T1D-DN KPMP Urban Rural (T1D-DN KUR) Recruitment Site
INSTITUTION
Mayo Clinic Rochester, MN
PRINCIPAL INVESTIGATOR
Kudva, Yogish C.
FUNDING
$791K
YEAR
2025
MOONBASE SCORE
Still being scored
LOADING MOONBASE SCORE
Abstract
PROJECT SUMMARY/ABSTRACT This application, submitted by a multi-disciplinary research team, responds to RFA-DK-25-022: Precision Medicine for Type 1 Diabetic Nephropathy (U01 Clinical Trial Not Allowed). The goal of the RFA is to expand the Kidney Precision Medicine Project (KPMP) by adding new research sites to recruit individuals with Type 1 Diabetes (T1D) at various stages of or high risk for Diabetic Nephropathy (DN) for a longitudinal study involving research kidney biopsies at enrollment. Our institution is well-positioned to enroll a diverse T1D population, supported by robust electronic databases for participant recruitment and phenotype determination. We have extensive experience with clinical trials in the T1D population, enhancing our ability to recruit and retain participants. Resources include a T1D registry and the Expanded Rochester Epidemiology Project (E-REP), covering 27 counties in Minnesota and Wisconsin, linking medical records for over 60 years. This includes populations from rural regions with lower socioeconomic status, often underrepresented in clinical research We have integrated the HOUsing-based SocioEconomic Status (HOUSES) index and Rural-Urban Commuting Area (RUCA) classifications into a Technology-Enabled Subject Recruitment System (TESRS) to enhance recruitment efficiency from rural and under-resourced populations. In addition, we have access to Institutional cohorts performing genetic testing with archived samples and laboratory measurements including renal function. Support from ethicists experienced in biorepository consent and genomic research result return, along with patient advocacy partnerships, will help implement KPMP protocols for kidney tissue biopsy procurement. The development of surrogate markers for early and progressive kidney injury, including novel image-based biomarkers and cardiovascular (CV) events proposed by us aims to clarify disease pathways and identify high- risk T1D patients for DN and CV morbidity and mortality. Results of this project may facilitate drug discovery and has potential to improve outcomes of people with T1D DN.
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