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

Sent on Friday, 2011 Sep 09
Search (sepsis[MeSH Terms] OR septic shock[MeSH Terms] OR altitude[MeSH Terms] OR genomics[MeSH Terms] OR genetics[MeSH Terms] OR retrotransposons[MeSH Terms] OR macrophage[MeSH Terms]) AND ("2009/8/8"[Publication Date] : "3000"[Publication Date]) AND (("Science"[Journal] OR "Nature"[Journal] OR "The New England journal of medicine"[Journal] OR "Lancet"[Journal] OR "Nature genetics"[Journal] OR "Nature medicine"[Journal]) OR (Hume DA[Author] OR Baillie JK[Author] OR Faulkner, Geoffrey J[Author]))
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PubMed Results

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1.	Nature. 2011 Aug 31;477(7362):54-60. doi: 10.1038/nature10354. Human metabolic individuality in biomedical and pharmaceutical research. Suhre K, Shin SY, Petersen AK, Mohney RP, Meredith D, Wägele B, Altmaier E; CARDIoGRAM, Deloukas P, Erdmann J, Grundberg E, Hammond CJ, de Angelis MH, Kastenmüller G, Köttgen A, Kronenberg F, Mangino M, Meisinger C, Meitinger T, Mewes HW, Milburn MV, Prehn C, Raffler J, Ried JS, Römisch-Margl W, Samani NJ, Small KS, Wichmann HE, Zhai G, Illig T, Spector TD, Adamski J, Soranzo N, Gieger C, Assimes TL, Deloukas P, Erdmann J, Holm H, Kathiresan S, König IR, McPherson R, Reilly MP, Roberts R, Samani NJ, Schunkert H, Stewart AF. Collaborators: Kathiresan S, Reilly MP, Samani NJ, Schunkert H, Erdmann J, Assimes TL, Boerwinkle E, Erdmann J, Hall A, Hengstenberg C, Kathiresan S, König IR, Laaksonen R, McPherson R, Reilly MP, Samani NJ, Schunkert H, Thompson JR, Thorsteinsdottir U, Ziegler A, König IR, Thompson JR, Absher D, Chen L, Cupples LA, Halperin E, Li M, Musunuru K, Preuss M, Schillert A, Thorleifsson G, Voight BF, Wells GA, Absher D, Assimes TL, Fortmann S, Go A, Hlatky M, Iribarren C, Knowles J, Myers R, Quertermous T, Sidney S, Risch N, Tang H, Blankenberg S, Zeller T, Schillert A, Wild P, Ziegler A, Schnabel R, Sinning C, Lackner K, Tiret L, Nicaud V, Cambien F, Bickel C, Rupprecht HJ, Perret C, Proust C, Münzel T, Barbalic M, Bis J, Boerwinkle E, Chen IY, Cupples LA, Dehghan A, Demissie-Banjaw S, Folsom A, Glazer N, Gudnason V, Harris T, Heckbert S, Levy D, Lumley T, Marciante K, Morrison A, O'Donnell CJ, Psaty BM, Rice K, Rotter JI, Siscovick DS, Smith N, Smith A, Taylor KD, van Duijn C, Volcik K, Whitteman J, Ramachandran V, Hofman A, Uitterlinden A, Gretarsdottir S, Gulcher JR, Holm H, Kong A, Stefansson K, Thorgeirsson G, Andersen K, Thorleifsson G, Thorsteinsdottir U, Erdmann J, Fischer M, Grosshennig A, Hengstenberg C, König IR, Lieb W, Linsel-Nitschke P, Preuss M, Stark K, Schreiber S, Wichmann HE, Ziegler A, Schunkert H, Aherrahrou Z, Bruse P, Doering A, Erdmann J, Hengstenberg C, Illig T, Klopp N, König IR, Linsel-Nitschke P, Loley C, Medack A, Meisinger C, Meitinger T, Nahrstedt J, Peters A, Preuss M, Stark K, Wagner AK, Wichmann HE, Willenborg C, Ziegler A, Schunkert H, Böhm BO, Dobnig H, Grammer TB, Halperin E, Hoffmann MM, Kleber M, Laaksonen R, März W, Meinitzer A, Winkelmann BR, Pilz S, Renner W, Scharnagl H, Stojakovic T, Tomaschitz A, Winkler K, Voight BF, Musunuru K, Guiducci C, Burtt N, Gabriel SB, Siscovick DS, O'Donnell CJ, Elosua R, Peltonen L, Salomaa V, Schwartz SM, Melander O, Altshuler D, Kathiresan S, Stewart AF, Chen L, Dandona S, Wells GA, Jarinova O, McPherson R, Roberts R, Reilly MP, Li M, Qu L, Wilensky R, Matthai W, Hakonarson HH, Devaney J, Burnett MS, Pichard AD, Kent KM, Satler L, Lindsay JM, Waksman R, Knouff CW, Waterworth DM, Walker MC, Mooser V, Epstein SE, Rader DJ, Samani NJ, Thompson JR, Braund PS, Nelson CP, Wright BJ, Balmforth AJ, Ball SG, Hall AS. Source Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany. karsten@suhre.fr Abstract Genome-wide association studies (GWAS) have identified many risk loci for complex diseases, but effect sizes are typically small and information on the underlying biological processes is often lacking. Associations with metabolic traits as functional intermediates can overcome these problems and potentially inform individualized therapy. Here we report a comprehensive analysis of genotype-dependent metabolic phenotypes using a GWAS with non-targeted metabolomics. We identified 37 genetic loci associated with blood metabolite concentrations, of which 25 show effect sizes that are unusually high for GWAS and account for 10-60% differences in metabolite levels per allele copy. Our associations provide new functional insights for many disease-related associations that have been reported in previous studies, including those for cardiovascular and kidney disorders, type 2 diabetes, cancer, gout, venous thromboembolism and Crohn's disease. The study advances our knowledge of the genetic basis of metabolic individuality in humans and generates many new hypotheses for biomedical and pharmaceutical research.
	PMID: 21886157 [PubMed - indexed for MEDLINE]