Evidence map›Paper›PMID 35692191›Full record

ArticleIntestinal research2023

Compositional changes in fecal microbiota associated with clinical phenotypes and prognosis in Korean patients with inflammatory bowel disease.

Seung Yong Shin, Young Kim, Won-Seok Kim, Jung Min Moon, Kang-Moon Lee, Sung-Ae Jung, Hyesook Park, Eun Young Huh, Byung Chang Kim, Soo Chan Lee and 2 more

Open access · diamondAbstract read
In one paragraph

Article in Intestinal research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
1.8field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 5 institutions in 2 countries.

Seung Yong ShinDepartment of Internal Medicine, Chung-Ang University College of Medicine, Seoul, Korea.
Young KimDepartment of Internal Medicine, Chung-Ang University College of Medicine, Seoul, Korea.
Won-Seok KimDepartment of Internal Medicine, Chung-Ang University College of Medicine, Seoul, Korea.
Jung Min MoonDepartment of Internal Medicine, Chung-Ang University College of Medicine, Seoul, Korea.
Kang-Moon LeeDepartment of Internal Medicine, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Suwon, Korea.
Sung-Ae JungDepartment of Internal Medicine, Graduate Program in System Health Science and Engineering, Ewha Womans University College of Medicine, Seoul, Korea.
Hyesook ParkDepartment of Preventive Medicine, Graduate Program in System Health Science and Engineering, Ewha Womans University College of Medicine, Seoul, Korea.
Eun Young HuhSouth Texas Center of Emerging Infectious Diseases (STCEID) and Department of Molecular Microbiology and Immunology, The University of Texas at San Antonio, San Antonio, TX, USA.
Byung Chang KimDivision of Gastroenterology, Center for Colorectal Cancer, Research Institute and Hospital, National Cancer Center, Goyang, Korea.
Soo Chan LeeSouth Texas Center of Emerging Infectious Diseases (STCEID) and Department of Molecular Microbiology and Immunology, The University of Texas at San Antonio, San Antonio, TX, USA.
Chang Hwan ChoiDepartment of Internal Medicine, Chung-Ang University College of Medicine, Seoul, Korea.
IBD Research Group of the Korean Association for the Study of Intestinal DiseasesDepartment of Internal Medicine, Chung-Ang University College of Medicine, Seoul, Korea.
Chung-Ang University · KREwha Womans University · KRTexas Center for Infectious Disease · USNational Cancer Center · KRThe Catholic University of Korea St. Vincent's Hospital · KR

Funding

CTSA/IIMS UT Health Pilot GrantKorean Association for the Study of Intestinal DiseasesMax and Minnie Tomerlin Voelcker FundNational Research Foundation of Korea 2020R1F1A1075489
6 · The paper itself

Abstract

BACKGROUND/

aimsThe fecal microbiota of Korean patients with inflammatory bowel disease (IBD) was investigated with respect to disease phenotypes and taxonomic biomarkers for diagnosis and prognosis of IBD.

methodsFecal samples from 70 ulcerative colitis (UC) patients, 39 Crohn's disease (CD) patients, and 100 healthy control individuals (HC) were collected. The fecal samples were amplified via polymerase chain reaction and sequenced using Illumina MiSeq. The relationships between fecal bacteria and clinical phenotypes were analyzed using the EzBioCloud database and 16S microbiome pipeline.

resultsThe alpha-diversity of fecal bacteria was significantly lower in UC and CD (P<0.05) compared to that in HC. Bacterial community compositions in UC and CD were significantly different from that of HC according to Bray-Curtis dissimilarities, and there was also a difference between community composition in UC and CD (P=0.01). In UC, alpha-diversity was further decreased when the disease was more severe and the extent of disease was greater, and community composition significantly differed depending on the extent of the disease. We identified 9 biomarkers of severity and 6 biomarkers of the extent of UC. We also identified 5 biomarkers of active disease and 3 biomarkers of ileocolonic involvement in CD. Lachnospiraceae and Ruminococcus gnavus were biomarkers for better prognosis in CD.

conclusionsThe fecal microbiota profiles of IBD patients were different from those of HC, and several bacterial taxa may be used as biomarkers to determine disease phenotypes and prognosis. These data may also help discover new therapeutic targets for IBD.

Indexed as

BiomarkersInflammatory bowel diseaseMicrobiotaPhenotypePrognosis

Identifiers

PMID35692191
PMCPMC9911276
OpenAlexW4282590820

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.