Simultaneous spatial mapping of RNA and protein targets in human kidney tissue
Shreeram Akilesh   (Seattle, WA)
Diabetic nephropathy (DN) is a major complication of diabetes with severe impacts on patient morbidity and mortality. Approximately 30-40% of patients with diabetes will develop DN, which preferentially affects the glomerulus, the proximal filtration unit of the kidney nephron. DN is characterized early on by mesangial expansion and basement membrane thickening with progression to nodular glomerulosclerosis at later stages. These histologic changes are closely correlated to proteinuria and progressive decline in renal function. In spite of intense effort, to date, there is no clinically available therapeutic strategy to arrest or reverse these pathologic changes of DN. The failure of clinical translation of basic research findings is likely due to an imperfect understanding of pathogenic mechanisms, differences in human and animal model disease processes and an incomplete perspective of potential biomarkers. In particular, the levels of RNA and protein biomarkers are often discrepant; this emphasizes the need for their simultaneous measurement for key disease targets in order to understand gene regulation and temporal dynamics. As single-cell technologies advance, it is becoming apparent that there is striking variability in gene expression patterns, which may be contributing to heterogeneity of patients affected by DN. The spatial basis for this heterogeneity in expression has not been explored to date. Therefore, to address these deficiencies, we seek to simultaneously localize and quantify the RNA and protein expression patterns of 10 key targets implicated in glomerular pathology of DN using human kidney tissues. We will leverage a powerful in situ RNA and protein detection methodology (SABER) recently developed by Dr. Beliveau and the kidney pathobiology expertise of Dr. Akilesh to accomplish this goal. The resulting tools, protocols and analysis routines will be shared with DiaComp investigators and will be generally applicable to other target organs affected by diabetes. When successful, this high-risk, high-reward project will open up new avenues of research in DN and empower other DiaComp investigators to utilize these methods in their model systems.
Data for this report has not yet been released.