RESUMO
Background: attention-deficit/hyperactivity disorder (ADHD) is associated with both polygenic liability and environmental exposures, both intrinsic to the family, such as family conflict, and extrinsic, such as air pollution. However, much less is known about the interplay between environmental and genetic risks relevant to ADHD-a better understanding of which could inform both mechanistic models and clinical prediction algorithms. Methods: Two independent data sets, the population-based Adolescent Brain Cognitive Development Study (ABCD) (N = 11,876) and the case-control Oregon-ADHD-1000 (N = 1449), were used to examine additive (G + E) and interactive (GxE) effects of selected polygenic risk scores (PRS) and environmental factors in a cross-sectional design. Genetic risk was measured using PRS for nine mental health disorders/traits. Exposures included family income, family conflict/negative sentiment, and geocoded measures of area deprivation, lead exposure risk, and air pollution exposure (nitrogen dioxide and fine particulate matter). Results: ADHD PRS and family conflict jointly predicted concurrent ADHD symptoms in both cohorts. Additive-effects models, including both genetic and environmental factors, explained significantly more variation in symptoms than any individual factor alone (joint R 2 = .091 for total symptoms in ABCD; joint R 2 = .173 in Oregon-ADHD-1000; all delta-R 2 p-values <2e-7). Significant effect size heterogeneity across ancestry groups was observed for genetic and environmental factors (e.g., Q = 9.01, p = .011 for major depressive disorder PRS; Q = 13.34, p = .001 for area deprivation). GxE interactions observed in the full ABCD cohort suggested stronger environmental effects when genetic risk is low, though they did not replicate. Conclusions: Reproducible additive effects of PRS and family environment on ADHD symptoms were found, but GxE interaction effects were not replicated and appeared confounded by ancestry. Results highlight the potential value of combining exposures and PRS in clinical prediction algorithms. The observed differences in risks across ancestry groups warrant further study to avoid health care disparities.
RESUMO
Poor metabolic health during pregnancy is associated with health concerns for pregnant individuals and their offspring. Lower socioeconomic status (SES) is one risk factor for poor metabolic health, and may be related to limited access to healthful and affordable foods (e.g., living in a food desert). This study evaluates the respective contributions of SES and food desert severity on metabolic health during pregnancy. The food desert severity of 302 pregnant individuals was determined using the United States Department of Agriculture Food Access Research Atlas. SES was measured using total household income adjusted for household size, years of education, and amount of reserve savings. Information about participants' glucose concentrations one hour following an oral glucose tolerance test during the second trimester was extracted from medical records and percent adiposity during the second trimester was assessed using air displacement plethysmography. Information about participants' nutritional intake during the second trimester was obtained by trained nutritionists via three unannounced 24-h dietary recalls. Structural equation models showed that lower SES predicted higher food desert severity (ß = - 0.20, p = 0.008) and higher adiposity (ß = - 0.27, p = 0.016) and consumption of a more pro-inflammatory diet (ß = - 0.25, p = 0.003) during the second trimester of pregnancy. Higher food desert severity also predicted higher percent adiposity during the second trimester (ß = 0.17, p = 0.013). Food desert severity significantly mediated the relationship between lower SES and higher percent adiposity during the second trimester (ßindirect = - 0.03, 95% CI [- 0.079, - 0.004]). These findings indicate that access to healthful and affordable foods is a mechanism by which SES contributes to adiposity during pregnancy and may inform interventions intended to improve metabolic health during pregnancy.
