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Sender's message: Sepsis or genomics or altitude: JKB_daily1

Sent on Wednesday, 2014 March 26
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PubMed Results

Items 1 - 4 of 4

1.	Nat Genet. 2014 Feb;46(2):93. doi: 10.1038/ng.2893. Standards for clinical use of genetic variants. [No authors listed]
	PMID: 24473319 [PubMed - indexed for MEDLINE]
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2.	Nat Genet. 2014 Feb;46(2):176-81. doi: 10.1038/ng.2856. Epub 2013 Dec 22. Integrated genomic analysis identifies recurrent mutations and evolution patterns driving the initiation and progression of follicular lymphoma. Okosun J1, Bödör C2, Wang J3, Araf S4, Yang CY5, Pan C6, Boller S5, Cittaro D7, Bozek M8, Iqbal S4, Matthews J4, Wrench D4, Marzec J9, Tawana K4, Popov N4, O'Riain C4, O'Shea D4, Carlotti E4, Davies A10, Lawrie CH11, Matolcsy A12, Calaminici M4, Norton A13, Byers RJ14, Mein C8, Stupka E7, Lister TA4, Lenz G15, Montoto S4, Gribben JG4, Fan Y6, Grosschedl R5, Chelala C9, Fitzgibbon J4. Author information: 11] Centre for Haemato-Oncology, Barts Cancer Institute, Queen Mary University of London, London, UK. [2]. 21] Centre for Haemato-Oncology, Barts Cancer Institute, Queen Mary University of London, London, UK. [2] 1st Department of Pathology and Experimental Cancer Research, Semmelweis University, Budapest, Hungary. [3]. 31] Centre for Molecular Oncology, Barts Cancer Institute, Queen Mary University of London, London, UK. [2]. 4Centre for Haemato-Oncology, Barts Cancer Institute, Queen Mary University of London, London, UK. 5Department of Cellular and Molecular Immunology, Max Planck Institute of Immunobiology and Epigenetics, Freiburg, Germany. 61] School of Biology, Georgia Institute of Technology, Atlanta, Georgia, USA. [2] Parker H. Petit Institute for Bioengineering and Biosciences, Georgia Institute of Technology, Atlanta, Georgia, USA. 7Centre for Translational Genomics and Bioinformatics, San Raffaele Scientific Institute, Milan, Italy. 8Genome Centre, Barts and the London School of Medicine and Dentistry, London, UK. 9Centre for Molecular Oncology, Barts Cancer Institute, Queen Mary University of London, London, UK. 10Cancer Sciences Division, University of Southampton, Southampton, UK. 11Oncology Department, Biodonostia Research Institute, San Sebastian, Spain. 121st Department of Pathology and Experimental Cancer Research, Semmelweis University, Budapest, Hungary. 13Department of Histopathology, Christie National Health Service (NHS) Foundation Trust, Manchester, UK. 14Department of Histopathology, Manchester Royal Infirmary, Manchester, UK. 15 Department of Hematology, Oncology and Tumor Immunology, Charité Universitätsmedizin, Berlin, Germany. Abstract Follicular lymphoma is an incurable malignancy, with transformation to an aggressive subtype representing a critical event during disease progression. Here we performed whole-genome or whole-exome sequencing on 10 follicular lymphoma-transformed follicular lymphoma pairs followed by deep sequencing of 28 genes in an extension cohort, and we report the key events and evolutionary processes governing tumor initiation and transformation. Tumor evolution occurred through either a 'rich' or 'sparse' ancestral common progenitor clone (CPC). We identified recurrent mutations in linker histone, JAK-STAT signaling, NF-κB signaling and B cell developmental genes. Longitudinal analyses identified early driver mutations in chromatin regulator genes (CREBBP, EZH2 and KMT2D (MLL2)), whereas mutations in EBF1 and regulators of NF-κB signaling (MYD88 and TNFAIP3) were gained at transformation. Collectively, this study provides new insights into the genetic basis of follicular lymphoma and the clonal dynamics of transformation and suggests that personalizing therapies to target key genetic alterations in the CPC represents an attractive therapeutic strategy. PMCID: PMC3907271 [Available on 2014/8/1]
	PMID: 24362818 [PubMed - indexed for MEDLINE]
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3.	Nat Genet. 2014 Feb;46(2):200-4. doi: 10.1038/ng.2852. Epub 2013 Dec 15. Meta-analysis of gene-level tests for rare variant association. Liu DJ1, Peloso GM2, Zhan X1, Holmen OL3, Zawistowski M4, Feng S4, Nikpay M5, Auer PL6, Goel A7, Zhang H8, Peters U9, Farrall M7, Orho-Melander M10, Kooperberg C11, McPherson R5, Watkins H7, Willer CJ8, Hveem K12, Melander O10, Kathiresan S13, Abecasis GR1. Author information: 11] Center for Statistical Genetics, Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, USA. [2]. 21] Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA. [2] Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, USA. [3] Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA. [4]. 31] HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, Levanger, Norway. [2] St. Olav Hospital, Trondheim University Hospital, Trondheim, Norway. [3]. 4Center for Statistical Genetics, Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, USA. 5University of Ottawa Heart Institute, Ottawa, Ontario, Canada. 61] Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA. [2] School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA. 71] Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK. [2] Department of Cardiovascular Medicine, University of Oxford, Oxford, UK. 81] Division of Cardiology, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan, USA. [2] Department of Human Genetics, University of Michigan Medical School, Ann Arbor, Michigan, USA. 91] Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA. [2] Department of Epidemiology, University of Washington School of Public Health, Seattle, Washington, USA. 101] Department of Cardiovascular Medicine, University of Oxford, Oxford, UK. [2] Department of Clinical Sciences, Lund University, Malmö, Sweden. 111] Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA. [2] Department of Biostatistics, University of Washington School of Public Health, Seattle, Washington, USA. 121] HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, Levanger, Norway. [2] Department of Medicine, Levanger Hospital, Nord-Trøndelag Health Trust, Levanger, Norway. 131] Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA. [2] Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, USA. [3] Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA. [4] Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA. [5]. Abstract The majority of reported complex disease associations for common genetic variants have been identified through meta-analysis, a powerful approach that enables the use of large sample sizes while protecting against common artifacts due to population structure and repeated small-sample analyses sharing individual-level data. As the focus of genetic association studies shifts to rare variants, genes and other functional units are becoming the focus of analysis. Here we propose and evaluate new approaches for performing meta-analysis of rare variant association tests, including burden tests, weighted burden tests, variable-threshold tests and tests that allow variants with opposite effects to be grouped together. We show that our approach retains useful features from single-variant meta-analysis approaches and demonstrate its use in a study of blood lipid levels in ∼18,500 individuals genotyped with exome arrays. PMCID: PMC3939031 [Available on 2014/8/1]
	PMID: 24336170 [PubMed - indexed for MEDLINE]
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4.	Nat Genet. 2014 Feb;46(2):152-60. doi: 10.1038/ng.2853. Epub 2013 Dec 15. Therapeutic modulation of eIF2α phosphorylation rescues TDP-43 toxicity in amyotrophic lateral sclerosis disease models. Kim HJ1, Raphael AR2, LaDow ES3, McGurk L4, Weber RA4, Trojanowski JQ5, Lee VM5, Finkbeiner S3, Gitler AD2, Bonini NM4. Author information: 11] Department of Biology, University of Pennsylvania, Philadelphia, Pennsylvania, USA. [2]. 2Department of Genetics, Stanford University School of Medicine, Stanford, California, USA. 3Gladstone Institute of Neurological Disease, San Francisco, California, USA. 4Department of Biology, University of Pennsylvania, Philadelphia, Pennsylvania, USA. 5Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA. Abstract Amyotrophic lateral sclerosis (ALS) is a fatal, late-onset neurodegenerative disease primarily affecting motor neurons. A unifying feature of many proteins associated with ALS, including TDP-43 and ataxin-2, is that they localize to stress granules. Unexpectedly, we found that genes that modulate stress granules are strong modifiers of TDP-43 toxicity in Saccharomyces cerevisiae and Drosophila melanogaster. eIF2α phosphorylation is upregulated by TDP-43 toxicity in flies, and TDP-43 interacts with a central stress granule component, polyA-binding protein (PABP). In human ALS spinal cord neurons, PABP accumulates abnormally, suggesting that prolonged stress granule dysfunction may contribute to pathogenesis. We investigated the efficacy of a small molecule inhibitor of eIF2α phosphorylation in ALS models. Treatment with this inhibitor mitigated TDP-43 toxicity in flies and mammalian neurons. These findings indicate that the dysfunction induced by prolonged stress granule formation might contribute directly to ALS and that compounds that mitigate this process may represent a novel therapeutic approach. PMCID: PMC3934366 [Available on 2014/8/1]
	PMID: 24336168 [PubMed - indexed for MEDLINE]
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