Comparing Analytical Methods for the Gut Microbiome and Aging: Gut Microbial Communities and Body Weight in the Osteoporotic Fractures in Men (MrOS) Study. (6th February 2020)

• Record Type: Journal Article
• Authors: Shardell, Michelle; Parimi, Neeta; Langsetmo, Lisa; Tanaka, Toshiko; Jiang, Lingjing; Orwoll, Eric; Shikany, James M; Kado, Deborah M; Cawthon, Peggy M
• Editors: Masternak, Michal
• Is Part Of: Journals of gerontology. Volume 75:Number 7(2020)
• Page Start: 1267
• Page End: 1275
• Publication Date: 2020-02-06
• Subjects: Compositional analysis -- Frailty -- Bayesian regression -- Network analysis; Geriatrics -- Periodicals; Gerontology -- Periodicals; 618.97
• DOI: 10.1093/gerona/glaa034
• Languages: English
• ISSNs: 1079-5006

Abstract

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.