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Meta-Analysis
. 2017 May;49(5):789-794.
doi: 10.1038/ng.3823. Epub 2017 Mar 27.

Genome-wide association study of glioma subtypes identifies specific differences in genetic susceptibility to glioblastoma and non-glioblastoma tumors

Beatrice S Melin  1 Jill S Barnholtz-Sloan  2 Margaret R Wrensch  3   4 Christoffer Johansen  5 Dora Il'yasova  6   7   8 Ben Kinnersley  9 Quinn T Ostrom  2 Karim Labreche  9   10 Yanwen Chen  2 Georgina Armstrong  11 Yanhong Liu  11 Jeanette E Eckel-Passow  12 Paul A Decker  12 Marianne Labussière  10 Ahmed Idbaih  10   13 Khe Hoang-Xuan  10   13 Anna-Luisa Di Stefano  10   13 Karima Mokhtari  10   13 Jean-Yves Delattre  10   13 Peter Broderick  9 Pilar Galan  14 Konstantinos Gousias  15 Johannes Schramm  15 Minouk J Schoemaker  9 Sarah J Fleming  16 Stefan Herms  16 Stefanie Heilmann  17 Markus M Nöthen  17 Heinz-Erich Wichmann  18   19   20 Stefan Schreiber  21 Anthony Swerdlow  9   22 Mark Lathrop  23 Matthias Simon  15 Marc Sanson  10   13 Ulrika Andersson  1 Preetha Rajaraman  24 Stephen Chanock  24 Martha Linet  24 Zhaoming Wang  24 Meredith Yeager  24 GliomaScan ConsortiumJohn K Wiencke  3   4 Helen Hansen  3 Lucie McCoy  3 Terri Rice  3 Matthew L Kosel  12 Hugues Sicotte  12 Christopher I Amos  25 Jonine L Bernstein  26 Faith Davis  27 Dan Lachance  28 Ching Lau  29 Ryan T Merrell  30 Joellen Shildkraut  7   8 Francis Ali-Osman  7   31 Siegal Sadetzki  32   33 Michael Scheurer  29 Sanjay Shete  34 Rose K Lai  35 Elizabeth B Claus  36   37 Sara H Olson  26 Robert B Jenkins  38 Richard S Houlston  9   39 Melissa L Bondy  11
Affiliations
Meta-Analysis

Genome-wide association study of glioma subtypes identifies specific differences in genetic susceptibility to glioblastoma and non-glioblastoma tumors

Beatrice S Melin et al. Nat Genet. 2017 May.

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.

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Figures

Figure 1
Figure 1
Genome-wide discovery-phase meta-analysis P-values (−log10P) plotted against their chromosomal positions. (a) All glioma. (b) GBM. (c) Non-GBM tumors. The red horizontal line corresponds to a significance threshold of P = 5.0 × 10−8. New and known loci are labeled in red and blue, respectively.
Figure 2
Figure 2
Relative impact of SNP associations at known and newly identified risk loci for GBM and non-GBM tumors. Odds ratios (ORs) derived with respect to the risk allele. Asterisks denote SNPs showing a significant difference between GBM and non-GBM tumors from the case-only analysis as detailed in Supplementary Table 4.

References

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