| Literature DB >> 28346443 |
Beatrice S Melin1, Jill S Barnholtz-Sloan2, Margaret R Wrensch3,4, Christoffer Johansen5, Dora Il'yasova6,7,8, Ben Kinnersley9, Quinn T Ostrom2, Karim Labreche9,10, Yanwen Chen2, Georgina Armstrong11, Yanhong Liu11, Jeanette E Eckel-Passow12, Paul A Decker12, Marianne Labussière10, Ahmed Idbaih10,13, Khe Hoang-Xuan10,13, Anna-Luisa Di Stefano10,13, Karima Mokhtari10,13, Jean-Yves Delattre10,13, Peter Broderick9, Pilar Galan14, Konstantinos Gousias15, Johannes Schramm15, Minouk J Schoemaker9, Sarah J Fleming16, Stefan Herms16, Stefanie Heilmann17, Markus M Nöthen17, Heinz-Erich Wichmann18,19,20, Stefan Schreiber21, Anthony Swerdlow9,22, Mark Lathrop23, Matthias Simon15, Marc Sanson10,13, Ulrika Andersson1, Preetha Rajaraman24, Stephen Chanock24, Martha Linet24, Zhaoming Wang24, Meredith Yeager24, John K Wiencke3,4, Helen Hansen3, Lucie McCoy3, Terri Rice3, Matthew L Kosel12, Hugues Sicotte12, Christopher I Amos25, Jonine L Bernstein26, Faith Davis27, Dan Lachance28, Ching Lau29, Ryan T Merrell30, Joellen Shildkraut7,8, Francis Ali-Osman7,31, Siegal Sadetzki32,33, Michael Scheurer29, Sanjay Shete34, Rose K Lai35, Elizabeth B Claus36,37, Sara H Olson26, Robert B Jenkins38, Richard S Houlston9,39, Melissa L Bondy11.
Abstract
Genome-wide association studies (GWAS) have transformed our understanding of glioma susceptibility, but individual studies have had limited power to identify risk loci. We performed a meta-analysis of existing GWAS and two new GWAS, which totaled 12,496 cases and 18,190 controls. We identified five new loci for glioblastoma (GBM) at 1p31.3 (rs12752552; P = 2.04 × 10-9, odds ratio (OR) = 1.22), 11q14.1 (rs11233250; P = 9.95 × 10-10, OR = 1.24), 16p13.3 (rs2562152; P = 1.93 × 10-8, OR = 1.21), 16q12.1 (rs10852606; P = 1.29 × 10-11, OR = 1.18) and 22q13.1 (rs2235573; P = 1.76 × 10-10, OR = 1.15), as well as eight loci for non-GBM tumors at 1q32.1 (rs4252707; P = 3.34 × 10-9, OR = 1.19), 1q44 (rs12076373; P = 2.63 × 10-10, OR = 1.23), 2q33.3 (rs7572263; P = 2.18 × 10-10, OR = 1.20), 3p14.1 (rs11706832; P = 7.66 × 10-9, OR = 1.15), 10q24.33 (rs11598018; P = 3.39 × 10-8, OR = 1.14), 11q21 (rs7107785; P = 3.87 × 10-10, OR = 1.16), 14q12 (rs10131032; P = 5.07 × 10-11, OR = 1.33) and 16p13.3 (rs3751667; P = 2.61 × 10-9, OR = 1.18). These data substantiate that genetic susceptibility to GBM and non-GBM tumors are highly distinct, which likely reflects different etiology.Entities:
Mesh:
Year: 2017 PMID: 28346443 PMCID: PMC5558246 DOI: 10.1038/ng.3823
Source DB: PubMed Journal: Nat Genet ISSN: 1061-4036 Impact factor: 41.307