# Improving disease subtyping and physiological characterization of adult-onset diabetes in electronic health records

> **NIH NIH U01** · VANDERBILT UNIVERSITY MEDICAL CENTER · 2024 · $596,339

## Abstract

ABSTRACT
Diabetes is broadly classified as type 1 diabetes (T1D), with primary defect in insulin production due to
autoimmune destruction of beta cells, and type 2 diabetes (T2D), with primary defect in insulin sensitivity in
organs that regulate energy metabolism. There is an emerging conceptual change that diabetes is not
composed of discrete sets of syndromes but a spectrum of heterogenous phenotypes with complex
pathophysiology across different ethnic and racial populations. More than 90% of adult patients with diabetes
are classified as T2D with variable clinical risk factors, prognosis, and treatment response. There is an unmet
need to assess individual risk for developing diabetes, its complications, and drug response based on
underlying pathophysiology, which change over time. This proposal will embark on studies of large-scale
electronic health records (EHRs) with comprehensive phenome assessed during the course of diabetes, and
multi-omics integration, to address the following Specific Aims. AIM 1: Classification of diabetes subtypes using
clinical features in EHRs of diverse ancestries. AIM 2: Classification of diabetes subtypes in response to
treatments for diabetes and cardiometabolic diseases in EHRs of diverse ancestries. AIM 3: Multi-omics
characterization of diabetes subtypes in African Americans. Successful implementation of the proposal will
build a framework to identify subtypes of diabetes and their underlying physiological drivers to impact clinical
practice towards more precise diagnosis, prognosis, and effective intervention.

## Key facts

- **NIH application ID:** 10983694
- **Project number:** 1U01DK140952-01
- **Recipient organization:** VANDERBILT UNIVERSITY MEDICAL CENTER
- **Principal Investigator:** Eric R Gamazon
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $596,339
- **Award type:** 1
- **Project period:** 2024-09-01 → 2029-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10983694

## Citation

> US National Institutes of Health, RePORTER application 10983694, Improving disease subtyping and physiological characterization of adult-onset diabetes in electronic health records (1U01DK140952-01). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10983694. Licensed CC0.

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