Early Signs of Gut Microbiome Aging: Biomarkers of Inflammation, Metabolism, and Macromolecular Damage in Young Adulthood

被引:28
作者
Renson, Audrey [1 ]
Harris, Kathleen Mullan [2 ,3 ]
Dowd, Jennifer B. [4 ]
Gaydosh, Lauren [5 ]
McQueen, Matthew B. [6 ]
Krauter, Kenneth S. [7 ]
Shannahan, Michael [8 ]
Aiello, Allison E. [1 ]
机构
[1] Univ N Carolina, Gillings Sch Global Publ Hlth, Dept Epidemiol, Chapel Hill, NC 27599 USA
[2] Univ N Carolina, Dept Sociol, Chapel Hill, NC 27599 USA
[3] Univ N Carolina, Carolina Populat Ctr, Chapel Hill, NC 27599 USA
[4] Univ Oxford, Leverhulme Ctr Demog Sci, Oxford, England
[5] Vanderbilt Univ, Ctr Med Hlth & Soc, 221 Kirkland Hall, Nashville, TN 37235 USA
[6] Univ Colorado, Dept Integrat Physiol, Boulder, CO 80309 USA
[7] Univ Colorado, Dept Mol Cellular & Dev Biol, Boulder, CO 80309 USA
[8] Univ Zurich, Inst Sociol, Zurich, Switzerland
来源
JOURNALS OF GERONTOLOGY SERIES A-BIOLOGICAL SCIENCES AND MEDICAL SCIENCES | 2020年 / 75卷 / 07期
基金
美国国家卫生研究院;
关键词
Gastrointestinal microbiota; Cellular senescence; Lipid metabolism; Glucose metabolism; Bayesian analysis; IMMUNITY; OBESITY; AGE; HEALTH;
D O I
10.1093/gerona/glaa122
中图分类号
R592 [老年病学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 100203 ;
摘要
Emerging links between gut microbiota and diseases of aging point to possible shared immune, metabolic, and cellular damage mechanisms, operating long before diseases manifest. We conducted 16S rRNA sequencing of fecal samples collected from a subsample (n = 668) of Add Health Wave V, a nationally representative longitudinal study of adults aged 32-42. An overlapping subsample (n = 345) included whole-blood RNA-seq. We examined associations between fecal taxonomic abundances and dried blood spot-based markers of lipid and glucose homeostasis and C-reactive protein (measured in Wave IV), as well as gene expression markers of inflammation, cellular damage, immune cell composition, and transcriptomic age (measured in Wave V), using Bayesian hierarchical models adjusted for potential confounders. We additionally estimated a co-abundance network between inflammation-related genes and bacterial taxa using penalized Gaussian graphical models. Strong and consistent microbiota associations emerged for HbA1c, glucose, C-reactive protein, and principal components of genes upregulated in inflammation, DNA repair, and reactive oxygen species, with Streptococcus infantis, Pseudomonas spp., and Peptoniphilus as major players for each. This pattern was largely echoed (though attenuated) for immunological cell composition gene sets, and only Serratia varied meaningfully by transcriptomic age. Network co-abundance indicated relationships between Prevotella sp., Bacteroides sp., and Ruminococcus sp. and gut immune/metabolic regulatory activity, and Ruminococcus sp, Dialister, and Butyrivibrio crossotus with balance between Th1 and Th2 inflammation. In conclusion, many common associations between microbiota and major physiologic aging mechanisms are evident in early-mid adulthood and suggest avenues for early detection and prevention of accelerated aging.
引用
收藏
页码:1258 / 1266
页数:9
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