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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

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 Background Although 20 pancreatic cancer susceptibility loci have been identified through genome-wide association studies in individuals of European ancestry, much of its heritability remains unexplained and the genes responsible largely unknown. Methods To discover novel pancreatic cancer risk loci and possible causal genes, we performed a pancreatic cancer transcriptome-wide association study in Europeans using three approaches: FUSION, MetaXcan, and Summary-MulTiXcan. We integrated genome-wide association studies summary statistics from 9040 pancreatic cancer cases and 12 496 controls, with gene expression prediction models built using transcriptome data from histologically normal pancreatic tissue samples (NCI Laboratory of Translational Genomics [n = 95] and Genotype-Tissue Expression v7 [n = 174] datasets) and data from 48 different tissues (Genotype-Tissue Expression v7, n = 74–421 samples). Results We identified 25 genes whose genetically predicted expression was statistically significantly associated with pancreatic cancer risk (false discovery rate < .05), including 14 candidate genes at 11 novel loci (1p36.12: CELA3B; 9q31.1: SMC2, SMC2-AS1; 10q23.31: RP11-80H5.9; 12q13.13: SMUG1; 14q32.33: BTBD6; 15q23: HEXA; 15q26.1: RCCD1; 17q12: PNMT, CDK12, PGAP3; 17q22: SUPT4H1; 18q11.22: RP11-888D10.3; and 19p13.11: PGPEP1) and 11 at six known risk loci (5p15.33: TERT, CLPTM1L, ZDHHC11B; 7p14.1: INHBA; 9q34.2: ABO; 13q12.2: PDX1; 13q22.1: KLF5; and 16q23.1: WDR59, CFDP1, BCAR1, TMEM170A). The association for 12 of these genes (CELA3B, SMC2, and PNMT at novel risk loci and TERT, CLPTM1L, INHBA, ABO, PDX1, KLF5, WDR59, CFDP1, and BCAR1 at known loci) remained statistically significant after Bonferroni correction. Conclusions By integrating gene expression and genotype data, we identified novel pancreatic cancer risk loci and candidate functional genes that warrant further investigation.

Introduction. Acquired severe aplastic anemia (SAA) is a life-threatening disorder characterized by severe progressive pancytopenia and hypocellular bone marrow. The etiology of acquired SAA is not understood but believed to be related to abnormal immune responses to environmental exposures. We conducted a genome-wide association study (GWAS) to identify common germline variants associated with SAA. Methods. We identified 895 patients with SAA who underwent related or unrelated hematopoietic cell transplant (HCT) with clinical data and pre-HCT blood samples available in the Center for International Blood and Marrow Transplant Research (CIBMTR) database and biorepository. Pre-HCT DNA was extracted from blood of patients with SAA and genome-wide genotyping was conducted using the Illumina OmniExpress array. We excluded 93 inherited bone marrow failure cases. The SAA cases were grouped cases into discovery and validation sets based on time of batch sample receipt. Analyses were limited to patients of European ancestry based on principal component analyses to minimize the potential effect of population stratification. Controls were genomically matched and selected from previously scanned cancer-free subjects at the Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, NCI. The final analysis included 534 acquired SAA cases (359 in the discovery set and 175 in the validation set), and 2,455 controls (1,396 in the discovery set, and 1,059 in the validation set). Results. Patients with SAA in this study received HCT between 1989-2015 at a median age of 21 years, 56% were male, and the median time between SAA diagnosis and HCT was 11 months. Strong genome-wide association signals were identified across the human leukocyte antigen (HLA) genes encoded at the major histocompatibility complex (MHC) on chromosome 6p21 (Figure 1). The top SNP was located in the P4 binding pocket of the HLA class II gene HLA-DPB1(rs1042151A>G, p.Met105Val, pooled-odds ratio [OR]=1.75, 95% confidence interval [CI]=1.50-2.03, p=1.94x10-13). The expression of HLA-DP in CD19+ cells from 175 healthy donors was significantly different by rs1042151 A>G genotype (p=2.04x10-6) (Figure 2). A second SNP near HLA-B, rs28367832G>A, also reached genome-wide significance (pooled-OR=1.49, 95% CI=1.22-1.78, p=7.27x10-9). Copy-number variant analysis and next generation sequencing also identified somatic, clonal copy-neutral loss-of-heterozygosity affecting class I HLA genes in 8.6% of the SAA cases and none of the controls. Conclusion. This SAA GWAS identified strong association signals between common germline genetic variants in HLA class I and II genes and SAA. The main SNP is associated with changes in HLA-DP expression suggesting a key role for this locus in SAA etiology. This study adds further evidence to the connection between SAA and immune dysregulation. Disclosures Cerhan: Janssen: Membership on an entity's Board of Directors or advisory committees; NanoString: Research Funding; Celgene: Research Funding. Lee:Incyte: Research Funding; Syndax: Research Funding; Amgen: Research Funding; Novartis: Research Funding; Takeda: Research Funding; Kadmon: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; AstraZeneca: Research Funding.

Abstract Introduction The 2-3 fold excess risk of multiple myeloma (MM) among family members of cases suggests a heritable contribution to risk. Recently, a genome-wide association study (GWAS) identified two genome-wide significant and one promising novel loci associated with multiple myeloma risk. To confirm these associations and identify additional novel risk loci, we performed a four-center, genome-wide association meta-analysis. Methods A fixed effects model was used for the meta-analysis which included a total of 1248 cases and 1485 controls, all of European descent, genotyped and analyzed at four separate centers with samples contributed by 10 studies. After quality control and imputation using the 1000 Genomes Project, the analysis included ∼9.5 million variants (λ=1.024). Associations between (single nucleotide polymorphisms) SNP genotypes and MM risk were evaluated under a log-additive model of inheritance, with each study adjusting for age, sex, and up to 10 principal components to control for population stratification. Promising results were replicated in an independent set of 1587 cases and 1770 controls using TaqMan, for a total of 2835 and 3255 cases and controls, respectively, in a combined meta-analysis. Results The discovery meta-analysis did not reveal any genome-wide significant associations (defined as p<5 x 10-8). We used a novel pruning algorithm to identify the top 35 most promising single nucleotide polymorphisms (SNPs) to advance to replication. We successfully genotyped 22 SNPs in the replication set. In the combined discovery and replication meta-analysis, rs1345359 at 12q23.1 was the most strongly associated SNP (P=9 x 10-8, Table 1). The variant allele C was associated with reduced risk (odds ratio discovery set [OR]= 0.69, OR replication set = 0.78, OR combined = 0.74). A second locus at 20q13.2 (rs150220835), was associated with a two-fold increased risk (P=1.22 x 10-6), a borderline increased risk (P=0.0900) and 45% increased risk (P=2.44 X 10-5) in the discovery, replication, and combined analysis sets respectively (Table 1). We also confirmed the association between MM risk and two previously published SNPs (rs4487645, p=0.0007and rs105251, p=0.0044) (Broderick et al., Nat. Genet., 2011). The third previously suggested SNP (rs6746082) was of nominal significance (p=0.0517) in the meta-analysis. Discussion We confirmed the association between MM risk and two previously published SNPs and identified a possible association with a novel SNP in chromosome 12q23.1 (rs1345359). This SNP is not located in a gene nor associated with biofeatures in ENCODE, thus further examination of correlated SNPs is necessary to identify a functional SNP linked to this locus. We also found suggestive evidence for a second locus at 20q13.2 requiring additional replication. Larger studies would improve risk variant discovery for this rare hematologic malignancy. Disclosures: Wolf: Celgene: Honoraria, Research Funding; Millenium: Honoraria; Onyx: Honoraria. Anderson:Celgene, Millennium, BMS, Onyx: Membership on an entity’s Board of Directors or advisory committees; Acetylon, Oncopep: Scientific Founder , Scientific Founder Other.

Abstract Small lymphocytic lymphoma (SLL) is an incurable indolent lymphoma, and there are relatively few prognostic biomarkers for this important NHL subtype. We evaluated the hypothesis that inherited variability in cytokine and immune-related genes was associated with overall survival in SLL. We genotyped 73 SNPs in 44 candidate genes in 140 SLL patients aged 20–70 years who participated in a population-based case-control study conducted from 1998–2000 through the Surveillance, Epidemiology, and End Results (SEER) cancer registries in Detroit, Seattle, Iowa, and Los Angeles. DNA was extracted from a venous blood sample or mouthwash buccal cell sample. All genotyping was conducted at the National Cancer Institute Core Genotyping Facility using the Taqman platform. Histology, 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 in the spring of 2005. Cox proportional hazards analysis was used to estimate the hazard ratio (HR) and 95% confidence interval for the association between individual SNPs and overall survival, adjusted for age, demographic and clinical factors. Multiple simultaneous modeling strategies were used to identify the best summary multi-SNP risk score to predict survival. At last follow-up, there were 45 deaths in 140 patients (32%). The median follow-up of the 95 surviving patients was 58 months (range 24–75 months). In multivariate modeling, SNPs in IL13 (rs1800925; HRCC=2.36, 1.24–4.49), IL7R (rs1494555; HRGG =2.20, 0.84–5.76), and TNF-alpha (rs1800630; HRAC/AA=1.73, 0.95–3.17) were the strongest and most robust predictors of survival. Two or more deleterious genotypes from these three SNPs increased the risk of death (HR=2.2, 1.2–4.1) compared with one or fewer deleterious genotypes (p=0.009). Three groups (low, intermediate, and high risk) were defined by combining the SNP score and a clinical/demographic score. The 5-year Kaplan-Meier survival estimates for these groups were 85%, 65%, and 11%, respectively. Compared to patients with a low risk score, patients with intermediate (HR=2.5, 1.2–5.1) or high (HR=11, 4.3–27.7) risk scores had poorer overall survival (p=3.9 x 10−8). Our preliminary results suggest that SNPs in IL13, IL7R, and TNF-alpha alone and in combination predict overall survival in SLL, lending support to the hypothesis that host genetic background is a promising class of prognostic biomarkers in SLL.

Abstract DLBCL is a curable subtype of non-Hodgkin lymphoma, although a significant number of patients do not achieve a remission or they relapse with conventional chemotherapy. While clinical variables (e.g., IPI), tumor (somatic) genetic alterations, and gene expression profiling have all been shown to predict outcome, there remains a need for additional prognostic biomarkers. One understudied class of biomarkers is host genetic background. We evaluated the hypothesis that germline variability in 73 SNPs from 44 candidate immune genes was associated with overall survival in DLBCL. We addressed this hypothesis in 365 DLBCL patients aged 20–70 years who participated in a population-based case-control study conducted from 1998–2000 (prior to the use of R-CHOP) through the Surveillance, Epidemiology, and End Results (SEER) cancer registries in Detroit, Seattle, Iowa, and Los Angeles. Germline DNA was extracted from a venous blood sample or mouthwash buccal cell sample, which was collected a median of 4.8 months after diagnosis in this population-based study. All genotyping was conducted at the National Cancer Institute Core Genotyping Facility using the Taqman platform, and was successful in over 95% of the DNA samples for the SNPs evaluated. Histology, 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 in the spring of 2005. Cox proportional hazards analysis was used to evaluate the association between individual SNPs, adjusted for age, demographic and clinical factors. Parallel modeling strategies were used to identify the best summary multi-SNP risk score to predict survival. At a median follow-up of 56 months (range, 27-78 months) for surviving patients, there were 96 deaths in 365 patients (26%). In multivariate modeling, SNPs in IL1A (rs1800587; HRCT/TT=1.90, 1.26–2.87), IL6 (rs1800795; HRGG=1.48, 0.99–2.23), IL-10 (rs1800896; HRAG/GG=1.48, 0.91–2.38), and IFNGR2 (rs2070385; HRAG/GG=1.35, 0.86–2.11) were the strongest and most robust predictors of overall survival. A summary score of the number of deleterious genotypes from these four genes in combination with clinical and demographic variables was strongly associated with survival (p=9.3 x 10−12); Kaplan-Meier 5-year survival estimates for low, intermediate, and high risk patients were 89%, 68%, and 47% respectively. In conclusion, host genetic background as measured by germline polymorphisms in immune genes including IL1A, IL6, IL10, and IFNGR2 were associated with overall survival in DLBCL after accounting for clinical and demographic factors. These promising results require confirmation and need further evaluation in patients treated with R-CHOP in conjunction with tumor and other prognostic biomarkers.

Abstract We previously identified five single nucleotide polymorphisms (SNPs) at four susceptibility loci for diffuse large B-cell lymphoma (DLBCL) in individuals of European ancestry through a large genome-wide association study (GWAS). To further elucidate genetic susceptibility to DLBCL, we sought to validate two loci at 3q13.33 and 3p24.1 that were suggestive in the original GWAS with additional genotyping. In the meta-analysis (5662 cases and 9237 controls) of the four original GWAS discovery scans and three replication studies, the 3q13.33 locus (rs9831894; minor allele frequency [MAF] = 0.40) was associated with DLBCL risk [odds ratio (OR) = 0.83, P = 3.62 × 10−13]. rs9831894 is in linkage disequilibrium (LD) with additional variants that are part of a super-enhancer that physically interacts with promoters of CD86 and ILDR1. In the meta-analysis (5510 cases and 12 817 controls) of the four GWAS discovery scans and four replication studies, the 3p24.1 locus (rs6773363; MAF = 0.45) was also associated with DLBCL risk (OR = 1.20, P = 2.31 × 10−12). This SNP is 29 426-bp upstream of the nearest gene EOMES and in LD with additional SNPs that are part of a highly lineage-specific and tumor-acquired super-enhancer that shows long-range interaction with AZI2 promoter. These loci provide additional evidence for the role of immune function in the etiology of DLBCL, the most common lymphoma subtype.

AbstractEpidemiologic studies show an increased risk of non‐Hodgkin lymphoma (NHL) in patients with autoimmune disease (AD), due to a combination of shared environmental factors and/or genetic factors, or a causative cascade: chronic inflammation/antigen‐stimulation in one disease leads to another. Here we assess shared genetic risk in genome‐wide‐association‐studies (GWAS).Secondary analysis of GWAS of NHL subtypes (chronic lymphocytic leukemia, diffuse large B‐cell lymphoma, follicular lymphoma, and marginal zone lymphoma) and ADs (rheumatoid arthritis, systemic lupus erythematosus, and multiple sclerosis). Shared genetic risk was assessed by (a) description of regional genetic of overlap, (b) polygenic risk score (PRS), (c)"diseasome", (d)meta‐analysis.Descriptive analysis revealed few shared genetic factors between each AD and each NHL subtype. The PRS of ADs were not increased in NHL patients (nor vice versa). In the diseasome, NHLs shared more genetic etiology with ADs than solid cancers (p = .0041). A meta‐analysis (combing AD with NHL) implicated genes of apoptosis and telomere length.This GWAS‐based analysis four NHL subtypes and three ADs revealed few weakly‐associated shared loci, explaining little total risk. This suggests common genetic variation, as assessed by GWAS in these sample sizes, may not be the primary explanation for the link between these ADs and NHLs.