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Renal Disease Biomarkers

Center of Economic Excellence



Award Amount

$5 million

Extramural Research Funding

$7.1 Million

Research Focus

Identifying biomarkers that identify or predict prognosis for acute kidney injury, diabetic neuropathy, lupus nephritis, and focal segmental alomerulosclerosis.

University Partner

Medical University of South Carolina (MUSC)

Private Sector Partner

Multiple Industry Partners

The Renal Disease Biomarkers Center addresses the need for reliable and prognostic biomarkers, or biological indicators, for acute kidney injury and chronic kidney failure. Statewide medical practice-based networks are conducting proteomic analysis to identify candidate biomarkers of renal disease. Accurate and sensitive biomarkers are essential for early detection and therefore treatment of this disease.

This area of research is especially relevant in South Carolina. Diabetes is the leading cause of kidney failure, and South Carolina has a higher rate of diabetes than the U.S. average. According to the Centers for Disease Control and Prevention, more than nine percent of South Carolinians have diabetes, compared to seven percent nationally. Discoveries generated from this Center have the potential to reduce healthcare costs and bring revenue to the state through intellectual property development and commercialization of newly identified biomarkers for kidney disease.

Faculty associated with the Center continue to partner with the Southern Acute Kidney Injury Network (SAKInet) made up of four researchers from Duke University, George Washington University, the University of Tennessee system, and  MD Anderson Cancer Center (Texas) to facilitate biomarker discovery. Two other consortia have been formed: BioMaSC (Biomarker SC) is composed of nephrologists and primary care physicians across South Carolina, while MUSCRATS (MUSC Research and Translational Science) is composed of MUSC alumni practicing nephrologists.

Investigators have published a manuscript, which identifies a set of proteins in urine that can distinguish between two common acute kidney diseases, which are difficult to diagnose clinically. This discovery may lead to developing a crucial clinical test.

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