Research Finds Common Gene Variations Could Explain Differences in Complex Genetic Characteristics
Findings Could Shed Light on Genetic Causes of Eye Diseases, Other Conditions
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Boston (May 9, 2011) – Past genetic studies have shown that 45% of common DNA variation accounts for the differences in height we see in the general population. Researchers have now taken this work one step further by confirming these findings for height in a much larger sample and by applying the methodology to three other traits of general medical interest: body mass index (BMI), von Willebrand factor (vWF) and QT interval (QTi).
Their findings, with are posted online now in Nature Genetics and slated for publication in the journal in June, show that these methods are applicable to a variety of traits, such as those related to conditions affecting the eye. This study suggests that investing in very large sample sizes will lead to a better understanding of how common gene variants are related to complex traits, and possibly to the discovery of new biochemical pathways for these traits, which may serve as new targets to favorably modify medically related traits.
Louis Pasquale, M.D., director of the Glaucoma Service at Mass. Eye and Ear, and Distinguished Ophthalmology Scholar and Associate Professor of Ophthalmology, Harvard Medical School, is third author of the study. An explanation of the findings is provided below.
Background: In 2001, the blue print of the human genome was published and President Bill Clinton acknowledged this event as a landmark scientific accomplishment. When the code was completed, it was remarkable how similar it was in individuals who were seemingly unrelated. Specifically, the human genome contains 3 billion letters (A’s, T’s, C’s and G’s) and one in every 300 letters contains common variation. This led geneticists to postulate that these variable spots contributed to differences in traits such as height and weight. More importantly, these spots, also referred to as single nucleotide polymorphisms or SNPs (where an ‘A’ can be substituted with a ‘T’, for example) may also account for complex diseases such as Type 2 Diabetes, where the genetic basis is not well understood.
Technological advances allowed investigators to test the hypothesis that SNPs account for variability in complex traits. Genome-wide association studies (GWAS) allow researchers to test the hypothesis that SNPs account for variation in complex traits. Collectively these studies have confirmed this hypothesis and have yielded tremendous advances in our understanding of how genes contribute to traits such as height and eye diseases, such as macular degeneration. Dr. Peter Visscher from Queensland, Australia developed a method to calculate how much common variation in our DNA accounts for human traits. Using this method, he reported that 45% of common DNA variation accounts for the differences in height we see in the general population. Prior studies only uncovered 10% of common genetic variants associated with height.
Study Details and Findings: In the June issue of Nature Genetics, Dr. Pasquale and colleagues expand on Dr. Visscher’s initial observations by first confirming the finding for height in a much larger sample derived from the Nurses Health Study, Health Professionals Follow-up Study and the Atherosclerosis Risk in Communities Study. Then, they applied the methodology to three other traits of general medical interest: body mass index (BMI), von Willebrand factor (vWF) and QT interval (QTi). BMI is a measure of weight adjusted for height that is associated with several diseases including Type 2 Diabetes mellitus. vWF is a protein important in blood clotting, whereas QTi is a marker related to the heart rhythm. GWAS published thus far explain approximately 1.5%, 13% and 7% of the variation in BMI, vWF and QTi respectively. Using Dr. Visscher’s methods, this study shows that 17%, 25% and 21% of the variance in these respective traits is explained by common SNPs. The reason that published GWAS have not found the rest of the common SNPs associated with these traits is that the studies are not sufficiently large to find them.
This research proves that Dr. Visscher’s methods are applicable to a variety of traits and could likely be applied to eye traits such as eye size. Furthermore, this study suggests that investing in very large sample sizes will lead to a better understanding of how common gene variants are related to complex traits. Since common gene variants explain a considerable amount of variation of complex traits, this investment may lead to the discovery of new biochemical pathways for these traits. Finally, these new biochemical pathways may serve as new targets to favorably modify medically related traits.
Authors: Jian Yang, Teri A Manolio, Louis R Pasquale, Eric Boerwinkle, Neil Caporaso, Julie M Cunningham, Mariza de Andrade, Bjarke Feenstra, Eleanor Feingold, M Geoffrey Hayes, William G Hill, Maria Teresa Landi, Alvaro Alonso, Guillaume Lettre, Peng Lin, Hua Ling, William Lowe, Rasika A Mathias, Mads Melbye, Elizabeth Pugh, Marilyn C Cornelis, Bruce S Weir, Michael E Goddard and Peter M Visscher.
Funding support for the Gene, Environment Association Studies (GENEVA) project has been provided through the US National Institutes of Health Genes, Environment and Health Initiative.
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Founded in 1824, Mass. Eye and Ear is an independent specialty hospital, an international center for treatment and research, and a teaching affiliate of the Harvard Medical School. Information about Mass. Eye and Ear is available on its website at www.MassEyeAndEar.org.