Diagnostics & Imaging Week

Doctors already know that certain lifestyle factors like smoking, diet and exercise can influence a person’s blood fat, or lipid levels, important risk factors for coronary artery disease (CAD). Now, scientists are trying to better understand the genetic contribution to cardiovascular risk.

In an international collaboration supported primarily by the National Institutes of Health, scientists have discovered more than 25 genetic variants in 18 genes connected to cholesterol and lipid levels. Seven of the 18 genes previously had not been connected to these levels, while the 11 others confirm previous discoveries, the NIH noted. In the investigation, published online Monday and in the February print edition of Nature Genetics, the associated genes were found through studies of more than 20,000 individuals and more than 2 million genetic variants, spanning the entire genome. These variants potentially open the door to strategies for the treatment and prevention of CAD.

“Now that we know that some of these new genes can affect cholesterol levels, and can have an effect on CAD, we might be able to start looking for a new pharmaceutical to treat the disease,” David Schlessinger, PhD, chief of the National Institute on Aging’s Laboratory of Genetics, told Diagnostics & Imaging Week.

The purpose of the study was to identify comprehensively genetic variants that influence lipid levels and to examine the relationships between these genetic variants and risk of CAD. High levels of low-density lipoprotein (LDL) — “bad” cholesterol — appear to increase the risk of CAD by narrowing or blocking arteries that carry blood to the heart. High levels of high-density lipoprotein (HDL) – “good” cholesterol — appear to lower the risk. High levels of triglycerides, which make up a large part of the body’s fat and are also found in the bloodstream, are also associated with increased risk of CAD.

Cristen Willer, PhD, of the University of Michigan’s School of Public Health (Ann Arbor), and Serena Sanna, PhD, of the C.N.R. Institute of Neurogenetics and Neuropharmacology (Monserrato, Italy), and other members of the SardiNIA Study of Aging, including investigators at NIA, conducted the study, along with members of the Finland-United States Investigation of Non-Insulin-Dependent Diabetes Mellitus Genetics (FUSION) study, which included investigators in North Carolina, Michigan, Finland, Los Angeles and from the National Human Genome Research Institute. SardiNIA and FUSION investigators also coordinated the efforts of other groups in France, the UK and across the U.S.

The study relied on a relatively new approach, known as a genome-wide association study (GWAS).

“It’s a notable consortium effort, because one of the things that’s become clear in these genome-wide association studies, is the more people you have involved with good results, the stronger the results become and the greater your power is to being able to detect the genes involved,” said Schlessinger, the NIA project officer for SardiNIA.

The GWAS strategy enables researchers to survey the entire human genetic blueprint, or genome, not just the genetic variants in a few genes. The human genome contains about 3 billion base pairs, or letters, of DNA. Small, single-letter variations naturally occur about once in every 1,000 letters of the DNA code.

Most of these genetic variants have not yet been associated with particular traits or disease risks. However, in some instances, people with a certain trait, such as higher levels of LDL cholesterol, tend to have one version of the variant, while those with lower levels are more likely to have the other version. In such instances, researchers may infer that there is an association between the values of the trait and the variants in the gene.

Typically, GWAS studies have been carried out in samples where all individuals are examined with the same gene chip, an experimental device that allows investigators to measure more than 100,000 genetic variants in a single experiment. But in this study, investigators developed and employed new statistical methods that allowed them to combine data across different gene chips and examine much larger numbers of participants.

With the statistical power gained by new programs that facilitated pooling of the large SardiNIA, FUSION and Diabetes Genetic Initiative (DGI) datasets, researchers were able to identify variations in 18 genes that influence HDL, LDL and/or triglyceride levels. This list of lipid-associated genes is substantially longer than what was generated by analyses of individual datasets, which had only pointed to one to three genes each, according to the study’s authors. Of the seven newly implicated genes, two were associated with HDL levels, one with LDL levels, three with triglyceride levels and one with both triglycerides and LDL levels.

“These results are yet another example of how genome-wide association studies are opening exciting new avenues for biomedical research,” said NHGRI director Francis Collins, MD, PhD, who is a coauthor of the study and an investigator in NHGRI’s Genome Technology Branch. “While some of the genetic variants we identified are known to play a well-established role in lipid metabolism, others have no obvious connection. Further studies to identify the precise genes and biological pathways involved could shed new light on lipid metabolism.”

Scientists estimate that the genetic contribution to lipid levels is about 30% to 40%; the genetic variants uncovered in the new study are responsible for about 5% to 8% of that contribution, the researchers note.

“In this study we carried out a comprehensive search for common variants of large effect. The genetic factors still to be discovered might turn out to be common variants with smaller effects or rare variants with a large effect,” said Karen Mohlke, PhD, of the University of North Carolina (Chapel Hill), who co-directed the study with Gon alo Abecasis, PhD, of the University of Michigan’s School of Public Health.

To determine if the genetic variants associated with lipid levels also influence risk of heart disease, the researchers compared their results with results from the Wellcome Trust Case Control Consortium’s (Oxford, UK) recent genome-wide association study of CAD involving 15,000 British individuals. They found that all gene variants associated with increased LDL levels also were more prevalent among people with CAD. People with the gene variant for high triglyceride levels also had an increased risk for CAD, although the relationship was not as strong. No relationship was found between HDL and CAD.

Schlessinger told D&IW that this study was just a first step in a long path to potential clinical implications.

“What we’re looking for, ultimately, are novel therapeutics and/or life-style modifications that can be recommended to individuals to help manage blood lipid levels and reduce risk of heart disease,” he said.

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