Background: Graft-versus-host disease (GVHD) results from recognition of host antigens by donor T cells following allogeneic hematopoietic cell transplantation (AHCT). Notably, histoincompatibility between donor and recipient is necessary but not sufficient to elicit GVHD. Therefore, we tested the hypothesis that some donors may be "stronger alloresponders" than others, and consequently more likely to elicit GVHD.

Methods And Findings: To this end, we measured the gene-expression profiles of CD4(+) and CD8(+) T cells from 50 AHCT donors with microarrays. We report that pre-AHCT gene-expression profiling segregates donors whose recipient suffered from GVHD or not. Using quantitative PCR, established statistical tests, and analysis of multiple independent training-test datasets, we found that for chronic GVHD the "dangerous donor" trait (occurrence of GVHD in the recipient) is under polygenic control and is shaped by the activity of genes that regulate transforming growth factor-beta signaling and cell proliferation.

Conclusions: These findings strongly suggest that the donor gene-expression profile has a dominant influence on the occurrence of GVHD in the recipient. The ability to discriminate strong and weak alloresponders using gene-expression profiling could pave the way to personalized transplantation medicine.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1796639PMC
http://dx.doi.org/10.1371/journal.pmed.0040023DOI Listing

Publication Analysis

Top Keywords

gene-expression profiling
12
graft-versus-host disease
8
donor gene-expression
8
occurrence gvhd
8
gvhd recipient
8
gvhd
6
gene-expression
5
prediction graft-versus-host
4
disease humans
4
donor
4

Similar Publications

The plant Polygonum capitatum (P. capitatum) contains a variety of flavonoids that are distributed differently among different parts. Nevertheless, differentially expressed genes (DEGs) associated with this heterogeneous distribution have not been identified.

View Article and Find Full Text PDF

Objective: Juvenile dermatomyositis (JDM) is a complex autoimmune disease, and its pathogenesis remains poorly understood. Building upon previous research on the immunological and inflammatory aspects of JDM, this study aims to investigate the role of pyroptosis in the pathogenesis of JDM using a comprehensive bioinformatics approach.

Methods: Two microarray datasets (GSE3307 and GSE11971) were obtained from the Gene Expression Omnibus database, and a list of 62 pyroptosis-related genes was compiled.

View Article and Find Full Text PDF

Screening potential diagnostic biomarkers for PLA2R‑associated idiopathic membranous nephropathy by WGCNA analysis and LASSO algorithm.

Ren Fail

December 2025

Department of Nephrology, Xiamen Key Laboratory of Precision Diagnosis and Treatment of Chronic Kidney Disease, The Fifth Hospital of Xiamen, Xiamen, Fujian, China.

Adult nephrotic syndrome is primarily caused by membranous nephropathy (MN), with idiopathic membranous nephropathy (IMN) being a prominent subtype. The onset of phospholipase A2 receptor (PLA2R1)-associated IMN is critically linked to M-type PLA2R1 exposure, yet the mechanism underlying glomerular injury remains unclear. In this study, membranous nephropathy datasets (GSE115857, GSE200828) were retrieved from GEO.

View Article and Find Full Text PDF

Background: Spinal cord injury (SCI) triggers a complex inflammatory response that impedes neural repair and functional recovery. The modulation of macrophage phenotypes is thus considered a promising therapeutic strategy to mitigate inflammation and promote regeneration.

Methods: We employed microarray and single-cell RNA sequencing (scRNA-seq) to investigate gene expression changes and immune cell dynamics in mice following crush injury at 3 and 7 days post-injury (dpi).

View Article and Find Full Text PDF

Background: Human kinesin family member 11 (KIF11) plays a vital role in regulating the cell cycle and is implicated in the tumorigenesis and progression of various cancers, but its role in endometrial cancer (EC) is still unclear. Our current research explored the prognostic value, biological function and targeting strategy of KIF11 in EC through approaches including bioinformatics, machine learning and experimental studies.

Methods: The GSE17025 dataset from the GEO database was analyzed via the limma package to identify differentially expressed genes (DEGs) in EC.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!