the heritability of BMI SD score was significantly higher among children living in overall higher-risk home environments (86%; 95% CI, 68%-89%) compared with those living in overall lower-risk home environments (39%; 95% CI, 21%-57%). The findings were similar when examining the heritability of BMI in the separate food and physical activity environment domains.Conclusions and relevanceThese findings support the hypothesis that obesity-related genes are more strongly associated with BMI in more obesogenic home environments. Modifying the early home environment to prevent weight gain may be particularly important for children genetically at risk for obesity.

Project description:IntroductionNeighborhood socioeconomic (nSES) factors have been implicated in prostate cancer (PCa) disparities. In line with the Precision Medicine Initiative that suggests clinical and socioenvironmental factors can impact PCa outcomes, we determined whether nSES variables are associated with time to PCa diagnosis and could inform PCa clinical risk assessment.Materials and methodsThe study sample included 358 high risk men (PCa family history and/or Black race), aged 35-69 years, enrolled in an early detection program. Patient variables were linked to 78 nSES variables (employment, income, etc.) from previous literature via geocoding. Patient-level models, including baseline age, prostate specific antigen (PSA), digital rectal exam, as well as combined models (patient plus nSES variables) by race/PCa family history subgroups were built after variable reduction methods using Cox regression and LASSO machine-learning. Model fit of patient and combined models (AIC) were compared; p-values<0.05 were significant. Model-based high/low nSES exposure scores were calculated and the 5-year predicted probability of PCa was plotted against PSA by high/low neighborhood score to preliminarily assess clinical relevance.ResultsIn combined models, nSES variables were significantly associated with time to PCa diagnosis. Workers mode of transportation and low income were significant in White men with a PCa family history. Homeownership (%owner-occupied houses with >3 bedrooms) and unemployment were significant in Black men with and without a PCa family history, respectively. The 5-year predicted probability of PCa was higher in men with a high neighborhood score (weighted combination of significant nSES variables) compared to a low score (e.g., Baseline PSA level of 4ng/mL for men with PCa family history: White-26.7% vs 7.7%; Black-56.2% vs 29.7%).DiscussionUtilizing neighborhood data during patient risk assessment may be useful for high risk men affected by disparities. However, future studies with larger samples and validation/replication steps are needed.

Dataset Information

Gene-obesogenic environment interactions on body mass indices for older black and white men and women from the Health and Retirement Study.

Publications

Gene-obesogenic environment interactions on body mass indices for older black and white men and women from the Health and Retirement Study.

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