Gut Microbiome Pattern Reflects Healthy Ageing and Predicts Survival in Humans
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ARTICLES https://doi.org/10.1038/s42255-021-00348-0 Gut microbiome pattern reflects healthy ageing and predicts survival in humans Tomasz Wilmanski 1, Christian Diener1, Noa Rappaport 1, Sushmita Patwardhan1, Jack Wiedrick2, Jodi Lapidus2, John C. Earls1,9, Anat Zimmer1, Gustavo Glusman 1, Max Robinson 1, James T. Yurkovich 1, Deborah M. Kado3, Jane A. Cauley4, Joseph Zmuda4, Nancy E. Lane5, Andrew T. Magis 1, Jennifer C. Lovejoy1,10, Leroy Hood1, Sean M. Gibbons 1,6,7 ✉ , Eric S. Orwoll 2 ✉ and Nathan D. Price 1,8 ✉ The gut microbiome has important effects on human health, yet its importance in human ageing remains unclear. In the present study, we demonstrate that, starting in mid-to-late adulthood, gut microbiomes become increasingly unique to individuals with age. We leverage three independent cohorts comprising over 9,000 individuals and find that compositional uniqueness is strongly associated with microbially produced amino acid derivatives circulating in the bloodstream. In older age (over ~80 years), healthy individuals show continued microbial drift towards a unique compositional state, whereas this drift is absent in less healthy individuals. The identified microbiome pattern of healthy ageing is characterized by a depletion of core genera found across most humans, primarily Bacteroides. Retaining a high Bacteroides dominance into older age, or having a low gut microbiome uniqueness measure, predicts decreased survival in a 4-year follow-up. Our analysis identifies increasing compositional uniqueness of the gut microbiome as a component of healthy ageing, which is characterized by distinct microbial metabolic outputs in the blood. he ecological dynamics of the human gut microbiome have younger controls7–9. Some studies have also reported higher levels been characterized by rapid change in early life (0–3 years), of gut α-diversity in centenarians compared with younger individu- followed by a long period of relative stability, ending with als8–10, indicating that gut microbiomes continue to develop within T 1,2 gradual changes associated with advanced age . Particularly in their hosts, even in the later decades of human life. The loss of core older populations (65+ years), studies over the past few years have taxa, the exact identities of which may vary across different human revealed a number of associations between gut microbiome compo- populations (Bacteroides versus Prevotella spp.)11, and the increase sition and measures of physical fitness3, frailty4 and diet5, highlight- in α-diversity reported in long-lived individuals, suggest that gut ing the importance of proper gut microbiome function into the later microbiomes may become increasingly divergent, or unique, to each decades of human life. Despite substantial progress in our under- individual as they age. This phenomenon of community composi- standing of the human gut microbiome, still very little is known tional divergence seen in centenarians may be key to understanding about when age-associated changes in the gut microbiome begin, how the gut microbiome contributes to the changing physiological how these changes influence host physiology, and whether ageing landscape accompanying human ageing. patterns within the gut microbiome simply reflect, or contribute to, Gut microbial associations reported in centenarians are often long-term health and survival outcomes. Importantly, identifying inconsistent with studies of elderly populations. In particular, stud- ageing patterns within the gut microbiome could have major clini- ies on the ELDERMET cohort (that is, the most extensively stud- cal implications for both monitoring and modifying gut microbi- ied cohort of older people with gut microbiome data to date) have ome health throughout the human lifespan. reported an increased dominance of the core genera Bacteroides, Several studies conducted on centenarian populations provided Alistipes and Parabacteroides in those aged 65+ years compared with potential insight into gut microbial trajectories associated with age- healthy, younger controls12. Measures of α-diversity have also been ing. Biagi et al.6 demonstrated that gut microbiomes of centenar- shown to negatively correlate with frailty4, indicating that changes ians (aged ≤104 years) and supercentenarians (104+ years) show in the gut microbiome correspond to age-associated decline. Studies a depletion in core abundant taxa (Bacteroides, Roseburia and on older long-term-care residents further characterized a gradual Faecalibacterium spp., among others), complemented by an increase shift in gut microbiome composition associated with the duration in the prevalence of rare taxa. Similar findings have since been of stay in the care facility2,13, whereas a more recent study dem- reported in other centenarian populations across the world, such as onstrated that older individuals (aged 60+ years) exhibited higher in Sardinian, Chinese and Korean centenarians, relative to healthy, variability in gut microbiome composition relative to younger 1Institute for Systems Biology, Seattle, WA, USA. 2Oregon Health and Science University, Portland, OR, USA. 3Herbert Wertheim School of Public Health and Human Longevity Science at UCSD and Department of Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA. 4Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA. 5Center for Musculoskeletal Health, Department of Internal Medicine, University of California Davis Medical Center, Sacramento, CA, USA. 6eScience Institute, University of Washington, Seattle, WA, USA. 7Department of Bioengineering, University of Washington, Seattle, WA, USA. 8Onegevity Health, New York, NY, USA. 9Present address: Onegevity Health, New York, NY, USA. 10Present address: Lifestyle Medicine Institute, Redlands, CA, USA. ✉e-mail: [email protected]; [email protected]; [email protected] 274 NatURE MetaBOLISM | VOL 3 | February 2021 | 274–286 | www.nature.com/natmetab NATURE METABOLISM ARTICLES a b c d Arivale cohort Vendor A n = 2,539 Age (years): 21–82 (47.5 ± 12.1) Male: 37.5% Vendor B n = 3,653 n = 1,114 Age (years): 18–87 (48.0 ± 12.2) Age (years): 18–87 (49.4 ± 12.5) Male: 40.4% Male: 47.0% MrOS cohort Discovery n = 599 Validation Age (years): 78–98 (84.2 ± 4.1) Measure microbiomes Male: 100% n = 907 Validation n = 308 Age (years): 78–98 (84.2 ± 4.0) Age (years): 78–97 (84.0 ± 3.8) Male: 100% Male: 100% Fig. 1 | Conceptual outline of study and analysis workflow. a, The two different study populations used: the Arivale cohort and the MrOS cohort. b, Each of these two study populations further subdivided into two groups; the Arivale cohort was split based on the microbiome vendor used to collect and process samples whereas the MrOS cohort separated into discovery and validation groups, based on the batch in which the samples were run (discovery samples were processed in the initial batch, and validation samples approximately 3 years later). c, Profiles of the microbiomes from these four study populations, beginning with the Arivale cohort, and validating our findings across the additional populations. d, Further exploration by our analysis pipeline of the associations across the identified gut microbiome ageing pattern, lifestyle factors and host physiology in the combined Arivale cohort, as well as health metrics and mortality in the combined MrOS cohort. individuals (aged 20–60 years), which has been attributed to a puta- Arivale cohort to identify gut microbiome ageing patterns across tive increase in abundance of pathobionts at the expense of ben- most of the adult human lifespan, and investigate how these pat- eficial gut bacteria14. Collectively, these and other studies1 provide terns correspond to host physiology. We then extended our analysis a view of the human gut microbiome across the adult lifespan as into the MrOS cohort, where we had detailed health metrics and relatively stable up until old age, at which point gradual composi- follow-up data on mortality, to evaluate how the patterns identified tional shifts occur that reflect, and potentially contribute to, declin- within the Arivale cohort correspond to health and survival in the ing health. later decades of human life. The heterogeneity of findings in ageing studies indicates that there may be multiple gut microbiome patterns of ageing, some of A gut microbiome ageing pattern spans much of the adult lifes- which reflect better health and life expectancy outcomes than oth- pan. To characterize gut microbial patterns associated with ageing, ers. Although recent analyses have demonstrated a link between we initially performed a β-diversity analysis comparing all available gut microbiome composition and long-term health outcomes15,16, baseline microbiome samples from a heterogeneous, and relatively the scarcity of cohorts with longitudinal follow-up data, the lack healthy, Arivale population (Fig. 1 and Extended Data Fig. 1). To of detailed molecular phenotyping and health metrics, and the capture the compositional divergence indicative of healthy ageing relatively small sample sizes of existing studies on ageing limit our observed in centenarians, our analysis involved extracting the min- understanding of gut microbial changes seen across the human imum value for each individual from a calculated Bray–Curtis dis- lifespan. In the present study, we overcome these limitations and similarity matrix. This value reflects how dissimilar an individual is present an analysis of the gut microbiome and phenotypic data from their nearest