Comparing Analytical Methods for the Gut Microbiome and Aging: Gut Microbial Communities and Body Weight in the Osteoporotic Fractures in Men (MrOS) Study

Michelle Shardell, Neeta Parimi, Lisa Langsetmo, Toshiko Tanaka, Lingjing Jiang, Eric Orwoll, James M. Shikany, Deborah M. Kado, Peggy M. Cawthon

Research output: Contribution to journalArticle

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
JournalThe journals of gerontology. Series A, Biological sciences and medical sciences
Volume75
Issue number7
DOIs
StatePublished - Jun 18 2020

Keywords

  • Bayesian regression
  • Compositional analysis
  • Frailty
  • Network analysis

ASJC Scopus subject areas

  • Aging
  • Geriatrics and Gerontology

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