New research findings indicate that LDL – the “bad” cholesterol – may have company as a major risk factor for heart attacks that occur at an early age. The new culprit: a mutation in VLDL – or very low-density lipoprotein – a group of triglyceride-rich lipoproteins. The study is published in the February 5, 2015 issue of Nature.

Generated by one component of the National Heart, Lung, and Blood Institute’s (NHLBI) massive exome sequencing project (ESP), the study’s results show that low-density lipoprotein receptor (LDLR) and apolipoprotein A-V (APOA5) gene mutations can mean a higher risk of early-onset myocardial infarction (MI), a chronic leading cause of death worldwide. The researchers, including University of Vermont Professor of Pathology Russell Tracy, Ph.D., found that in addition to LDL cholesterol, disordered metabolism of triglyceride-rich lipoproteins – VLDL – contributes to MI risk.

“This study pretty much nails it down,” says Tracy, a member of both the ESP steering committee and its Early Onset MI Project Team, who also serves as interim senior associate dean for research at the UVM College of Medicine. “In my view, there is no longer any question that VLDL is participatory in atherosclerosis and heart disease.”

Established in 2009, the $64-million multi-center ESP was the first large sequencing study on DNA samples and data gathered from population studies; its goal was the discovery of genes that are responsible for heart, lung and blood disorders, found in between extremely rare genetic mutations (less than 1 in 10,000 people) and common genetic variations. When the project began, the ability to sequence the entire genome in the 9 or 10,000 people participating in ESP was not yet an option; today, 6 years later, the NHLBI is funding whole genome sequencing instead. Yet to date the multi-cohort, multi-center ESP remains the largest sequencing study focused on heart disease, says Tracy.

In this particular study, Tracy and colleagues nationwide defined early onset as MI occurring in men under age 50 and in women under age 60 and compared their genes to those in older individuals who had not experienced MI. During the discovery phase, they conducted association testing of each individual mutation, comparing hundreds of thousands of variants in nearly 1,000 cases and 1,000 controls, but did not find statistical significance. They then conducted burden testing (where you compare how many variants in total occurred in each gene in the Cases compared to the same gene in Controls; there are ~25,000 genes in humans), and although they moved closer, and several candidates emerged, but they still showed nothing of statistical significance.

In the second phase, the researchers examined some of the specific variants they’d found in discovery in 64,000 people and conducted array-based genotyping in 15,000 among them. Finally, in another 12,000 individuals, they sequenced only certain genes, based on hint lists, yielding a p value in APOA5 that was statistically significant. They also exome sequenced almost 8,000 additional individuals to establish the new mutatioons in LDLR. It was “an impressive amount of work,” says Tracy, whose UVM lab served as a source of some of the DNA, and as a quality control focal point for nearly all the DNA sequenced at the two Genome Sequencing Centers (University of Washington, Seattle WA, and the Broad Institute, Cambridge MA).

LDLR mutations were found in about two percent of the early onset MI cases; APOA5 was identified for the first time as a “bona fide” MI gene, with the roles of triglyceride-rich lipoproteins and the lipoprotein lipase pathway in early-onset MI now made clearer. In addition, the paper underscored the importance of sequencing thousands of cases, coupled with careful statistical analysis, to determine rare variant discovery for complex disease.

“This fits in perfectly with President Obama’s recent initiative in Precision Medicine,” says Tracy. “While the initial focus of the President’s initiative will be cancer, results from ESP and other studies confirm that precise definitions of chronic diseases such as heart disease and diabetes will follow along quickly, leading to exciting and critically important improvements in risk prediction, diagnosis and therapy.”