Citations

Abstract Background Regular use of aspirin and other non-steroidal anti-inflammatory drugs (NSAIDs) is associated with lower risk of colorectal cancer (CRC). Genome-wide interaction analysis (GxE) has identified a few variants that may modify the effects of NSAIDs on CRC risk. However, limited statistical power remains a concern. Restricting analyses by using functional genomic information to aggregate variants into biologically relevant sets can reduce the number of tests, thereby increasing statistical power. We tested the interactions between variant models of gene expression and NSAIDs use on CRC risk. Methods Functional weights of each variant were estimated using PrediXcan based on jointly measured transcriptomes and genomes data of transverse colon tissues from the Genotype-Tissue Expression (GTEx) Project for all genes with sufficient heritability (≥1%). A mixed-effects model was used to assess the GxE effects in a gene among 9,917 incident CRC cases and 10,533 controls from 17 (nested) case-control studies from the Colon Cancer Family Registry (CCFR) and Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO). GxE analysis was done by modeling the interaction between predicted gene expression and NSAID use (fixed effects), and residual variant-specific GxE effects that are not accounted for (random effects). Regular user of aspirin and/or non-aspirin NSAIDs was compared to non-regular users. False discovery rate (FDR) was used to account for multiple comparison and FDR≤0.2 was considered genome-wide significant. Secondary analysis was performed on significant genes and duration of use among users. Results Regular use of aspirin was higher among controls (30.3%) compared to cases (24.3%). Among the 4,842 genes tested, SORD significantly modified the effect of regular use of aspirin on CRC risk (p-interaction = 1.45×10-5; FDR=0.07). The SORD gene encodes sorbitol dehydrogenase (SORD), which oxidizes sorbitol to fructose in the polyol pathway. Decreased SORD concentrations were previously observed to dramatically increase in colorectal adenoma cells when compared to normal mucosa cells, suggesting the involvement of dysregulated polyol metabolisms in colorectal tumorigenesis. However, the duration of aspirin use was not statistically significantly associated with SORD gene expression on CRC risk (p=0.149) among 5,560 aspirin users. No significant interactions were observed between genetically determined colon gene expression levels and any NSAID use or non-aspirin NSAID use at FDR<0.2. Conclusions Incorporating functional information, we discovered a novel gene that may interact with aspirin use to confer CRC risk. These findings provide preliminary support for new biological insights that could help understand the chemopreventive mechanisms of aspirin on CRC. We aim to replicate these findings in additional studies. Citation Format: Xiaoliang Wang, Yu-Ru Su, Andrew T. Chan, Stephanie Bien, Sonja I. Bernt, Hermann Brenner, Graham Casey, Jenny Chang-Claude, Steven J. Gallinger, Robert W. Haile, Tabitha A. Harrison, Michael Hoffmeister, Mark A. Jenkins, Amit Joshi, Yi Lin, Noralane M. Lindor, Loic Le Marchand, Hongmei Nan, Polly A. Newcomb, John D. Potter, Martha L. Slattery, Steve N. Thibodeau, Emily White, Li Hsu, Ulrike Peters. Functionally informed genome-wide interaction analysis of nonsteroidal anti-inflammatory drugs on colorectal cancer risk [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 2965.

Abstract Over 50 genetic variants have been associated with colorectal cancer (CRC) risk through genome-wide association studies (GWAS), yet these variants represent only a fraction of the total estimated heritability. CRC is a heterogenous disease with diverse tumor etiology. Assessing genetic risk in molecular subtypes may help to identify novel loci and characterize genetic risk among tumor subtypes. We used microsatellite instability (MSI), an established CRC classifier with etiological and therapeutic relevance, to define CRC subtypes for GWAS analyses. We conducted a case-case analysis to estimate odds ratios (OR) and 95% confidence intervals (CI) for association of genome-wide variants with microsatellite stable (MSS) versus unstable (MSI) carcinomas. We ran an inverse-variance weighted fixed-effects meta-analysis across GWAS in a discovery set of 4,163 population-based CRC cases with harmonized microsatellite instability (MSI) marker and imputed genotype data. For each analysis, we used log-additive logistic regression, adjusting for age, sex, and principal components to account for population substructure. We then followed up with replication of 102 SNPs that reached p-values less than 5x10-6 in 1,698 cases. A total of 845 (20.3%) cancer cases were microsatellite unstable in the discovery population and 174 (10.2%) were unstable in the replication population. No variants reached the genome-wide significance level of 5x10-8 in the discovery set. However, we identified two variants that reached a Bonferroni corrected p-value of 4.0x10-4 in the replication set. This included one variant in MLH1 (Replication: OR=1.74, 95% CI=1.53-1.98, p=1.63x10-5; Discovery+Replication: OR=1.45, 95% CI=1.37-1.54, p=9.76x10-11) and one variant in LOC105377645 (Replication: OR=1.70, 95% CI=1.49-1.94, p=5.13x10-5; Discovery+Replication: OR=1.45, 95% CI=1.37-1.54, p=9.76 x 10-11). The MLH1 gene is a DNA mismatch repair gene implicated in Lynch Syndrome, the hallmark of which is microsatellite instability. This is the first genome-wide scan to identify a common variant in MLH1 that is associated with CRC. This variant (minor allele frequency, MAF = 23% in this all European ancestry population) is located in the 5'-untranslated region of MLH1 and is thought to act as a long-range regulator of DCLK3, a potential tumor driver gene. The second variant, located in LOC105377645 with an MAF of 22%, is in an uncharacterized region of the genome and has not previously been implicated in cancer development. These findings suggest that accounting for molecular heterogeneity is important for discovery and characterization of genetic variants associated with CRC risk. We plan to run polytomous regression analyses, increase our sample size, and further investigate CRC subtypes by CIMP, BRAF mutation, KRAS mutation status. Citation Format: Tabitha A. Harrison, Yiwen Lu, Chenjie Zeng, Flora Qu, Kristin Anderson, Hermann Brenner, Daniel D. Buchanan, Peter T. Campbell, Andrew T. Chan, Jenny Chang-Claude, Graham G. Giles, Bethany Van Guelpen, Michael Hoffmeister, Mark A. Jenkins, Noralane M. Lindor, Roger L. Milne, Polly A. Newcomb, Reiko Nishihara, Michael O. Woods, Shuji Ogino, John D. Potter, Martha L. Slattery, Wei Sun, Stephen N. Thibodeau, Li Hsu, Ulrike Peters. Genome-wide association study by colorectal carcinoma subtype [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 229.

Abstract Background Previous genome-wide association studies (GWAS) have identified 42 loci (P < 5 × 10−8) associated with risk of colorectal cancer (CRC). Expanded consortium efforts facilitating the discovery of additional susceptibility loci may capture unexplained familial risk. Methods We conducted a GWAS in European descent CRC cases and control subjects using a discovery–replication design, followed by examination of novel findings in a multiethnic sample (cumulative n = 163 315). In the discovery stage (36 948 case subjects/30 864 control subjects), we identified genetic variants with a minor allele frequency of 1% or greater associated with risk of CRC using logistic regression followed by a fixed-effects inverse variance weighted meta-analysis. All novel independent variants reaching genome-wide statistical significance (two-sided P < 5 × 10−8) were tested for replication in separate European ancestry samples (12 952 case subjects/48 383 control subjects). Next, we examined the generalizability of discovered variants in East Asians, African Americans, and Hispanics (12 085 case subjects/22 083 control subjects). Finally, we examined the contributions of novel risk variants to familial relative risk and examined the prediction capabilities of a polygenic risk score. All statistical tests were two-sided. Results The discovery GWAS identified 11 variants associated with CRC at P < 5 × 10−8, of which nine (at 4q22.2/5p15.33/5p13.1/6p21.31/6p12.1/10q11.23/12q24.21/16q24.1/20q13.13) independently replicated at a P value of less than .05. Multiethnic follow-up supported the generalizability of discovery findings. These results demonstrated a 14.7% increase in familial relative risk explained by common risk alleles from 10.3% (95% confidence interval [CI] = 7.9% to 13.7%; known variants) to 11.9% (95% CI = 9.2% to 15.5%; known and novel variants). A polygenic risk score identified 4.3% of the population at an odds ratio for developing CRC of at least 2.0. Conclusions This study provides insight into the architecture of common genetic variation contributing to CRC etiology and improves risk prediction for individualized screening.

Abstract The Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) in collaboration with the Colorectal Cancer Family Registry (CCFR) aims to identify genetic variants and environmental risk factors that impact colorectal cancer (CRC). Over 30 studies from North America, Europe, and Australia participate in GECCO. These studies have collected clinical, epidemiological, and survival data, as well as blood and tumor biospecimens, for over 80,000 CRC cases and controls. The current study aims to conduct targeted deep sequencing of tumors and matching normal DNA to identify recurrent and novel somatic and germline variants in 4,200 CRC cases. To achieve this goal, an AmpliSeq targeted sequencing panel of 1.12 Mbp was constructed to sequence the coding regions of 190 significantly mutated genes identified from whole exome sequencing datasets generated by the Nurses’ Health Study and Health Professional’s Follow-up Study, and The Cancer Genome Atlas. The panel also covers coding regions of 15 genes with germline high penetrance mutations in CRC, 54 regions to detect CRC-related copy number alterations (CNAs), and microsatellite and homopolymer repeat regions to identify defective DNA mismatch repair. Primers were also included to detect Fusobacterium nucleatum DNA in tumor biopsies, as F. nucleatum is thought to promote CRC carcinogenesis. Sequencing of the DNA libraries on Illumina HiSeq 2500 produced a mean coverage of greater than 500X for tumor DNA and 100X for normal DNA, with &gt;85% of the bases covered at the target at 50x. So far, targeted sequencing of &gt;1,500 DNA samples from CRC tumors and normal tissues has identified recurrent and novel somatic mutations, germline genetic variants, and hypermutation status of the tumors due to defective DNA mismatch repair or pathogenic mutations in the POLE gene. Targeted sequencing has also allowed quantification of the F. nucleatum DNA in tumor biopsies; the results were validated by a multiplex QPCR assay. At the AACR annual meeting, we will present targeted sequencing results generated from the first two GECCO-participating studies (n=1,300 cases). These data will be valuable for future association testing of somatic mutations, CNAs, hypermutation status, and F. nucleatum with germline genetic variants, lifestyle, and environmental risk factors and survival. This large study will allow development of better strategies for diagnosis, treatment, and prevention of CRC. Citation Format: Syed H. Zaidi, Wei Sun, Jeroen Huyghe, Catherine S. Grasso, Quang Trinh, Charles Connolly, Amy French, Jasmine Mu, Marios Giannakis, Eve Shinbrot, Ivan Borozan, Michael J. Quist, Hermann Brenner, Daniel Buchanan, Peter Campbell, Andrew Chan, Jenny Chang-Claude, Vincent Ferretti, Charles Fuchs, Andrea Gsur, Marc Gunter, Tabitha Harrison, Michael Hoffmeister, Wen-Yi Huang, Paul Krzyzanowski, Stephen Lee, Mathieu Lemire, Jessica Miller, Danielle Pasternack, Cherie Teney, Elaine Mardis, Polly Newcomb, Lincoln Stein, Lee Timms, David Wheeler, Christina Yung, Niha Zubair, Levi Garraway, Shuji Ogino, Li Hsu, Steven Gallinger, Stephen Thibodeau, Thomas Hudson, Ulrike Peters. Targeted deep sequencing of colorectal tumor tissues to study associations of tumor subtypes with germline genetic, lifestyle, and environmental risk factors [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 1286. doi:10.1158/1538-7445.AM2017-1286

Genome-wide association studies have identified >50 common variants associated with kidney function, but these variants do not fully explain the variation in eGFR. We performed a two-stage meta-analysis of associations between genotypes from the Illumina exome array and eGFR on the basis of serum creatinine (eGFRcrea) among participants of European ancestry from the CKDGen Consortium ( n Stage1 : 111,666; n Stage2 : 48,343). In single-variant analyses, we identified single nucleotide polymorphisms at seven new loci associated with eGFRcrea ( PPM1J , EDEM3, ACP1, SPEG, EYA4, CYP1A1 , and ATXN2L ; P Stage1 <3.7×10 −7 ), of which most were common and annotated as nonsynonymous variants. Gene-based analysis identified associations of functional rare variants in three genes with eGFRcrea, including a novel association with the SOS Ras/Rho guanine nucleotide exchange factor 2 gene, SOS2 ( P =5.4×10 −8 by sequence kernel association test). Experimental follow-up in zebrafish embryos revealed changes in glomerular gene expression and renal tubule morphology in the embryonic kidney of acp1- and sos2 -knockdowns. These developmental abnormalities associated with altered blood clearance rate and heightened prevalence of edema. This study expands the number of loci associated with kidney function and identifies novel genes with potential roles in kidney formation.

Abstract Background: Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers, and cancer-related traits. Methods: The OncoArray can be genotyped using a novel technology developed by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers, and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy among centers and by ethnic background. Results: The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis. Conclusions: Results from these analyses will enable researchers to identify new susceptibility loci, perform fine-mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental, and lifestyle-related exposures. Impact: Ongoing analyses will shed light on etiology and risk assessment for many types of cancer. Cancer Epidemiol Biomarkers Prev; 26(1); 126–35. ©2016 AACR.