American Heart Month — Basic Scientists Seek to Uncover the Fundamentals of Heart Disease Risk Factors

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American Heart Month spotlights heart disease, the leading cause of death among Americans, according to the Centers for Disease Control and Prevention.

Basic science researchers at the Johns Hopkins University School of Medicine are advancing heart health research by finding avenues that could advance drugs that regulate blood sugar, alleviate high blood pressure and improve how heart disease is treated.

Members of the media who would like to hear more from these scientists should contact Alexandria Carolan ([email protected]) or Vanessa Wasta ([email protected]).

Fine-Tuning the Basics of Blood Sugar

Evan O’Brien, Ph.D., assistant professor of biophysics and biophysical chemistry, Johns Hopkins University School of Medicine

Regulating blood sugar levels is key to maintaining heart health. When blood sugar levels are uncontrolled, glucose can build up in the bloodstream and lead to diabetes, a high-risk factor for heart disease.

To unravel the complexity of maintaining blood sugar levels, Evan O’Brien studies the basic properties of G-protein coupled receptors — a family of proteins that stud the surface of cells. Among this family of proteins are glucagon-like peptide-1 receptors, which are the target of the drug semaglutide or Ozempic, a weight loss drug and treatment for diabetes.  

Using sophisticated microscopes to super chill these receptors and see their movement at an atomic level, O’Brien’s lab is studying how members of this glucagon family of receptors are activated, and how this activation is regulated through interactions with other partners in our cells.

 “Through our research, we hope to better understand the complex signaling of this family of proteins, leading us to new discoveries that can help us fine-tune drugs that treat diabetes and obesity,” O’Brien says.

This “Smell” Receptor in the Heart and Other Organs May Control Blood Pressure 

Jennifer Pluznick, Ph.D., professor of physiology, Johns Hopkins University School of Medicine

Pluznick has found unique roles for olfactory receptors — odor sensors that are in various organs, including the heart. Does this mean your heart can smell a tasty plate of Valentine’s Day sweets? Not exactly, but these tiny proteins on the surface of cells can sniff out nearby chemicals in the body.

Using data from both mice and humans, a team of researchers led by Pluznick found that a specific olfactory receptor, Olfr558, may be responsible for — and help explain — sex differences in mammalian blood pressure.

The unusual connection between such protein receptors and sex differences in blood pressure may lead to a better understanding of long known differences in blood pressure between females and males. Understanding blood pressure differences can also help scientists fine-tune therapies that treat high blood pressure, a condition that can damage the arteries and lead to heart disease, Pluznick says.

 “Taking a closer look at the fundamental, scientific basis for sex differences in blood pressure may eventually help clinicians think about blood pressure treatment in new ways,” Pluznick says.

Digital twins 

Natalia Trayanova, Ph.D., Murray B. Sachs Professor of Biomedical Engineering, professor of medicine, Johns Hopkins University School of Medicine

Using artificial intelligence (AI), Trayanova creates detailed computer models of real patients’ hearts, also called digital twins, which can help scientists predict whether a patient will develop a life-threatening heart condition and find ways to treat it.

The AI-powered software, DIMON, helps researchers translate real-world systems and processes into mathematical representations of how objects and environments change over time and space. The AI model uses these mathematic equations and medical imaging data to predict a patient’s likelihood of developing a cardiac arrhythmia and their response to treatment. These arrhythmias, which cause irregular beating in the heart, can be fatal.

With their heart digital twins, Trayanova can diagnose whether patients might develop the often fatal condition and recommend ways to treat it.

Trayanova’s team tested the AI model on more than 1,000 heart digital twins. The platform accurately predicted how electrical signals propagated through each unique heart shape.