Where to Look into the Puzzle of Polyphenols and Health? The Postbiotics and Gut Microbiota Associated with Human Metabotypes

The full consensus on the role of dietary polyphenols as human‐health‐promoting compounds remains elusive. The two‐way interaction between polyphenols and gut microbiota (GM) (i.e., modulation of GM by polyphenols and their catabolism by the GM) is determinant in polyphenols’ effects. The identification of human metabotypes associated with a differential gut microbial metabolism of polyphenols has opened new research scenarios to explain the inter‐individual variability upon polyphenols consumption. The metabotypes unequivocally identified so far are those involved in the metabolism of isoflavones (equol and(or) O‐desmethylangolesin producers versus non‐producers) and ellagic acid (urolithin metabotypes, including producers of only urolithin‐A (UM‐A), producers of urolithin‐A, isourolithin‐A, and urolithin‐B (UM‐B), and non‐producers (UM‐0)). In addition, the microbial metabolites (phenolic‐derived postbiotics) such as equol, urolithins, valerolactones, enterolactone, and enterodiol, and 8‐prenylnaringenin, among others, can exert differential health effects. The knowledge is updated and position is taken here on i) the two‐way interaction between GM and polyphenols, ii) the evidence between phenolic‐derived postbiotics and health, iii) the role of metabotypes as biomarkers of GM and the clustering of individuals depending on their metabotypes (metabotyping) to explain polyphenols’ effects, and iv) the gut microbial metabolism of catecholamines to illustrate the intersection between personalized nutrition and precision medicine.     

Using a Metabotype Framework to Deliver Personalized Nutrition Improves Dietary Quality and Metabolic Health Parameters: A 12-Week Randomized Controlled Trial

Scope

Effective strategies for tailoring dietary advice to individuals are urgently needed. The effectiveness of personalized nutrition advice delivered using a metabotype framework in improving dietary quality and metabolic health biomarkers compared to population-level advice is investigated.

Materials and results

A 12-week parallel randomized controlled trial is performed with 107 healthy adults. Individuals in the personalized group are classified into metabotypes using four markers (triacylglycerol, high-density lipoprotein [HDL]-cholesterol, total cholesterol [TC], and glucose) and received dietary advice from decision tree algorithms containing metabotypes characteristics and individual traits. Individuals in the control group received generic dietary advice based on national guidelines. The personalized approach results in higher dietary quality assessed by the Alternate Mediterranean Diet Score (effect size [95% confidence interval, CI], 0.77 [0.07, 1.48], 12% versus 3% increase) and significantly lower concentrations of triacylglycerol (−0.17 [−0.28, −0.06] log10 mmol L⁻¹), TC (−0.42 [−0.74, −0.10] mmol L⁻¹), low-density lipoprotein (LDL)-cholesterol (−0.34, [−0.60, −0.09] mmol L⁻¹), and lower triacylglycerol-glucose index (−0.40, [−0.67, −0.13]). Sixteen phosphatidylcholines and six lysophosphatidylcholines, predominately with chain lengths of 30–36 carbons, are lower in the personalized group.

Conclusions

Personalized nutrition advice delivered using the metabotype framework is effective to improve dietary quality, which could result in reduced CVD risk, and metabolic heath biomarkers.