The molecular phenotype of endocapillary proliferation: novel therapeutic targets for IgA nephropathy

Abstract

IgA nephropathy (IgAN) is a clinically and pathologically heterogeneous disease. Endocapillary proliferation is associated with higher risk of progressive disease, and clinical studies suggest that corticosteroids mitigate this risk. However, corticosteroids are associated with protean cellular effects and significant toxicity. Furthermore the precise mechanism by which they modulate kidney injury in IgAN is not well delineated. To better understand molecular pathways involved in the development of endocapillary proliferation and to identify novel specific therapeutic targets, we evaluated the glomerular transcriptome of microdissected kidney biopsies from 22 patients with IgAN. Endocapillary proliferation was defined according to the Oxford scoring system independently by 3 nephropathologists. We analyzed mRNA expression using microarrays and identified transcripts differentially expressed in patients with endocapillary proliferation compared to IgAN without endocapillary lesions. Next, we employed both transcription factor analysis and in silico drug screening and confirmed that the endocapillary proliferation transcriptome is significantly enriched with pathways that can be impacted by corticosteroids. With this approach we also identified novel therapeutic targets and bioactive small molecules that may be considered for therapeutic trials for the treatment of IgAN, including resveratrol and hydroquinine. In summary, we have defined the distinct molecular profile of a pathologic phenotype associated with progressive renal insufficiency in IgAN. Exploration of the pathways associated with endocapillary proliferation confirms a molecular basis for the clinical effectiveness of corticosteroids in this subgroup of IgAN, and elucidates new therapeutic strategies for IgAN.

Figure 1. Literature-based analysis from the 424 genes regulated in E1 vs. E0 biopsies using Genomatix Pathway System (GePS) software.

The picture shows the 248 genes that were co-cited in PubMed abstracts in the same sentence with a function-word filter.