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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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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fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7873428</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3147706206</sourcerecordid><originalsourceid>FETCH-LOGICAL-b584t-bb4fa3bcbec170954f870002d00cc29ef09a4c02d440ff02fb3fe361f1f915bf3</originalsourceid><addsrcrecordid>eNqNkU1rFTEYhYMo9lr9Ay5kwI2bqW8-JpNxIZTiFxQKRdchyU3GXDNJTWYq99-bMvVquyhCICTvcw4nOQi9xHCCMeVvx2XexdASINBSgjHwR2iDGRf1JMRjtAHAfdv1bDhCz0rZAYAQA36KjijpKOfQbZC7VPGHj2MzeZOT9mmyzbXKXkVjGx_rckFNk5pT3jc6_bKh2fpiVbHvGtUElUfbhBRHPy9bH1Wogtlmk-Lso41zvSh1sn-OnjgVin1xux-jbx8_fD373J5ffPpydnre6k6wudWaOUW10dbgHoaOOdHX1GQLYAwZrINBMVPPjIFzQJymzlKOHXYD7rSjx-j96nu16MluTY2QVZBX2U8q72VSXt6dRP9djula9qKnjIhq8ObWIKefiy2znHwxNgQVbVqKJAzTYRg47iv6-h66S0uuf1AkxazvgRPgD1GECc47LjiuFFmpWkIp2bpDZAzypmy5li1vypZr2VX06t_HHiR_2q1AuwJ62v2f4clf_hDzAcFvbsbGCw</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2486656861</pqid></control><display><type>article</type><title>Ranking microbiome variance in inflammatory bowel disease: a large longitudinal intercontinental study</title><source>MEDLINE</source><source>PubMed Central</source><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</creator><creatorcontrib>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</creatorcontrib><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><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 & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>STEM Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>BMJ Journals</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Science Database</collection><collection>Biological Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Gut</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Clooney, Adam G</au><au>Eckenberger, Julia</au><au>Laserna-Mendieta, Emilio</au><au>Sexton, Kathryn A</au><au>Bernstein, Matthew T</au><au>Vagianos, Kathy</au><au>Sargent, Michael</au><au>Ryan, Feargal J</au><au>Moran, Carthage</au><au>Sheehan, Donal</au><au>Sleator, Roy D</au><au>Targownik, Laura E</au><au>Bernstein, Charles N</au><au>Shanahan, Fergus</au><au>Claesson, Marcus J</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Ranking microbiome variance in inflammatory bowel disease: a large longitudinal intercontinental study</atitle><jtitle>Gut</jtitle><stitle>Gut</stitle><addtitle>Gut</addtitle><date>2021-03-01</date><risdate>2021</risdate><volume>70</volume><issue>3</issue><spage>499</spage><epage>510</epage><pages>499-510</pages><issn>0017-5749</issn><issn>1468-3288</issn><eissn>1468-3288</eissn><abstract>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.</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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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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