Investigating Gene-Diet Interactions Impacting the Association Between Macronutrient Intake and Glycemic Traits.

TitleInvestigating Gene-Diet Interactions Impacting the Association Between Macronutrient Intake and Glycemic Traits.
Publication TypeJournal Article
Year of Publication2023
AuthorsWesterman, KE, Walker, ME, Gaynor, SM, Wessel, J, DiCorpo, D, Ma, J, Alonso, A, Aslibekyan, S, Baldridge, AS, Bertoni, AG, Biggs, ML, Brody, JA, Chen, Y-DIda, Dupuis, J, Goodarzi, MO, Guo, X, Hasbani, NR, Heath, A, Hidalgo, B, Irvin, MR, W Johnson, C, Kalyani, RR, Lange, L, Lemaitre, RN, Liu, C-T, Liu, S, Moon, J-Y, Nassir, R, Pankow, JS, Pettinger, M, Raffield, LM, Rasmussen-Torvik, LJ, Selvin, E, Senn, MK, Shadyab, AH, Smith, AV, Smith, NL, Steffen, L, Talegakwar, S, Taylor, KD, de Vries, PS, Wilson, JG, Wood, AC, Yanek, LR, Yao, J, Zheng, Y, Boerwinkle, E, Morrison, AC, Fornage, M, Russell, TP, Psaty, BM, Levy, D, Heard-Costa, NL, Ramachandran, VS, Mathias, RA, Arnett, DK, Kaplan, R, North, KE, Correa, A, Carson, A, Rotter, JI, Rich, SS, Manson, JAE, Reiner, AP, Kooperberg, C, Florez, JC, Meigs, JB, Merino, J, Tobias, DK, Chen, H, Manning, AK
Date Published2023 May 01
KeywordsDiabetes Mellitus, Diet, Eating, Genome-Wide Association Study, Glycated Hemoglobin, Guanine Nucleotide Dissociation Inhibitors, Humans

UNLABELLED: Few studies have demonstrated reproducible gene-diet interactions (GDIs) impacting metabolic disease risk factors, likely due in part to measurement error in dietary intake estimation and insufficient capture of rare genetic variation. We aimed to identify GDIs across the genetic frequency spectrum impacting the macronutrient-glycemia relationship in genetically and culturally diverse cohorts. We analyzed 33,187 participants free of diabetes from 10 National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program cohorts with whole-genome sequencing, self-reported diet, and glycemic trait data. We fit cohort-specific, multivariable-adjusted linear mixed models for the effect of diet, modeled as an isocaloric substitution of carbohydrate for fat, and its interactions with common and rare variants genome-wide. In main effect meta-analyses, participants consuming more carbohydrate had modestly lower glycemic trait values (e.g., for glycated hemoglobin [HbA1c], -0.013% HbA1c/250 kcal substitution). In GDI meta-analyses, a common African ancestry-enriched variant (rs79762542) reached study-wide significance and replicated in the UK Biobank cohort, indicating a negative carbohydrate-HbA1c association among major allele homozygotes only. Simulations revealed that >150,000 samples may be necessary to identify similar macronutrient GDIs under realistic assumptions about effect size and measurement error. These results generate hypotheses for further exploration of modifiable metabolic disease risk in additional cohorts with African ancestry.

ARTICLE HIGHLIGHTS: We aimed to identify genetic modifiers of the dietary macronutrient-glycemia relationship using whole-genome sequence data from 10 Trans-Omics for Precision Medicine program cohorts. Substitution models indicated a modest reduction in glycemia associated with an increase in dietary carbohydrate at the expense of fat. Genome-wide interaction analysis identified one African ancestry-enriched variant near the FRAS1 gene that may interact with macronutrient intake to influence hemoglobin A1c. Simulation-based power calculations accounting for measurement error suggested that substantially larger sample sizes may be necessary to discover further gene-macronutrient interactions.

Alternate JournalDiabetes
PubMed ID36791419
PubMed Central IDPMC10130485
Grant ListT32 DK007028 / DK / NIDDK NIH HHS / United States
K01 DK133637 / DK / NIDDK NIH HHS / United States
P30 ES030285 / ES / NIEHS NIH HHS / United States
K24 HL148521 / HL / NHLBI NIH HHS / United States
R01 HL145025 / HL / NHLBI NIH HHS / United States

Similar Publications