Trimethylamine N-Oxide Response to a Mixed Macronutrient Tolerance Test in a Cohort of Healthy United States Adults

Abstract

Plasma trimethylamine n-oxide (TMAO) concentration increases in responses to feeding TMAO, choline, phosphatidylcholine, L-carnitine, and betaine but it is unknown whether concentrations change following a mixed macronutrient tolerance test (MMTT) with limited amounts of TMAO precursors. In this proof-of-concept study, we provided healthy female and male adults (n = 97) ranging in age (18–65 years) and BMI (18–44 kg/m2) a MMTT (60% fat, 25% sucrose; 42% of a standard 2,000 kilo calorie diet) and recorded their metabolic response at fasting and at 30 min, 3 h, and 6 h postprandially. We quantified total exposure to TMAO (AUC-TMAO) and classified individuals by the blood draw at which they experienced their maximal TMAO concentration (TMAO-response groups). We related AUC-TMAO to the 16S rRNA microbiome, to two SNPs in the exons of the FMO3 gene (rs2266782, G>A, p.Glu158Lys; and rs2266780, A>G, p.Glu308Gly), and to a priori plasma metabolites. We observed varying TMAO responses (timing and magnitude) and identified a sex by age interaction such that AUC-TMAO increased with age in females but not in males (p-value = 0.0112). Few relationships between AUC-TMAO and the fecal microbiome and FMO3 genotype were identified. We observed a strong correlation between AUC-TMAO and TNF-α that depended on TMAO-response group. These findings promote precision nutrition and have important ramifications for the eating behavior of adults who could benefit from reducing TMAO exposure, and for understanding factors that generate plasma TMAO.

Heterogeneity in the response to n-3 polyunsaturated fatty acids

“…A limitation of this line of research is that we do not have a clear consensus on how the underlying gut microbiome composition of a given group of individuals and the subsequent remodeling of the gut microbiota with long-chain n-3 PUFAs will impact physiological outcomes. As discussed below, an understanding of the microbiome integrated with other known variables of heterogeneity in the response to EPA and DHA will be critical in driving precision studies, as revealed in other disciplines relying on similar approaches [15][16][17].…”