Brooks-Wilson, Angela R

Abstract Background: We previously identified 5 SNPs at 4 susceptibility loci for diffuse large B-cell lymphoma (DLBCL) in individuals of European ancestry through a large genome-wide association study (Cerhan et al, Nat Gen 2014;46:1233-8); however, much of the heritability remains unexplained. To further elucidate genetic susceptibility to DLBCL, we sought to validate 2 loci at 3q13.33 and 3p24.1 that were suggestive in the original report. Methods: We selected two SNPs rs9831894 (3q13.33) and rs6773363 (3p24.1) for de novo replication from studies at the Mayo Clinic, MD Anderson, and Memorial Sloan Kettering. Logistic regression was used to estimate odds ratios (ORs), using a log-additive model, and adjusting for age, gender and significant eigenvectors for each genotyping center separately. For both SNPs, we then conducted a meta-analysis of all replication studies (n=3) and our original GWAS studies (n=4), encompassing in total 5662 cases and 9237 controls for rs9831894, and 5510 cases and 12,817 controls for rs6773363. Meta-analysis was conducted using the fixed-effects inverse variance method based on the β estimates and standard errors from each study. Results: In a meta-analysis of the 4 original GWAS scans (3856 cases and 7666 controls), rs9831894 (MAF=0.40) was associated with DLBCL risk (OR=0.84, P=4.52 x 10-9) and this replicated in a meta-analysis of the 3 studies with de novo genotyping (OR=0.80, P=4.17 x 10-5); the overall meta-analysis showed a strong association with DLBCL risk (OR=0.83, P=3.62 x 10-13). This locus maps near a plausible candidate gene, CD86, a protein coding gene and a member of the immunoglobulin superfamily that encodes a type I membrane protein. Binding of CD86 with cytotoxic T-lymphocyte-associated protein 4 negatively regulates T-cell activation and diminishes the immune response, while binding of CD86 with CD28 antigen is a costimulatory signal for activation of the T-cell. In a meta-analysis of the same 4 GWAS scans, rs6773363 (MAF=0.45) was tentatively associated with DLBCL risk (OR=1.17, P= 3.68 x 10-7) and this replicated in a meta-analysis of the studies with de novo genotyping (OR=1.27, P=3.78 x 10-7); the overall meta-analysis showed a strong association with DLBCL risk (OR=1.20, P=2.31 x 10-12). This locus also maps near a plausible candidate gene, eomesodermin (EOMES), a transcription factor crucial for embryonic development of the central nervous system and also putatively involved in T-cell differentiation in viral infection defense. Conclusion: In this follow-up analysis of our initial GWAS, we have identified two additional loci associated with risk of DLBCL, the most common lymphoma subtype. These loci provide additional evidence for the role of immune function in the etiology of DLBCL. Citation Format: Geffen Kleinstern, Michelle Hildebrand, Vijai Joseph, Sonja I. Berndt, Hervé Ghesquières, James McKay, Sophia S. Wang, Alexandra Nieters, David Cox, Alain Monnereau, Angela R. Brooks-Wilson, Qing Lan, Mads Melbye, Rebecca D. Jackson, Lauren R. Teras, Mark P. Purdue, Claire M. Vajdic, Demetrius Albanes, Anne Zeleniuch-Jacquotte, Simon Crouch, Yawei Zhang, Susan L. Slager, Xifeng Wu, Karin E. Smedby, Gilles Salles, Christine F. Skibola, Nathaniel Rothman, Stephen J. Chanock, James R. Cerhan. Inherited variants at 3q13.33 and 3p24.1 influences risk of diffuse large B-cell lymphoma [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 221.

Abstract A growing number of loci within the human leukocyte antigen (HLA) region have been implicated in non-Hodgkin lymphoma (NHL) etiology. Here, we test a complementary hypothesis of “heterozygote advantage” regarding the role of HLA and NHL, whereby HLA diversity is beneficial and homozygous HLA loci are associated with increased disease risk. HLA alleles at class I and II loci were imputed from genome-wide association studies (GWAS) using SNP2HLA for 3,617 diffuse large B-cell lymphomas (DLBCL), 2,686 follicular lymphomas (FL), 2,878 chronic lymphocytic leukemia/small lymphocytic lymphomas (CLL/SLL), 741 marginal zone lymphomas (MZL), and 8,753 controls of European descent. Both DLBCL and MZL risk were elevated with homozygosity at class I HLA-B and -C loci (OR DLBCL = 1.31, 95% CI = 1.06–1.60; OR MZL = 1.45, 95% CI = 1.12–1.89) and class II HLA-DRB1 locus (OR DLBCL = 2.10, 95% CI = 1.24–3.55; OR MZL = 2.10, 95% CI = 0.99–4.45). Increased FL risk was observed with the overall increase in number of homozygous HLA class II loci (P trend < 0.0001, FDR = 0.0005). These results support a role for HLA zygosity in NHL etiology and suggests that distinct immune pathways may underly the etiology of the different NHL subtypes. Significance: HLA gene diversity reduces risk for non-Hodgkin lymphoma. Cancer Res; 78(14); 4086–96. ©2018 AACR.

Key Points PRS, based on the known CLL loci, predicts CLL risk with high discrimination. This PRS predicts risk of monoclonal B-cell lymphocytosis, a precursor to CLL and a condition that has clinical impact beyond risk for CLL.

Objective Determinants of the increased risk of diffuse large B-cell lymphoma (DLBCL) in SLE are unclear. Using data from a recent lymphoma genome-wide association study (GWAS), we assessed whether certain lupus-related single nucleotide polymorphisms (SNPs) were also associated with DLBCL. Methods GWAS data on European Caucasians from the International Lymphoma Epidemiology Consortium (InterLymph) provided a total of 3857 DLBCL cases and 7666 general-population controls. Data were pooled in a random-effects meta-analysis. Results Among the 28 SLE-related SNPs investigated, the two most convincingly associated with risk of DLBCL included the CD40 SLE risk allele rs4810485 on chromosome 20q13 (OR per risk allele=1.09, 95% CI 1.02 to 1.16, p=0.0134), and the HLA SLE risk allele rs1270942 on chromosome 6p21.33 (OR per risk allele=1.17, 95% CI 1.01 to 1.36, p=0.0362). Of additional possible interest were rs2205960 and rs12537284. The rs2205960 SNP, related to a cytokine of the tumour necrosis factor superfamily TNFSF4, was associated with an OR per risk allele of 1.07, 95% CI 1.00 to 1.16, p=0.0549. The OR for the rs12537284 (chromosome 7q32, IRF5 gene) risk allele was 1.08, 95% CI 0.99 to 1.18, p=0.0765. Conclusions These data suggest several plausible genetic links between DLBCL and SLE.

Abstract Background: Genome-wide association studies (GWAS) in European populations have identified genetic risk variants associated with multiple myeloma. Methods: We performed association testing of common variation in eight regions in 1,318 patients with multiple myeloma and 1,480 controls of European ancestry and 1,305 patients with multiple myeloma and 7,078 controls of African ancestry and conducted a meta-analysis to localize the signals, with epigenetic annotation used to predict functionality. Results: We found that variants in 7p15.3, 17p11.2, 22q13.1 were statistically significantly (P < 0.05) associated with multiple myeloma risk in persons of African ancestry and persons of European ancestry, and the variant in 3p22.1 was associated in European ancestry only. In a combined African ancestry–European ancestry meta-analysis, variation in five regions (2p23.3, 3p22.1, 7p15.3, 17p11.2, 22q13.1) was statistically significantly associated with multiple myeloma risk. In 3p22.1, the correlated variants clustered within the gene body of ULK4. Correlated variants in 7p15.3 clustered around an enhancer at the 3′ end of the CDCA7L transcription termination site. A missense variant at 17p11.2 (rs34562254, Pro251Leu, OR, 1.32; P = 2.93 × 10−7) in TNFRSF13B encodes a lymphocyte-specific protein in the TNF receptor family that interacts with the NF-κB pathway. SNPs correlated with the index signal in 22q13.1 cluster around the promoter and enhancer regions of CBX7. Conclusions: We found that reported multiple myeloma susceptibility regions contain risk variants important across populations, supporting the use of multiple racial/ethnic groups with different underlying genetic architecture to enhance the localization and identification of putatively functional alleles. Impact: A subset of reported risk loci for multiple myeloma has consistent effects across populations and is likely to be functional. Cancer Epidemiol Biomarkers Prev; 25(12); 1609–18. ©2016 AACR.