TY - JOUR

T1 - Age-specific genome-wide association study in glioblastoma identifies increased proportion of ‘lower grade glioma’-like features associated with younger age

AU - Ostrom, Quinn T.

AU - Kinnersley, Ben

AU - Armstrong, Georgina

AU - Rice, Terri

AU - Chen, Yanwen

AU - Wiencke, John K.

AU - McCoy, Lucie S.

AU - Hansen, Helen M.

AU - Amos, Christopher I.

AU - Bernstein, Jonine L.

AU - Claus, Elizabeth B.

AU - Eckel-Passow, Jeanette E.

AU - Il'yasova, Dora

AU - Johansen, Christoffer

AU - Lachance, Daniel H.

AU - Lai, Rose K.

AU - Merrell, Ryan T.

AU - Olson, Sara H.

AU - Sadetzki, Siegal

AU - Schildkraut, Joellen M.

AU - Shete, Sanjay

AU - Rubin, Joshua B.

AU - Andersson, Ulrika

AU - Rajaraman, Preetha

AU - Chanock, Stephen J.

AU - Linet, Martha S.

AU - Wang, Zhaoming

AU - Yeager, Meredith

AU - Houlston, Richard S.

AU - Jenkins, Robert B.

AU - Wrensch, Margaret R.

AU - Melin, Beatrice

AU - Bondy, Melissa L.

AU - Barnholtz-Sloan, Jill S.

AU - on behalf of the GliomaScan consortium

PY - 2018

Y1 - 2018

N2 - Glioblastoma (GBM) is the most common malignant brain tumor in the United States. Incidence of GBM increases with age, and younger age-at-diagnosis is significantly associated with improved prognosis. While the relationship between candidate GBM risk SNPs and age-at-diagnosis has been explored, genome-wide association studies (GWAS) have not previously been stratified by age. Potential age-specific genetic effects were assessed in autosomal SNPs for GBM patients using data from four previous GWAS. Using age distribution tertiles (18–53, 54–64, 65+) datasets were analyzed using age-stratified logistic regression to generate p values, odds ratios (OR), and 95% confidence intervals (95%CI), and then combined using meta-analysis. There were 4,512 total GBM cases, and 10,582 controls used for analysis. Significant associations were detected at two previously identified SNPs in 7p11.2 (rs723527 [p 54–63 = 1.50x10 −9 , OR 54–63 = 1.28, 95%CI 54–63 = 1.18–1.39; p 64+ = 2.14x10 −11 , OR 64+ = 1.32, 95%CI 64+ = 1.21–1.43] and rs11979158 [p 54–63 = 6.13x10 −8 , OR 54–63 = 1.35, 95%CI 54–63 = 1.21–1.50; p 64+ = 2.18x10 −10 , OR 64+ = 1.42, 95%CI 64+ = 1.27–1.58]) but only in persons >54. There was also a significant association at the previously identified lower grade glioma (LGG) risk locus at 8q24.21 (rs55705857) in persons ages 18–53 (p 18–53 = 9.30 × 10 −11 , OR 18–53 = 1.76, 95%CI 18–53 = 1.49–2.10). Within The Cancer Genome Atlas (TCGA) there was higher prevalence of ‘LGG’-like tumor characteristics in GBM samples in those 18–53, with IDH1/2 mutation frequency of 15%, as compared to 2.1% [54–63] and 0.8% [64+] (p = 0.0005). Age-specific differences in cancer susceptibility can provide important clues to etiology. The association of a SNP known to confer risk for IDH1/2 mutant glioma and higher prevalence of IDH1/2 mutation within younger individuals 18–53 suggests that more younger individuals may present initially with ‘secondary glioblastoma.’.

AB - Glioblastoma (GBM) is the most common malignant brain tumor in the United States. Incidence of GBM increases with age, and younger age-at-diagnosis is significantly associated with improved prognosis. While the relationship between candidate GBM risk SNPs and age-at-diagnosis has been explored, genome-wide association studies (GWAS) have not previously been stratified by age. Potential age-specific genetic effects were assessed in autosomal SNPs for GBM patients using data from four previous GWAS. Using age distribution tertiles (18–53, 54–64, 65+) datasets were analyzed using age-stratified logistic regression to generate p values, odds ratios (OR), and 95% confidence intervals (95%CI), and then combined using meta-analysis. There were 4,512 total GBM cases, and 10,582 controls used for analysis. Significant associations were detected at two previously identified SNPs in 7p11.2 (rs723527 [p 54–63 = 1.50x10 −9 , OR 54–63 = 1.28, 95%CI 54–63 = 1.18–1.39; p 64+ = 2.14x10 −11 , OR 64+ = 1.32, 95%CI 64+ = 1.21–1.43] and rs11979158 [p 54–63 = 6.13x10 −8 , OR 54–63 = 1.35, 95%CI 54–63 = 1.21–1.50; p 64+ = 2.18x10 −10 , OR 64+ = 1.42, 95%CI 64+ = 1.27–1.58]) but only in persons >54. There was also a significant association at the previously identified lower grade glioma (LGG) risk locus at 8q24.21 (rs55705857) in persons ages 18–53 (p 18–53 = 9.30 × 10 −11 , OR 18–53 = 1.76, 95%CI 18–53 = 1.49–2.10). Within The Cancer Genome Atlas (TCGA) there was higher prevalence of ‘LGG’-like tumor characteristics in GBM samples in those 18–53, with IDH1/2 mutation frequency of 15%, as compared to 2.1% [54–63] and 0.8% [64+] (p = 0.0005). Age-specific differences in cancer susceptibility can provide important clues to etiology. The association of a SNP known to confer risk for IDH1/2 mutant glioma and higher prevalence of IDH1/2 mutation within younger individuals 18–53 suggests that more younger individuals may present initially with ‘secondary glioblastoma.’.

KW - age

KW - brain tumors

KW - glioma

U2 - 10.1002/ijc.31759

DO - 10.1002/ijc.31759

M3 - Journal article

C2 - 30152087

AN - SCOPUS:85053534188

VL - 143

SP - 2359

EP - 2366

JO - International Journal of Cancer

JF - International Journal of Cancer

SN - 0020-7136

IS - 10

ER -