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

on behalf of the GliomaScan consortium

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

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 [p54–63 = 1.50x10−9, OR54–63 = 1.28, 95%CI54–63 = 1.18–1.39; p64+ = 2.14x10−11, OR64+ = 1.32, 95%CI64+ = 1.21–1.43] and rs11979158 [p54–63 = 6.13x10−8, OR54–63 = 1.35, 95%CI54–63 = 1.21–1.50; p64+ = 2.18x10−10, OR64+ = 1.42, 95%CI64+ = 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 (p18–53 = 9.30 × 10−11, OR18–53 = 1.76, 95%CI18–53 = 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.’.

Original languageEnglish (US)
Pages (from-to)2359-2366
Number of pages8
JournalInternational Journal of Cancer
Volume143
Issue number10
DOIs
StatePublished - Nov 15 2018

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Genome-Wide Association Study
Glioblastoma
Glioma
Single Nucleotide Polymorphism
Neoplasms
Atlases
Age Distribution
Mutation Rate
Brain Neoplasms
Meta-Analysis
Logistic Models
Odds Ratio
Genome
Confidence Intervals
Mutation
Incidence

Keywords

  • age
  • brain tumors
  • glioma

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

Cite this

Age-specific genome-wide association study in glioblastoma identifies increased proportion of ‘lower grade glioma’-like features associated with younger age. / on behalf of the GliomaScan consortium.

In: International Journal of Cancer, Vol. 143, No. 10, 15.11.2018, p. 2359-2366.

Research output: Contribution to journalArticle

@article{495052ebc90547eaa6df1d7527583032,
title = "Age-specific genome-wide association study in glioblastoma identifies increased proportion of ‘lower grade glioma’-like features associated with younger age",
abstract = "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 [p54–63 = 1.50x10−9, OR54–63 = 1.28, 95{\%}CI54–63 = 1.18–1.39; p64+ = 2.14x10−11, OR64+ = 1.32, 95{\%}CI64+ = 1.21–1.43] and rs11979158 [p54–63 = 6.13x10−8, OR54–63 = 1.35, 95{\%}CI54–63 = 1.21–1.50; p64+ = 2.18x10−10, OR64+ = 1.42, 95{\%}CI64+ = 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 (p18–53 = 9.30 × 10−11, OR18–53 = 1.76, 95{\%}CI18–53 = 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.’.",
keywords = "age, brain tumors, glioma",
author = "{on behalf of the GliomaScan consortium} and Ostrom, {Quinn T.} and Ben Kinnersley and Georgina Armstrong and Terri Rice and Yanwen Chen and Wiencke, {John K.} and McCoy, {Lucie S.} and Hansen, {Helen M.} and Amos, {Christopher I.} and Bernstein, {Jonine L.} and Claus, {Elizabeth B.} and Eckel-Passow, {Jeanette E} and Dora Il'yasova and Christoffer Johansen and Lachance, {Daniel H} and Lai, {Rose K.} and Merrell, {Ryan T.} and Olson, {Sara H.} and Siegal Sadetzki and Schildkraut, {Joellen M.} and Sanjay Shete and Rubin, {Joshua B.} and Ulrika Andersson and Preetha Rajaraman and Chanock, {Stephen J.} and Linet, {Martha S.} and Zhaoming Wang and Meredith Yeager and Houlston, {Richard S.} and Jenkins, {Robert Brian} and Wrensch, {Margaret R.} and Beatrice Melin and Bondy, {Melissa L.} and Barnholtz-Sloan, {Jill S.}",
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T1 - Age-specific genome-wide association study in glioblastoma identifies increased proportion of ‘lower grade glioma’-like features associated with younger age

AU - on behalf of the GliomaScan consortium

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 Brian

AU - Wrensch, Margaret R.

AU - Melin, Beatrice

AU - Bondy, Melissa L.

AU - Barnholtz-Sloan, Jill S.

PY - 2018/11/15

Y1 - 2018/11/15

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 [p54–63 = 1.50x10−9, OR54–63 = 1.28, 95%CI54–63 = 1.18–1.39; p64+ = 2.14x10−11, OR64+ = 1.32, 95%CI64+ = 1.21–1.43] and rs11979158 [p54–63 = 6.13x10−8, OR54–63 = 1.35, 95%CI54–63 = 1.21–1.50; p64+ = 2.18x10−10, OR64+ = 1.42, 95%CI64+ = 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 (p18–53 = 9.30 × 10−11, OR18–53 = 1.76, 95%CI18–53 = 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 [p54–63 = 1.50x10−9, OR54–63 = 1.28, 95%CI54–63 = 1.18–1.39; p64+ = 2.14x10−11, OR64+ = 1.32, 95%CI64+ = 1.21–1.43] and rs11979158 [p54–63 = 6.13x10−8, OR54–63 = 1.35, 95%CI54–63 = 1.21–1.50; p64+ = 2.18x10−10, OR64+ = 1.42, 95%CI64+ = 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 (p18–53 = 9.30 × 10−11, OR18–53 = 1.76, 95%CI18–53 = 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.’.

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