CD36 identified by weighted gene co-expression network analysis as a hub candidate gene in lupus nephritis

Abstract

Lupus nephritis (LN) is a severe manifestation of systemic lupus erythematosus (SLE), which often progresses to end-stage renal disease (ESRD) and ultimately leads to death. At present, there are no definitive therapies towards LN, so that illuminating the molecular mechanism behind the disease has become an urgent task for researchers. Bioinformatics has become a widely utilized method for exploring genes related to disease. This study set out to conduct weighted gene co-expression network analysis (WGCNA) and screen the hub gene of LN. We performed WGCNA on the microarray expression profile dataset of GSE104948 from the Gene Expression Omnibus (GEO) database with 18 normal and 21 LN samples of glomerulus. A total of 5,942 genes were divided into 5 co-expression modules, one of which was significantly correlated to LN. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted on the LN-related module, and the module was proved to be associated mainly with the activation of inflammation, immune response, cytokines, and immune cells. Genes in the most significant GO terms were extracted for sub-networks of WGNCA. We evaluated the centrality of genes in the sub-networks by Maximal Clique Centrality (MCC) method and CD36 was ultimately screened out as a hub candidate gene of the pathogenesis of LN. The result was verified by its differentially expressed level between normal and LN in GSE104948 and the other three multi-microarray datasets of GEO. Moreover, we further demonstrated that the expression level of CD36 is related to the WHO Lupus Nephritis Class of LN patients with the help of Nephroseq database. The current study proposed CD36 as a vital candidate gene in LN for the first time and CD36 may perform as a brand-new biomarker or therapeutic target of LN in the future.

Identification and Validation of IFI44 as Key Biomarker in Lupus Nephritis

“…They found that LN-related genes were mainly involved in immune and inflammatory responses, which are in agreement with what we found. Likewise, the GSE104948 dataset was analyzed by WGCNA, and CD36 was ultimately screened out as a hub gene of the pathogenesis of LN ( 45 ). However, neither of their findings have been validated in LN patients.…”

Crucial transcripts predict response to initial immunoglobulin treatment in acute Kawasaki disease

“…Modules that are highly relevant to clinical trait are further analyzed and crucial transcripts are identified. WGCNA has been proven to be useful in various types of diseases, such as cancer 11 , immune disease 12 , chronic disease 13 .…”

Identification of MEDAG as a Hub Candidate Gene in the Onset and Progression of Type 2 Diabetes Mellitus by Comprehensive Bioinformatics Analysis

“…Weighted gene coexpression network analysis (WGCNA) is a bioinformatics analysis tool based on the hypothesis that the biological expression pattern of genes obeys the characteristics of a scale-free network, and the central factors in the network would be more easily found out when the coexpression relationships are weighted [3]. The technique has been broadly used to explore new hub candidate genes, biomarkers, or therapeutic targets in various kinds of diseases including acute diseases, chronic diseases, infectious diseases, and tumors [4][5][6][7].…”