Can a Simple Blood Test Lead to Early Detection of Heart Attack?

The key to heart attack survival is to quickly and accurately determine whether a patient has in fact suffered a heart attack. Current methods used to diagnose and confirm a heart attack can take too long.

The key to heart attack survival is to quickly and accurately determine whether a patient has in fact suffered a heart attack. Current methods used to diagnose and confirm a heart attack can take too long. However, the authors of a study published in the September issue of the Journal of Clinical Investigation report they have developed a new means of detecting key metabolite changes that can accurately identify a heart attack within 10 minutes of its occurrence.

Researchers at Massachusetts General Hospital in Boston used “emerging metabolomic tools” to evaluate blood samples drawn from patients in whom the researchers had induced myocardial infarction (MI). The research team identified changes in patients’ “circulating levels of metabolites participating in pyrimidine metabolism, the tricarboxylic acid cycle and its upstream contributors, and the pentose phosphate pathway.” They reported that alterations in these key diagnostic metabolites were “detected as early as 10 minutes after” MI.

The basis for this study was investigators’ hypothesis that “small biochemicals may leak from injured myocardial cells before cellular damage would permit egress of macromolecules, potentially allowing for earlier detection of disease.” They noted that currently used “indicators of myocardial injury” (including the myocardial isoform of CK-MB and cardiac troponins) “reflect leakage of cardiac enzymes or structural proteins from irreversibly damaged cardiomyocytes,” but “are not reliably detected until at least 4 hours after myocardial injury.”

The high degree of accuracy the researchers attained using these methods lead them to confidently “identify a role for metabolic profiling in the early detection of myocardial injury and suggest that similar approaches may be used for detection or prediction of other disease states.”