Modifying effect of metabotype on diet–diabetes associations

Abstract

Purpose Inter-individual metabolic differences may be a reason for previously inconsistent results in diet-diabetes associations. We aimed to investigate associations between dietary intake and diabetes for metabolically homogeneous subgroups ('metabotypes') in a large cross-sectional study. Methods We used data of 1517 adults aged 38-87 years from the German population-based KORA FF4 study (2013/2014). Dietary intake was estimated based on the combination of a food frequency questionnaire and multiple 24-h food lists. Glucose tolerance status was classified based on an oral glucose tolerance test in participants without a previous diabetes diagnosis using American Diabetes Association criteria. Logistic regression was applied to examine the associations between dietary intake and diabetes for two distinct metabotypes, which were identified based on 16 biochemical and anthropometric parameters. Results A low intake of fruits and a high intake of total meat, processed meat and sugar-sweetened beverages (SSB) were significantly associated with diabetes in the total study population. Stratified by metabotype, associations with diabetes remained significant for intake of total meat (OR 1.67, 95% CI 1.04-2.67) and processed meat (OR 2.23, 95% CI 1.24-4.04) in the metabotypes with rather favorable metabolic characteristics, and for intake of fruits (OR 0.83, 95% CI 0.68-0.99) and SSB (OR:1.21, 95% CI 1.09-1.35) in the more unfavorable metabotype. However, only the association between SSB intake and diabetes differed significantly by metabotype (p value for interaction = 0.01). Conclusions Our findings suggest an influence of metabolic characteristics on diet-diabetes associations, which may help to explain inconsistent previous results. The causality of the observed associations needs to be confirmed in prospective and intervention studies.

Evaluation of the Metabotype Concept Identified in an Irish Population in the German KORA Cohort Study

“…In previous analyses on metabotyping, [ 8,15 ] we also identified three metabotype clusters in both the KORA F4 and the KORA FF4 studies using extensive sets of grouping variables. We used in total 34 parameters in the KORA F4 study and a subset of 16 parameters in the KORA FF4 study.…”

“…In both metabotyping approaches used in the KORA studies, that is, assignment of participants to existing metabotype clusters identified in NANS (conducted here) and identification of metabotype clusters by cluster analysis, [ 8,15 ] a more metabolically unfavorable cluster 3, an intermediate cluster 2 and a more metabolically favorable cluster 1 were found. However, the two approaches resulted in a difference in the number of individuals per cluster for cluster 1 (34% vs 44%) and cluster 2 (46% vs 36%) with a stable percentage but not the identical individuals in cluster 3 (20% vs 20%).…”

“…However, for the development of targeted disease prevention strategies, it is necessary to identify differences between metabotype clusters in their association of diet and/or physical activity with disease‐specific outcomes. Since only few studies investigated such differences between metabotypes, [ 10,15,36–38 ] further studies are needed for the development of targeted disease prevention strategies on the metabotype subgroup level and for testing the effectiveness. In addition, this could be also relevant for more specific metabolically subgroups such as of diabetic patients.…”

“…[ 23 ] All participants gave their written informed consent and the studies were approved by the Ethics Committee of the Bavarian Chamber of Physicians. To ensure comparability with previous investigations on metabotyping in the KORA studies, [ 8,15 ] the same sample sizes were used (KORA F4 study: n = 1768, KORA FF4 study: n = 2279).…”

“…[ 8–14 ] For example, we used in previous projects various biochemical parameters from blood and urine as well as anthropometric measures for the identification of metabotypes in the German population‐based Cooperative Health Research in the Region of Augsburg (KORA) cohort study. [ 8,15 ]…”