The three-city population-based cohort study also found preliminary evidence to support the potential mediation by impaired cardio-metabolic health (diabetes and hypercholesterolemia).
The strong biological interplay between diet, the gut microbiota and the central nervous system, is known as the gut–brain axis. And emerging evidence suggests a link between gut metabolites and cognitive ageing and associated diseases, in particular dementia and Alzheimer’s disease (AD). Candidate metabolites include: anthranilic acid; trimethylamine oxide (TMAO); cholesterol-derived biliary acids; and short-chain fatty acids (SCFA).
But the authors of the current study note that detection of diet- and gut-derived metabolites requires highly sensitive metabolomics approaches, which have been developed only recently and have not yet been applied on a large scale in biomedical research. Plus studies have been limited in sample size and in the number of candidate metabolites analysed, and causality has also been a critical limitation in microbiome research.
The current study therefore applied a large-scale and quantitative multi-metabolite platform to serum samples to determine circulating levels of 72 food- and gut microbiota-derived metabolites and studied their association with cognitive decline.
The authors note that the prospective design ensured that any of the biological changes observed in participants that did not exhibit signs of dementia allowed the identification of early gut–brain axis markers of cognitive aging, while minimising the risk of reverse causality.
They conclude: "In this novel exploration of the gut–brain axis, we measured a large panel of postbiotics in a cohort of older persons and found an association between increased circulating propionic acid levels and higher cognitive decline.
"Propionic acid may be derived from the fermentation of undigested dietary fiber by the gut microbiota, as well as from dietary intake, as it is a common food preservative in processed food such as meat, dairy products and sweets.
"Moreover, we found preliminary evidence to support the potential mediation by impaired cardio-metabolic health (diabetes and hypercholesterolemia), which deserves further research"
Results
The Three-City (3C) study is a French cohort initiated in 1999 with the primary aim of studying vascular risk factors for dementia. It included 9294 non-institutionalized community dwellers aged 65 years or over from the following three French cities: Bordeaux (n = 2104), Dijon (n = 4931) and Montpellier (n = 2259).
In the discovery stage, seven food- and gut-microbiota-derived metabolites associated with the odds of cognitive decline were selected, including three amino acid derivatives (phenylacetylglutamine, indolelactic acid and kynurenic acid); a TMAO substrate (betaine), a vitamin B (pantothenic acid), a SCFA (propionic acid) and a polyphenol derivative (3′,4′-DHPV-S). Among these, only propionic acid was replicated in the validation stage.
For each 1 standard deviation (SD) increase in propionic acid concentration in serum, the odds of cognitive decline increased by 40% in the discovery sample and by 26% in the validation sample.
After adjustment for potential confounders, propionic acid remained significantly associated with cognitive decline.
Additional analyses found propionic acid strongly correlated with blood glucose (r = 0.79) and with intakes of meat and cheese (r > 0.15), but not fiber (r = 0.04), suggesting a minor role of prebiotic foods per se, but a possible link to processed foods, in which propionic acid is a common preservative.
Methods
At baseline, face-to-face interviews were conducted to collect socio-demographic data, lifestyle and health parameters. In addition, anthropometric and blood pressure measurements were performed, as well as fasting blood sampling for the constitution of a biobank. The number of medications regularly consumed by participants was recorded. Follow-up visits were conducted at home every two to three years. At baseline and at each follow-up visit, a battery of cognitive tests was performed by a certified and experienced neuropsychologist.
In Bordeaux, a nutritional survey was performed by a trained dietitian during a home interview conducted at the first follow-up in 2001–2002, including a food frequency questionnaire and a 24 hour recall.
Targeted metabolomics was conducted using a quantitative multi-metabolite platform for the simultaneous detection and quantification of 206 food-related metabolites, gut microbiota derivatives and endogenous metabolites.
In this study, researchers focused on 72 out of the 206 metabolites of the targeted metabolomics platform that are known to be produced or influenced by the gut microbiota, including aromatic amino acids and derivatives, biogenic quaternary amines, secondary bile acids, B-group vitamins, SCFA and metabolites derived from the gut biotransformation of dietary polyphenols.
The authors note some limitations of this study, including the risk of false negatives which could not be dismissed completely. They also note the sample size could be insufficient to ensure adequate statistical power to detect differences in the levels of metabolites with low circulating basal values and high inter- and intra-individual variability. Also, serum samples were analysed at the study baseline only; therefore, we could not examine longitudinal changes in the serum metabolome during the course of cognitive decline.
The metabolite panel did not cover all metabolites of the gut–brain axis (due to the lack of available standards, or detection limitations by UHPLC-MS/MS technologies). For example, some microbiota-derived metabolites that are potentially related to cognition, such as γ-aminobutyric acid (GABA), ammonium, some phytoestrogens and oligosaccharides, such as lipopolysaccharide (LPS), were not quantified.
Source: Nutrients
https://doi.org/10.3390/nu14214688 (registering DOI)
"Exploration of the Gut–Brain Axis through Metabolomics Identifies Serum Propionic Acid Associated with Higher Cognitive Decline in Older Persons"
Neuffer, J.; González-Domínguez, R.; Lefèvre-Arbogast, S.; Low, D.Y.; Driollet, B.; Helmer, C.; Du Preez, A.; de Lucia, C.; Ruigrok, S.R.; Altendorfer, B.; Aigner, L.; Lucassen, P.J.; Korosi, A.; Thuret, S.; Manach, C.; Pallàs, M.; Urpi-Sardà, M.; Sánchez-Pla, A.; Andres-Lacueva, C.; Samieri, C.