# Novel quantitative proteomic approaches to define the altered interplay between OGlcNAcylation and Phosphorylation in myofilament dysfunction of diabetic hearts

> **NIH NIH K01** · UNIVERSITY OF TEXAS RIO GRANDE VALLEY · 2020 · $124,579

## Abstract

Project Abstract/Summary
The candidate
 I am a Mexican-American MD/PhD who works as a basic scientist. I am also an Assistant Professor in
the Johns Hopkins School of Medicine, Division of Pediatric Cardiology where I also completed my post-
doctoral fellowship training. My interest in and commitment to a translational and basic research career started
as a 4th year medical student. I am convinced that funding through the NIH/NHLBI Mentored Career
Development Award to Promote Faculty Diversity in Biomedical Research will be instrumental to achieve my
goal, which is to become an independent investigator and a future leader in the field of molecular cardiology
and its translation into the advancement of therapies of diabetic cardiomyopathy and heart failure. 
Research Proposal: Novel quantitative proteomic approaches to define the altered interplay between
O-GlcNAcylation and Phosphorylation in myofilament dysfunction of diabetic hearts
 In North America, the 2010 prevalence of diabetes was 37.4 million (10.2%) and is on a steady rise16.
Diabetic patients are 2 to 4 times more at risk of dying from heart disease than the general population17.
Among cardiovascular complications, diabetic cardiomyopathy refers to a progressive diastolic and systolic
dysfunction due to a contractile deficit of the cardiac muscle that develops independently from coronary artery
disease. While it is present in 60% of diabetic patients, no therapy is currently available to halt or significantly
alter the course of diabetic cardiomyopathy18.
 Post-translational modifications of the sarcomere regulate cardiac function and when dysregulated
contribute to cardiac dysfunction. Recent work in our group has focused on the identification, quantification and
functional characterization of myofilament O-GlcNAcylation and Phosphorylation1-8. The goal of this proposal is
to use state of the art quantitative proteomic approaches to extensively map and perform site-specific
quantification of all potentially O-GlcNAcylated and Phosphorylated myofilament proteins of normal and
diabetic hearts during baseline cardiac function and during β-adrenergic and force-frequency stimulation. By
comparing O-GlcNAc/Phosphate stoichiometry changes between baseline and enhanced workload we will
identify key sites for abnormal myofilament function in diabetic cardiomyopathy. By using gene transfer
techniques, the present proposal also will perform in vivo and in vitro functional work to define the role of the
interplay between O-GlcNAcylation and Phosphorylation and the mechanisms that lead to impaired cardiac
contractile reserve in diabetes. Advances in this field can potentially generate early diagnostic tools for diabetic
cardiomyopathy and open new therapeutic venues to fix the
molecular motors of a failing diabetic heart. The specific aims of
this proposal are
Aim 1: To perform global myofilament site-specific O-
GlcNAcylation and Phosphorylation mapping and quantification in
normal and type 2 dia...

## Key facts

- **NIH application ID:** 10004702
- **Project number:** 5K01HL133368-05
- **Recipient organization:** UNIVERSITY OF TEXAS RIO GRANDE VALLEY
- **Principal Investigator:** Genaro Antonio Ramirez-Correa
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $124,579
- **Award type:** 5
- **Project period:** 2016-09-01 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10004702

## Citation

> US National Institutes of Health, RePORTER application 10004702, Novel quantitative proteomic approaches to define the altered interplay between OGlcNAcylation and Phosphorylation in myofilament dysfunction of diabetic hearts (5K01HL133368-05). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10004702. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*