Gut Microbiota Markers and Dietary Habits Associated with Extreme Longevity in Healthy Sardinian Centenarians - PubMed (original) (raw)

Gut Microbiota Markers and Dietary Habits Associated with Extreme Longevity in Healthy Sardinian Centenarians

Vanessa Palmas et al. Nutrients. 2022.

Abstract

This study was aimed at characterizing the gut microbiota (GM) and its functional profile in two groups of Sardinian subjects with a long healthy life expectancy, overall named Long-Lived Subjects (LLS) [17 centenarians (CENT) and 29 nonagenarians (NON)] by comparing them to 46 healthy younger controls (CTLs). In addition, the contribution of genetics and environmental factors to the GM phenotype was assessed by comparing a subgroup of seven centenarian parents (CPAR) with a paired cohort of centenarians' offspring (COFF). The analysis was performed through Next Generation Sequencing (NGS) of the V3 and V4 hypervariable region of the 16S rRNA gene on the MiSeq Illumina platform. The Verrucomicrobia phylum was identified as the main biomarker in CENT, together with its members Verrucomicrobiaceae, Akkermansia and Akkermansia muciniphila. In NON, the strongest associations concern Actinobacteria phylum, Bifidobacteriaceae and Bifidobacterium, while in CTLs were related to the Bacteroidetes phylum, Bacteroidaceae, Bacteroides and Bacteroides spp. Intestinal microbiota of CPAR and COFF did not differ significantly from each other. Significant correlations between bacterial taxa and clinical and lifestyle data, especially with Mediterranean diet adherence, were observed. We observed a harmonically balanced intestinal community structure in which the increase in taxa associated with intestinal health would limit and counteract the action of potentially pathogenic bacterial species in centenarians. The GM of long-lived individuals showed an intrinsic ability to adapt to changing environmental conditions, as confirmed by functional analysis. The GM analysis of centenarians' offspring suggest that genetics and environmental factors act synergistically as a multifactorial cause in the modulation of GM towards a phenotype similar to that of centenarians, although these findings need to be confirmed by larger study cohorts and by prospective studies.

Keywords: 16S rRNA; Mediterranean diet; bowel function; centenarians; gut dysbiosis; inflammation; intestinal eubiosis; intestinal microbiota; lifestyle; longevity.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1

Figure 1

GM alpha and beta diversity analysis between CENT, NON and CTLs groups. (A) Plots indicate a statistically significant difference in the Shannon index between CENT and NON, evaluated by Kruskal-Wallis test. p equal to or less than 0.05 was considered statistically significant. (B) The Non-Metric Multidimensional Scaling (NMDS) plot based on Bray-Curtis distance matrix, performed in R software v.3.5.2 (ggplot2 package), showed a marked separation between the GM communities of LLS groups and CTLs. The statistical significance among the groups was determined with Permutational Multivariate Analysis of Variance (PERMANOVA) performed in R-vegan, function adonis (sum of square s = 1.498, mean of squares = 0.749, F = 6.074, R = 0.1201, p = 0.001). Significant segregation persisted only in the comparison between CENT and CTLs (p = 0.006) and between NON and CTLs (p = 0.003) following the pairwise PERMANOVA test performed in R (RVAdeMemoire package). p ≤ 0.05 was considered statistically significant. CENT = centenarian subjects, NON = nonagenarian subjects, CTLs = healthy younger controls, MDS = Multidimensional Scaling.

Figure 2

Figure 2

Linear Discriminant Analysis Effect Size (LEfSe) of microbial taxa between CENT, NON and CTLs.

Figure 3

Figure 3

Spearman correlation analysis between GM alterations and clinical variables in CENT and NON. Heatmaps were generated in GraphPad Prism v.7.0d. A correlation heatmap was used to represent significant statistical correlation values (Rho) between intestinal microbiota taxa significantly associated with CENT (A), NON (B) and clinical features. In the heatmap, violet squares indicate significant negative correlations (Rho < 0.0, _p_ ≤ 0.05) and blue squares indicate significant positive correlations (Rho > 0.0, p ≤ 0.05). Only p ≤ 0.05 are shown. BMI = Body Mass Index, ADL = Activities of Daily Living, DMS = Mediterranean Diet score, MMSE = Mini Mental State Evaluation, MNA = Mini Nutritional Assessment, PASE = Physical Activity Scale for the Elderly.

Figure 4

Figure 4

Statistically significant functional alterations of intestinal microbiome between CENT and NON and between LLS and CTLs. Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) algorithm was performed on Galaxy software v.1.0. (

https://galaxy.morganlangille.com/

), accessed on 18 May 2020, to infer metagenome composition in the samples by analyzing OTUs generated by QIIME pipeline. Bacterial metabolic pathways were predicted and classified by the Kyoto Encyclopedia of Genes and Genomes (KEGG). Statistical differences were analyzed for all metabolism pathways using the Statistical Analysis of Metagenomic Profiles (STAMP) software. Statistical significance was tested using Welch’s test, with a Storey False Discovery Rate correction (FDR) correction. q equal to or less than 0.05 was considered statistically significant. (A) Pathways more abundant in CENT are on the positive side (green circle with 95% CI); pathways less abundant in CENT are on the negative side (red circle with 95% CI). Mean proportions are shown in stacks (CENT = green; NON = red). The difference in mean proportions indicates the mean proportion CENT minus the mean proportion NON. (B,C) Pathways more abundant are on the positive side (red or green circle with 95% CI). Pathways less abundant are on the negative side (blue circle with 95% CI). Mean proportions are shown in stacks (CENT = red, NON = green; CTLs = blue. The difference in mean proportions indicates the mean proportion LLS group minus the mean proportion CTLs. CENT = centenarian subjects, NON = nonagenarian subjects, CTLs = healthy younger controls, LLS = long-lived subjects.

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