Citations

Abstract Background: Persons of African ancestry (AA) have a 2-3-fold higher risk of multiple myeloma (MM) than persons of European ancestry (EA). Like other B-cell malignancies, genome-wide association scans (GWAS) have identified MM risk variants in the HLA region in persons of EA. We conducted a case-control analysis with data from the National Marrow Donor Program (NMDP)1comprising MM patients typed for bone marrow transplant to donor controls matched by race-ethnicity, and found associations between specific HLA alleles/haplotypes and MM risk that varied by race and ethnicity. To confirm our results and identify additional novel signals, we have now investigated associations between HLA alleles and haplotypes and MM risk in the African American Multiple Myeloma Study (AAMMS) Cohort. Methods: The source of subjects was the AAMMS, in which AA MM patients were identified from 10 cancer centers and 4 Surveillance, Epidemiology and End-Results (SEER) Program cancer registries in order to identify genetic risk factors for MM among AAs. A GWAS was conducted using the Illumina Human Core BeadChip array on DNA samples from 1,305 AA MM patients in the AAMMS comparing results to those from 7,078 AA controls with GWAS data generated from the Illumina 1MDuo2. The major histocompatibility complex (MHC) region single nucleotide polymorphisms (SNPs) were imputed to classical HLA variants using HIBAG. Unconditional logistic regression was used to estimate HLA associations, adjusting for sex, age and the first 2 principal components. P-values were adjusted for false discovery rate (FDR) for each locus group. Results: We did not identify any single HLA alleles associated with MM risk among AAs. However, several B*07:02-containing haplotypes were associated with MM risk (odds ratios [OR] ranging from 2.38 to 2.64 and FDR P-values ranging from 1.43 x 10-6 to 3.57 x 10-8). We found associations between MM risk and genotypes containing DRB3*02:02, including DRB3*02:02~DRB1*11:01+ DRB3*02:02~DRB1*11:01 (OR=1.93, PFDR= 9.36 x 10-5) similar to those observed in the NMDP study1. Novel findings included associations between MM risk and HLA Class I haplotypes B*53:01+ B*57:01 (OR=1.94, PFDR= 0.003) and C04:01~B*53:01+C*06:02~B*57:01 (OR=1.96, PFDR= 0.0050). Results from an ongoing meta-analysis between the two data sets (one based on an imputed GWAS and one based on NMDP HLA typing) will be presented. Conclusions: This study is the second to examine HLA alleles and risk of MM among AA's and is by far the largest. We confirmed a previously observed association between an HLA Class II DRB3 variant and MM risk and confirmed an association with B*07 haplotypes previously observed among EAs1. We also identified novel associations between other HLA Class I haplotypes and MM risk in AA's. Because HLA is highly polymorphic, many HLA alleles are rare variants for which genetic associations are difficult to detect without very large sample sizes. Further investigation with large sample sizes will be necessary to refine these associations in order to better identify the underlying causal alleles and determine the functional significance of these HLA associations. 1Beksac M, Gragert L, Fingerson S, et al.: HLA polymorphism and risk of multiple myeloma.Leukemia. 2016 Jul 27. doi: 10.1038/leu.2016.199. 2Rand KA, Song C, Hwang AE, et al. Genetic susceptibility markers of multiple myeloma in African-Americans. Abstract # 2030, 56th Annual American Society of Hematology Meeting, San Francisco, California, 2014. Disclosures Ailawadhi: Pharmacyclics: Consultancy; Novartis: Consultancy; Amgen Inc: Consultancy; Takeda Oncology: Consultancy. Nooka:Spectrum, Novartis, Onyx pharmaceuticals: Consultancy. Zonder:Pharmacyclics: Other: DSMC membership; Prothena: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Bristol Myers Squibb: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Janssen: Consultancy, Honoraria. Lonial:BMS: Consultancy; Novartis: Consultancy; Millenium: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Merck: Consultancy; Celgene: Consultancy; BMS: Consultancy; Novartis: Consultancy; Onyx: Consultancy; Janssen: Consultancy; Onyx: Consultancy.

AbstractOver 22,000 cases of ovarian cancer were diagnosed in 2007 in the United States, but only a fraction of them can be attributed to mutations in highly penetrant genes such as BRCA1. To determine whether low-penetrance genetic variants contribute to ovarian cancer risk, we genotyped 1,536 single nucleotide polymorphisms (SNP) in several candidate gene pathways in 848 epithelial ovarian cancer cases and 798 controls in the North Carolina Ovarian Cancer Study (NCO) using a customized Illumina array. The inflammation gene interleukin-18 (IL18) showed the strongest evidence for association with epithelial ovarian cancer in a gene-by-gene analysis (P = 0.002) with a <25% chance of being a false-positive finding (q value = 0.240). Using a multivariate model search algorithm over 11 IL18 tagging SNPs, we found that the association was best modeled by rs1834481. Further, this SNP uniquely tagged a significantly associated IL18 haplotype and there was an increased risk of epithelial ovarian cancer per rs1834481 allele (odds ratio, 1.24; 95% confidence interval, 1.06-1.45). In a replication stage, 12 independent studies from the Ovarian Cancer Association Consortium (OCAC) genotyped rs1834481 in an additional 5,877 cases and 7,791 controls. The fixed effects estimate per rs1834481 allele was null (odds ratio, 0.99; 95% confidence interval, 0.94-1.05) when data from the 12 OCAC studies were combined. The effect estimate remained unchanged with the addition of the initial North Carolina Ovarian Cancer Study data. This analysis shows the importance of consortia, like the OCAC, in either confirming or refuting the validity of putative findings in studies with smaller sample sizes. (Cancer Epidemiol Biomarkers Prev 2008;17(12):3567–72)