deCODE study refines understanding of link between cholesterol and heart disease
May 4, 2016 – REYKJAVIK. deCODE genetics, a global leader in analyzing and understanding the human genome, today announced the discovery by a team of its scientists of a trove of single-letter variations in the sequence of the human genome that affect cholesterol levels and modulate risk of heart disease. The discoveries, published this week in the online edition of Nature Genetics, are the result of one of the most comprehensive population analyses of genetic and clinical data ever undertaken to understand how different levels of cholesterols and fat in the bloodstream can affect the development of plaques in the arteries. This phenomenon, called atherosclerosis, is the hallmark of coronary artery disease (CAD), a broad definition of heart disease that includes heart attack and is the leading cause of death in the industrialized world.
“Discoveries like these underscore why we are studying the genome and why doing so at population scale is critically important,” said Kari Stefansson, founder and CEO of deCODE and lead author on the papers. “We are not only illuminating in unprecedented detail how we should best use blood testing to gauge individual risk of heart disease, but have also found specific promising targets for the development of new drugs that could help to keep people healthy.”
“And just as important, we have been able to show that recent studies emphasizing the independent role of triglycerides in heart disease were probably only capturing part of the picture. These studies were crucially important in calling attention to important disease risk that was not being captured in our measurements of LDL and HDL cholesterol alone. However what we have been able to show by looking at such massive datasets is that the risk attributed to triglycerides is more likely due to cholesterol that travels with them in circulating lipoproteins. Our findings suggest that that risk is best captured by measuring non-HDL cholesterol levels, and this should spur an important conversation within the cardiology community to develop the most sensitive standard for testing for this risk,” Dr Stefansson concluded.
The deCODE team analyzed whole-genome sequence data from 120,000 Icelanders in tandem with several factors commonly measured in clinical blood tests: on levels of LDL cholesterol (so-called “bad cholesterol”); HDL cholesterol (often called “good cholesterol”); triglycerides (a major component of fat in the human body and which has recently been suggested as a major risk factor for CAD); and non-HDL cholesterol, a broader category that captures the standard LDL measurement as well as otherwise uncaptured cholesterol in the bloodstream. This identified thirteen previously unknown rare and low-frequency single-letter variations in nine genes, and confirmed fourteen previously reported variants. They then took these results to develop genetic risk scores for the different lipid fractions - LDL cholesterol, HDL cholesterol, triglyceride and non-HDL cholesterol - and correlated them with CAD in 33,000 cases and 240,000 control subjects. This analysis demonstrated that non-HDL cholesterol was a better measure of risk of CAD than LDL cholesterol, and that triglyceride levels alone did not correlate with CAD risk. The most likely explanation for this, the authors conclude, is that non-HDL levels are capturing the risk conferred both by LDL cholesterol and remnant atherogenic cholesterol risk carried in triglyceride-rich lipoproteins that are not captured in current LDL testing.
SOURCE deCODE genetics