Cargando…

Fungal dysbiosis predicts the diagnosis of pediatric Crohn’s disease

AIM: To investigate the accuracy of fungal dysbiosis in mucosa and stool for predicting the diagnosis of Crohn’s disease (CD). METHODS: Children were prospectively enrolled in two medical centers: one university hospital and one private gastroenterology clinic in the city of Riyadh, Kingdom of Saudi...

Descripción completa

Detalles Bibliográficos
Autores principales: El Mouzan, Mohammad I, Korolev, Kirill S, Al Mofarreh, Mohammad A, Menon, Rajita, Winter, Harland S, Al Sarkhy, Ahmad A, Dowd, Scot E, Al Barrag, Ahmad M, Assiri, Asaad A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Baishideng Publishing Group Inc 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6196340/
https://www.ncbi.nlm.nih.gov/pubmed/30356965
http://dx.doi.org/10.3748/wjg.v24.i39.4510
_version_ 1783364537808846848
author El Mouzan, Mohammad I
Korolev, Kirill S
Al Mofarreh, Mohammad A
Menon, Rajita
Winter, Harland S
Al Sarkhy, Ahmad A
Dowd, Scot E
Al Barrag, Ahmad M
Assiri, Asaad A
author_facet El Mouzan, Mohammad I
Korolev, Kirill S
Al Mofarreh, Mohammad A
Menon, Rajita
Winter, Harland S
Al Sarkhy, Ahmad A
Dowd, Scot E
Al Barrag, Ahmad M
Assiri, Asaad A
author_sort El Mouzan, Mohammad I
collection PubMed
description AIM: To investigate the accuracy of fungal dysbiosis in mucosa and stool for predicting the diagnosis of Crohn’s disease (CD). METHODS: Children were prospectively enrolled in two medical centers: one university hospital and one private gastroenterology clinic in the city of Riyadh, Kingdom of Saudi Arabia. The children with confirmed diagnosis of CD by standard guidelines were considered cases, and the others were considered non-inflammatory bowel disease controls. Mucosal and stool samples were sequenced utilizing Illumina MiSeq chemistry following the manufacturer’s protocols, and abundance and diversity of fungal taxa in mucosa and stool were analyzed. Sparse logistic regression was used to predict the diagnosis of CD. The accuracy of the classifier was tested by computing the receiver operating characteristic curves with 5-fold stratified cross-validation under 100 permutations of the training data partition and the mean area under the curve (AUC) was calculated. RESULTS: All the children were Saudi nationals. There were 15 children with CD and 20 controls. The mean age was 13.9 (range: 6.7-17.8) years for CD children and 13.9 (3.25-18.6) years for controls, and 10/15 (67%) of the CD and 13/20 (65%) of the control subjects were boys. CD locations at diagnosis were ileal (L1) in 4 and colonic (L3) in 11 children, while CD behavior was non-stricturing and non-penetrating (B1) in 12 and stricturing (B2) in 3 children. The mean AUC for the fungal dysbiosis classifier was significantly higher in stools (AUC = 0.85 ± 0.057) than in mucosa (AUC = 0.71 ± 0.067) (P < 0.001). Most fungal species were significantly more depleted in stools than mucosal samples, except for Saccharomyces cerevisiae and S. bayanus, which were significantly more abundant. Diversity was significantly more reduced in stools than in mucosa. CONCLUSION: We found high AUC of fungal dysbiosis in fecal samples of children with CD, suggesting high accuracy in predicting diagnosis of CD.
format Online
Article
Text
id pubmed-6196340
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher Baishideng Publishing Group Inc
record_format MEDLINE/PubMed
spelling pubmed-61963402018-10-23 Fungal dysbiosis predicts the diagnosis of pediatric Crohn’s disease El Mouzan, Mohammad I Korolev, Kirill S Al Mofarreh, Mohammad A Menon, Rajita Winter, Harland S Al Sarkhy, Ahmad A Dowd, Scot E Al Barrag, Ahmad M Assiri, Asaad A World J Gastroenterol Observational Study AIM: To investigate the accuracy of fungal dysbiosis in mucosa and stool for predicting the diagnosis of Crohn’s disease (CD). METHODS: Children were prospectively enrolled in two medical centers: one university hospital and one private gastroenterology clinic in the city of Riyadh, Kingdom of Saudi Arabia. The children with confirmed diagnosis of CD by standard guidelines were considered cases, and the others were considered non-inflammatory bowel disease controls. Mucosal and stool samples were sequenced utilizing Illumina MiSeq chemistry following the manufacturer’s protocols, and abundance and diversity of fungal taxa in mucosa and stool were analyzed. Sparse logistic regression was used to predict the diagnosis of CD. The accuracy of the classifier was tested by computing the receiver operating characteristic curves with 5-fold stratified cross-validation under 100 permutations of the training data partition and the mean area under the curve (AUC) was calculated. RESULTS: All the children were Saudi nationals. There were 15 children with CD and 20 controls. The mean age was 13.9 (range: 6.7-17.8) years for CD children and 13.9 (3.25-18.6) years for controls, and 10/15 (67%) of the CD and 13/20 (65%) of the control subjects were boys. CD locations at diagnosis were ileal (L1) in 4 and colonic (L3) in 11 children, while CD behavior was non-stricturing and non-penetrating (B1) in 12 and stricturing (B2) in 3 children. The mean AUC for the fungal dysbiosis classifier was significantly higher in stools (AUC = 0.85 ± 0.057) than in mucosa (AUC = 0.71 ± 0.067) (P < 0.001). Most fungal species were significantly more depleted in stools than mucosal samples, except for Saccharomyces cerevisiae and S. bayanus, which were significantly more abundant. Diversity was significantly more reduced in stools than in mucosa. CONCLUSION: We found high AUC of fungal dysbiosis in fecal samples of children with CD, suggesting high accuracy in predicting diagnosis of CD. Baishideng Publishing Group Inc 2018-10-21 2018-10-21 /pmc/articles/PMC6196340/ /pubmed/30356965 http://dx.doi.org/10.3748/wjg.v24.i39.4510 Text en ©The Author(s) 2018. Published by Baishideng Publishing Group Inc. All rights reserved. http://creativecommons.org/licenses/by-nc/4.0/ This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is 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 and the use is non-commercial.
spellingShingle Observational Study
El Mouzan, Mohammad I
Korolev, Kirill S
Al Mofarreh, Mohammad A
Menon, Rajita
Winter, Harland S
Al Sarkhy, Ahmad A
Dowd, Scot E
Al Barrag, Ahmad M
Assiri, Asaad A
Fungal dysbiosis predicts the diagnosis of pediatric Crohn’s disease
title Fungal dysbiosis predicts the diagnosis of pediatric Crohn’s disease
title_full Fungal dysbiosis predicts the diagnosis of pediatric Crohn’s disease
title_fullStr Fungal dysbiosis predicts the diagnosis of pediatric Crohn’s disease
title_full_unstemmed Fungal dysbiosis predicts the diagnosis of pediatric Crohn’s disease
title_short Fungal dysbiosis predicts the diagnosis of pediatric Crohn’s disease
title_sort fungal dysbiosis predicts the diagnosis of pediatric crohn’s disease
topic Observational Study
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6196340/
https://www.ncbi.nlm.nih.gov/pubmed/30356965
http://dx.doi.org/10.3748/wjg.v24.i39.4510
work_keys_str_mv AT elmouzanmohammadi fungaldysbiosispredictsthediagnosisofpediatriccrohnsdisease
AT korolevkirills fungaldysbiosispredictsthediagnosisofpediatriccrohnsdisease
AT almofarrehmohammada fungaldysbiosispredictsthediagnosisofpediatriccrohnsdisease
AT menonrajita fungaldysbiosispredictsthediagnosisofpediatriccrohnsdisease
AT winterharlands fungaldysbiosispredictsthediagnosisofpediatriccrohnsdisease
AT alsarkhyahmada fungaldysbiosispredictsthediagnosisofpediatriccrohnsdisease
AT dowdscote fungaldysbiosispredictsthediagnosisofpediatriccrohnsdisease
AT albarragahmadm fungaldysbiosispredictsthediagnosisofpediatriccrohnsdisease
AT assiriasaada fungaldysbiosispredictsthediagnosisofpediatriccrohnsdisease