The DOI matches its Crossref record; 67 of the 67 references it cites were found in a registry or an index.
Aging progression of human gut microbiota
Open accessAbstract
Background: Human gut microbiota are important for human health and have been regarded as a “forgotten organ”, whose variation is closely linked with various factors, such as host genetics, diet, pathological conditions and external environment. The diversity of human gut microbiota has been correlated with aging, which was characterized by different abundance of bacteria in various age groups. In the literature, most of the previous studies of age-related gut microbiota changes focused on individual species in the gut community with supervised methods. Here, we aimed to examine the underlying aging progression of the human gut microbial community from an unsupervised perspective. Results: We obtained raw 16S rRNA sequencing data of subjects ranging from newborns to centenarians from a previous study, and summarized the data into a relative abundance matrix of genera in all the samples. Without using the age information of samples, we applied an unsupervised algorithm to recapitulate the underlying aging progression of microbial community from hosts in different age groups and identify genera associated to this progression. Literature review of these identified genera indicated that for individuals with advanced ages, some beneficial genera are lost while some genera related with inflammation and cancer increase. Conclusions: The multivariate unsupervised analysis here revealed the existence of a continuous aging progression of human gut microbiota along with the host aging process. The identified genera associated to this aging process are meaningful for designing probiotics to maintain the gut microbiota to resemble a young age, which hopefully will lead to positive impact on human health, especially for individuals in advanced age groups.
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“Desulfovibrio, one of the main H2S-producing gut bacteria [59], is known to be associated with PD due to its elevated abundance [60].”
From Healthy Human Fecal Microbiota Transplantation into Mice Attenuates MPTP-Induced Neurotoxicity via AMPK/SOD2 Pathway (2023) · cites this paper as [59]
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“The aging process of the host parallels a continuous aging progression of the GM (90).”
From Signalling cognition: The gut microbiota and hypothalamic-pituitary-adrenal axis (2023) · cites this paper as [90]
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Metadata
- Authors
- Xu, C., Zhu, H., & Qiu, P.
- Affiliations
- Georgia Institute of Technology (US)
- Peking University (CN)
- Corresponding author
- Qiu, Peng
- Venue
- BMC Microbiology
- Published
- 2019-10-28
- Volume
- 19
- Issue
- 1
- Pages
- 236-236
- ISSN
- 1471-2180 (ISSN-L)
- PMC
- PMC6819604
- OpenAlex
- W2982520321
- Cited by
- 258
- References
- 67
- Citations by year
- 2026: 21 · 2025: 26 · 2024: 52 · 2023: 39 · 2022: 50 · 2021: 43 · 2020: 27
- FWCI
- 9.92
- Type
- journal article
- Language
- en
- Update notices
- correction (2021-04-28)
- Open access
- gold
- doi.org
- Locations
- BMC Microbiology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Science Foundation (1552784)
- Georgia Institute of Technology
- China Scholarship Council
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Health Sciences › Dentistry › Periodontics › Oral microbiology and periodontitis research
- Life Sciences › Agricultural and Biological Sciences › Food Science › Probiotics and Fermented Foods
- Keywords
- gut microbiota, aging, age-related microbial changes, 16S rRNA gene sequencing, unsupervised clustering, microbial genera, probiotics, centenarians, inflammation, tumor-associated bacteria
- MeSH terms
- Gastrointestinal Microbiome, Unsupervised Machine Learning, Adolescent, Adult, Age Factors, Aged, Aged, 80 and over, Aging, Bacteria, Child, Child, Preschool, DNA, Bacterial, DNA, Ribosomal, Female, Humans, Infant, Infant, Newborn, Male, Middle Aged, Phylogeny, RNA, Ribosomal, 16S, Sequence Analysis, DNA, Young Adult
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