Integrative Multimodal Metabolomics to Early Predict Cognitive Decline Among Amyloid Positive Community-Dwelling Older Adults.

Alzheimer's disease is strongly linked to metabolic abnormalities. We aimed to distinguish amyloid-positive people who progressed to cognitive decline from those who remained cognitively intact. We performed untargeted metabolomics of blood samples from amyloid-positive individuals, before any sign of cognitive decline, to distinguish individuals who progressed to cognitive decline from those who remained cognitively intact. A plasma-derived metabolite signature was developed from Supercritical Fluid chromatography coupled with high-resolution mass spectrometry (SFC-HRMS) and nuclear magnetic resonance (NMR) metabolomics. The 2 metabolomics data sets were analyzed by Data Integration Analysis for Biomarker discovery using Latent approaches for Omics studies (DIABLO), to identify a minimum set of metabolites that could describe cognitive decline status. NMR or SFC-HRMS data alone cannot predict cognitive decline. However, among the 320 metabolites identified, a statistical method that integrated the 2 data sets enabled the identification of a minimal signature of 9 metabolites (3-hydroxybutyrate, citrate, succinate, acetone, methionine, glucose, serine, sphingomyelin d18:1/C26:0 and triglyceride C48:3) with a statistically significant ability to predict cognitive decline more than 3 years before decline. This metabolic fingerprint obtained during this exploratory study may help to predict amyloid-positive individuals who will develop cognitive decline. Due to the high prevalence of brain amyloid-positivity in older adults, identifying adults who will have cognitive decline will enable the development of personalized and early interventions.

Plasma Metabolome Analysis Suggests That L-Arginine Supplementation Affects Microbial Activity Resulting in a Decrease in Trimethylamine N-oxide-A Randomized Controlled Trial in Healthy Overweight Adults with Cardiometabolic Risk Factors.

Background: The effects of supplementation with L-arginine (L-arg), the precursor of nitric oxide (NO), on vascular and cardiometabolic health have largely been explored. Whether other mechanisms of the action of L-arg exist remains unknown, as arginine metabolism is complicated. Objective: We aimed to characterize the effect of low dose L-arg supplementation on overall human metabolism both in a fasting state and in response to an allostatic stress. Methods: In a randomized, double-blind, crossover study, 32 healthy overweight adults (mean age 45 y) with cardiometabolic risk (fasting plasma triglycerides >150 mg/dL; waist circumference >94 cm [male] or >80 cm [female]) were treated with 1.5 g sustained-release L-arg 3 times/d (4.5 g/d) or placebo for 4 wk. On the last day of treatment, volunteers consumed a high-fat meal challenge (900 kcal, 80% as fat, 13% as carbohydrate, and 7% as protein). Plasma was collected at fasting, 2, 4, and 6 h after the challenge, and the metabolome was analyzed by high-resolution liquid chromatography-mass spectrometry. Metabolic profiles were analyzed using linear mixed models-principal component analysis. Results: The challenge meal explained most of the changes in the metabolome. The overall effect of L-arg supplementation significantly explained 0.5% of the total variance, irrespective of the response to the challenge meal (P < 0.05). Among the metabolites that explain most of the L-arg effect, we found many amino acids, including branched-chain amino acids, that were decreased by L-arg supplementation. L-arg also decreased trimethylamine N-oxide (TMAO). Other changes suggest that L-arg increased methyl demand. Conclusions: Analysis of the effect of 4 wk of L-arg supplementation on the metabolome reveals important effects on methyl balance and gut microbiota activity, such as a decrease in TMAO. Further studies are needed to investigate those mechanisms and the implications of these changes for long-term health.This trial was registered at clinicaltrials.gov as NCT02354794.