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Celiac.com 06/15/2017 - Enteropathy-associated T cell lymphoma (EATL) subtypes are characterized by loss of function of SETD2. Although EATL is rare condition, it is deadly. It is also the most common neoplastic complication of celiac disease. A team of researchers recently conducted whole-exome sequencing of 69 EATL tumors, which helped them to define the genetic landscape of EATL. They found that SETD2 was silenced in 32% of EATL patients, making it the most frequently silenced gene in EATL. The research team included AB Moffitt, SL Ondrejka, M McKinney, RE Rempel, JR Goodlad, CH Teh, S Leppa, S Mannisto, PE Kovanen, E Tse, RKH Au-Yeung, YL Kwong, G Srivastava, J Iqbal, J Yu, K Naresh, D Villa, RD Gascoyne, J Said, MB Czader, A Chadburn, KL Richards, D Rajagopalan, NS Davis, EC Smith, BC Palus, TJ Tzeng, JA Healy, PL Lugar, J Datta, C Love, S Levy, DB Dunson, Y Zhuang, ED Hsi, and SS Dave. The team also noted that the JAK-STAT pathway was the most frequently mutated pathway, with frequent mutations in STAT5B as well as JAK1, JAK3, STAT3, and SOCS1, and that the condition causes highly overlapping genetic alterations among the mutations in KRAS, TP53, and TERT Type I EATL and type II EATL (monomorphic epitheliotropic intestinal T cell lymphoma), which indicates shared mechanisms underlying their causes. To model the effects of SETD2 loss in vivo, the team developed a T cell-specific knockout mouse. These mice manifested an expansion of γδ T cells, indicating novel roles for SETD2 in T cell development and lymphomagenesis. The team's data provides the most comprehensive genetic portrait to date of this rare, but deadly disease, and will likely play a key role in future classifications of EATL. Source: J Exp Med. 2017 May 1;214(5):1371-1386. doi: 10.1084/jem.20160894. Epub 2017 Apr 19. The researchers are variously affiliated with the Duke Center for Genomics and Computational Biology, Duke University, Durham, NC, the Duke Cancer Institute, Duke University School of Medicine, Durham, NC, the Pathology and Laboratory Medicine Institute, Cleveland Clinic, Cleveland, OH, the Haematological Malignancy Diagnostic Service, St. James's University Hospital, Leeds LS9 7TF, England, UK, the Haematology Department, Western General Hospital, Edinburgh, Scotland, UK, the Department of Oncology and Research Program Unit, Faculty of Medicine, Helsinki University Hospital Cancer Center and University of Helsinki in Helsinki, Finland, HUSLAB and Medicum, Helsinki University Hospital Cancer Center and University of Helsinki, Helsinki, Finland, the University of Hong Kong, Queen Mary Hospital, Hong Kong, China, the University of Nebraska Medical Center, Omaha, NE, Imperial College London, London, England, UK, the British Columbia Cancer Agency, University of British Columbia, Vancouver, BC, Canada, the University of California, Los Angeles, Los Angeles, CA, Indiana University, Indianapolis, IN, the Presbyterian Hospital, Pathology and Cell Biology, Cornell University, New York, NY, the University of North Carolina at Chapel Hill, Chapel Hill, NC, the Department of Medicine, Duke University School of Medicine, Durham, NC, the Department of Statistical Science, Duke University, Durham, NC, the Hudson Alpha Institute for Biotechnology, Huntsville, AL 35806, and the Department of Immunology, Duke University School of Medicine, Durham, NC.
Celiac.com 06/08/2012 - In a new study, researchers at Brigham and Women's Hospital (BWH) addressed whether the genetic risk of the most common medical conditions, including celiac disease, stems from many rare mutations that each confer a high degree of risk in various people, or from common differences throughout the genome that modestly influence risk. They used data and new analysis tools to assess new methods to better understand gene mutations for celiac and three other diseases, rheumatoid arthritis, coronary artery disease and myocardial infarction (heart attack); and type 2 diabetes. The researchers developed a new statistical method that used what is called "polygenic risk score analysis," to estimate the heritable genetic markers of these diseases that is explained by common differences across the genome. The method makes use of data from earlier genome-wide association studies, or GWAS, an approach used to scan DNA samples for common genetic markers seen throughout the population—called SNPs (single nucleotide polymorphisms). For rheumatoid arthritis, the team used computer simulations to show that the underlying genetic risk is largely due to many common alleles rather than rare mutations. They observed similar results for celiac disease (43 percent), myocardial infarction (48 percent) and type 2 diabetes (49 percent). "What is remarkable," says senior author Robert Plenge, MD, PhD, BWH director of Genetics and Genomics in the Division of Rheumatology, Immunology and Allergy, "is that our statistical model was broadly applicable to several common diseases, not just rheumatoid arthritis...Our study provides a clear strategy for discovering additional risk alleles for these and likely many other common diseases." According to the researchers, these methods can be applied to other genome-wide datasets (e.g., GWAS or whole genome sequencing) to estimate the degree to which there is a genetic component. Source: Nature Genetics 44, 483–489 (2012) doi:10.1038/ng.2232