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Cross‐Sectional Study: New Approach for Diagnostic Identification of Non‐Robust Older Adult
Scope The aging biomarkers are alternatives and none of them can act as a strong predictor of frailty during the progression of aging. Several studies reveal the relationship between metabolites and frailty or gut microbiota and frailty. However, the connection between metabolites and gut microbiota...
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Published in: | Molecular nutrition & food research 2023-07, Vol.67 (13), p.e2300056-n/a |
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container_title | Molecular nutrition & food research |
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creator | Wen, Chiung‐Jung Koh, Yen‐Chun Tung, Yen‐Chen Ho, Pin‐Yu Hsieh, Shu‐Chen Lo, Yi‐Chen Tsai, Jaw‐Shiun Pan, Min‐Hsiung |
description | Scope
The aging biomarkers are alternatives and none of them can act as a strong predictor of frailty during the progression of aging. Several studies reveal the relationship between metabolites and frailty or gut microbiota and frailty. However, the connection between metabolites and gut microbiota in non‐robust older adults has not been discussed yet. The study aims to combine the findings of serum metabolites and gut microbiota in non‐robust subjects as a possible diagnostic biomarker.
Methods and results
Frailty‐related assessments are conducted to ensure the discrimination of non‐robustness. The serum and fecal are collected for serum metabolomics and gut microbiota analysis. Robust and non‐robust subjects show very different gut microbial compositions. Among the gut microbial differences, Escherichia/Shigella and its higher taxonomic ranks are found to have the most discriminative abundance among compared groups. More importantly, the abundance of Escherichia/Shigella is found to be positively correlated (p < 0.05) with the level of discriminant metabolites, such as serum oxoglutarate, glutamic acid, and 1‐methyladenosine.
Conclusion
These results indicate the obvious interrelation between gut microbiota and serum metabolites in non‐robust older adults. Besides, the findings suggest that Escherichia/Shigella can be a potential biomarker candidate for robustness sub‐phenotypic identification.
The abundance of Escherichia/Shigella is found to be positively correlated with the level of discriminant metabolites, such as serum oxoglutarate, glutamic acid, and 1‐methyladenosine. |
doi_str_mv | 10.1002/mnfr.202300056 |
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The aging biomarkers are alternatives and none of them can act as a strong predictor of frailty during the progression of aging. Several studies reveal the relationship between metabolites and frailty or gut microbiota and frailty. However, the connection between metabolites and gut microbiota in non‐robust older adults has not been discussed yet. The study aims to combine the findings of serum metabolites and gut microbiota in non‐robust subjects as a possible diagnostic biomarker.
Methods and results
Frailty‐related assessments are conducted to ensure the discrimination of non‐robustness. The serum and fecal are collected for serum metabolomics and gut microbiota analysis. Robust and non‐robust subjects show very different gut microbial compositions. Among the gut microbial differences, Escherichia/Shigella and its higher taxonomic ranks are found to have the most discriminative abundance among compared groups. More importantly, the abundance of Escherichia/Shigella is found to be positively correlated (p < 0.05) with the level of discriminant metabolites, such as serum oxoglutarate, glutamic acid, and 1‐methyladenosine.
Conclusion
These results indicate the obvious interrelation between gut microbiota and serum metabolites in non‐robust older adults. Besides, the findings suggest that Escherichia/Shigella can be a potential biomarker candidate for robustness sub‐phenotypic identification.
The abundance of Escherichia/Shigella is found to be positively correlated with the level of discriminant metabolites, such as serum oxoglutarate, glutamic acid, and 1‐methyladenosine.</description><identifier>ISSN: 1613-4125</identifier><identifier>EISSN: 1613-4133</identifier><identifier>DOI: 10.1002/mnfr.202300056</identifier><identifier>PMID: 37154673</identifier><language>eng</language><publisher>Germany: Wiley Subscription Services, Inc</publisher><subject>Abundance ; Adults ; Aged ; Aging ; Biomarkers ; Cross-Sectional Studies ; Diagnostic systems ; Escherichia ; Escherichia/Shigella ; Feces ; Frailty ; Gastrointestinal Microbiome ; Glutamic acid ; Humans ; Intestinal microflora ; Metabolites ; Metabolomics ; Microbiota ; Microorganisms ; Older people ; Proteobacteria ; RNA, Ribosomal, 16S ; Robustness ; serum metabolites ; Shigella</subject><ispartof>Molecular nutrition & food research, 2023-07, Vol.67 (13), p.e2300056-n/a</ispartof><rights>2023 Wiley‐VCH GmbH</rights><rights>2023 Wiley-VCH GmbH.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3683-74134ac9a09797c63a4ad17aa12d9ae6883b6c1640077214c68fd554968bb67c3</citedby><cites>FETCH-LOGICAL-c3683-74134ac9a09797c63a4ad17aa12d9ae6883b6c1640077214c68fd554968bb67c3</cites><orcidid>0000-0001-7683-873X ; 0000-0002-5188-7030</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37154673$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Wen, Chiung‐Jung</creatorcontrib><creatorcontrib>Koh, Yen‐Chun</creatorcontrib><creatorcontrib>Tung, Yen‐Chen</creatorcontrib><creatorcontrib>Ho, Pin‐Yu</creatorcontrib><creatorcontrib>Hsieh, Shu‐Chen</creatorcontrib><creatorcontrib>Lo, Yi‐Chen</creatorcontrib><creatorcontrib>Tsai, Jaw‐Shiun</creatorcontrib><creatorcontrib>Pan, Min‐Hsiung</creatorcontrib><title>Cross‐Sectional Study: New Approach for Diagnostic Identification of Non‐Robust Older Adult</title><title>Molecular nutrition & food research</title><addtitle>Mol Nutr Food Res</addtitle><description>Scope
The aging biomarkers are alternatives and none of them can act as a strong predictor of frailty during the progression of aging. Several studies reveal the relationship between metabolites and frailty or gut microbiota and frailty. However, the connection between metabolites and gut microbiota in non‐robust older adults has not been discussed yet. The study aims to combine the findings of serum metabolites and gut microbiota in non‐robust subjects as a possible diagnostic biomarker.
Methods and results
Frailty‐related assessments are conducted to ensure the discrimination of non‐robustness. The serum and fecal are collected for serum metabolomics and gut microbiota analysis. Robust and non‐robust subjects show very different gut microbial compositions. Among the gut microbial differences, Escherichia/Shigella and its higher taxonomic ranks are found to have the most discriminative abundance among compared groups. More importantly, the abundance of Escherichia/Shigella is found to be positively correlated (p < 0.05) with the level of discriminant metabolites, such as serum oxoglutarate, glutamic acid, and 1‐methyladenosine.
Conclusion
These results indicate the obvious interrelation between gut microbiota and serum metabolites in non‐robust older adults. Besides, the findings suggest that Escherichia/Shigella can be a potential biomarker candidate for robustness sub‐phenotypic identification.
The abundance of Escherichia/Shigella is found to be positively correlated with the level of discriminant metabolites, such as serum oxoglutarate, glutamic acid, and 1‐methyladenosine.</description><subject>Abundance</subject><subject>Adults</subject><subject>Aged</subject><subject>Aging</subject><subject>Biomarkers</subject><subject>Cross-Sectional Studies</subject><subject>Diagnostic systems</subject><subject>Escherichia</subject><subject>Escherichia/Shigella</subject><subject>Feces</subject><subject>Frailty</subject><subject>Gastrointestinal Microbiome</subject><subject>Glutamic acid</subject><subject>Humans</subject><subject>Intestinal microflora</subject><subject>Metabolites</subject><subject>Metabolomics</subject><subject>Microbiota</subject><subject>Microorganisms</subject><subject>Older people</subject><subject>Proteobacteria</subject><subject>RNA, Ribosomal, 16S</subject><subject>Robustness</subject><subject>serum metabolites</subject><subject>Shigella</subject><issn>1613-4125</issn><issn>1613-4133</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNqFkLtOwzAUhi0EgnJZGZElFpYW28exE7aqXCVopRZmy3EcSJXGxU6EuvEIPCNPQqKWDixM5wzf_-ucD6FTSgaUEHa5qHI_YIQBISQSO6hHBYU-pwC7251FB-gwhDkhQBmHfXQAkkZcSOghNfIuhO_Pr5k1deEqXeJZ3WSrKzy2H3i4XHqnzRvOncfXhX6tXKgLgx8yW9VFXhjdZbDL8dhVbcnUpU2o8aTMrMfDrCnrY7SX6zLYk808Qi-3N8-j-_7j5O5hNHzsGxAx9GV7Mdcm0SSRiTQCNNcZlVpTliXaijiGVBgqOCFSMsqNiPMsingi4jQV0sARulj3tge_NzbUalEEY8tSV9Y1QbGY0khECeEtev4HnbvGt593FDDBmATaUoM1ZTpB3uZq6YuF9itFierUq0692qpvA2eb2iZd2GyL_7puAb4GPorSrv6pU0_j2ynnEcAP6f6PfQ</recordid><startdate>202307</startdate><enddate>202307</enddate><creator>Wen, Chiung‐Jung</creator><creator>Koh, Yen‐Chun</creator><creator>Tung, Yen‐Chen</creator><creator>Ho, Pin‐Yu</creator><creator>Hsieh, Shu‐Chen</creator><creator>Lo, Yi‐Chen</creator><creator>Tsai, Jaw‐Shiun</creator><creator>Pan, Min‐Hsiung</creator><general>Wiley Subscription Services, Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>7QP</scope><scope>7T5</scope><scope>7T7</scope><scope>7TK</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>H94</scope><scope>P64</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-7683-873X</orcidid><orcidid>https://orcid.org/0000-0002-5188-7030</orcidid></search><sort><creationdate>202307</creationdate><title>Cross‐Sectional Study: New Approach for Diagnostic Identification of Non‐Robust Older Adult</title><author>Wen, Chiung‐Jung ; Koh, Yen‐Chun ; Tung, Yen‐Chen ; Ho, Pin‐Yu ; Hsieh, Shu‐Chen ; Lo, Yi‐Chen ; Tsai, Jaw‐Shiun ; Pan, Min‐Hsiung</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3683-74134ac9a09797c63a4ad17aa12d9ae6883b6c1640077214c68fd554968bb67c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Abundance</topic><topic>Adults</topic><topic>Aged</topic><topic>Aging</topic><topic>Biomarkers</topic><topic>Cross-Sectional Studies</topic><topic>Diagnostic systems</topic><topic>Escherichia</topic><topic>Escherichia/Shigella</topic><topic>Feces</topic><topic>Frailty</topic><topic>Gastrointestinal Microbiome</topic><topic>Glutamic acid</topic><topic>Humans</topic><topic>Intestinal microflora</topic><topic>Metabolites</topic><topic>Metabolomics</topic><topic>Microbiota</topic><topic>Microorganisms</topic><topic>Older people</topic><topic>Proteobacteria</topic><topic>RNA, Ribosomal, 16S</topic><topic>Robustness</topic><topic>serum metabolites</topic><topic>Shigella</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wen, Chiung‐Jung</creatorcontrib><creatorcontrib>Koh, Yen‐Chun</creatorcontrib><creatorcontrib>Tung, Yen‐Chen</creatorcontrib><creatorcontrib>Ho, Pin‐Yu</creatorcontrib><creatorcontrib>Hsieh, Shu‐Chen</creatorcontrib><creatorcontrib>Lo, Yi‐Chen</creatorcontrib><creatorcontrib>Tsai, Jaw‐Shiun</creatorcontrib><creatorcontrib>Pan, Min‐Hsiung</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Immunology Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Neurosciences Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Molecular nutrition & food research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wen, Chiung‐Jung</au><au>Koh, Yen‐Chun</au><au>Tung, Yen‐Chen</au><au>Ho, Pin‐Yu</au><au>Hsieh, Shu‐Chen</au><au>Lo, Yi‐Chen</au><au>Tsai, Jaw‐Shiun</au><au>Pan, Min‐Hsiung</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Cross‐Sectional Study: New Approach for Diagnostic Identification of Non‐Robust Older Adult</atitle><jtitle>Molecular nutrition & food research</jtitle><addtitle>Mol Nutr Food Res</addtitle><date>2023-07</date><risdate>2023</risdate><volume>67</volume><issue>13</issue><spage>e2300056</spage><epage>n/a</epage><pages>e2300056-n/a</pages><issn>1613-4125</issn><eissn>1613-4133</eissn><abstract>Scope
The aging biomarkers are alternatives and none of them can act as a strong predictor of frailty during the progression of aging. Several studies reveal the relationship between metabolites and frailty or gut microbiota and frailty. However, the connection between metabolites and gut microbiota in non‐robust older adults has not been discussed yet. The study aims to combine the findings of serum metabolites and gut microbiota in non‐robust subjects as a possible diagnostic biomarker.
Methods and results
Frailty‐related assessments are conducted to ensure the discrimination of non‐robustness. The serum and fecal are collected for serum metabolomics and gut microbiota analysis. Robust and non‐robust subjects show very different gut microbial compositions. Among the gut microbial differences, Escherichia/Shigella and its higher taxonomic ranks are found to have the most discriminative abundance among compared groups. More importantly, the abundance of Escherichia/Shigella is found to be positively correlated (p < 0.05) with the level of discriminant metabolites, such as serum oxoglutarate, glutamic acid, and 1‐methyladenosine.
Conclusion
These results indicate the obvious interrelation between gut microbiota and serum metabolites in non‐robust older adults. Besides, the findings suggest that Escherichia/Shigella can be a potential biomarker candidate for robustness sub‐phenotypic identification.
The abundance of Escherichia/Shigella is found to be positively correlated with the level of discriminant metabolites, such as serum oxoglutarate, glutamic acid, and 1‐methyladenosine.</abstract><cop>Germany</cop><pub>Wiley Subscription Services, Inc</pub><pmid>37154673</pmid><doi>10.1002/mnfr.202300056</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0001-7683-873X</orcidid><orcidid>https://orcid.org/0000-0002-5188-7030</orcidid></addata></record> |
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subjects | Abundance Adults Aged Aging Biomarkers Cross-Sectional Studies Diagnostic systems Escherichia Escherichia/Shigella Feces Frailty Gastrointestinal Microbiome Glutamic acid Humans Intestinal microflora Metabolites Metabolomics Microbiota Microorganisms Older people Proteobacteria RNA, Ribosomal, 16S Robustness serum metabolites Shigella |
title | Cross‐Sectional Study: New Approach for Diagnostic Identification of Non‐Robust Older Adult |
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