Healthful eating patterns, serum metabolite profile and risk of diabetes in a population-based prospective study of US Hispanics/Latinos

Abstract

Aims/hypothesis: We aimed to evaluate associations of multiple recommended dietary patterns (i.e. the alternate Mediterranean diet [aMED], the Healthy Eating Index [HEI]-2015 and the healthful Plant-based Diet Index [hPDI]) with serum metabolite profile, and to examine dietary-pattern-associated metabolites in relation to incident diabetes.

Methods: We included 2842 adult participants free from diabetes, CVD and cancer during baseline recruitment of the Hispanic Community Health Study/Study of Latinos. Metabolomics profiling of fasting serum was performed using an untargeted approach. Dietary pattern scores were derived using information collected by two 24 h dietary recalls. Dietary-pattern-associated metabolites were identified using multivariable survey linear regressions and their associations with incident diabetes were assessed using multivariable survey Poisson regressions with adjustment for traditional risk factors.

Results: We identified eight metabolites (mannose, γ/β-tocopherol, N1-methylinosine, pyrraline and four amino acids) that were inversely associated with all dietary scores. These metabolites were detrimentally associated with various cardiometabolic risk traits, especially insulin resistance. A score comprised of these metabolites was associated with elevated risk of diabetes (RR_{per SD} 1.54 [95% CI 1.29, 1.83]), and this detrimental association appeared to be attenuated or eliminated by having a higher score for aMED (p_interaction = 0.0001), HEI-2015 (p_interaction = 0.020) or hPDI (p_interaction = 0.023). For example, RR (95% CI) of diabetes for each SD increment in the metabolite score was 1.99 (1.44, 2.37), 1.67 (1.17, 2.38) and 1.08 (0.86, 1.34) across the lowest to the highest tertile of aMED score, respectively.

Conclusions/interpretation: Various recommended dietary patterns were inversely related to a group of metabolites that were associated with elevated risk of diabetes. Adhering to a healthful eating pattern may attenuate or eliminate the detrimental association between metabolically unhealthy serum metabolites and risk of diabetes.

Keywords: Diabetes; Dietary guidelines; Dietary patterns; Metabolomics.

Fig. 1

Serum metabolites associated with three dietary patterns (a) and the corresponding metabolism pathways (b). Dietary-pattern-related metabolites (FDR-adjusted p<0.05) were identified using survey linear regressions with adjustments for age, sex, study field centre, Hispanic/Latino background, education, annual household income, smoking status, drinking status (not for aMED-only metabolite score), total energy intake, physical activity, BMI, use of antihypertensive drugs, use of lipid-lowering drugs and fasting time before blood sample collection

Fig. 2

Cross-sectional association between scores of dietary-pattern-related metabolites and cardiometabolic traits. Metabolites indicated by green arrowhead were positvely associated with dietary pattern score(s), and metabolites indicated by yellow arrowhead were inversely associated with dietary pattern score(s). Results are partial Spearman correlations with adjustment for covariates listed in Fig. 1 legend. HDL-C, HDL-cholesterol

Fig. 3

Cross-sectional association between 40 individual metabolites significantly associated with three dietary scores and cardiometabolic traits. Results are partial Spearman correlations with adjustment for age, sex, study field centre, Hispanic/Latino background, education, annual household income, smoking status, drinking status (not for aMED-only metabolite score), total energy intake, physical activity, BMI, use of antihypertensive drugs, use of lipid-lowering drugs and fasting time before blood sample collection. CMPF, 3-carboxy-4-methyl-5-propyl-2-furanpropanoic acid; HDL-C, HDL-cholesterol

Fig. 4

Association between score of eight metabolites (inversely associated with all dietary scores) and incident diabetes. Results are shown as RR (95% CI) from survey Poisson regressions with adjustment for age, sex, study field centre, Hispanic/Latino background, education, annual household income, smoking status, drinking status (not for aMED-only metabolite score), total energy intake, physical activity, BMI, hypertension, dyslipidaemia and fasting time before blood sample collection. T, tertile