Nature: Scientists identify new genetic variants connected to cholesterol, lipid levels
Scientists have discovered more than 25 genetic variants in 18 genes connected to cholesterol and lipid levels in an international collaboration supported primarily by the National Institutes of Health (NIH), published online Jan. 13 and in the February print issue of Nature Genetics.
Discovered by an international collaboration supported primarily by the National Institutes of Health (NIH), seven of the 18 genes previously had not been connected to these levels, while the 11 others confirm previous discoveries.
The associated genes were found through the examination of more than 20,000 individual studies and more than 2 million genetic variants, spanning the entire genome. The variants could potentially lead to strategies for the treatment and prevention of coronary artery disease (CAD).
Richard J. Hodes, MD, National Institute on Aging director, said that it is known “that certain lifestyle factors like smoking, diet and physical activity greatly affect a person's lipid profiles. This study is an important, basic step in finding the genes that influence lipid levels and heart disease so that we can better understand the genetic contribution to cardiovascular risk.”
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) 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) appear to lower the risk. High levels of triglycerides also are associated with increased risk of CAD.
To identify genetic variants that play a role in lipid levels, researchers turned to a relatively new approach, known as a genome-wide association study (GWAS). 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 approximately 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 the 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.
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 the study, investigators developed and employed new statistical methods that allowed them to combine data across different gene chips and thus examine much larger numbers of participants.
With the statistical wealth gained by new programs that facilitated pooling of the large SardiNIA, FUSION and Diabetes Genetic Initiative datasets, researchers were able to identify variations in 18 genes that influence HDL, LDL and/or triglyceride levels.
The Finland-United States Investigation of Non-Insulin-Dependent Diabetes Mellitus Genetics (FUSION) study 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 United Kingdom and across the United States.
Discovered by an international collaboration supported primarily by the National Institutes of Health (NIH), seven of the 18 genes previously had not been connected to these levels, while the 11 others confirm previous discoveries.
The associated genes were found through the examination of more than 20,000 individual studies and more than 2 million genetic variants, spanning the entire genome. The variants could potentially lead to strategies for the treatment and prevention of coronary artery disease (CAD).
Richard J. Hodes, MD, National Institute on Aging director, said that it is known “that certain lifestyle factors like smoking, diet and physical activity greatly affect a person's lipid profiles. This study is an important, basic step in finding the genes that influence lipid levels and heart disease so that we can better understand the genetic contribution to cardiovascular risk.”
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) 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) appear to lower the risk. High levels of triglycerides also are associated with increased risk of CAD.
To identify genetic variants that play a role in lipid levels, researchers turned to a relatively new approach, known as a genome-wide association study (GWAS). 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 approximately 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 the 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.
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 the study, investigators developed and employed new statistical methods that allowed them to combine data across different gene chips and thus examine much larger numbers of participants.
With the statistical wealth gained by new programs that facilitated pooling of the large SardiNIA, FUSION and Diabetes Genetic Initiative datasets, researchers were able to identify variations in 18 genes that influence HDL, LDL and/or triglyceride levels.
The Finland-United States Investigation of Non-Insulin-Dependent Diabetes Mellitus Genetics (FUSION) study 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 United Kingdom and across the United States.