A Mediterranean Diet-Based Metabolomic Score and Cognitive Decline in Older Adults: A Case-Control Analysis Nested within the Three-City Cohort Study.

SCOPE: Evidence on the Mediterranean diet (MD) and age-related cognitive decline (CD) is still inconclusive partly due to self-reported dietary assessment. The aim of the current study is to develop an MD- metabolomic score (MDMS) and investigate its association with CD in community-dwelling older adults. METHODS AND RESULTS: This study includes participants from the Three-City Study from the Bordeaux (n = 418) and Dijon (n = 422) cohorts who are free of dementia at baseline. Repeated measures of cognition over 12 years are collected. An MDMS is designed based on serum biomarkers related to MD key food groups and using a targeted metabolomics platform. Associations with CD are investigated through conditional logistic regression (matched on age, sex, and education level) in both sample sets. The MDMS is found to be inversely associated with CD (odds ratio [OR] [95% confidence interval (CI)] = 0.90 [0.80-1.00]; p = 0.048) in the Bordeaux (discovery) cohort. Results are comparable in the Dijon (validation) cohort, with a trend toward significance (OR [95% CI] = 0.91 [0.83-1.01]; p = 0.084). CONCLUSIONS: A greater adherence to the MD, here assessed by a serum MDMS, is associated with lower odds of CD in older adults.

Phytochemicals in Legumes: A Qualitative Reviewed Analysis.

Legumes are an excellent source of nutrients and phytochemicals. They have been recognized for their contributions to health, sustainability, and the economy. Although legumes comprise several species and varieties, little is known about the differences in their phytochemical composition and the magnitude of these. Therefore, the aim of this review is to describe and compare the qualitative profile of phytochemicals contained in legumes and identified through LC-MS and GC-MS methods. Among the 478 phytochemicals reported in 52 varieties of legumes, phenolic compounds were by far the most frequently described (n = 405, 85%). Metabolomics data analysis tools were used to visualize the qualitative differences, showing beans to be the most widely analyzed legumes and those with the highest number of discriminant phytochemicals (n = 180, 38%). A Venn diagram showed that lentils, beans, soybeans, and chickpeas shared only 7% of their compounds. This work highlighted the huge chemical diversity among legumes and identified the need for further research in this field and the use of metabolomics as a promising tool to achieve it.

Discovery of Intake Biomarkers of Lentils, Chickpeas, and White Beans by Untargeted LC-MS Metabolomics in Serum and Urine.

SCOPE: To identify reliable biomarkers of food intake (BFIs) of pulses. METHODS AND RESULTS: A randomized crossover postprandial intervention study is conducted on 11 volunteers who consumed lentils, chickpeas, and white beans. Urine and serum samples are collected at distinct postprandial time points up to 48 h, and analyzed by LC-HR-MS untargeted metabolomics. Hypaphorine, trigonelline, several small peptides, and polyphenol-derived metabolites prove to be the most discriminating urinary metabolites. Two arginine-related compounds, dopamine sulfate and epicatechin metabolites, with their microbial derivatives, are identified only after intake of lentils, whereas protocatechuic acid is identified only after consumption of chickpeas. Urinary hydroxyjasmonic and hydroxydihydrojasmonic acids, as well as serum pipecolic acid and methylcysteine, are found after white bean consumption. Most of the metabolites identified in the postprandial study are replicated as discriminants in 24 h urine samples, demonstrating that in this case the use of a single, noninvasive sample is suitable for revealing the consumption of pulses. CONCLUSIONS: The results of the present untargeted metabolomics work reveals a broad list of metabolites that are candidates for use as biomarkers of pulse intake. Further studies are needed to validate these BFIs and to find the best combinations of them to boost their specificity.