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Gene co-expression networks are associated with obesity-related traits in kidney transplant recipients

Authors :
Rosario B. Jaime-Lara
Abhrarup Roy
Yupeng Wang
Ansley Stanfill
Ann K. Cashion
Paule V. Joseph
Source :
BMC Medical Genomics, Vol 13, Iss 1, Pp 1-12 (2020)
Publication Year :
2020
Publisher :
BMC, 2020.

Abstract

Abstract Background Obesity is common among kidney transplant recipients; However biological mediators of obesity are not well understood in this population. Because subcutaneous adipose tissue can be easily obtained during kidney transplant surgery, it provides a unique avenue for studying the mechanisms of obesity for this group. Although differential gene expression patterns were previously profiled for kidney transplant patients, gene co-expression patterns can shed light on gene modules not yet explored on the coordinative behaviors of gene transcription in biological and disease processes from a systems perspective. Methods In this study, we collected 29 demographic and clinical variables and matching microarray expression data for 26 kidney transplant patients. We conducted Weighted Gene Correlation Network Analysis (WGCNA) for 5758 genes with the highest average expression levels and related gene co-expression to clinical traits. Results A total of 35 co-expression modules were detected, two of which showed associations with obesity-related traits, mainly at baseline. Gene Ontology (GO) enrichment was found for these two clinical trait-associated modules. One module consisting of 129 genes was enriched for a variety of processes, including cellular homeostasis and immune responses. The other module consisting of 36 genes was enriched for tissue development processes. Conclusions Our study generated gene co-expression modules associated with obesity-related traits in kidney transplant patients and provided new insights regarding the cellular biological processes underlying obesity in this population.

Details

Language :
English
ISSN :
17558794
Volume :
13
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BMC Medical Genomics
Publication Type :
Academic Journal
Accession number :
edsdoj.37dee2472e1f4f92a932f424cb26e1b4
Document Type :
article
Full Text :
https://doi.org/10.1186/s12920-020-0702-5