Advanced age has been associated with alterations to the microbiome within the intestinal tract as well as intestinal permeability (i.e., “leaky gut”). Prior studies suggest that intestinal permeability may contribute to increases in systemic inflammation—an aging hallmark—possibly via microorganisms entering the circulation. Yet, no studies exist describing the state of the circulating microbiome among older persons. To compare microbiota profiles in serum between healthy young (20–35 years, n = 24) and older adults (60–75 years, n = 24) as well as associations between differential microbial populations and prominent indices of age-related inflammation. Unweighted Unifrac analysis, a measure of β-diversity, revealed that microbial communities clustered differently between young and older adults. Several measures of α-diversity, including chao1 (p = 0.001), observed species (p = 0.001), and phylogenetic diversity (p = 0.002) differed between young and older adults. After correction for false discovery rate (FDR), age groups differed (all p values ≤ 0.016) in the relative abundance of the phyla Bacteroidetes, SR1, Spirochaetes, Bacteria_Other, TM7, and Tenericutes. Significant positive correlations (p values ≤ 0.017 after FDR correction) were observed between IGF1 and Bacteroidetes (ρ = 0.380), Spirochaetes (ρ = 0.528), SR1 (ρ = 0.410), and TM7 (ρ = 0.399). Significant inverse correlations were observed for IL6 with Bacteroidetes (ρ = − 0.398) and TM7 (ρ = − 0.423), as well as for TNFα with Bacteroidetes (ρ = − 0.344). Similar findings were observed at the class taxon. These data are the first to demonstrate that the richness and composition of the serum microbiome differ between young and older adults and that these factors are linked to indices of age-related inflammation.
INTRODUCTION: Alterations in the composition of the human gut microbiome and its metabolites have been linked to gut epithelial neoplasia. We hypothesized that differences in mucosa-adherent Barrett's microbiota could link to risk factors, providing risk of progression to neoplasia. Methods: Paired biopsies from both diseased and nonaffected esophagus (as well as gastric cardia and gastric juice for comparison) from patients with intestinal metaplasia (n = 10), low grade dysplasia (n = 10), high grade dysplasia (n = 10), esophageal adenocarcinoma (n = 12), and controls (n = 10) were processed for mucosa-associated bacteria and analyzed by 16S ribosomal ribonucleic acid V4 gene DNA sequencing. Taxa composition was tested using a generalized linear model based on the negative binomial distribution and the log link functions of the R Bioconductor package edgeR. Results: The microbe composition of paired samples (disease vs nondisease) comparing normal esophagus with intestinal metaplasia, low grade dysplasia, high grade dysplasia, and adenocarcinoma showed significant decreases in the phylum Planctomycetes and the archaean phylum Crenarchaeota ( P < 0.05, false discovery rate corrected) in diseased tissue compared with healthy controls and intrasample controls (gastric juice and unaffected mucosa). Genera Siphonobacter, Balneola, Nitrosopumilus, and Planctomyces were significantly decreased ( P < 0.05, false discovery rate corrected), representing <10% of the entire genus community. These changes were unaffected by age, tobacco use, or sex for Crenarcha. DISCUSSSION: There are similar significant changes in bacterial genera in Barrett's esophageal mucosa, dysplasia, and adenocarcinoma compared with controls and intrapatient unaffected esophagus. Further work will establish the biologic plausibility of these specific microbes' contributions to protection from or induction of esophageal epithelial dysplasia.
ObjectiveTo examine the gut microbiome composition among individuals with acute and long‐standing spinal cord injury (SCI).MethodsSeven individuals with acute spinal cord injury (A‐SCI, 36 ± 13 y, 2F/5M, C4‐T10, AIS A‐D) and 10 individuals with long‐standing SCI (L‐SCI, 49 ± 9 y, 1F/9M, C4‐T12, AIS A, B, and D ) were recruited. Stool samples were collected after a median of 7 days after the onset of SCI (range: 4–11 days) from participants with A‐SCI in the hospital. The median number of years post injury for the L‐SCI group was 22 years at the time of stool collection. Parapak® vials was used for collection of the stool samples. Fecal microbiota DNA was extracted using Zymo® Fecal DNA Isolation kit. PCR was used to amplify the V4 region of the 16S rRNA gene, and the PCR products were sequenced using an Illumina MiSeq platform. Bioinformatics analyses started with assessment of raw data and filtering low‐quality data using FASTQC and FASTX, respectively. A combination of tools in the QIIME suite were utilized for clustering reads into operational taxonomic units (uclust) and taxa assignment (PyNAST and Fasttree). Several metrics for alpha and beta diversity were determined for group comparisons. Significant differences between groups (A‐SCI vs L‐SCI) were determined by PERMANOVA test on each of the beta diversity indices. A Kruskal‐Wallis test was performed to compare the abundances of key taxa between groups using tools within the QIIME suite.ResultsMicrobiota alpha diversity was not significantly different between groups. However, group differences were observed in beta diversity (unweighted and weighted UniFrac analyses, P < 0.05 for both). Principle coordinate analysis showed a separation of two groups (see attached figure). Individuals with chronic SCI had higher abundances of bacteria in the Clostridiaceae, Lachnospiraceae, and Alcaligenaceae families, lower abundances of S24‐7 family, and higher abundances of Parabacteroides genus (family Porphyromonadaceae) (P < 0.05).ConclusionThese data for the first time demonstrated a sustained shift in gut microbiota composition in individuals with L‐SCI vs. A‐SCI. Specifically, microbes linked to the development of metabolic syndrome, central nervous system‐related bowel disorders, and physical inactivity are elevated in adults with L‐SCI. Future studies are warranted to evaluate the involvement of gut microbiota in the development of metabolic disorders among individuals with L‐SCI.Support or Funding InformationThis work was supported by KL2TR001419‐01 (CY‐F) and H133N110008 (McLain A)This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.
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