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Associations between Pro- and Anti-Inflammatory Gastro-Intestinal Microbiota, Diet, and Cognitive Functioning in Dutch Healthy Older Adults: The NU-AGE Study

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van Soest, Annick P. M., Hermes, Gerben D. A., Berendsen, Agnes A. M., van de Rest, Ondine, Zoetendal, Erwin G., Fuentes, Susana, Santoro, Aurelia, Franceschi, Claudio, de Groot, Lisette C. P. G. M., de Vos, Willem M.·2020·Nutrients
DOI 10.3390/nu12113471PMC PMC7697493
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Abstract

Dietary modulation of the gastro-intestinal microbiota is a potential target in improving healthy ageing and age-related functional outcomes, including cognitive decline. We explored the association between diet, gastro-intestinal microbiota and cognition in Dutch healthy older adults of the ‘New dietary strategies addressing the specific needs of the elderly population for healthy aging in Europe’ (NU-AGE) study. The microbiota profile of 452 fecal samples from 226 subjects was determined using a 16S ribosomal RNA gene-targeted microarray. Dietary intake was assessed by 7-day food records. Cognitive functioning was measured with an extensive cognitive test battery. We observed a dietary and microbial pro- to anti-inflammatory gradient associated with diets richer in animal- or plant-based foods. Fresh fruits, nuts, seeds and peanuts, red and processed meat and grain products were most strongly associated to microbiota composition. Plant-rich diets containing fresh fruits, nuts, seeds and peanuts were positively correlated with alpha-diversity, various taxa from the Bacteroidetes phylum and anti-inflammatory species, including those related to Faecalibacterium prausnitzii and Eubacterium rectale and E. biforme. Animal product-rich diets associated with pro-inflammatory species, including those related to Ruminococcus gnavus and Collinsella spp.. Cognition was neither associated with microbiota composition nor alpha-diversity. In conclusion, diets richer in animal- and plant-based foods were related to a pro- and anti-inflammatory microbial profile, while cognition was associated with neither.

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Crossref · 10.3390/nu12113471

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Figure 1 Microbiota covariates. Impact of all measured variables on microbiota composition defined as percentage variation explained (R2) out of all the total microbiota variation. A higher R2 implies a stronger effect size.
Figure 1 Microbiota covariates. Impact of all measured variables on microbiota composition defined as percentage variation explained (R2) out of all the total microbiota variation. A higher R2 implies a stronger effect size.CC BY · PubMed Central
Figure 2 Association of microbiota with food groups, nutrients and BMI. Samples are plotted as grey circles. (A) Redundancy analysis (RDA) bi-plot of microbiota with explanatory variables; food groups (red), nutrients (blue) and phenotypical characteristics (green). (B) RDA bi-plot of samples with the associated microbial taxa (indicated as genera or species-level groups) The direction of the arrows depicts the abundance of microbial taxa. Length of the arrows is a measure of fit. The variable arrows approximate the correlation between species and explanatory variables. Samples near the coordinate origin (zero point) suggest near zero correlation. The further a sample falls in the direction indicated by the arrow, the higher the correlation.
Figure 2 Association of microbiota with food groups, nutrients and BMI. Samples are plotted as grey circles. (A) Redundancy analysis (RDA) bi-plot of microbiota with explanatory variables; food groups (red), nutrients (blue) and phenotypical characteristics (green). (B) RDA bi-plot of samples with the associated microbial taxa (indicated as genera or species-level groups) The direction of the arrows depicts the abundance of microbial taxa. Length of the arrows is a measure of fit. The variable arrows approximate the correlation between species and explanatory variables. Samples near the coordinate origin (zero point) suggest near zero correlation. The further a sample falls in the direction indicated by the arrow, the higher the correlation.CC BY · PubMed Central
Figure 3 Correlation of alpha-diversity with microbiota covariates (A) and cognition variables (B). Pearson correlation of significant microbiota covariates were calculated. p values are corrected for multiple testing using the Benjamini–Hochberg procedure. *** q < 0.001, ** q < 0.01 * q < 0.05.
Figure 3 Correlation of alpha-diversity with microbiota covariates (A) and cognition variables (B). Pearson correlation of significant microbiota covariates were calculated. p values are corrected for multiple testing using the Benjamini–Hochberg procedure. *** q < 0.001, ** q < 0.01 * q < 0.05.CC BY · PubMed Central

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  1. Lewis, R., and Kupke, T. (1977, January 4–7). The Lafayette Clinic Repeatable Neuropsychological Test Battery: Its Development and Research Applications. Proceedings of the Annual Meeting of the Southeastern Psychological Association, Hollywood, FL, USA.

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Metadata

Authors
van Soest, A. P. M., Hermes, G. D. A., Berendsen, A. A. M., van de Rest, O., Zoetendal, E. G., Fuentes, S., Santoro, A., Franceschi, C., de Groot, L. C. P. G. M., & de Vos, W. M.
Affiliations
  • Division of Human Nutrition and Health, Wageningen University &amp; Research, 6708WE Wageningen, The Netherlands
  • Wageningen University & Research (NL)
  • National Institute for Public Health and the Environment (NL)
  • University of Bologna (IT)
  • N. I. Lobachevsky State University of Nizhny Novgorod (RU)
  • Laboratory of Microbiology, Wageningen University &amp; Research, 6708WE Wageningen, The Netherlands
ORCID
Venue
Nutrients
Publisher
MDPI AG
Published
2020-11-12
Volume
12
Issue
11
Pages
3471
ISSN
2072-6643 (ISSN-L)
DOI
10.3390/nu12113471
PMC
PMC7697493
OpenAlex
W3103664997
Cited by
118
References
89
Citations by year
2026: 8 · 2025: 22 · 2024: 26 · 2023: 38 · 2022: 19 · 2021: 5
FWCI
5.02
Type
journal article
Language
en
Open access
Licence
Locations
  • Nutrients (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Socio-Environmental Systems Modeling (acceptedVersion, cc-by)
  • Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Työväentutkimus Vuosikirja (submittedVersion)
  • Rivm Repository (Netherlands National Institute for Public Health and the Environment) (submittedVersion)
  • Rivm (National Institute for Public Health and the Environment) (submittedVersion)
  • Rivm (National Institute for Public Health and the Environment) (submittedVersion, other-oa)
  • Data Archiving and Networked Services (DANS) (submittedVersion, cc-by)
Funders
  • Seventh Framework Programme (266486)
  • Horizon 2020 Framework Programme (818368)
  • Spinoza award of The Netherlands Organization for Scientific Research 2008 (n/a)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Nutritional Studies and Diet
  • Life Sciences › Agricultural and Biological Sciences › Food Science › Probiotics and Fermented Foods
Keywords
gut microbiota, diet, cognitive function, older adults, healthy aging, inflammation, plant-based diet, animal-based diet, alpha diversity, Faecalibacterium prausnitzii, Ruminococcus gnavus, Bacteroidetes, red and processed meat, fresh fruits, nuts and seeds, cognitive decline
MeSH terms
Gastrointestinal Microbiome, Aged, Bacteria, Cognition, Feces, Female, Humans, Male, Netherlands, RNA, Ribosomal, 16S, Diet, Mediterranean, Healthy Volunteers

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