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The impact of late-career job loss and genetic risk on body mass index: Evidence from variance polygenic scores.

ABSTRACT: Unemployment shocks from the COVID-19 pandemic have reignited concerns over the long-term effects of job loss on population health. Past research has highlighted the corrosive effects of unemployment on health and health behaviors. This study examines whether the effects of job loss on changes in body mass index (BMI) are moderated by genetic predisposition using data from the U.S. Health and Retirement Study (HRS). To improve detection of gene-by-environment (G × E) interplay, we interacted layoffs from business closures-a plausibly exogenous environmental exposure-with whole-genome polygenic scores (PGSs) that capture genetic contributions to both the population mean (mPGS) and variance (vPGS) of BMI. Results show evidence of genetic moderation using a vPGS (as opposed to an mPGS) and indicate genome-wide summary measures of phenotypic plasticity may further our understanding of how environmental stimuli modify the distribution of complex traits in a population.

SUBMITTER: Schmitz LL

PROVIDER: S-EPMC8027610 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature

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The impact of late-career job loss and genetic risk on body mass index: Evidence from variance polygenic scores.

Schmitz Lauren L LL Goodwin Julia J Miao Jiacheng J Lu Qiongshi Q Conley Dalton D

Scientific reports 20210407 1

Unemployment shocks from the COVID-19 pandemic have reignited concerns over the long-term effects of job loss on population health. Past research has highlighted the corrosive effects of unemployment on health and health behaviors. This study examines whether the effects of job loss on changes in body mass index (BMI) are moderated by genetic predisposition using data from the U.S. Health and Retirement Study (HRS). To improve detection of gene-by-environment (G × E) interplay, we interacted lay ...[more]

PMID: 33828129

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Project description:Background: Maternal smoking during pregnancy has adverse health effects on the offspring, including lower birth weight and increased risk for obesity. These outcomes are also influenced by common genetic polymorphisms. We aimed to investigate the combined effect of maternal smoking during pregnancy and genetic predisposition on birth weight and body mass index (BMI)-related traits in 1,086 children of the Human Early Life Exposome (HELIX) project. Methods: Maternal smoking during pregnancy was self-reported. Phenotypic traits were assessed at birth or at the age of 8 years. Ten polygenic risk scores (PRSs) per trait were calculated using the PRSice v2 program. For birth weight, we estimated two sets of PRSs based on two different base GWAS summary statistics: PRS-EGG, which includes HELIX children, and PRS-PanUK, which is completely independent. The best PRS per trait (highest R 2) was selected for downstream analyses, and it was treated in continuous or categorized into three groups. Multivariate linear regression models were applied to evaluate the association of the explanatory variables with the traits of interest. The combined effect was evaluated by including an interaction term in the regression models and then running models stratified by the PRS group. Results: BMI-related traits were correlated among them but not with birth weight. A similar pattern was observed for their PRSs. On average, the PRSs explained ∼4% of the phenotypic variation, with higher PRS values related to higher trait values (p-value <5.55E-08). Sustained maternal smoking was associated with lower birth weight and higher BMI and related traits (p-value <2.99E-02). We identified a gene by environment (GxE) interaction for birth weight between sustained maternal smoking and the PRS-EGG in three groups (p-value interaction = 0.01), which was not replicated with the PRS-PanUK (p-value interaction = 0.341). Finally, we did not find any statistically significant GxE interaction for BMI-related traits (p-value interaction >0.237). Conclusion: Sustained maternal smoking and the PRSs were independently associated with birth weight and childhood BMI-related traits. There was low evidence of GxE interactions.

Project description:ImportanceExcess weight, the prevalence of which is high and increasing in many countries, is linked to multiple adverse health outcomes, including increased colorectal cancer (CRC) risk. Better communication of health risks associated with excess weight might support efforts of prevention.ObjectiveTo evaluate the individual and joint associations of body mass index (BMI) and polygenic risk with CRC, to assess potential interactions among them, and to quantify by how much increased polygenic risk for CRC can be offset by having a BMI within reference range.Design, setting, and participantsThis population-based case-control study was conducted in the Rhine-Neckar region of southwest Germany, with recruitment from 2003 to 2017. Participants with both risk factor and genetic information were included for analysis. Data analysis was conducted from December 8, 2021, to February 17, 2022.ExposuresBMI was calculated as self-reported weight in kilograms approximately 10 years before diagnosis or interview and current height in meters squared. A polygenic risk score (PRS) was built based on 140 CRC-related risk loci.Main outcomes and measuresIndividual and joint associations of BMI and PRS with CRC were estimated using multiple logistic regression. Associations of excess weight with CRC were quantified by adjusted odds ratios (aORs) and genetic risk equivalents (GREs), the equivalent outcomes conveyed by defined differences in PRS percentiles.ResultsAmong 9169 participants (median [IQR] age, 69 [62-76] years; 5589 [61.0%] male participants) included, 5053 had CRC and 4116 did not. BMI of 30 or greater was associated with higher odds of having CRC compared with BMI less than 25 (aOR, 1.71; 95% CI, 1.49-1.97), independent of PRS levels (P for interaction = .45). Participants with BMI of 30 or greater and a PRS in the highest tertile had higher odds of CRC compared with participants with BMI less than 25 and a PRS in the lowest tertile (aOR, 3.82; 95% CI, 3.03-4.82). The estimated association of BMI greater than 30 with CRC risk was equivalent to that of having a 41 (95% CI, 29-53)-percentile higher PRS. BMI of 30 or greater was particularly associated with stage IV CRC (aOR, 2.21; 95% CI, 1.71-2.84).Conclusions and relevanceThese findings suggest that excess weight was associated with CRC regardless of PRS levels. The association of having a BMI within reference range may be similar to that of having a substantially lower polygenic risk for CRC.

Dataset Information

The impact of late-career job loss and genetic risk on body mass index: Evidence from variance polygenic scores.

Publications

The impact of late-career job loss and genetic risk on body mass index: Evidence from variance polygenic scores.

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