School of Medicine Publications and Presentations

Document Type

Article

Publication Date

3-14-2024

Abstract

Background: Socioeconomic Status (SES) is a potent environmental determinant of health. To our knowledge, no assessment of genotype-environment interaction has been conducted to consider the joint effects of socioeconomic status and genetics on risk for metabolic disease. We analyzed data from the Mexican American Family Studies (MAFS) to evaluate the hypothesis that genotype-by-environment interaction (GxE) is an essential determinant of variation in risk factors for metabolic syndrome (MS).

Methods: We employed a maximum likelihood estimation of the decomposition of variance components to detect GxE interaction. After excluding individuals with diabetes and individuals on medication for diabetes, hypertension, or dyslipidemia, we analyzed 12 MS risk factors: fasting glucose (FG), fasting insulin (FI), 2-h glucose (2G), 2-h insulin (2I), body mass index (BMI), waist circumference (WC), leptin (LP), high-density lipoprotein-cholesterol (HDL-C), triglycerides (TG), total serum cholesterol (TSC), systolic blood pressure (SBP), and diastolic blood pressure (DBP). Our SES variable used a combined score of Duncan's socioeconomic index and education years. Heterogeneity in the additive genetic variance across the SES continuum and a departure from unity in the genetic correlation coefficient were taken as evidence of GxE interaction. Hypothesis tests were conducted using standard likelihood ratio tests.

Results: We found evidence of GxE for fasting glucose, 2-h glucose, 2-h insulin, BMI, and triglycerides. The genetic effects underlying the insulin/glucose metabolism component of MS are upregulated at the lower end of the SES spectrum. We also determined that the household variance for systolic blood pressure decreased with increasing SES. Conclusion: These results show a significant change in the GxE interaction underlying the major components of MS in response to changes in socioeconomic status. Further mRNA sequencing studies will identify genes and canonical gene pathways to support our molecular-level hypotheses.

Comments

Copyright © 2024 Diego, Manusov, Mao, Almeida, Peralta, Curran, Mahaney, Göring, Blangero and Williams-Blangero. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Publication Title

Frontiers in Genetics

DOI

10.3389/fgene.2024.1240462

Academic Level

faculty

Mentor/PI Department

Office of Human Genetics

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