A metabolome and microbiome wide association study of healthy eating index points to the mechanisms linking dietary pattern and metabolic status

Abstract

Background: Healthy eating index (HEI), a measure of diet quality, associates with metabolic health outcomes; however, the molecular basis is unclear. We conducted a multi-omic study to examine whether HEI associates with the circulatory and gut metabolome and investigated the gut microbiome-HEI interaction on circulating and gut metabolites.

Methods: Through a cross-sectional study, we evaluated diet quality in healthy individuals [the ABO Glycoproteomics in Platelets and Endothelial Cells (ABO) Study, n = 73], metabolites (measured at Metabolon Inc.) in plasma (n = 800) and gut (n = 767) and the gut microbiome at enterotype and microbial taxa (n = 296) levels. Pathway analysis was conducted using Metaboanalyst 4.0. We performed multi-variable linear regression to explore both the HEI-metabolites and HEI-microbiome associations and how metabolites were affected by the HEI-microbiome interaction. In the Fish oils and Adipose Inflammation Reduction (FAIR) Study (n = 25), analyses on HEI and plasma metabolites were replicated. Estimates of findings from both studies were pooled in random-effects meta-analysis.

Results: The HEI-2015 was associated with 74 plasma and 73 gut metabolites (mostly lipids) and with 47 metabolites in the meta-analysis of the ABO and FAIR Studies. Compared to Enterotype-1 participants, those with Enterotype-2 had higher diet quality (p = 0.01). We also identified 9 microbial genera associated with HEI, and 35 plasma and 40 gut metabolites linked to the HEI-gut microbiome interaction. Pathways involved in the metabolism of polar lipids, amino acids and caffeine strongly associated with diet quality. However, the HEI-microbiome interaction not only influenced the pathways involved in the metabolism of branch-chain amino acids, it also affected upstream pathways including nucleotide metabolism and amino acids biosynthesis.

Conclusions: Our multi-omic analysis demonstrated that changes in metabolism, measured by either circulatory/gut metabolites or metabolic pathways, are influenced by not only diet quality but also gut microbiome alterations shaped by the quality of diet consumed. Future work is needed to explore the causality in the interplay between HEI and gut-microbiome composition in metabolism.

Keywords: Diet quality; Healthy eating index; Metabolic pathway; Metabolome; Microbiome; Multi-omic study.

Figure 1-

Pooled estimates of the association between healthy eating index (HEI) score and metabolites from ABO and FAIR studies. Overall estimates obtained from forest plots and random-effects meta-analysis of ABO and FAIR studies evaluating the associations of HEI with plasma metabolites. The estimate on the X-axis represent multivariable-adjusted effect estimate (β) and were derived from linear regression models adjusting for age, sex and BMI in each study. The reported results belong to 47 significant associations out of 640 metabolites (identified in both the ABO and FAIR Studies) that were tested. Closed squares and horizontal bars represent the overall estimates and 95% CIs. I^2 represents statistical heterogeneity among the ABO and FAIR Studies, with the values of 25%, 50% and 75% regarded as low, moderate and high heterogeneity, respectively.

Figure 2-

Metabolomic pathway analysis, generated by MetaboAnalyst software, for plasma metabolites (A) and gut metabolites (B). Circles indicate the matched pathways. The color of each circle changes according to the p-values (more significant changes of metabolites in the pathway are shown by darker colors), while the pathway impact score is depicted by the size of the circle. The most impacted pathways with the highest statistical significance scores are annotated for clarity. In plasma the raw P-values were 0.006, 0.01, and 0.02 for glycerophospholipid metabolism, glycine, serine and threonine metabolism, and caffeine metabolism, respectively. In stool, the raw P-values for the two significant pathways, histidine metabolism, and caffeine metabolism, were 0.03 and 0.04, respectively.

Figure 3-

Metabolite sets enrichment analysis (MSEA) overview reached through plotting log of p-values which are obtained from pathway enrichment analysis on Y-axis and pathway impact values which are obtained from pathway topology analysis on X-axis.