Comprehensive analysis of IgA nephropathy expression profiles: identification of potential biomarkers and therapeutic agents.
BACKGROUND
IgA nephropathy (IgAN) is a kidney disease recognized by the presence of IgA antibody depositions in kidneys. The underlying mechanisms of this complicated disease are remained to be explored and still, there is an urgent need for the discovery of noninvasive biomarkers for its diagnosis. In this investigation, an integrative approach was applied to mRNA and miRNA expression profiles in PBMCs to discover a gene signature and novel potential targets/biomarkers in IgAN.


METHODS
Datasets were selected from gene expression omnibus database. After quality control checking, two datasets were analyzed by Limma to identify differentially expressed genes/miRNAs (DEGs and DEmiRs). Following identification of DEmiR-target genes and data integration, intersecting mRNAs were subjected to different bioinformatic analyses. The intersecting mRNAs, DEmiRs, related transcription factors (from TRRUST database), and long-non coding RNAs (from LncTarD database) were used for the construction of a multilayer regulatory network via Cytoscape.


RESULT
"GSE25590" (miRNA) and "GSE73953" (mRNA) datasets were analyzed and after integration, 628 intersecting mRNAs were identified. The mRNAs were mainly associated with "Innate immune system", "Apoptosis", as well as "NGF signaling" pathways. A multilayer regulatory network was constructed and several hub-DEGs (Tp53, STAT3, Jun, etc.), DEmiRs (miR-124, let-7b, etc.), TFs (NF-kB, etc.), and lncRNAs (HOTAIR, etc.) were introduced as potential factors in the pathogenesis of IgAN.


CONCLUSION
Integration of two different expression datasets and construction of a multilayer regulatory network not only provided a deeper insight into the pathogenesis of IgAN, but also introduced several key molecules as potential therapeutic target/non-invasive biomarkers.
['Gholaminejad|Alieh|A|', 'Gheisari|Yousof|Y|', 'Jalali|Sedigheh|S|', 'Roointan|Amir|A|']
IgA nephropathy Biomarkers Gene expression Computational biology Gene regulatory network