Houlston, Richard S

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.’

Abstract Glioma incidence is highest in non-Hispanic Whites, where it occurs ~2x as frequently compared with other race/ethnicity groups. Glioma GWAS to date have included European ancestry populations only, and it is unknown whether variants identified by these analyses are associated with glioma in non- European ancestry populations. African Americans and Hispanics are admixed populations with varying proportions of European ancestry. While global ancestry may be similar within admixed groups, the proportion of European ancestry at each allele can vary across the genome. As glioma is more common in European ancestry populations, the presence of increased local European ancestry in these admixed populations could be used to identify glioma risk loci. Here we assessed whether excess European ancestry at established risk loci (Melin et al, Nature Genetics, 2017) was associated with glioma risk in non-European ancestry populations. Global ancestry was estimated using fastStructure, and local ancestry was estimated using RFMix. Both methods used 1,000 genomes project reference populations (African: YRI; European: CEU; East Asian: CHB/JPT; and Native American: CLM/PEL/MXL). We evaluated differences in local European ancestry between cases and controls using logistic regression conditioned on global European ancestry within 500kb of 25 previously identified risk variants among individuals with ≥50% African ancestry, and ≥30% Native American ancestry for all gliomas, and for grade IV glioblastoma (GBM) and grade II-III non-GBM. There were 347 individuals (184 cases and 163 controls) with ≥50% global African ancestry, and 277 individuals (153 cases and 124 controls) with ≥30% global American ancestry. There was no significant difference in proportion of global European ancestry between cases and controls with ≥50% global African ancestry (cases: 18.2%, controls: 17.7%, p=0.6834), and no significant difference in proportion of global European ancestry between cases and controls with ≥30% global American ancestry (cases: 51.1%, controls: 49.0%, p=0.2123). Among individuals with >50% African ancestry, we observed a nominally significant association between all glioma and increased local European ancestry at 7p11.2 (EGFR, pmin=0.0070) and between GBM and increased local European ancestry at 22q13.1 (CSNK1E, pmin=0.0098), both near SNPs previously associated with glioblastoma in majority European-ancestry populations. The dataset used for this analysis represents the largest collection of genotyped non-European glioma cases. These results suggest that glioma risk in African Americans may be associated with an increased local European ancestry variants at glioma risk loci previously identified in majority European ancestry populations (7p11.2 and 22q13.1). Citation Format: Quinn T. Ostrom, Kathleen M. Egan, L. Burt Nabors, Travis Gerke, Reid C. Thompson, Jeffrey J. Olson, Renato LaRocca, Sajeel Chowdhary, Jeanette E. Eckel-Passow, Georgina Armstrong, John K. Wiencke, Christopher I. Amos, Jonine L. Bernstein, Elizabeth B. Claus, Dora Il'yasova, Christoffer Johansen, Daniel H. Lachance, Rose Lai, Ryan T. Merrell, Sara H. Olson, Siegal Sadetzki, Joellen Schildkraut, Sanjay Shete, Richard S. Houlston, Robert B. Jenkins, Beatrice Melin, Melissa L. Bondy, Jill S. Barnholtz-Sloan. Evaluating glioma risk associated with extent of European admixture in African-Americans and Latinos [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 233.

Abstract BACKGROUND: Incidence of glioma varies significantly by sex, and most glioma histologies occur with greater incidence in males. Previous analyses have examined the impact of estrogen exposure as a risk factor for these tumors, but have found results of varying significance and low effect size. There may be differences in effect of previously discovered risk alleles that contribute to sex differences. METHODS: Using data collected for three previous glioma GWAS in European-ancestry populations (MD Anderson Cancer Center, the San Francisco Adult Glioma Study, and the Glioma International Case Control Study) we assessed sex-specific effects for 14 previously identified and 13 newly identified glioma risk SNPs (27 total) overall and for glioblastoma (GBM) and non-GBM tumors separately. There were 3,892 male cases (59% GBM), 4,522 male controls, 2,500 female cases (52% GBM) and 4,940 female controls. Sex-specific odds ratios (ORM and ORF), 95% confidence intervals (95% CI) and p values (pM and pF) were generated using stratified logistic regression models. Data from each study were analyzed separately and combined using inverse variance weighted meta-analysis. Results were considered statistically significant at p<6.2x10-4. RESULTS: In GBM, rs11979158 (7p11.2, pM=1.01x10-10, ORM=1.43 [95% CI: 1.28-1.59]; pF=3.43x10-3, ORF=1.22 [95% CI: 1.07-1.39]) and rs2562152 (16p13.3, pM=5.59x10-4, ORM=1.23 [95% CI: 1.09-1.39]; pF=1.22x10-1, ORF=1.12 [95% CI: 0.97-1.29]) had significant effect in males only. In non-GBM gliomas, rs12076373 (1q44, pM=3.56x10-7, ORM=1.41, 95% CI: 1.23-1.61; pF=1.76x10-2, ORF=1.20, 95% CI: 1.03-1.38), rs11979158 (7p11.2, pM=1.77x10-5, ORM=1.32 [95% CI: 1.16-1.49]; pF=2.73x10-1, ORF=1.08 [95% CI: 0.94-1.24]), and rs3751667 (16p13.3, pM=9.44x10-7, ORM=1.30 [95% CI: 1.17-1.44]; pF=5.18x10-2, ORF=1.13 [95% CI: 1.00-1.28]) had significant effect in males only. Effect size for rs55705857 (8q24.21) varied significantly by sex, with ORM=2.63 (95% CI: 2.24-3.09, pM=4.42x10-32), as compared to ORF=3.95 (95% CI: 3.28-4.76, pF=1.82x10-47). A sensitivity analysis was performed due to allele frequency heterogeneity by study and results did not change. CONCLUSIONS: Sex differences and other demographic differences in cancer susceptibility can provide important clues to etiology, and these differences can be leveraged for discovery in genetic association studies. Significant differences in effect size may suggest variation in genetic effect of risk alleles or in unidentified risk factors that vary in prevalence or effect by sex. There may also be differences in the distribution of molecular subtypes within each histology by sex. Further investigation using an agnostic approach may further elucidate the relationship between effect of risk alleles and sex. Citation Format: Quinn T. Ostrom, Ben Kinnersley, Margaret Wrensch, Jeanette E. Eckel-Passow, Georgina Armstrong, Terri Rice, Yanwen Chen, John Wiencke, Lucie McCoy, Helen Hansen, Christopher Amos, Jonine L. Bernstein, Elizabeth B. Claus, Dora Il'yasova, Christoffer Johansen, Daniel Lachance, Rose Lai, Ching C. Lau, Ryan T. Merrell, Sara H. Olson, Siegal Sadetzki, Joellen Schildkraut, Sanjay Shete, Richard S. Houlston, Robert B. Jenkins, Beatrice Melin, Melissa Bondy, Jill S. Barnholtz-Sloan. Estimating sex-specific effects of genetic loci associated with glioma risk [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1315. doi:10.1158/1538-7445.AM2017-1315

Abstract BACKGROUND: Glioma accounts for ~27% of all primary brain tumors and is responsible for ~13,000 cancer-related deaths in the US each year. Glioma tumors can be broadly classified into glioblastoma (GBM) and lower-grade non-GBM. Typically gliomas have a poor prognosis irrespective of medical care, with the most common form, GBM, having a five-year survival rate of only 5%. While genome-wide association studies (GWAS) have transformed our understanding of glioma susceptibility, individual studies have had limited power to identify risk loci. METHODS: We performed the largest glioma GWAS to date, comprising a meta-analysis of six existing GWAS (6,405 cases, 14,100 controls) as well as new GWAS from the Glioma International Case Control Consortium (GICC; 4,572 cases and 3,286 controls) and University of California, San Francisco (UCSF)-Mayo (1,519 cases, 804 controls), totaling 12,496 cases (6,191 classified as GBM, 5,819 as non-GBM) and 18,190 controls. RESULTS: We identified five new risk loci for GBM at 1p31.3 (rs12752552; near JAK1, P=2.04×10-9, odds ratio (OR)=1.22), 11q14.1 (rs11233250; P=9.95×10-10, OR=1.24), 16p13.3 (rs2562152; near MPG, P=1.93x10-8, OR=1.21), 16q12.1 (rs10852606; HEATR3, P=1.29×10-11, OR=1.18), 22q13.1 (rs2235573; P=1.76×10-10, OR=1.15) and eight for non-GBM at 1q32.1 (rs4252707; MDM4, P=3.34×10-9, OR=1.19), 1q44 (rs12076373; AKT3, P=2.63×10-10, OR=1.23), 2q33.3 (rs7572263; near IDH1, P=2.18×10-10, OR=1.20), 3p14.1 (rs11706832; LRIG1, P=7.66×10-9, OR=1.15), 10q24.33 (rs11598018; OBFC1, P=3.39×10-8, OR=1.14), 11q21 (rs7107785; P=3.87×10-10, OR=1.16), 14q12 (rs10131032; P=5.07x10-11, OR=1.33) and 16p13.3 (rs3751667; P=2.61×10-9, OR=1.18). Case-only analyses confirmed the specificity of 11q14.1, 16p13.3 and 22q13.1 associations for GBM and 1q44, 2q33.3, 3p14.1, 11q21 and 14q12 for non-GBM tumors. In the combined meta-analysis, among previously published glioma risk SNPs, those for all glioma at 17p13.1 (TP53), GBM at 5p15.33 (TERT), 7p11.2 (EGFR), 9p21.3 (CDKN2B-AS1) and 20q13.33 (RTEL1) and for non-GBM at 8q24.21 (CCDC26), 11q23.2, 11q23.3 (PHLDB1) and 15q24.2 (ETFA) showed even greater evidence for association. SNPs at 10q25.2 and 12q12.1 for non-GBM tumors retained genome-wide significance (i.e. P<5.0x10-8). Associations at the previously reported loci for GBM at 3q26.2 (near TERC) and 12q23.33 (POLR3B) did not retain statistical significance. CONCLUSIONS: Our findings substantiate genetic susceptibility to GBM and non-GBM glioma being highly distinct, consistent with their distinctive molecular profiles presumably resulting from different etiological pathways. Functional analyses should lead to further insights into the biological basis of the different glioma histologies. Such information can inform gene discovery initiatives and therefore have a measurable impact on the successful development of new therapeutic agents. Citation Format: Ben Kinnersley, Beatrice S. Melin, Jill S. Barnholtz-Sloan, Margaret R. Wrensch, Christoffer Johansen, Dora Il’yasova, Quinn Ostrom, and members of GICC, Karim Labreche, Jeanette E. Eckel-Passow, Paul A. Decker, Marianne Labussière, Ahmed Idbaih, Khe Hoang-Xuan, Anna-Luisa Di Stefano, Karima Mokhtari, Jean-Yves Delattre, Pilar Galan, Konstantinos Gousias, Johannes Schramm, Minouk J. Schoemaker, Sarah J. Fleming, Stefan Herms, Stefanie Heilmann, Marcus M. Nöthen, Heinz-Erich Wichmann, Stefan Schreiber, Anthony Swerdlow, Mark Lathrop, Matthias Simon, Marc Sanson, Preetha Rajaraman, Stephen Chanock, Martha Linet, Zhaoming Wang, Meredith Yeager, Rose K. Lai, Elizabeth B. Claus, Sara H. Olson, Robert B. Jenkins, Richard S. Houlston, Melissa L. Bondy. Genome-wide association study of glioma reveals specific differences in genetic susceptibility to glioblastoma and non-glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1302. doi:10.1158/1538-7445.AM2017-1302

While elevated blood cholesterol has been associated with an increased risk of colorectal cancer (CRC) in observational studies, causality is uncertain. Here we apply a Mendelian randomisation (MR) analysis to examine the potential causal relationship between lipid traits and CRC risk. We used single nucleotide polymorphisms (SNPs) associated with blood levels of total cholesterol (TC), triglyceride (TG), low‐density lipoprotein (LDL), and high‐density lipoprotein (HDL) as instrumental variables (IV). We calculated MR estimates for each risk factor with CRC using SNP‐CRC associations from 9,254 cases and 18,386 controls. Genetically predicted higher TC was associated with an elevated risk of CRC (odds ratios (OR) per unit SD increase = 1.46, 95% confidence interval [CI]: 1.20–1.79, p = 1.68 × 10−4). The pooled ORs for LDL, HDL, and TG were 1.05 (95% CI: 0.92–1.18, p = 0.49), 0.94 (95% CI: 0.84–1.05, p = 0.27), and 0.98 (95% CI: 0.85–1.12, p = 0.75) respectively. A genetic risk score for 3‐hydoxy‐3‐methylglutaryl‐coenzyme A reductase (HMGCR) to mimic the effects of statin therapy was associated with a reduced CRC risk (OR = 0.69, 95% CI: 0.49–0.99, p = 0.046). This study supports a causal relationship between higher levels of TC with CRC risk, and a further rationale for implementing public health strategies to reduce the prevalence of hyperlipidaemia.

Thiopurine‐related hematotoxicity in pediatric acute lymphoblastic leukemia (ALL) and inflammatory bowel diseases has been linked to genetically defined variability in thiopurine S‐methyltransferase (TPMT) activity. While gene testing of TPMT is being clinically implemented, it is unclear if additional genetic variation influences TPMT activity with consequences for thiopurine‐related toxicity. To examine this possibility, we performed a genome‐wide association study (GWAS) of red blood cell TPMT activity in 844 Estonian individuals and 245 pediatric ALL cases. Additionally, we correlated genome‐wide genotypes to human hepatic TPMT activity in 123 samples. Only genetic variants mapping to chromosome 6, including the TPMT gene region, were significantly associated with TPMT activity ( P < 5.0 × 10 ‐8 ) in each of the three GWAS and a joint meta‐analysis of 1,212 cases (top hit P = 1.2 × 10 ‐72 ). This finding is consistent with TPMT genotype being the primary determinant of TPMT activity, reinforcing the rationale for genetic testing of TPMT alleles in routine clinical practice to individualize mercaptopurine dosage.

Telomeres cap chromosome ends, protecting them from degradation, double‐strand breaks, and end‐to‐end fusions. Telomeres are maintained by telomerase, a reverse transcriptase encoded by TERT, and an RNA template encoded by TERC. Loci in the TERT and adjoining CLPTM1L region are associated with risk of multiple cancers. We therefore investigated associations between variants in 22 telomere structure and maintenance gene regions and colorectal, breast, prostate, ovarian, and lung cancer risk. We performed subset‐based meta‐analyses of 204,993 directly‐measured and imputed SNPs among 61,851 cancer cases and 74,457 controls of European descent. Independent associations for SNP minor alleles were identified using sequential conditional analysis (with gene‐level p value cutoffs ≤3.08 × 10−5). Of the thirteen independent SNPs observed to be associated with cancer risk, novel findings were observed for seven loci. Across the DCLRE1B region, rs974494 and rs12144215 were inversely associated with prostate and lung cancers, and colorectal, breast, and prostate cancers, respectively. Across the TERC region, rs75316749 was positively associated with colorectal, breast, ovarian, and lung cancers. Across the DCLRE1B region, rs974404 and rs12144215 were inversely associated with prostate and lung cancers, and colorectal, breast, and prostate cancers, respectively. Near POT1, rs116895242 was inversely associated with colorectal, ovarian, and lung cancers, and RTEL1 rs34978822 was inversely associated with prostate and lung cancers. The complex association patterns in telomere‐related genes across cancer types may provide insight into mechanisms through which telomere dysfunction in different tissues influences cancer risk.

Abstract Background: Numerous epidemiologic studies have examined the association between aspirin (ASA), non-steroid anti-inflammatory drugs (NSAIDs) and the development of glioma, but the results have been inconsistent. The goal of this study was to evaluate the relationship between the intake of these drugs and glioma risk in a large, international case-control study. Methods: Between 2010 and 2015, the Glioma International Case-Control Study (GICC) recruited newly diagnosed glioma cases and matched controls in 14 different sites across five countries. Each subject was interviewed using a standardized questionnaire to obtain NSAIDs and ASA use. We examined the associations between ever use (at least &gt; 6 months), duration of drug use and glioma histology. Ever use data on 4533 glioma cases and 4171 controls was combined using maximum likelihood estimation/restricted maximum likelihood meta-analysis methods. Furthermore, based on a priori hypotheses, we performed subgroup analyses based on gender and glioma histological grades. Results: Use of ASA for &gt; 6 months was associated with a 33% lower glioma risk compared to those who never took it (adjusted Meta-OR 0.67, 95% CI 0.54-0.83). Duration of intake showed a significant trend test (p &lt; 0.0001), with ORs became lower for increasing number of years of ASA use. In subgroup analyses, intake of ASA was significantly associated with glioma risk in both men and women (adjusted Meta-OR = 0.65, 95% CI 0.51-0.84 for men; adjusted Meta-OR = 0.74, 95% CI 0.58-0.93 for women). ASA intake was protective for grade IV glioma (glioblastoma) and grade II/III glioma (adjusted meta-OR 0.63, 95% CI 0.5-0.8 for glioblastoma; adjusted meta-OR 0.67, 95% CI 0.50 - 0.89 for grade II/III glioma). For NSAIDs intake, ever use &gt; 6 months was not associated with glioma risk (adjusted meta-OR 0.87, 95% CI 0.71-1.07). However, NSAIDs use was protective for women (adjusted meta-OR 0.72, 95% CI 0.55-0.93) in subgroup analyses but not for men (adjusted meta-OR 1.03; 95% CI 0.86-1.23). The interaction between gender, NSAIDs and glioma risk was significant (p-value 0.0076).. Sensitivity analyses excluding those who took ASA or NSAIDs within the past 12 months for headache, and the removal of proxy respondents did not change our results. Conclusion: ASA was associated with a significant protective effect for glioma, but NSAIDs were only associated with reduced glioma risk in women. Given the possibility of recall bias in case-control studies of brain tumors, we may verify dosage and duration of drug intake in those countries with electronic pharmacy records within the GICC. Citation Format: Rose K. Lai, Renke Zhou, E. Susan Amirian, Christoffer Johansen, Michael E. Scheurer, Georgina N. Armstrong, Ching C. Lau, Elizabeth B. Claus, Jill S. Barnholtz-Sloan, Dora Il’yasova, Joellen Schildkraut, Francis Ali-Osman, Siegal Sadetzki, Richard Houlston, Robert B. Jenkins, Daniel Lachance, Sara H. Olson, Jonine L. Bernstein, Ryan T. Merrell, Margaret R. Wrensch, Faith G. Davis, Sanjay Shete, Christopher I. Amos, Beatrice S. Melin, Melissa Bondy. Aspirin, non-steroidal anti-inflammatory drugs (NSAIDs) and the risk of glioma: Results from the Glioma International Case Control Study. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3446.

Abstract Identifying genetic variants with pleiotropic associations can uncover common pathways influencing multiple cancers. We took a two-stage approach to conduct genome-wide association studies for lung, ovary, breast, prostate, and colorectal cancer from the GAME-ON/GECCO Network (61,851 cases, 61,820 controls) to identify pleiotropic loci. Findings were replicated in independent association studies (55,789 cases, 330,490 controls). We identified a novel pleiotropic association at 1q22 involving breast and lung squamous cell carcinoma, with eQTL analysis showing an association with ADAM15/THBS3 gene expression in lung. We also identified a known breast cancer locus CASP8/ALS2CR12 associated with prostate cancer, a known cancer locus at CDKN2B-AS1 with different variants associated with lung adenocarcinoma and prostate cancer, and confirmed the associations of a breast BRCA2 locus with lung and serous ovarian cancer. This is the largest study to date examining pleiotropy across multiple cancer-associated loci, identifying common mechanisms of cancer development and progression. Cancer Res; 76(17); 5103–14. ©2016 AACR.