domingo, 29 de julio de 2012

Scientists Find Many Common Genetic Variations Play a Role in Common Diseases

Scientists Find Many Common Genetic Variations Play a Role in Common Diseases



July 2012

Scientists Find Many Common Genetic Variations Play a Role in Common Diseases

Scientists have long known that genetic variations play a role in the development of many common medical conditions. What they haven’t known is whether a small number of variants have a large effect on their development, or whether a large number have a small effect. New research supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) and reported in Nature Genetics suggests that the cause of four common diseases — rheumatoid arthritis, celiac disease, coronary artery disease, and type 2 diabetes — is multiple variants with small effects.
Starting with rheumatoid arthritis, the researchers developed a new statistical method to estimate the genetic component of these diseases that are explained by common differences throughout the genome. Development of the method involved putting existing genetic data from 5,500 patients with rheumatoid arthritis, and 20,000 people without the disease, into the model and looking for areas where there was a greater occurrence of a genetic variation than would be expected by chance alone.
Using computer simulations, they were able to demonstrate that the underlying risk in rheumatoid arthritis is largely due to many common variations, rather than a few rare ones.
From there, they went on to apply that statistical method to the three other diseases. For each disease, they found that there are hundreds of small variations that are common in the general population, each with a small effect on the risk of disease. This finding, says lead author Robert Plenge, M.D., Ph.D., represents one of the most predominant components of the genetic architecture that has yet to be explained. There are probably hundreds more variations with a small effect that remain to be discovered. The research suggested there were probably a smaller number of rare variations that contribute, as well.
Dr. Plenge says although most of the variations are common in the general population, it is getting the right — or wrong — combination of them, along with environmental factors, that will lead to rheumatoid arthritis. Getting a different combination of genetic factors and environmental factors could lead to celiac disease, coronary artery disease, type 2 diabetes, or other diseases.
The finding has implications for better understanding of these diseases — and potentially others for which there is a genetic component — and their treatment, says Dr. Plenge, director of Genetics and Genomics in the Division of Rheumatology, Immunology and Allergy at Brigham and Women’s Hospital (BWH). It results from a multidisciplinary collaboration of geneticists, clinicians, and computer scientists, led by Dr. Plenge and BWH colleagues Eli Stahl, Ph.D., and Soumya Raychaudhuri, M.D., Ph.D.
Dr. Plenge says the findings will help direct researchers to the next wave of genetic studies that could lead to the discovery of common variations that affect disease risk. A better understanding of the genetic variations, and how strongly they affect disease risk, could eventually lead to better and more precise strategies for treating these diseases.
The mission of the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), a part of the U.S. Department of Health and Human Services’ National Institutes of Health (NIH), is to support research into the causes, treatment, and prevention of arthritis and musculoskeletal and skin diseases; the training of basic and clinical scientists to carry out this research; and the dissemination of information on research progress in these diseases. For more information about the NIAMS, call the information clearinghouse at (301) 495-4484 or (877) 22-NIAMS (free call) or visit the NIAMS website at http://www.niams.nih.gov.
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Stahl EA, Wegmann D, Trynka G, Gutierrez-Achury J, Do R, Voight BF, Kraft P, Chen R, Kallberg HJ, Kurreeman FA; Diabetes Genetics Replication and Meta-analysis Consortium; Myocardial Infarction Genetics Consortium, Kathiresan S, Wijmenga C, Gregersen PK, Alfredsson L, Siminovitch KA, Worthington J, de Bakker PI, Raychaudhuri S, Plenge RM. Bayesian inference analyses of the polygenic architecture of rheumatoid arthritis. Nat Genet. 2012 Mar 25;44(5):483-9. doi: 10.1038/ng.2232.
Nat Genet. 2012 Mar 25;44(5):483-9. doi: 10.1038/ng.2232. PMID: 22446960

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