Pinaki Sarder, PhD, is conducting research that could help determine if and when diabetes patients will develop diabetic nephropathy.

Research Could Lead to Faster Detection of Diabetic Nephropathy

Published February 12, 2018 This content is archived.

story by bill bruton

Pinaki Sarder, PhD, assistant professor of pathology and anatomical sciences, has received a grant from the National Institute of Diabetes and Digestive and Kidney DiseasesDiabetic Complications Consortium to study the computational imaging of renal structures for diagnosing diabetic nephropathy.

“If we can identify if and when a patient is going to have renal failure, then you could give more aggressive treatment. ”
Assistant professor of pathology and anatomical sciences
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DN Can Lead to Kidney Failure in Severe Cases

Diabetic nephropathy — also known as diabetic kidney disease — is a serious kidney-related complication for persons with type 1 and type 2 diabetes. In severe cases it can lead to kidney failure.

“Diabetes is a huge problem. By 2050 one in three Americans may have diabetes,” Sarder says.

Up to 40 percent of people with diabetes develop kidney disease.

Determining Which Patients Will Develop DN is Difficult

For persons with DN, their kidneys become so overworked they start getting damaged.

However, determining which diabetes patients will develop DN has proven elusive.

“The guiding standard doesn’t give a good way to diagnose when people will shift from diabetes to diabetic nephropathy,” Sarder says.

End-Stage Renal Disease Proves Costly

DN is a serious problem in the U.S. It causes end-stage renal disease (ESRD) for 225,000 U.S. patients — 50 percent of all ESRD cases — and accounts for $19,000 in Medicare costs yearly for each patient.

Measurement of minute urinary albumin is the most common non-invasive clinical biomarker of DN. However, traditional clinical biometrics typically only detect DN with high precision in the later stages of the disease.

Computer Aids in Determining Who Will Develop DN

Through computer modeling — combined with actual biopsies — Sarder and his team hope to develop ways to determine in early stages which patients will develop DN.

“If we can identify if and when a patient is going to have renal failure, then you could give more aggressive treatment,” says Sarder, principal investigator for the study.

Tomaszewski Collaborating on Research

John E. Tomaszewski, MD, the Peter A. Nickerson, PhD, Professor and Chair of the Department of Pathology and Anatomical Sciences, will mentor the team and provide human renal biopsies and clinical data. Tomaszewski, a SUNY Distinguished Professor, is an expert in renal pathology and pathology informatics.

Gregory E. Wilding, PhD, professor and chair of UB’s Department of Biostatistics, will work with Sarder on evaluating the statistical significance of the proposed work involving data from multiple institutes.

Other collaborators are:

  • Agnes B. Fogo, MD, Vanderbilt University
  • Sanjay Jain, MD, PhD, Washington University in St. Louis
  • John Michael Walsh, PhD, University of Illinois at Chicago