Circulatory dietary and gut-derived metabolites predict early cognitive decline.

Neuroprotective metabolites choline, 5-hydroxyindole acetic acid (5-HIAA), and indole propionic acid (IPA) were lower in SCI and MCI individuals compared to healthy controls.

• Multiple linear regression modelling identified these three metabolites as significantly reduced in early cognitive decline groups.
• Regression models were adjusted for sex, BMI, age, albumin, liver and kidney function, and background diet.
• Study included 50 participants per group (cognitively healthy, SCI, and MCI), matched for age, BMI, and sex (n = 150 total).
• Metabolites were measured using mass spectrometry platforms determining serum concentrations.

The cytotoxic metabolite indoxyl sulfate and kynurenic acid were elevated in SCI and MCI participants compared to healthy controls.

• Elevated indoxyl sulfate and kynurenic acid were identified via multiple linear regression adjusted for age, sex, BMI, albumin, liver and kidney function, and background diet.
• Indoxyl sulfate is described as a cytotoxic metabolite thought to contribute to neuroinflammation, blood-brain barrier dysfunction, and neuronal degeneration.
• Measurements were derived from serum samples across the three matched cognitive groups (n = 50 per group).

A random forest algorithm with multiclass classification identified six metabolites as classifiers of early cognitive decline, achieving an AUC of 0.79.

• The six metabolites identified were indoxyl sulfate, choline, 5-hydroxyindole acetic acid, IPA, kynurenic acid, and kynurenine.
• The random forest model achieved an area under the curve (AUC) of 0.79.
• The machine learning approach validated findings from the multiple linear regression analysis.
• The panel spanned tryptophan-related compounds and a choline-related metabolite from a broader 33-metabolite panel that also included bile acids and TMAO-related metabolites.

The study measured a panel of 33 serum metabolites across three cognitive groups using mass spectrometry.

• The 33 metabolites comprised 13 tryptophan-related compounds, 15 bile acid compounds, 3 TMAO-related metabolites, and 2 cresol metabolites.
• Participants were n = 50 per group across cognitively healthy, subjective cognitive impairment (SCI), and mild cognitive impairment (MCI) groups, matched for age, BMI, and sex.
• 16S rRNA amplicon sequencing was also employed to identify bacterial taxa associated with metabolic changes.
• Both multiple linear regression and machine learning techniques were applied to identify the metabolite panel.

Microbial dysbiosis in early cognitive decline and Alzheimer's disease can modulate levels of microbe-derived metabolites thought to contribute to neuroinflammation, blood-brain barrier dysfunction, and neuronal degeneration.

• Microbe-derived metabolites (MDM) are proposed to play a role in the pathophysiology of early cognitive decline.
• The precise role of MDM in cognitive decline and their potential value as risk factors is described as 'poorly understood' prior to this study.
• The study addresses the gap by profiling MDM across healthy controls, SCI, and MCI participants.

The authors propose that microbial-derived metabolites may serve as putative composite biomarkers for metabolic risk stratification and support development of minimally invasive screening tools.

• The six-metabolite panel achieved an AUC of 0.79 in classifying early cognitive decline.
• The authors highlight 'potential clinical relevance for metabolic risk stratification' and 'future development of minimally invasive screening tools.'
• The study used serum-based measurements, supporting the minimally invasive nature of potential future screening.