Molecular debris can predict cardiovascular risks

February 20, 2010 05:04 pm | Updated November 17, 2021 07:06 am IST - Washington

Social activists and school children take posters and placards from a stall during the 'BSNL Dil Ka Darbar', a heart disease awareness programme. File Photo: Rajeev Bhatt

Social activists and school children take posters and placards from a stall during the 'BSNL Dil Ka Darbar', a heart disease awareness programme. File Photo: Rajeev Bhatt

Molecular “trash” circulating in the blood seem to predict cardiovascular disease and untimely death, say researchers.

The discovery comes from the largest study of its kind for cardiovascular disease and is the first to identify specific metabolic profiles associated with coronary artery disease (CAD), heart attacks and death among coronary catheterisation patients.

The Duke University Medical Centre (DUMC) study analysed metabolites, molecular debris left over after the body breaks food down into energy sources and building blocks of cells and tissues.

Scientists believe metabolites may be useful in diagnosing disease, said Svati Shah, Duke cardiologist and genetics, who led the study. But the tiny molecules are notoriously hard to identify, quantify and characterise.

Shah has been studying metabolic signatures in heart disease for several years and led earlier research showing that metabolic profiles associated with early-onset CAD can be inherited.

Shah and William Kraus, professor of medicine at Duke and the senior study author, wanted to know if they could isolate and identify particular metabolites associated with CAD.

They selected 174 patients who had experienced early-onset CAD and compared them to 174 controls who had undergone catheterisation but who were not found to have CAD.

Using a panel of 69 metabolites previously identified as potentially involved in the development of CAD, they examined the metabolic profiles in both groups.

“We found two sets, or clusters of metabolites that seemed to differentiate between the two groups,” says Shah.

Using multiple analytic and statistical methods, they found two factors that were clearly associated with CAD and one factor that predicted greater risk of heart attack or death among such patients, said a DUMC release.

“When we added these biomarkers to traditional clinical risk models, we found that they increased the accuracy of projected risk,” says Shah.

These findings were published online in Circulation Genetics.

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