Gut Microbiota Dysbiosis Associated with Persistent Fatigue in Hematopoietic Cell Transplantation Survivors.


Journal

Transplantation and cellular therapy
ISSN: 2666-6367
Titre abrégé: Transplant Cell Ther
Pays: United States
ID NLM: 101774629

Informations de publication

Date de publication:
06 2021
Historique:
received: 05 01 2021
revised: 15 02 2021
accepted: 21 02 2021
pubmed: 30 3 2021
medline: 3 7 2021
entrez: 29 3 2021
Statut: ppublish

Résumé

Fatigue is one of the most prevalent and distressing complications among hematopoietic stem cell transplantation (HCT) survivors, negatively affecting physical, social, and emotional domains of quality of life. Chronic systemic inflammation has been linked to alterations in nervous system activity and initiation of distressing symptoms, such as fatigue. Damage to gut mucosa due to alteration in gut microbiota (GM) composition and microbial translocation has been shown to increase systemic proinflammatory cytokines. The aim of this study was to evaluate the relationship between fatigue and GM by measuring the differences in GM composition in HCT survivors with and without persistent fatigue. This cross-sectional study included 30 adults who underwent HCT for a hematologic disease and were at least 1 year post-HCT. Patients with chronic graft-versus-host disease were excluded. Fatigue severity was assessed by the Brief Fatigue Inventory (BFI). Based on the BFI score, patients were grouped into 2 categories: 0 to 3 (without fatigue) and ≥4 (with fatigue). The V1 to V3 region of the 16S rRNA gene from fecal specimens was sequenced using the Illumina MiSeq. Sequencing reads were processed, denoised, and replicated, chimeras were filtered, amplicon sequence variants (ASVs) were generated, and taxonomy was assigned using DADA2. Beta diversity analysis through principal coordinate analysis was generated using the Bray-Curtis dissimilarity matrix, and the difference was tested using linear model with generalized least squares in R. An alpha diversity analysis was performed using Chao1. Linear discriminant analysis effect size (LEfSe) was used to find markers that differ between the 2 groups. Based on the BFI results, patients were categorized into 2 cohorts: with fatigue (n = 14) and without fatigue (n = 16). The 2 cohorts were similar in terms of demographics, disease, and transplant characteristics. Based on the GM analysis, there was a significant difference in GM composition (beta diversity) between the 2 cohorts (P = .001). Alpha diversity (richness) was also significantly lower in survivors with fatigue (P =.002). LEfSe analysis identified 46 discriminative features (P < .05; linear discriminant analysis score >2) whose relative abundance varied significantly among individuals with fatigue and those without fatigue. Ten ASVs were associated with the patients with fatigue, and 36 ASVs were associated with those without fatigue. Several ASVs enriched in survivors with fatigue included organisms such as Klebsiella and Enterococcus, which have been implicated in inflammatory bowel diseases. The ASVs enriched in the cohort without fatigue were members of the Ruminococcaceae family (Oscillospira spp) and the Lachnospiraceae family (Fusicatenibacter and Coprococcus spp), which are known to have the ability to ferment complex plant carbohydrates. These findings show an association between GM composition and fatigue and suggest a microbial contribution to clinically significant fatigue post-HCT, which may guide the development of new approaches to treating fatigue based on manipulation of the GM.

Identifiants

pubmed: 33775619
pii: S2666-6367(21)00704-1
doi: 10.1016/j.jtct.2021.02.017
pii:
doi:

Substances chimiques

RNA, Ribosomal, 16S 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

498.e1-498.e8

Informations de copyright

Published by Elsevier Inc.

Auteurs

Nosha Farhadfar (N)

Institute on Aging, University of Florida, Gainesville, Florida. Electronic address: nosha.farhadfar@medicine.ufl.edu.

Raad Z Gharaibeh (RZ)

Institute on Aging, University of Florida, Gainesville, Florida.

Wendy J Dahl (WJ)

Institute on Aging, University of Florida, Gainesville, Florida.

Lacey Mead (L)

Institute on Aging, University of Florida, Gainesville, Florida.

Karima M Alabasi (KM)

Institute of Food and Agricultural Sciences, Univeristy of Florida, Gainesville, 32608.

Rachel Newsome (R)

Institute on Aging, University of Florida, Gainesville, Florida.

Vivian IrizarryGatell (V)

Institute on Aging, University of Florida, Gainesville, Florida.

Michael T Weaver (MT)

Institute on Aging, University of Florida, Gainesville, Florida.

Zeina Al-Mansour (Z)

Institute on Aging, University of Florida, Gainesville, Florida.

Christian Jobin (C)

Institute on Aging, University of Florida, Gainesville, Florida.

Debra Lyon (D)

Institute on Aging, University of Florida, Gainesville, Florida.

John R Wingard (JR)

Institute on Aging, University of Florida, Gainesville, Florida.

Debra Lynch Kelly (DL)

Institute on Aging, University of Florida, Gainesville, Florida.

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Classifications MeSH