# Genetic investigations of cardiometabolic disease: pleiotropy, gene x environment and causal inference analyses

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2024 · $734,221

## Abstract

PROJECT SUMMARY
Cardiometabolic disease refers to a set of clinically overlapping diseases, including coronary artery disease,
stroke, type 2 diabetes, hypertension, kidney disease and liver disease. These `cardiometabolic' diseases are
distinct but share common risk factors, including low density lipoprotein, triglycerides, systolic blood pressure,
central adiposity and glycemic measures. We label this set of inter-related and heritable metabolic and
hemodynamic traits the `cardiometabolic' (CM) heath profile. The CM health profile builds and extends the
metabolic syndrome paradigm to interrogate the disease risk heterogeneity, variables underlying
pathophysiology and predisposition to specific adverse consequences. Our focus is on examination of the
shared biology of the components and their role in the pathophysiology of CM disease endpoints, rather than
consideration of disease syndromes. Differences in end-organ consequences suggests that there may be
subtypes of the CM health profile with potentially different underlying pathophysiology and propensity for
adverse outcomes. We hypothesize that genetic analyses can enhance biological insights into CM health
profile component and disease endpoints by exploiting our mega-scale size sample of 1,365,750 subjects,
across five racial-ethnic groups, and consideration of pleiotropy, genetic subtyping, environmental modulation,
and causal inference analyses. We propose the following specific aims: 1) Pleiotropy, genetic classification and
association analysis of CM health profile components; 2) Gene x environment (GxE) interaction analyses of
CM disease endpoints; and 3) Causal inference analysis of CM health profile components, risk factors and
disease endpoints. There is a pressing need to better understand the genetic architecture of CM health profile,
relationship of components and their role in disease endpoints. If successful, this proposal will increase
genomic discovery, identify novel loci, and pathways, and enhance biological insights of CM health profile and
disease morbidity. We anticipate that our comprehensive approach to understand CM health profile biology will
bring us several steps closer towards identifying novel molecular targets and modifiable risks to achieve this
goal.

## Key facts

- **NIH application ID:** 10881478
- **Project number:** 1R01DK136796-01A1
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** RANY SALEM
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $734,221
- **Award type:** 1
- **Project period:** 2024-08-01 → 2028-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10881478

## Citation

> US National Institutes of Health, RePORTER application 10881478, Genetic investigations of cardiometabolic disease: pleiotropy, gene x environment and causal inference analyses (1R01DK136796-01A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10881478. Licensed CC0.

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