Comparing analytical methods for the gut microbiome and aging: Gut microbial communities and body weight in the osteoporotic fractures in men (MrOS) study

Osteoporotic Fractures in Men (MrOS) Study Group

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Determining the role of gut microbial communities in aging-related phenotypes, including weight loss, is an emerging gerontology research priority. Gut microbiome datasets comprise relative abundances of microbial taxa that necessarily sum to 1; analysis ignoring this feature may produce misleading results. Using data from the Osteoporotic Fractures in Men (MrOS) study (n = 530; mean [SD] age = 84.3 [4.1] years), we assessed 163 genera from stool samples and body weight. We compared conventional analysis, which does not address the sum-to-1 constraint, to compositional analysis, which does. Specifically, we compared elastic net regression (for variable selection) and conventional Bayesian linear regression (BLR) and network analysis to compositional BLR and network analysis; adjusting for past weight, height, and other covariates. Conventional BLR identified Roseburia and Dialister (higher weight) and Coprococcus-1 (lower weight) after multiple comparisons adjustment (p < .0125); plus Sutterella and Ruminococcus-1 (p < .05). No conventional network module was associated with weight. Using compositional BLR, Coprococcus-2 and Acidaminococcus were most strongly associated with higher adjusted weight; Coprococcus-1 and Ruminococcus-1 were most strongly associated with lower adjusted weight (p < .05), but nonsignificant after multiple comparisons adjustment. Two compositional network modules with respective hub taxa Blautia and Faecalibacterium were associated with adjusted weight (p < .01). Findings depended on analytical workflow. Compositional analysis is advocated to appropriately handle the sum-to-1 constraint.

Original languageEnglish (US)
Pages (from-to)1267-1275
Number of pages9
JournalJournals of Gerontology - Series A Biological Sciences and Medical Sciences
Volume75
Issue number7
DOIs
StatePublished - 2020

Keywords

  • Bayesian regression
  • Compositional analysis
  • Frailty
  • Network analysis

ASJC Scopus subject areas

  • Aging
  • Geriatrics and Gerontology

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