Ranking microbiome variance in inflammatory bowel disease: a large longitudinal intercontinental study

ObjectiveThe microbiome contributes to the pathogenesis of inflammatory bowel disease (IBD) but the relative contribution of different lifestyle and environmental factors to the compositional variability of the gut microbiota is unclear.DesignHere, we rank the size effect of disease activity, medica...

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Veröffentlicht in:Gut 2021-03, Vol.70 (3), p.499-510
Hauptverfasser: Clooney, Adam G, Eckenberger, Julia, Laserna-Mendieta, Emilio, Sexton, Kathryn A, Bernstein, Matthew T, Vagianos, Kathy, Sargent, Michael, Ryan, Feargal J, Moran, Carthage, Sheehan, Donal, Sleator, Roy D, Targownik, Laura E, Bernstein, Charles N, Shanahan, Fergus, Claesson, Marcus J
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container_end_page 510
container_issue 3
container_start_page 499
container_title Gut
container_volume 70
creator Clooney, Adam G
Eckenberger, Julia
Laserna-Mendieta, Emilio
Sexton, Kathryn A
Bernstein, Matthew T
Vagianos, Kathy
Sargent, Michael
Ryan, Feargal J
Moran, Carthage
Sheehan, Donal
Sleator, Roy D
Targownik, Laura E
Bernstein, Charles N
Shanahan, Fergus
Claesson, Marcus J
description ObjectiveThe microbiome contributes to the pathogenesis of inflammatory bowel disease (IBD) but the relative contribution of different lifestyle and environmental factors to the compositional variability of the gut microbiota is unclear.DesignHere, we rank the size effect of disease activity, medications, diet and geographic location of the faecal microbiota composition (16S rRNA gene sequencing) in patients with Crohn’s disease (CD; n=303), ulcerative colitis (UC; n = 228) and controls (n=161), followed longitudinally (at three time points with 16 weeks intervals).ResultsReduced microbiota diversity but increased variability was confirmed in CD and UC compared with controls. Significant compositional differences between diseases, particularly CD, and controls were evident. Longitudinal analyses revealed reduced temporal microbiota stability in IBD, particularly in patients with changes in disease activity. Machine learning separated disease from controls, and active from inactive disease, when consecutive time points were modelled. Geographic location accounted for most of the microbiota variance, second to the presence or absence of CD, followed by history of surgical resection, alcohol consumption and UC diagnosis, medications and diet with most (90.3%) of the compositional variance stochastic or unexplained.ConclusionThe popular concept of precision medicine and rational design of any therapeutic manipulation of the microbiota will have to contend not only with the heterogeneity of the host response, but also with widely differing lifestyles and with much variance still unaccounted for.
doi_str_mv 10.1136/gutjnl-2020-321106
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Significant compositional differences between diseases, particularly CD, and controls were evident. Longitudinal analyses revealed reduced temporal microbiota stability in IBD, particularly in patients with changes in disease activity. Machine learning separated disease from controls, and active from inactive disease, when consecutive time points were modelled. Geographic location accounted for most of the microbiota variance, second to the presence or absence of CD, followed by history of surgical resection, alcohol consumption and UC diagnosis, medications and diet with most (90.3%) of the compositional variance stochastic or unexplained.ConclusionThe popular concept of precision medicine and rational design of any therapeutic manipulation of the microbiota will have to contend not only with the heterogeneity of the host response, but also with widely differing lifestyles and with much variance still unaccounted for.</description><identifier>ISSN: 0017-5749</identifier><identifier>ISSN: 1468-3288</identifier><identifier>EISSN: 1468-3288</identifier><identifier>DOI: 10.1136/gutjnl-2020-321106</identifier><identifier>PMID: 32536605</identifier><language>eng</language><publisher>England: BMJ Publishing Group Ltd and British Society of Gastroenterology</publisher><subject>Canada ; colonic microflora ; Crohn's disease ; Deoxyribonucleic acid ; Diet ; DNA ; Environmental factors ; Ethnicity ; Female ; Food ; Gastrointestinal Microbiome ; Genomics ; Geography ; Humans ; Inflammatory Bowel Disease ; Inflammatory bowel diseases ; Inflammatory Bowel Diseases - drug therapy ; Inflammatory Bowel Diseases - microbiology ; Intestinal microflora ; Intestine ; Ireland ; Laboratories ; Learning algorithms ; Life Style ; Longitudinal Studies ; Machine Learning ; Male ; Microbiomes ; Microbiota ; Middle Aged ; Precision medicine ; rRNA 16S ; Surveys and Questionnaires ; Ulcerative colitis</subject><ispartof>Gut, 2021-03, Vol.70 (3), p.499-510</ispartof><rights>Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.</rights><rights>Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.</rights><rights>2021 Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ . Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2020 Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/ This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ . Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-b584t-bb4fa3bcbec170954f870002d00cc29ef09a4c02d440ff02fb3fe361f1f915bf3</citedby><cites>FETCH-LOGICAL-b584t-bb4fa3bcbec170954f870002d00cc29ef09a4c02d440ff02fb3fe361f1f915bf3</cites><orcidid>0000-0001-8041-3574 ; 0000-0002-5712-0623</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7873428/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7873428/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32536605$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Clooney, Adam G</creatorcontrib><creatorcontrib>Eckenberger, Julia</creatorcontrib><creatorcontrib>Laserna-Mendieta, Emilio</creatorcontrib><creatorcontrib>Sexton, Kathryn A</creatorcontrib><creatorcontrib>Bernstein, Matthew T</creatorcontrib><creatorcontrib>Vagianos, Kathy</creatorcontrib><creatorcontrib>Sargent, Michael</creatorcontrib><creatorcontrib>Ryan, Feargal J</creatorcontrib><creatorcontrib>Moran, Carthage</creatorcontrib><creatorcontrib>Sheehan, Donal</creatorcontrib><creatorcontrib>Sleator, Roy D</creatorcontrib><creatorcontrib>Targownik, Laura E</creatorcontrib><creatorcontrib>Bernstein, Charles N</creatorcontrib><creatorcontrib>Shanahan, Fergus</creatorcontrib><creatorcontrib>Claesson, Marcus J</creatorcontrib><title>Ranking microbiome variance in inflammatory bowel disease: a large longitudinal intercontinental study</title><title>Gut</title><addtitle>Gut</addtitle><addtitle>Gut</addtitle><description>ObjectiveThe microbiome contributes to the pathogenesis of inflammatory bowel disease (IBD) but the relative contribution of different lifestyle and environmental factors to the compositional variability of the gut microbiota is unclear.DesignHere, we rank the size effect of disease activity, medications, diet and geographic location of the faecal microbiota composition (16S rRNA gene sequencing) in patients with Crohn’s disease (CD; n=303), ulcerative colitis (UC; n = 228) and controls (n=161), followed longitudinally (at three time points with 16 weeks intervals).ResultsReduced microbiota diversity but increased variability was confirmed in CD and UC compared with controls. Significant compositional differences between diseases, particularly CD, and controls were evident. Longitudinal analyses revealed reduced temporal microbiota stability in IBD, particularly in patients with changes in disease activity. Machine learning separated disease from controls, and active from inactive disease, when consecutive time points were modelled. Geographic location accounted for most of the microbiota variance, second to the presence or absence of CD, followed by history of surgical resection, alcohol consumption and UC diagnosis, medications and diet with most (90.3%) of the compositional variance stochastic or unexplained.ConclusionThe popular concept of precision medicine and rational design of any therapeutic manipulation of the microbiota will have to contend not only with the heterogeneity of the host response, but also with widely differing lifestyles and with much variance still unaccounted for.</description><subject>Canada</subject><subject>colonic microflora</subject><subject>Crohn's disease</subject><subject>Deoxyribonucleic acid</subject><subject>Diet</subject><subject>DNA</subject><subject>Environmental factors</subject><subject>Ethnicity</subject><subject>Female</subject><subject>Food</subject><subject>Gastrointestinal Microbiome</subject><subject>Genomics</subject><subject>Geography</subject><subject>Humans</subject><subject>Inflammatory Bowel Disease</subject><subject>Inflammatory bowel diseases</subject><subject>Inflammatory Bowel Diseases - drug therapy</subject><subject>Inflammatory Bowel Diseases - microbiology</subject><subject>Intestinal microflora</subject><subject>Intestine</subject><subject>Ireland</subject><subject>Laboratories</subject><subject>Learning algorithms</subject><subject>Life Style</subject><subject>Longitudinal Studies</subject><subject>Machine Learning</subject><subject>Male</subject><subject>Microbiomes</subject><subject>Microbiota</subject><subject>Middle Aged</subject><subject>Precision medicine</subject><subject>rRNA 16S</subject><subject>Surveys and Questionnaires</subject><subject>Ulcerative colitis</subject><issn>0017-5749</issn><issn>1468-3288</issn><issn>1468-3288</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>9YT</sourceid><sourceid>ACMMV</sourceid><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNqNkU1rFTEYhYMo9lr9Ay5kwI2bqW8-JpNxIZTiFxQKRdchyU3GXDNJTWYq99-bMvVquyhCICTvcw4nOQi9xHCCMeVvx2XexdASINBSgjHwR2iDGRf1JMRjtAHAfdv1bDhCz0rZAYAQA36KjijpKOfQbZC7VPGHj2MzeZOT9mmyzbXKXkVjGx_rckFNk5pT3jc6_bKh2fpiVbHvGtUElUfbhBRHPy9bH1Wogtlmk-Lso41zvSh1sn-OnjgVin1xux-jbx8_fD373J5ffPpydnre6k6wudWaOUW10dbgHoaOOdHX1GQLYAwZrINBMVPPjIFzQJymzlKOHXYD7rSjx-j96nu16MluTY2QVZBX2U8q72VSXt6dRP9djula9qKnjIhq8ObWIKefiy2znHwxNgQVbVqKJAzTYRg47iv6-h66S0uuf1AkxazvgRPgD1GECc47LjiuFFmpWkIp2bpDZAzypmy5li1vypZr2VX06t_HHiR_2q1AuwJ62v2f4clf_hDzAcFvbsbGCw</recordid><startdate>20210301</startdate><enddate>20210301</enddate><creator>Clooney, Adam G</creator><creator>Eckenberger, Julia</creator><creator>Laserna-Mendieta, Emilio</creator><creator>Sexton, Kathryn A</creator><creator>Bernstein, Matthew T</creator><creator>Vagianos, Kathy</creator><creator>Sargent, Michael</creator><creator>Ryan, Feargal J</creator><creator>Moran, Carthage</creator><creator>Sheehan, Donal</creator><creator>Sleator, Roy D</creator><creator>Targownik, Laura E</creator><creator>Bernstein, Charles N</creator><creator>Shanahan, Fergus</creator><creator>Claesson, Marcus J</creator><general>BMJ Publishing Group Ltd and British Society of Gastroenterology</general><general>BMJ Publishing Group LTD</general><general>BMJ Publishing Group</general><scope>9YT</scope><scope>ACMMV</scope><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>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88I</scope><scope>8AF</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BTHHO</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2P</scope><scope>M7P</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-8041-3574</orcidid><orcidid>https://orcid.org/0000-0002-5712-0623</orcidid></search><sort><creationdate>20210301</creationdate><title>Ranking microbiome variance in inflammatory bowel disease: a large longitudinal intercontinental study</title><author>Clooney, Adam G ; Eckenberger, Julia ; Laserna-Mendieta, Emilio ; Sexton, Kathryn A ; Bernstein, Matthew T ; Vagianos, Kathy ; Sargent, Michael ; Ryan, Feargal J ; Moran, Carthage ; Sheehan, Donal ; Sleator, Roy D ; Targownik, Laura E ; Bernstein, Charles N ; Shanahan, Fergus ; Claesson, Marcus J</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-b584t-bb4fa3bcbec170954f870002d00cc29ef09a4c02d440ff02fb3fe361f1f915bf3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Canada</topic><topic>colonic microflora</topic><topic>Crohn's disease</topic><topic>Deoxyribonucleic acid</topic><topic>Diet</topic><topic>DNA</topic><topic>Environmental factors</topic><topic>Ethnicity</topic><topic>Female</topic><topic>Food</topic><topic>Gastrointestinal Microbiome</topic><topic>Genomics</topic><topic>Geography</topic><topic>Humans</topic><topic>Inflammatory Bowel Disease</topic><topic>Inflammatory bowel diseases</topic><topic>Inflammatory Bowel Diseases - drug therapy</topic><topic>Inflammatory Bowel Diseases - microbiology</topic><topic>Intestinal microflora</topic><topic>Intestine</topic><topic>Ireland</topic><topic>Laboratories</topic><topic>Learning algorithms</topic><topic>Life Style</topic><topic>Longitudinal Studies</topic><topic>Machine Learning</topic><topic>Male</topic><topic>Microbiomes</topic><topic>Microbiota</topic><topic>Middle Aged</topic><topic>Precision medicine</topic><topic>rRNA 16S</topic><topic>Surveys and Questionnaires</topic><topic>Ulcerative colitis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Clooney, Adam G</creatorcontrib><creatorcontrib>Eckenberger, Julia</creatorcontrib><creatorcontrib>Laserna-Mendieta, Emilio</creatorcontrib><creatorcontrib>Sexton, Kathryn A</creatorcontrib><creatorcontrib>Bernstein, Matthew T</creatorcontrib><creatorcontrib>Vagianos, Kathy</creatorcontrib><creatorcontrib>Sargent, Michael</creatorcontrib><creatorcontrib>Ryan, Feargal J</creatorcontrib><creatorcontrib>Moran, Carthage</creatorcontrib><creatorcontrib>Sheehan, Donal</creatorcontrib><creatorcontrib>Sleator, Roy D</creatorcontrib><creatorcontrib>Targownik, Laura E</creatorcontrib><creatorcontrib>Bernstein, Charles N</creatorcontrib><creatorcontrib>Shanahan, Fergus</creatorcontrib><creatorcontrib>Claesson, Marcus J</creatorcontrib><collection>BMJ Open Access Journals</collection><collection>BMJ Journals:Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health &amp; 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n=303), ulcerative colitis (UC; n = 228) and controls (n=161), followed longitudinally (at three time points with 16 weeks intervals).ResultsReduced microbiota diversity but increased variability was confirmed in CD and UC compared with controls. Significant compositional differences between diseases, particularly CD, and controls were evident. Longitudinal analyses revealed reduced temporal microbiota stability in IBD, particularly in patients with changes in disease activity. Machine learning separated disease from controls, and active from inactive disease, when consecutive time points were modelled. Geographic location accounted for most of the microbiota variance, second to the presence or absence of CD, followed by history of surgical resection, alcohol consumption and UC diagnosis, medications and diet with most (90.3%) of the compositional variance stochastic or unexplained.ConclusionThe popular concept of precision medicine and rational design of any therapeutic manipulation of the microbiota will have to contend not only with the heterogeneity of the host response, but also with widely differing lifestyles and with much variance still unaccounted for.</abstract><cop>England</cop><pub>BMJ Publishing Group Ltd and British Society of Gastroenterology</pub><pmid>32536605</pmid><doi>10.1136/gutjnl-2020-321106</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0001-8041-3574</orcidid><orcidid>https://orcid.org/0000-0002-5712-0623</orcidid><oa>free_for_read</oa></addata></record>
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source MEDLINE; PubMed Central
subjects Canada
colonic microflora
Crohn's disease
Deoxyribonucleic acid
Diet
DNA
Environmental factors
Ethnicity
Female
Food
Gastrointestinal Microbiome
Genomics
Geography
Humans
Inflammatory Bowel Disease
Inflammatory bowel diseases
Inflammatory Bowel Diseases - drug therapy
Inflammatory Bowel Diseases - microbiology
Intestinal microflora
Intestine
Ireland
Laboratories
Learning algorithms
Life Style
Longitudinal Studies
Machine Learning
Male
Microbiomes
Microbiota
Middle Aged
Precision medicine
rRNA 16S
Surveys and Questionnaires
Ulcerative colitis
title Ranking microbiome variance in inflammatory bowel disease: a large longitudinal intercontinental study
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