Variants in the CDKN2B and RTEL1 regions are associated with high-grade glioma susceptibility

TLDR: Wrensch et al. as mentioned in this paper found that variants in the CDKN2B and RTEL1 regions are associated with high-grade glioma susceptibility and showed that the direction of association was the same in discovery and replication phases.

Abstract: LETTERS Variants in the CDKN2B and RTEL1 regions are associated with high-grade glioma susceptibility Margaret Wrensch 1,2,12 , Robert B Jenkins 3,12 , Jeffrey S Chang 4,12 , Ru-Fang Yeh 4,12 , Yuanyuan Xiao 4 , Paul A Decker 5 , Karla V Ballman 5 , Mitchel Berger 1 , Jan C Buckner 6 , Susan Chang 1 , Caterina Giannini 3 , Chandralekha Halder 3 , Thomas M Kollmeyer 3 , Matthew L Kosel 5 , Daniel H LaChance 7 , Lucie McCoy 1 , Brian P O’Neill 7 , Joe Patoka 1 , Alexander R Pico 8 , Michael Prados 1 , Charles Quesenberry 9 , Terri Rice 1 , Amanda L Rynearson 3 , Ivan Smirnov 1 , Tarik Tihan 10 , Joe Wiemels 2,4 , Ping Yang 11,13 & John K Wiencke 1,2,13 The causes of glioblastoma and other gliomas remain obscure 1,2 To discover new candidate genes influencing glioma susceptibility, we conducted a principal component– adjusted 3 genome-wide association study (GWAS) of 275,895 autosomal variants among 692 adult high-grade glioma cases (622 from the San Francisco Adult Glioma Study (AGS) and 70 from the Cancer Genome Atlas (TCGA)) 4 and 3,992 controls (602 from AGS and 3,390 from Illumina iControlDB (iControls)) For replication, we analyzed the 13 SNPs with P o 10 A6 using independent data from 176 high-grade glioma cases and 174 controls from the Mayo Clinic On 9p21, rs1412829 near CDKN2B had discovery P ¼ 34 Â 10 A8 , replication P ¼ 00038 and combined P ¼ 185 Â 10 A10 On 20q133, rs6010620 intronic to RTEL1 had discovery P ¼ 15 Â 10 A7 , replication P ¼ 000035 and combined P ¼ 340 Â 10 A9 For both SNPs, the direction of association was the same in discovery and replication phases Subject characteristics, including participation rates for the discovery GWAS and replication phases, are listed in Supplementary Table 1a,b The distribution of P values from the principal component–adjusted logistic regression additive model across the genome for high-grade glioma cases versus controls (Fig 1) suggests potentially meaningful associations for several SNPs on chromosomes 1, 5, 9, 11 and 20 Supplementary Table 2 summarizes results for the 13 SNPs with P o 10 A6 for association with high-grade glioma in discovery data along with results from replication data; SNPs with Hardy-Weinberg P o 10 A5 in controls or with 45% missing data in any case or control group were excluded Three of these 13 SNPs (rs1412829 on 9p21, and rs6010620 and rs4809324 intronic to RTEL1 on 20q133) had significant association with high-grade glioma risk in the discovery phase (principal component analysis P o 18 Â 10 A7 ), were inde- pendent risk predictors in a multivariable analysis of 13 top hits, and were replicated in the Mayo Clinic dataset (Table 1) As shown in Table 1 and Supplementary Table 2, the minor allele frequencies for the three SNPs consistently differed in the same direction between high-grade glioma cases and controls regardless of data source (AGS, TCGA, iControls or Mayo Clinic) Supplementary Table 3 shows results from the multivariable model of discovery data that included all 13 SNPs (four from the 9p21 region, three in RTEL1, plus six others in other locations) Eight SNPs, including one in the 9p21 region and two intronic to RTEL1, remained independently associated with high- grade glioma risk after adjustment for other SNPs This was expected given the strong linkage disequilibrium (LD) evident for the four 9p21 SNPs and two of the three RTEL1 SNPs (Supplementary Table 4) In discovery data, only the interaction between chromosome 9p21 SNP rs1412829 and TERT SNP rs2736100 on chromosome 5 was statistically significant with Wald test P ¼ 0019 (see Supplementary P value Chromosome © 2009 Nature America, Inc All rights reserved Figure 1 Distribution of P values from principal component–adjusted logistic regression additive model across the genome for high-grade glioma cases versus controls The 13 SNPs with P o 10 A6 are shown in red 1 Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA 2 Institute of Human Genetics, University of California, San Francisco, San Francisco, California, USA 3 Department of Experimental Pathology, Mayo Clinic, Rochester, Minnesota, USA 4 Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California, USA 5 Division of Biostatistics, 6 Department of Oncology and 7 Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA 8 Gladstone Institute of Cardiovascular Disease, University of California, San Francisco, San Francisco, California, USA 9 Division of Research, Kaiser Permanente, Oakland, California, USA 10 Department of Pathology, University of California, San Francisco, San Francisco, California, USA 11 Division of Epidemiology, Mayo Clinic, Rochester, Minnesota, USA 12 These authors contributed equally to this work 13 These authors jointly directed the work Correspondence should be addressed to MW (margaretwrensch@ucsfedu) Received 13 March; accepted 1 June; published online 5 July 2009; doi:101038/ng408 NATURE GENETICS ADVANCE ONLINE PUBLICATION