Chanock, Stephen Jacob

Abstract Registry-based epidemiologic studies suggest associations between chronic inflammatory intestinal diseases and pancreatic ductal adenocarcinoma (PDAC). As genetic susceptibility contributes to a large proportion of chronic inflammatory intestinal diseases, we hypothesize that the genomic regions surrounding established genome-wide associated variants for these chronic inflammatory diseases are associated with PDAC. We examined the association between PDAC and genomic regions (±500 kb) surrounding established common susceptibility variants for ulcerative colitis, Crohn's disease, inflammatory bowel disease, celiac disease, chronic pancreatitis, and primary sclerosing cholangitis. We analyzed summary statistics from genome-wide association studies data for 8,384 cases and 11,955 controls of European descent from two large consortium studies using the summary data-based adaptive rank truncated product method to examine the overall association of combined genomic regions for each inflammatory disease group. Combined genomic susceptibility regions for ulcerative colitis, Crohn disease, inflammatory bowel disease, and chronic pancreatitis were associated with PDAC at P values < 0.05 (0.0040, 0.0057, 0.011, and 3.4 × 10−6, respectively). After excluding the 20 PDAC susceptibility regions (±500 kb) previously identified by GWAS, the genomic regions for ulcerative colitis, Crohn disease, and inflammatory bowel disease remained associated with PDAC (P = 0.0029, 0.0057, and 0.0098, respectively). Genomic regions for celiac disease (P = 0.22) and primary sclerosing cholangitis (P = 0.078) were not associated with PDAC. Our results support the hypothesis that genomic regions surrounding variants associated with inflammatory intestinal diseases, particularly, ulcerative colitis, Crohn disease, inflammatory bowel disease, and chronic pancreatitis are associated with PDAC. Significance: The joint effects of common variants in genomic regions containing susceptibility loci for inflammatory bowel disease and chronic pancreatitis are associated with PDAC and may provide insights to understanding pancreatic cancer etiology.

Abstract So far, 23 germline susceptibility loci have been associated with multiple myeloma (MM) risk. It is unclear whether the genetic variation associated with MM susceptibility also predisposes to its precursor, monoclonal gammopathy of undetermined significance (MGUS). Leveraging 2434 MM cases, 754 MGUS cases, and 2 independent sets of controls (2567/879), we investigated potential shared genetic susceptibility of MM and MGUS by (1) performing MM and MGUS genome-wide association studies (GWAS); (2) validating the association of a polygenic risk score (PRS) based on 23 established MM loci (MM-PRS) with risk of MM, and for the first time with MGUS; and (3) examining genetic correlation of MM and MGUS. Heritability and genetic estimates yielded 17% (standard error [SE] ±0.04) and 15% (SE ±0.11) for MM and MGUS risk, respectively, and a 55% (SE ±0.30) genetic correlation. The MM-PRS was associated with risk of MM when assessed continuously (odds ratio [OR], 1.17 per SD; 95% confidence interval [CI], 1.13-1.21) or categorically (OR, 1.70; 95% CI, 1.38-2.09 for highest; OR, 0.71; 95% CI, 0.55-0.90 for lowest compared with middle quintile). The MM-PRS was similarly associated with MGUS (OR, 1.19 per SD; 95% CI, 1.14-1.26 as a continuous measure, OR, 1.77, 95%CI: 1.29-2.43 for highest and OR, 0.70, 95%CI: 0.50-0.98 for lowest compared with middle quintile). MM and MGUS associations did not differ by age, sex, or MM immunoglobulin isotype. We validated a 23-SNP MM-PRS in an independent series of MM cases and provide evidence for its association with MGUS. Our results suggest shared common genetic susceptibility to MM and MGUS.

Abstract Background: Obesity and diabetes are major modifiable risk factors for pancreatic cancer. Interactions between genetic variants and diabetes/obesity have not previously been comprehensively investigated in pancreatic cancer at the genome-wide level. Methods: We conducted a gene–environment interaction (GxE) analysis including 8,255 cases and 11,900 controls from four pancreatic cancer genome-wide association study (GWAS) datasets (Pancreatic Cancer Cohort Consortium I–III and Pancreatic Cancer Case Control Consortium). Obesity (body mass index ≥30 kg/m2) and diabetes (duration ≥3 years) were the environmental variables of interest. Approximately 870,000 SNPs (minor allele frequency ≥0.005, genotyped in at least one dataset) were analyzed. Case–control (CC), case-only (CO), and joint-effect test methods were used for SNP-level GxE analysis. As a complementary approach, gene-based GxE analysis was also performed. Age, sex, study site, and principal components accounting for population substructure were included as covariates. Meta-analysis was applied to combine individual GWAS summary statistics. Results: No genome-wide significant interactions (departures from a log-additive odds model) with diabetes or obesity were detected at the SNP level by the CC or CO approaches. The joint-effect test detected numerous genome-wide significant GxE signals in the GWAS main effects top hit regions, but the significance diminished after adjusting for the GWAS top hits. In the gene-based analysis, a significant interaction of diabetes with variants in the FAM63A (family with sequence similarity 63 member A) gene (significance threshold P < 1.25 × 10−6) was observed in the meta-analysis (PGxE = 1.2 ×10−6, PJoint = 4.2 ×10−7). Conclusions: This analysis did not find significant GxE interactions at the SNP level but found one significant interaction with diabetes at the gene level. A larger sample size might unveil additional genetic factors via GxE scans. Impact: This study may contribute to discovering the mechanism of diabetes-associated pancreatic cancer.

Abstract We evaluated the joint associations between a new 313-variant PRS (PRS313) and questionnaire-based breast cancer risk factors for women of European ancestry, using 72 284 cases and 80 354 controls from the Breast Cancer Association Consortium. Interactions were evaluated using standard logistic regression and a newly developed case-only method for breast cancer risk overall and by estrogen receptor status. After accounting for multiple testing, we did not find evidence that per-standard deviation PRS313 odds ratio differed across strata defined by individual risk factors. Goodness-of-fit tests did not reject the assumption of a multiplicative model between PRS313 and each risk factor. Variation in projected absolute lifetime risk of breast cancer associated with classical risk factors was greater for women with higher genetic risk (PRS313 and family history) and, on average, 17.5% higher in the highest vs lowest deciles of genetic risk. These findings have implications for risk prevention for women at increased risk of breast cancer.

Abstract Background. The strongest established prognostic factors for follicular lymphoma are age and clinical factors. Biologic studies suggest a major role for the host immunologic environment in follicular lymphomagenesis, which is in part determined by host genetic background. Cytokines are key regulators of immune function and regulation, are highly polymorphic, and have been implicated in lymphoma etiology and prognosis. We evaluated the hypothesis that inherited variability in cytokine and related immune genes impact overall survival in follicular lymphoma. Methods. We genotyped 73 single nucleotide polymorphisms (SNPs) from 44 candidate cytokine and immune genes in 278 follicular lymphoma patients who participated in a population-based case-control study conducted from 1998–2000 in the Detroit, Iowa, Los Angeles and Seattle SEER (Surveillance, Epidemiology and End Results) cancer registries. Baseline clinical data and survival through early 2005 were obtained from cancer registry files. Cox proportional hazards analysis was used to estimate hazard ratios (HR) and corresponding 95% confidence intervals for the association between individual SNPs and overall survival, adjusting for age, demographic and clinical factors. We also used parallel modeling strategies to identify the best summary multi-SNP risk score to predict survival, and applied these results in a time-dependent receiver-operator characteristics (ROC) analysis. Results. The median age at diagnosis was 57 years (range, 25–74), and 59 (21%) of the patients died during follow-up, with a median follow-up of 59 months (range, 27 – 78 months) for surviving patients. In multivariate modeling, SNPs in IL8 (rs4073; HRTT=2.14, 1.26–3.63), IL2 (rs2069762; HRGT/TT=1.80, 1.06–3.05), IL12B (rs3212227; HRAA/CC=1.83, 1.06–3.06), and IL1RN (rs454078; HRAA=1.93, 1.11–3.34) were the strongest and most robust predictors of survival. A summary score of the number of deleterious genotypes from these four genes was strongly associated with survival (p=1.4 × 10−5) after accounting for demographic and clinical variables (HR=2.06 per deleterious genotype, 1.52–2.79). A combination of the four SNPs and the demographic and clinical risk scores was strongly associated with survival (p=1.8 × 10−11); the 5-year Kaplan Meier survival estimates were 96% (93%–100%), 72% (62%–83%) and 58% (48%–72%) for low, intermediate, and high risk groups respectively. In a time-dependent ROC analysis the three risk groups had an area under the curve (AUC) of 0.83 at 72 months of follow-up (95% CI 0.72–0.93). Conclusion: Host genetic variability in immune genes, particularly IL8, IL2, IL12B, and IL1RN, individually and particularly in combination, was associated with overall survival in follicular lymphoma after accounting for demographic and clinical factors. Host immunogenetics is a promising class of prognostic factors in follicular lymphoma that warrants further evaluation.

Abstract Background: Mantle cell lymphoma (MCL) is an incurable non-Hodgkin lymphoma. MCL is characterized by the chromosomal translocation t(11;14) leading to overexpression of cyclin D1 (CCND1), a regulator of the cell cycle. NF-κB plays a central role in key cellular processes, including cell cycle regulation and apoptosis, and it has been shown to be constitutively activated in MCL cell lines and in patient biopsy samples and to play a key role in the growth and survival of MCL cells. In an exploratory study, we evaluated the hypothesis that germline variation in candidate genes from the cell cycle and NF-κB pathways predict overall survival in MCL. Methods: We genotyped 235 SNPs from 29 cell cycle genes and 447 SNPs from 55 NF-κB genes in 39 MCL patients aged 38–64 years who participated in a population-based study conducted from 1998–2000 through the Surveillance, Epidemiology, and End Results (SEER) cancer registries in Detroit, Seattle, Iowa, and Los Angeles county. Tagging single nucleotide polymorphisms (SNPs) were selected from HapMap. Stage, presence of B-symptoms, first course of therapy, date of last follow-up, and vital status were derived from linkage to registry databases at each study site. To assess the statistical significance of a gene, we first used principal components analysis to capture the genetic variation of the SNPs within a gene. Cox proportional hazards analysis was then used to assess the association between the top principal components from a gene with overall survival. Results: Through early 2005, there were 22 deaths in 39 patients (56%). The median follow-up of the 17 surviving patients was 56 months (range 36–70). Eleven of the 55 genes (TNFSF14 p=0.0007, NF-κBIA p=0.003, IL1R2 p=0.01, TNFRSF25 p=0.02, TNFSF13B p=0.02, FAS p=0.03, TLR2 p=0.04, TNFSF10D p=0.04, TNFSF10 p=0.06, MAP3K2 p=0.06) in the NF-κB pathway were associated with overall survival. In the cell cycle pathway, only 3 of the 29 genes (CASP5 p=0.06, CASP9 p=0.09, BCL2 p=0.09) were associated with overall survival, and a previously reported SNP in CCND1 (rs603965) showed no association (p=0.5). Permutation p-values for observing at least this number of associated tests in each pathway due to chance (from multiple testing) was p=0.8 for the cell cycle pathway and p=0.03 for NF-κB pathway. The small sample size precluded multi-gene modeling. Conclusion: In a population series of MCL patients, we found suggestive evidence that host genetic variation in candidate NF-κB pathway genes affects overall survival. These results complement tumor expression data implicating this pathway in the pathogenesis of MCL. In addition, such findings further support the value of developing therapeutic targets from this pathway.

Abstract Background. Intracellular one-carbon transfer reactions are essential for nucleotide synthesis and methylation of biologic compounds including DNA. Previous studies have linked genetic variants in one-carbon metabolism genes with risk of developing NHL, but little is known regarding the impact of these variants on disease outcome. We evaluated the hypothesis that inherited genetic variation in genes involved in one-carbon metabolism is associated with overall survival in DLBCL. Methods. We genotyped 30 single nucleotide polymorphisms (SNPs) from 18 candidate one-carbon metabolism genes in 215 DLBCL patients who participated in a population-based case-control study conducted from 1998–2000 using the SEER (Surveillance, Epidemiology and End Results) cancer registries in the Detroit, Iowa, Los Angeles and Seattle. Stage, B-symptoms, first course of therapy, date of last follow-up and vital status through early 2005 were obtained from cancer registry files. Cox proportional hazards analysis was used to estimate hazard ratios (HR) and corresponding 95% confidence intervals for the association between individual SNPs and overall survival, adjusting for age, demographic and clinical factors. We also used parallel modeling strategies to identify the best summary multi-SNP risk score to predict survival. Results. The median age at diagnosis was 57 years (range, 20–74), and 50 (23%) of the patients died during follow-up, with a median follow-up of 57 months (range, 31–78 months) for surviving patients. After adjusting for demographic and clinical variables, SNPs in SHMT1 (rs1979276; HRCT/TT=2.47, 1.31–4.67), BHMT (rs585800; HRAT/TT=2.02, 1.16–3.54), and TCN1 (rs526934; HRTT=1.86, 1.04–3.33) were the strongest and most robust predictors of survival. A summary score of the number of deleterious genotypes (0–3) from these three genes was strongly associated with survival (p=7.9 x 10−5) after accounting for demographic and clinical variables (HR=2.58 per deleterious genotype, 95% CI 1.75–3.80). A risk score combining the three SNPs with clinical and demographic variables (score of 0 to 5) was even more strongly associated with survival (p=1.4 x 10−13); the Kaplan Meier survival curves are shown in the Figure. In a time-dependent ROC analysis, the combined risk score had a concordance index of 0.75 at 5 years of follow-up (95% CI 0.69–0.81). Conclusion: Host genetic variation in the one-carbon metabolism genes SHMT1, BHMT, and TCN1, individually and particularly in combination, was associated with overall DLBCL survival after accounting for clinical and demographic factors, supporting a role for this pathway in disease progression. Future work should evaluate interactions of genes from this pathway with dietary nutrients and therapeutic agents in DLBCL prognosis. Figure Figure

AbstractPrevious transcriptome‐wide association studies (TWAS) have identified breast cancer risk genes by integrating data from expression quantitative loci and genome‐wide association studies (GWAS), but analyses of breast cancer subtype‐specific associations have been limited. In this study, we conducted a TWAS using gene expression data from GTEx and summary statistics from the hitherto largest GWAS meta‐analysis conducted for breast cancer overall, and by estrogen receptor subtypes (ER+ and ER−). We further compared associations with ER+ and ER− subtypes, using a case‐only TWAS approach. We also conducted multigene conditional analyses in regions with multiple TWAS associations. Two genes, STXBP4 and HIST2H2BA, were specifically associated with ER+ but not with ER– breast cancer. We further identified 30 TWAS‐significant genes associated with overall breast cancer risk, including four that were not identified in previous studies. Conditional analyses identified single independent breast‐cancer gene in three of six regions harboring multiple TWAS‐significant genes. Our study provides new information on breast cancer genetics and biology, particularly about genomic differences between ER+ and ER− breast cancer.

Abstract Background: Lipid traits have been inconsistently linked to risk of non-Hodgkin lymphoma (NHL). We examined the association of genetically predicted lipid traits with risk of diffuse large B-cell lymphoma (DLBCL), chronic lymphocytic leukemia (CLL), follicular lymphoma (FL), and marginal zone lymphoma (MZL) using Mendelian randomization (MR) analysis. Methods: Genome-wide association study data from the InterLymph Consortium were available for 2,661 DLBCLs, 2,179 CLLs, 2,142 FLs, 824 MZLs, and 6,221 controls. SNPs associated (P < 5 × 10−8) with high-density lipoprotein (HDL, n = 164), low-density lipoprotein (LDL, n = 137), total cholesterol (TC, n = 161), and triglycerides (TG, n = 123) were used as instrumental variables (IV), explaining 14.6%, 27.7%, 16.8%, and 12.8% of phenotypic variation, respectively. Associations between each lipid trait and NHL subtype were calculated using the MR inverse variance–weighted method, estimating odds ratios (OR) per standard deviation and 95% confidence intervals (CI). Results: HDL was positively associated with DLBCL (OR = 1.14; 95% CI, 1.00–1.30) and MZL (OR = 1.09; 95% CI, 1.01–1.18), while TG was inversely associated with MZL risk (OR = 0.90; 95% CI, 0.83–0.99), all at nominal significance (P < 0.05). A positive trend was observed for HDL with FL risk (OR = 1.08; 95% CI, 0.99–1.19; P = 0.087). No associations were noteworthy after adjusting for multiple testing. Conclusions: We did not find evidence of a clear or strong association of these lipid traits with the most common NHL subtypes. While these IVs have been previously linked to other cancers, our findings do not support any causal associations with these NHL subtypes. Impact: Our results suggest that prior reported inverse associations of lipid traits are not likely to be causal and could represent reverse causality or confounding.

Abstract Persons of African ancestry (AA) have a twofold higher risk for multiple myeloma (MM) compared with persons of European ancestry (EA). Genome-wide association studies (GWASs) support a genetic contribution to MM etiology in individuals of EA. Little is known about genetic risk factors for MM in individuals of AA. We performed a meta-analysis of 2 GWASs of MM in 1813 cases and 8871 controls and conducted an admixture mapping scan to identify risk alleles. We fine-mapped the 23 known susceptibility loci to find markers that could better capture MM risk in individuals of AA and constructed a polygenic risk score (PRS) to assess the aggregated effect of known MM risk alleles. In GWAS meta-analysis, we identified 2 suggestive novel loci located at 9p24.3 and 9p13.1 at P < 1 × 10−6; however, no genome-wide significant association was noted. In admixture mapping, we observed a genome-wide significant inverse association between local AA at 2p24.1-23.1 and MM risk in AA individuals. Of the 23 known EA risk variants, 20 showed directional consistency, and 9 replicated at P < .05 in AA individuals. In 8 regions, we identified markers that better capture MM risk in persons with AA. AA individuals with a PRS in the top 10% had a 1.82-fold (95% confidence interval, 1.56-2.11) increased MM risk compared with those with average risk (25%-75%). The strongest functional association was between the risk allele for variant rs56219066 at 5q15 and lower ELL2 expression (P = 5.1 × 10−12). Our study shows that common genetic variation contributes to MM risk in individuals with AA.