# Credentialing metabolic disease genes through human genetics and functional genomics

> **NIH VA I01** · VA SAN DIEGO HEALTHCARE SYSTEM · 2024 · —

## Abstract

Insulin resistance is a major cause of type 2 diabetes (T2D), heart attacks, strokes and cancer. These chronic
metabolic diseases disproportionately affect veterans, especially black veterans. Targeting insulin resistance by
treating obesity is effective but the major clinical options, low calorie diets or bariatric surgery, are difficult to
sustain and scale for the over 40% of veterans afflicted with obesity. Thiazolidinediones (TZDs), specifically
target insulin resistance and have proven clinically effective in preventing T2D, heart attacks and strokes, but
serious side effects have limited their clinical use. New therapeutic targets to treat insulin resistance are
needed. In theory, ‘omics’ approaches such as genome wide association studies (GWAS) of surrogate
measures of insulin resistance or mining the transcriptomic response caused by weight loss/ TZD treatment
could provide a source of novel target genes, but both approaches have limitations including identifying
specific genes/mechanisms for GWAS and distinguishing correlation from causation in gene expression
studies. Importantly, existing GWAS studies contain predominantly European samples and thus bias against
genetic discovery in African ancestry individuals. Ultimately, the dozens to hundreds of genes nominated by
‘omics’ approaches must be sifted by functional investigation for biological mechanism and therapeutic
translation. Even when a potential insulin sensitizing effector gene is validated in the lab, credentialing its
relevance to human insulin sensitivity necessitates drug development and human trials, another poorly
scalable process that usually results in failure for lack of efficacy. However, the recent accumulation of genome
sequences in large, clinically characterized populations has revealed that nature has performed countless
human trials in the form of millions of naturally occurring, protein-altering genetic variants scattered throughout
almost every gene in the genome. High-throughput functional assays are the key to unlocking these
opportunities: 1) identifying novel candidate genes for insulin resistance and 2) leveraging nature’s clinical trials
for assessing therapeutic potential. In this application, we propose to utilize a newly developed massively
parallel adipocyte differentiation/ lipid accumulation assay in an integrative genomic approach to:
Aim 1: Systematically identify novel insulin resistance genes incorporating African ancestry specific genetic
discovery in the VA population and
Aim 2: Determine the clinical effect of novel insulin resistance genes on metabolic disease in humans using
data from 488,000 sequenced individuals.
This work will identify novel insulin sensitivity genes relevant to the VA population and include African
ancestry-specific genes. It will also provide critical information on the human, clinical consequence of
modulating function of selected genes to enable therapeutic translation.

## Key facts

- **NIH application ID:** 10797342
- **Project number:** 1I01BX006293-01A1
- **Recipient organization:** VA SAN DIEGO HEALTHCARE SYSTEM
- **Principal Investigator:** Amit Majithia
- **Activity code:** I01 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2024
- **Award amount:** —
- **Award type:** 1
- **Project period:** 2024-04-01 → 2028-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10797342

## Citation

> US National Institutes of Health, RePORTER application 10797342, Credentialing metabolic disease genes through human genetics and functional genomics (1I01BX006293-01A1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10797342. Licensed CC0.

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