The effects of the Green-Mediterranean diet on cardiometabolic health are linked to gut microbiome modifications: a randomized controlled trial

Abstract

Background: Previous studies have linked the Mediterranean diet (MED) with improved cardiometabolic health, showing preliminary evidence for a mediating role of the gut microbiome. We recently suggested the Green-Mediterranean (Green-MED) diet as an improved version of the healthy MED diet, with increased consumption of plant-based foods and reduced meat intake. Here, we investigated the effects of MED interventions on the gut microbiota and cardiometabolic markers, and the interplay between the two, during the initial weight loss phase of the DIRECT-PLUS trial.

Methods: In the DIRECT-PLUS study, 294 participants with abdominal obesity/dyslipidemia were prospectively randomized to one of three intervention groups: healthy dietary guidelines (standard science-based nutritional counseling), MED, and Green-MED. Both isocaloric MED and Green-MED groups were supplemented with 28g/day walnuts. The Green-MED group was further provided with daily polyphenol-rich green tea and Mankai aquatic plant (new plant introduced to a western population). Gut microbiota was profiled by 16S rRNA for all stool samples and shotgun sequencing for a select subset of samples.

Results: Both MED diets induced substantial changes in the community structure of the gut microbiome, with the Green-MED diet leading to more prominent compositional changes, largely driven by the low abundant, "non-core," microorganisms. The Green-MED diet was associated with specific microbial changes, including enrichments in the genus Prevotella and enzymatic functions involved in branched-chain amino acid degradation, and reductions in the genus Bifidobacterium and enzymatic functions responsible for branched-chain amino acid biosynthesis. The MED and Green-MED diets were also associated with stepwise beneficial changes in body weight and cardiometabolic biomarkers, concomitantly with the increased plant intake and reduced meat intake. Furthermore, while the level of adherence to the Green-MED diet and its specific green dietary components was associated with the magnitude of changes in microbiome composition, changes in gut microbial features appeared to mediate the association between adherence to the Green-MED and body weight and cardiometabolic risk reduction.

Conclusions: Our findings support a mediating role of the gut microbiome in the beneficial effects of the Green-MED diet enriched with Mankai and green tea on cardiometabolic risk factors.

Trial registration: The study was registered on ClinicalTrial.gov ( NCT03020186 ) on January 13, 2017.

Keywords: Cardiometabolic health; Meat; Mediterranean diet; Microbiota; Nutrition; Polyphenols; Weight loss.

Fig. 1

Changes in gut microbiome composition following 6-month dietary interventions. A Study design, adherence rate, and total sample count by category. B PCoA of all samples by group and time. The Green-MED group had undergone the most prominent compositional shift, with a significant interaction between group and time. P values denote the significance level of time-group interaction terms with all three groups (bold) and group-pair combinations by leave-one-out analysis (PERMANOVA). C, D Heatmap of changes in genus-level bacteria (C) and KEGG metabolizing modules (D) by lifestyle intervention group. For each cell, colors indicate the within-group change coefficient by MaAsLin2 between baseline and 6 months. The three dietary arms lead to distinct changes in patterns across genera and microbial metabolic pathways

Fig. 2

The non-core microbiome as a driver of general composition change. A All ASVs with prevalence above 3%, ordered by prevalence across all samples. “core” taxa were defined as > 50% prevalence, with the remaining taxa defined as “non-core.” B PCoA stratified by the non-core (<50% prevalence, top) and core microbiome (>50% prevalence, bottom). The compositional shift of the Green-MED group originated from the non-core (rare) taxa with a significant interaction between time and group in PERMANOVA. C Differences in within-group dissimilarity and between-group dissimilarity, by non-core (green points) and all taxa (gray points) microbiome composition. The Green-MED dieters’ microbiome composition assimilated each other at the 6-month point. This effect was even more dominant in the non-core fraction of the microbiome. Violin plots describe the distribution of 10⁶ random permutations of the same measure, shuffling sample labels at each iteration

Fig. 3

MED diets’ effects on microbial genera and metabolic pathways. A Heatmap of changes in genus-level bacteria by lifestyle intervention group, for taxa with significant time*group interaction. For each cell, colors indicate the within-group change coefficient over time and asterisks denote significance. Black-White annotations on the left denote the significance of between-group change difference (by MaAsLin2 time*group interaction). B Green-MED was distinguished by several changes, including an increase in Prevotella abundance and a decrease in Bifidobacterium. C Heatmap of changes in metabolism-related KEGG modules by lifestyle intervention group, for pathways with significant time*group interaction. For each cell, colors indicate the within-group change coefficient over time and asterisks denote significance. Black-white annotations on the left denote the significance of between-group change difference (by MaAsLin2 time*group interaction). Colors on the left denote the metabolism category. D The Green-MED diet was associated with increased BCAA degradation pathways and decreased BCAA biosynthesis. ****FDR < 0.001, ***FDR < 0.01, **FDR < 0.05, *FDR < 0.25

Fig. 4

Six-month changes in cardiometabolic markers and their associations with changes in global microbiome composition. Left: Forest plot of percent change in cardiometabolic health markers following 6 months of dietary intervention across groups. Significant changes in biomarkers are shown (FDR-corrected P Kendell tau < 0.25). Right: Associations between changes in the corresponding biomarker on the left and composition change (log2 fold change of all ASVs) by performing PERMANOVA test on a Euclidean distance matrix. The Green-MED diet improved cardiometabolic health, with changes in a subset of biomarkers, including body weight, waist circumference, blood pressure, and glycemic profile, being associated with microbiome compositional shift. ****FDR < 0.001, ***FDR < 0.01, **FDR < 0.05, *FDR < 0.25. FRS, Framingham Risk Score; GGT, gamma glutamyl transferase; SBP/DBP, systolic/diastolic blood pressure; MAP, mean arterial pressure; HDG, healthy dietary guidance; HDLc, high-density lipoprotein cholesterol; HOMA-IR, homoeostatic model assessment of insulin resistance; LDLc, low-density lipoprotein cholesterol; MED, Mediterranean; TC, total cholesterol; TG, triglycerides

Fig. 5

Green-MED adherence, cardiometabolic markers, and the association with specific bacteria and microbial metabolic pathways. A Left: Forest plot of Green-MED adherence score and its components following 6 months of dietary intervention across groups. Adherence was assessed using a 9-dimensional index, ranging from 0 (non-adherence) to 9 (full adherence). Right: Associations between changes in the corresponding dietary component on the left and compositional change (log2 fold change of all ASVs) by performing PERMANOVA test on the Euclidean distance matrix. Green-MED dieters adhered to their assigned intervention, with intake of specific components (tea and walnuts) being associated with microbiome compositional shift. B, C Heatmap showing the association patterns of changes in the Green-MED adherence score and change in genus taxa (B) and KEGG modules (C). Features are arranged from top to bottom by their correlations with the adherence score. For each cell, colors indicate the Spearman rho values. Several links between change in microbial features and change in biomarkers were observed. Specifically, changes in specific Green-MED-associated bacteria and microbial metabolic, e.g., Bifidobacterium and Leucin (BCAA) degradation, were associated with weight change following the intervention. D Mediation analysis: assessing the proportional mediatory effect of change in all genus-level taxa (calculated as #1 principal component of their change matrix) in the association between lifestyle intervention and weight change. Weight loss and Framingham risk score were found to be partially mediated by changes in the gut microbiome. ****FDR < 0.001, ***FDR < 0.01, **FDR < 0.05, *FDR < 0.25, ^#P value < 0.05. FRS, Framingham risk score; MAP, mean arterial pressure; HDG, healthy dietary guidance; HOMA-IR, homoeostatic model assessment of insulin resistance; LDLc, low-density lipoprotein cholesterol; MED, Mediterranean