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Pre-Transplant Prediction of Acute Graft-versus-Host Disease Using the Gut Microbiome
Gut microbiota is thought to influence host responses to allogeneic hematopoietic stem cell transplantation (aHSCT). Recent evidence points to this post-transplant for acute graft-versus-host disease (aGvHD). We asked whether any such association might be found pre-transplant and conducted a metagen...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9776596/ https://www.ncbi.nlm.nih.gov/pubmed/36552852 http://dx.doi.org/10.3390/cells11244089 |
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author | Zargari Marandi, Ramtin Jørgensen, Mette Ilett, Emma Elizabeth Nørgaard, Jens Christian Noguera-Julian, Marc Paredes, Roger Lundgren, Jens D. Sengeløv, Henrik MacPherson, Cameron Ross |
author_facet | Zargari Marandi, Ramtin Jørgensen, Mette Ilett, Emma Elizabeth Nørgaard, Jens Christian Noguera-Julian, Marc Paredes, Roger Lundgren, Jens D. Sengeløv, Henrik MacPherson, Cameron Ross |
author_sort | Zargari Marandi, Ramtin |
collection | PubMed |
description | Gut microbiota is thought to influence host responses to allogeneic hematopoietic stem cell transplantation (aHSCT). Recent evidence points to this post-transplant for acute graft-versus-host disease (aGvHD). We asked whether any such association might be found pre-transplant and conducted a metagenome-wide association study (MWAS) to explore. Microbial abundance profiles were estimated using ensembles of Kaiju, Kraken2, and DeepMicrobes calls followed by dimensionality reduction. The area under the curve (AUC) was used to evaluate classification of the samples (aGvHD vs. none) using an elastic net to test the relevance of metagenomic data. Clinical data included the underlying disease (leukemia vs. other hematological malignancies), recipient age, and sex. Among 172 aHSCT patients of whom 42 developed aGVHD post transplantation, a total of 181 pre-transplant tool samples were analyzed. The top performing model predicting risk of aGVHD included a reduced species profile (AUC = 0.672). Beta diversity (37% in Jaccard’s Nestedness by mean fold change, p < 0.05) was lower in those developing aGvHD. Ten bacterial species including Prevotella and Eggerthella genera were consistently found to associate with aGvHD in indicator species analysis, as well as relief and impurity-based algorithms. The findings support the hypothesis on potential associations between gut microbiota and aGvHD based on a data-driven approach to MWAS. This highlights the need and relevance of routine stool collection for the discovery of novel biomarkers. |
format | Online Article Text |
id | pubmed-9776596 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-97765962022-12-23 Pre-Transplant Prediction of Acute Graft-versus-Host Disease Using the Gut Microbiome Zargari Marandi, Ramtin Jørgensen, Mette Ilett, Emma Elizabeth Nørgaard, Jens Christian Noguera-Julian, Marc Paredes, Roger Lundgren, Jens D. Sengeløv, Henrik MacPherson, Cameron Ross Cells Article Gut microbiota is thought to influence host responses to allogeneic hematopoietic stem cell transplantation (aHSCT). Recent evidence points to this post-transplant for acute graft-versus-host disease (aGvHD). We asked whether any such association might be found pre-transplant and conducted a metagenome-wide association study (MWAS) to explore. Microbial abundance profiles were estimated using ensembles of Kaiju, Kraken2, and DeepMicrobes calls followed by dimensionality reduction. The area under the curve (AUC) was used to evaluate classification of the samples (aGvHD vs. none) using an elastic net to test the relevance of metagenomic data. Clinical data included the underlying disease (leukemia vs. other hematological malignancies), recipient age, and sex. Among 172 aHSCT patients of whom 42 developed aGVHD post transplantation, a total of 181 pre-transplant tool samples were analyzed. The top performing model predicting risk of aGVHD included a reduced species profile (AUC = 0.672). Beta diversity (37% in Jaccard’s Nestedness by mean fold change, p < 0.05) was lower in those developing aGvHD. Ten bacterial species including Prevotella and Eggerthella genera were consistently found to associate with aGvHD in indicator species analysis, as well as relief and impurity-based algorithms. The findings support the hypothesis on potential associations between gut microbiota and aGvHD based on a data-driven approach to MWAS. This highlights the need and relevance of routine stool collection for the discovery of novel biomarkers. MDPI 2022-12-16 /pmc/articles/PMC9776596/ /pubmed/36552852 http://dx.doi.org/10.3390/cells11244089 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zargari Marandi, Ramtin Jørgensen, Mette Ilett, Emma Elizabeth Nørgaard, Jens Christian Noguera-Julian, Marc Paredes, Roger Lundgren, Jens D. Sengeløv, Henrik MacPherson, Cameron Ross Pre-Transplant Prediction of Acute Graft-versus-Host Disease Using the Gut Microbiome |
title | Pre-Transplant Prediction of Acute Graft-versus-Host Disease Using the Gut Microbiome |
title_full | Pre-Transplant Prediction of Acute Graft-versus-Host Disease Using the Gut Microbiome |
title_fullStr | Pre-Transplant Prediction of Acute Graft-versus-Host Disease Using the Gut Microbiome |
title_full_unstemmed | Pre-Transplant Prediction of Acute Graft-versus-Host Disease Using the Gut Microbiome |
title_short | Pre-Transplant Prediction of Acute Graft-versus-Host Disease Using the Gut Microbiome |
title_sort | pre-transplant prediction of acute graft-versus-host disease using the gut microbiome |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9776596/ https://www.ncbi.nlm.nih.gov/pubmed/36552852 http://dx.doi.org/10.3390/cells11244089 |
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