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dc.contributor.authorYuan, Xiuxia
dc.contributor.authorWang, Yunpeng
dc.contributor.authorLi, Xue
dc.contributor.authorJiang, Jiajun
dc.contributor.authorKang, Yulin
dc.contributor.authorPang, Lijuan
dc.contributor.authorZhang, Peifen
dc.contributor.authorLi, Ang
dc.contributor.authorLv, Luxian
dc.contributor.authorAndreassen, Ole A.
dc.contributor.authorFan, Xiaoduo
dc.contributor.authorHu, Shaohua
dc.contributor.authorSong, Xueqin
dc.date2022-08-11T08:10:01.000
dc.date.accessioned2022-08-23T16:52:44Z
dc.date.available2022-08-23T16:52:44Z
dc.date.issued2021-08-10
dc.date.submitted2022-03-24
dc.identifier.citation<p>Yuan X, Wang Y, Li X, Jiang J, Kang Y, Pang L, Zhang P, Li A, Lv L, Andreassen OA, Fan X, Hu S, Song X. Gut microbial biomarkers for the treatment response in first-episode, drug-naïve schizophrenia: a 24-week follow-up study. Transl Psychiatry. 2021 Aug 10;11(1):422. doi: 10.1038/s41398-021-01531-3. PMID: 34376634; PMCID: PMC8355081. <a href="https://doi.org/10.1038/s41398-021-01531-3">Link to article on publisher's site</a></p>
dc.identifier.issn2158-3188 (Linking)
dc.identifier.doi10.1038/s41398-021-01531-3
dc.identifier.pmid34376634
dc.identifier.urihttp://hdl.handle.net/20.500.14038/42113
dc.description.abstractPreclinical studies have shown that the gut microbiota can play a role in schizophrenia (SCH) pathogenesis via the gut-brain axis. However, its role in the antipsychotic treatment response is unclear. Here, we present a 24-week follow-up study to identify gut microbial biomarkers for SCH diagnosis and treatment response, using a sample of 107 first-episode, drug-naive SCH patients, and 107 healthy controls (HCs). We collected biological samples at baseline (all participants) and follow-up time points after risperidone treatment (SCH patients). Treatment response was assessed using the Positive and Negative Symptoms Scale total (PANSS-T) score. False discovery rate was used to correct for multiple testing. We found that SCH patients showed lower alpha-diversity (the Shannon and Simpson's indices) compared to HCs at baseline (p = 1.21 x 10(-9), 1.23 x 10(-8), respectively). We also found a significant difference in beta-diversity between SCH patients and HCs (p = 0.001). At baseline, using microbes that showed different abundance between patients and controls as predictors, a prediction model can distinguish patients from HCs with an area under the curve (AUC) of 0.867. In SCH patients, after 24 weeks of risperidone treatment, we observed an increase of alpha-diversity toward the basal level of HCs. At the genus level, we observed decreased abundance of Lachnoclostridium (p = 0.019) and increased abundance Romboutsia (p = 0.067). Moreover, the treatment response in SCH patients was significantly associated with the basal levels of Lachnoclostridium and Romboutsia (p = 0.005 and 0.006, respectively). Our results suggest that SCH patients may present characteristic microbiota, and certain microbiota biomarkers may predict treatment response in this patient population.
dc.language.isoen_US
dc.relation<p><a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&list_uids=34376634&dopt=Abstract">Link to Article in PubMed</a></p>
dc.rightsCopyright © The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectSchizophrenia
dc.subjectHuman behaviour
dc.subjectBiological Factors
dc.subjectPsychiatry
dc.subjectPsychiatry and Psychology
dc.subjectTranslational Medical Research
dc.titleGut microbial biomarkers for the treatment response in first-episode, drug-naive schizophrenia: a 24-week follow-up study
dc.typeJournal Article
dc.source.journaltitleTranslational psychiatry
dc.source.volume11
dc.source.issue1
dc.identifier.legacyfulltexthttps://escholarship.umassmed.edu/cgi/viewcontent.cgi?article=5949&amp;context=oapubs&amp;unstamped=1
dc.identifier.legacycoverpagehttps://escholarship.umassmed.edu/oapubs/4915
dc.identifier.contextkey28414062
refterms.dateFOA2022-08-23T16:52:44Z
html.description.abstract<p>Preclinical studies have shown that the gut microbiota can play a role in schizophrenia (SCH) pathogenesis via the gut-brain axis. However, its role in the antipsychotic treatment response is unclear. Here, we present a 24-week follow-up study to identify gut microbial biomarkers for SCH diagnosis and treatment response, using a sample of 107 first-episode, drug-naive SCH patients, and 107 healthy controls (HCs). We collected biological samples at baseline (all participants) and follow-up time points after risperidone treatment (SCH patients). Treatment response was assessed using the Positive and Negative Symptoms Scale total (PANSS-T) score. False discovery rate was used to correct for multiple testing. We found that SCH patients showed lower alpha-diversity (the Shannon and Simpson's indices) compared to HCs at baseline (p = 1.21 x 10(-9), 1.23 x 10(-8), respectively). We also found a significant difference in beta-diversity between SCH patients and HCs (p = 0.001). At baseline, using microbes that showed different abundance between patients and controls as predictors, a prediction model can distinguish patients from HCs with an area under the curve (AUC) of 0.867. In SCH patients, after 24 weeks of risperidone treatment, we observed an increase of alpha-diversity toward the basal level of HCs. At the genus level, we observed decreased abundance of Lachnoclostridium (p = 0.019) and increased abundance Romboutsia (p = 0.067). Moreover, the treatment response in SCH patients was significantly associated with the basal levels of Lachnoclostridium and Romboutsia (p = 0.005 and 0.006, respectively). Our results suggest that SCH patients may present characteristic microbiota, and certain microbiota biomarkers may predict treatment response in this patient population.</p>
dc.identifier.submissionpathoapubs/4915
dc.contributor.departmentPsychotic Disorders Program, Department of Psychiatry
dc.source.pages422


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Copyright © The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
Except where otherwise noted, this item's license is described as Copyright © The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.