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J Nutr. 2020 Jan 1;150(1):149-158. doi: 10.1093/jn/nxz194.

Dietary Patterns Are Associated with Serum Metabolite Patterns and Their Association Is Influenced by Gut Bacteria among Older German Adults.

Author information

1
Department of Nutrition and Food Sciences, Nutritional Epidemiology, Rheinische Friedrich-Wilhelms-University Bonn, Bonn, Germany.
2
Center for Population and Health eV, Wiesbaden, Germany.
3
APC Microbiome Ireland, Teagasc/University College Cork, Cork, Ireland.
4
Teagasc Moorepark Food Research Centre, Fermoy, Ireland.
5
Department of Epidemiology, German Institute of Human Nutrition, Potsdam-Rehbrüke, Nuthetal, Germany.

Abstract

BACKGROUND:

Although dietary intakes and dietary intake patterns (DPs) have been associated with single metabolites, it is unclear whether DPs are also reflected in specific metabolite patterns (MPs). Moreover, the influence of groups of gut bacteria on the relationship between DPs and MPs is underexplored.

OBJECTIVES:

We aimed to investigate the association of DPs and serum MPs and also the modifying effect of the gut bacteria compositional patterns (BCPs).

METHODS:

This is a cross-sectional investigation among 225 individuals (median age: 63 y; 53% women) from the European Prospective Investigation into Cancer and Nutrition study. Dietary intakes were assessed by three 24-h dietary recalls, gut bacteria composition was quantified by 16S rRNA gene sequencing, and the serum metabolome was profiled by an untargeted approach. We identified DPs and BCPs by the treelet transform analysis. We modeled associations between DPs and 8 previously published MPs and the modifying effect of BCPs by fitting generalized linear models using DataSHIELD R.

RESULTS:

We identified 5 DPs and 7 BCPs. The "bread, margarine, and processed meat" and "fruiting vegetables and vegetable oils" DPs were positively associated with the "amino acids" (β = 0.35; 95% CI: 0.02, 0.69; P = 0.03) and "fatty acids" MPs (β = 0.45; 95% CI: 0.16, 0.74; P = 0.01), respectively. The "tea and miscellaneous" was inversely associated with the "amino acids" (β = -0.28; 95% CI: -0.52, -0.05; P = 0.02) and "amino acid derivatives" MPs (β = -0.21; 95% CI: -0.39, -0.02; P = 0.03). One BCP negatively modified the association between the "bread, margarine, and processed meat" DP and the "amino acids" MP (P-interaction = 0.01).

CONCLUSIONS:

In older German adults, DPs are reflected in MPs, and the gut bacteria attenuate 1 DP-MP association. These MPs should be explored as biomarkers of these jointly consumed foods while taking into account a potentially modifying role of the gut bacteria.

KEYWORDS:

DataSHIELD; dietary intake patterns; gut bacteria compositional patterns; serum metabolite patterns; treelet transform analysis

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