Temporal profile of the renal transcriptome of HIV-1 transgenic mice during disease progression.

Publication Type:

Journal Article


PLoS One, Volume 9, Issue 3, p.e93019 (2014)


Animals, asb, Disease Progression, Gene Expression Profiling, HIV-1, Kidney Cortex, Kidney Diseases, Mice, Mice, Transgenic, Reproducibility of Results, RNA, Messenger


Profiling of temporal changes of gene expression in the same kidney over the course of renal disease progression is challenging because repeat renal biopsies are rarely indicated in clinical practice. Here, we profiled the temporal change in renal transcriptome of HIV-1 transgenic mice (Tg26), an animal model for human HIV-associated nephropathy (HIVAN), and their littermates at three different time points (4, 8, and 12 weeks of age) representing early, middle, and late stages of renal disease by serial kidney biopsy. We analyzed both static levels of gene expression at three stages of disease and dynamic changes in gene expression between different stages. Analysis of static and dynamic changes in gene expression revealed that up-regulated genes at the early and middle stages are mostly involved in immune response and inflammation, whereas down-regulated genes mostly related to fatty acid and retinoid metabolisms. We validated the expression of a selected panel of genes that are up-regulated at the early stage (CCL2, CCL5, CXCL11, Ubd, Anxa1, and Spon1) by real-time PCR. Among these up-regulated genes, Spon1, which is a previously identified candidate gene for hypertension, was found to be up-regulated in kidney of human with diabetic nephropathy. Immunostaining of human biopsy samples demonstrated that protein expression of Spon1 was also markedly increased in kidneys of patients with both early and late HIVAN and diabetic nephropathy. Our studies suggest that analysis of both static and dynamic changes of gene expression profiles in disease progression avails another layer of information that could be utilized to gain a more comprehensive understanding of disease progression and identify potential biomarkers and drug targets.