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 & lt; 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 & lt; .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.

Abstract: Multiple myeloma (MM) is a neoplasm thought to arise from a damaged germinal center B-cell that progresses to a plasma cell clone arising in bone marrow. MM comprises 20% of all hematologic cancer deaths. Persons of African ancestry (AA) have a 1.5 to 2-fold higher risk compared to individuals of European ancestry (EA). Genetically driven differences in hematopoiesis may lead to variation in the levels white blood cell (WBC) subsets which could, in turn, be associated with MM etiology. There are differences in genetic determinants of WBC traits between EA and AA populations, with possible implications for the racial disparity in risk. We tested the above hypothesis using Mendelian randomization (MR), an approach that leverages genetic determinants of specific traits (i.e. WBC counts) to estimate their effects on the risk of an outcome; and a transcriptome-wide association study (TWAS), which utilizes genetic predictors of gene expression to identify susceptibility genes. These analytic approaches were applied to data from the African American Multiple Myeloma Study (AAMMS) consisting of 1813 cases and 8871 AA cancer-free controls to examine how differences in heritable WBC gene expression profiles influence MM risk. Genetic determinants of variation in WBC subsets in AA were obtained from the literature and supplemented with new genome-wide association findings in AA subjects from the UK Biobank cohort (n=6108). Odds ratios (OR) for MM per 1 standard deviation (SD) increase in each WBC phenotype were estimated using independent (linkage disequilibrium (LD) r2 〈 0.10) variants with P 〈 10-6 as genetic instruments. Analyses based on variants associated with WBC traits in AA populations did not identify any statistically-significant associations between MM risk and WBC overall (p=0.81, using 15 SNPs) or subsets (lymphocytes, monocytes, eosinophils, neutrophils and basophils, p 〉 0.05 for each). However, when we applied genetic determinants of WBC identified in 330,000 cancer-free EA UK Biobank participants (P 〈 10-8, replication P 〈 0.05, LD r2 〈 0.05), a statistically significant inverse relationship emerged between increasing lymphocyte counts and MM risk (OR=0.80, 95% CI: 0.66-0.97, p=0.02, using 385 SNPs), as well as increasing basophil counts (OR=0.63, 95% CI: 0.41-0.96, p=0.03, using 140 SNPs). Next, we examined the association between WBC gene expression profiles and MM risk in AAMMS data. We applied published and validated ancestry-specific models developed using the PrediXcan approach, which leverage germline genetic and transcriptomic data from the Multi-Ethnic Study of Atherosclerosis (MESA) (Mogil et al. PMID: 30096133). The primary TWAS used gene expression models trained in AA subjects (n=233), with sensitivity analyses using models developed in AA and Hispanic subjects (n=585). The TWAS significance threshold was based on the number of genes with significant germline prediction models (p 〈 0.05 and R2 ≥0.05) in AA, corresponding to P 〈 0.05/2700 = 1.85×10-5. The expression of two genes was significantly associated with MM risk: KANK1at 9p24.3 (P = 1.01×10-5) and DNAJC27at 2p23.3 (P = 1.56×10-5). KANK1is a candidate tumor suppressor gene for renal cell carcinoma and has recently been associated with MM risk in AA [Du, Blood 2017 130:3058]. Here we provide additional evidence for its role in MM etiology via gene expression-mediated mechanisms. DNAJC27 (previously known as RBJ) is a novel MM risk gene linked to constitutive activation of ERK in solid tumors. We also identified two suggestively associated genes: PRR14 (P = 1.34×10-4; combined AA-Hispanic sample: P = 1.56×10-6), which has been linked to MM risk in EA populations, and PARP16 (P = 9.46×10-5). To our knowledge this is the first study to comprehensively examine variation in WBC traits and gene expression profiles with respect to MM risk in AA. Our TWAS analysis leveraged data from the largest collection of genetic and gene expression data in AA, enabling ancestry-matched inference and identification of two novel risk genes. Although the limited availability of genetic instruments for WBC limited the power of MR analysis, findings using variants identified in European populations may offer some insight into trans-ethnic etiologic pathways and contribute to risk stratification strategies using genetic and blood cell count biomarkers. Future studies, particularly with MGUS-free controls, are needed to validate these results. Disclosures Song: Millennium Pharmaceuticals Inc: Employment. Rand:Ancestry.com: Employment. Ailawadhi:Cellectar: Research Funding; Janssen: Consultancy, Research Funding; Celgene: Consultancy; Pharmacyclics: Research Funding; Amgen: Consultancy, Research Funding; Takeda: Consultancy. Nooka:Takeda: Honoraria, Other: advisory board participation; Janssen: Honoraria, Other: advisory board participation; GSK: Honoraria, Other: advisory board participation; Spectrum pharmaceuticals: Honoraria, Other: advisory board participation; Adaptive technologies: Honoraria, Other: advisory board participation; Amgen: Honoraria, Other: advisory board participation; Celgene: Honoraria, Other: advisory board participation; BMS: Honoraria, Other: advisory board participation. Singhal:Bureau of Millennium/Takeda, Celgene, Janssen, Celgene, Bristol-Myers Squibb and Bluebird: Speakers Bureau. van Rhee:Takeda: Consultancy; Sanofi Genzyme: Consultancy; Castleman Disease Collaborative Network: Consultancy; EUSA: Consultancy; Adicet Bio: Consultancy; Kite Pharma: Consultancy; Karyopharm Therapeutics: Consultancy. Mehta:Millennium/Takeda, Celgene; stock in Celgene, Bristol-Myers Squibb and Bluebird: Speakers Bureau. Wolf:Takeda: Consultancy; Celgene: Consultancy; Novartis: Consultancy; Janssen: Consultancy; Amgen: Consultancy. Martin:Roche and Juno: Consultancy; Amgen, Sanofi, Seattle Genetics: Research Funding. Fiala:Incyte: Research Funding. Terebelo:Jannsen: Speakers Bureau; Celgene: Honoraria; Newland Medical Asociates: Employment. Anderson:Bristol-Myers Squibb: Other: Scientific Founder; Oncopep: Other: Scientific Founder; Amgen: Consultancy, Speakers Bureau; Janssen: Consultancy, Speakers Bureau; Takeda: Consultancy, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; Sanofi-Aventis: Other: Advisory Board. Vij:Bristol-Myers Squibb: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Genentech: Honoraria; Janssen: Honoraria; Karyopharm: Honoraria; Sanofi: Honoraria; Takeda: Honoraria, Research Funding. Bernal-Mizrachi:TAKEDA: Research Funding; Kodikas Therapeutic Solutions, Inc: Equity Ownership; Winship Cancer Institute: Employment, Patents & Royalties. Morgan:Amgen, Roche, Abbvie, Takeda, Celgene, Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Other: research grant, Research Funding. Zonder:Celgene Corporation: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Intellia: Consultancy, Membership on an entity's Board of Directors or advisory committees; Caelum: Consultancy, Membership on an entity's Board of Directors or advisory committees; Alnylam: Consultancy, Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Consultancy, Membership on an entity's Board of Directors or advisory committees. Huff:Member of Safety Monitoring Board for Johnson and Johnson: Membership on an entity's Board of Directors or advisory committees; Karyopharm, Sanofi, MiDiagnostics: Consultancy. Lonial:Karyopharm: Consultancy; Takeda: Consultancy, Research Funding; Amgen: Consultancy; BMS: Consultancy; Janssen: Consultancy, Research Funding; GSK: Consultancy; Celgene Corporation: Consultancy, Research Funding; Genentech: Consultancy. Orlowski:Poseida Therapeutics, Inc.: Research Funding.

Abstract: Background: Persons of African ancestry (AA) experience a 1.5-2-fold risk of multiple myeloma (MM) compared to persons of European ancestry (EA). We assembled a set of MM patients with self-reported AA in order to evaluate the contribution of genetics to etiology in this high-risk group. Methods: Here we present the results of a meta-analysis of two GWAS in 1,813 cases and 8,871 controls of AA. We also conducted an admixture mapping scan to identify risk alleles associated with local ancestry, 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. Finally, we conducted an eQTL analysis measuring gene expression in those genes harboring a risk variant in malignant plasma cells from 292 of the patients from a single site. Results: In GWAS analysis, we identified two suggestive novel loci located at 9p24.3 and 9p13.1 at P & lt;1 × 10-6, but 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. 20 of the 23 known EA risk variants showed directional consistency and 9 replicated at P & lt;0.05 in AA individuals. In eight regions, we identified markers that better capture MM risk in persons of AA. AA individuals with a PRS in the top 10% had a 1.82-fold (95%CI: 1.56, 2.11) increased MM risk compared to 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). Conclusion: Our study shows that common genetic variation contributes to MM risk individuals of AA. This abstract is also being presented as Poster C040. Citation Format: Zhaohui Du, Niels Weinhold, Gregory Chi Song, Kristen A. Rand, David J. Van Den Berg, Amie E. Hwang, Xin Sheng, Victor Hom, Sikander Ailawadhi, Ajay K. Nooka, Seema Singhal, Karen Pawlish, Edward Peters, Cathryn Bock, Ann Mohrbacher, Alexander Stram, Sonja I. Berndt, William J. Blot, Graham Casey, Victoria L. Stevens, Rick Kittles, Phyllis J. Goodman, W. Ryan Diver, Anselm Hennis, Barbara Nemesure, Eric A. Klein, Benjamin A. Rybicki, Janet L. Stanford, John S. Witte, Lisa Signorello, Esther M. John, Leslie Bernstein, Antoinette Stroup, Owen W. Stephens, Maurizio Zangari, Frits Van Rhee, Andrew Olshan, Wei Zheng, Jennifer J. Hu, Regina Ziegler, Sarah J. Nyante, Sue Ann Ingles, Michael Press, John David Carpten, Stephen Chanock, Jayesh Mehta, Graham A Colditz, Jeffrey Wolf, Thomas G. Martin, Michael Tomasson, Mark A. Fiala, Howard Terebelo, Nalini Janakiraman, Laurence Kolonel, Kenneth C. Anderson, Loic Le Marchand, Daniel Auclair, Brian C.-H. Chiu, Elad Ziv, Daniel Stram, Ravi Vij, Leon Bernal-Mizrachi, Gareth J. Morgan, Jeffrey A. Zonder, Carol Ann Huff, Sagar Lonial, Robert Z. Orlowski, David V. Conti, Christopher A. Haiman, Wendy Cozen. A meta-analysis of genome-wide association study and eQTL analysis of multiple myeloma among African Americans [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr PR05.

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 & lt; 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.

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.

Abstract: Abstract 4002 African-Americans (AA) have a 2–3-fold higher risk of multiple myeloma (MM) relative to Whites (Gebregziabher, 2006). We have formed a consortium and are conducting a multi-center study with 9 clinical centers and 4 NCI Surveillance, Epidemiology and End-Results (SEER) Program population-based cancer registries to determine the causes of the disease in this population and explain the excess risk (Myeloma in African-American Patients, MAP). Participation involves providing a blood or saliva specimen for DNA and answering a lifestyle and medical history questionnaire. At the end of the data collection period, a genome-wide scan will be performed and our results compared to those from 2,000 African-American controls participating in cohort studies. Patients with African ancestry (predominantly African-Americans) are identified from outpatient clinic rosters or from population-based cancer registries. For patients recruited at clinics, information on subtype, cytogenetics, FISH and lytic bone lesions is abstracted from medical records. To date, 601 patients have agreed to be in the study and we have received DNA samples from 592 patients; 54.6% are female and 45.4% are male. The mean age at diagnosis is 57 years (SD =11.2) with a median age at diagnosis of 58 years (range 27 to 90 years of age). Of the 514 subjects who completed a questionnaire, 7.8% were obese at age 20 (body mass index 〉 30) and 39% were obese 5 years prior to diagnosis. A first-degree relative with MM was reported by 17 cases (3%), 74% higher than the lifetime risk of 1.7% in the general population based on SEER data. In addition, cases reported 21 first-degree relatives with leukemia (4%), 7 with non-Hodgkin lymphoma (1%) and 14 with Hodgkin lymphoma (3%). To date, clinical information has been abstracted for 351 patients. Of these, 207 (58%) have active disease with the following distribution: stage I (30%), stage II (27%) and stage III (43%). The remainder have relapsed (13%), refractory (1%), relapsed and refractory (4%), or smoldering myeloma (6%), or are in remission (18%). The subtype distribution is: IgG (74%), IgA (11.4%), IgD (0.9%) and IgM (0.3%), and light chain only (13.5%); a distribution significantly different from that observed in a predominantly White population (P 〈 0.007) (Kyle, 2003), (Table 1). Lytic bone lesions were present in 67% of patients, similar to the prevalence observed in other series. FISH and cytogenetics data on hyperdiploidy, deletions in chromosome 13 and 17p, and IGH translocations are being collected on this large cohort of African-Americans patients and will be presented at the ASH meeting. Disease characteristics in AA patients appear to be different than those previously reported in predominantly White populations. Table 1. Type of multiple myeloma and presence of bony lesions in 351 African-American patients. African-American Patients Mayo Clinic1 n % % Type     IgA 38 11.4 20     IgD 3 0.9 〈 10     IgG 247 74 50     IgM 1 0.3 〈 10     Light Chain only 45 13.5 20     Total 334     Not Available 17 Lytic Bone Lesions     Present 160 67 70     Absent 79 33     Total 239     Not Available 112 1 Kyle RA, Gertz MA, Witzig TE, Lutz JA, Lacy MQ, Dispenzieri A, Fonseca R, Rajkumar SV, Offord JR, Larson DR, Plevak ME, Themeau TM, Gregg PR, Review of 1,027 patients with newly diagnosed multiple myeloma. Mayo Clin Proc, 78: 21–33, 2003. Disclosures: No relevant conflicts of interest to declare.

Abstract: Multiple myeloma (MM) is twice as common in African Americans (AA) compared to European Americans (EA). The reported familial clustering and the elevated MM risk among first-degree relatives of cases implicate genetic susceptibility. Previous genome-wide association studies (GWAS) in EA have identified 16 novel risk loci. In this study, we tested the generalizability of the established risk alleles to AA and conducted a meta-GWAS analysis using two sets of AA to identify additional novel common MM risk variants. In the first study, we genotyped 1,305 incident AA MM cases from the African American Multiple Myeloma Study (AAMMS) using the Illumina HumanCore GWAS array and compared them to 7,078 AA controls from the African Ancestry Prostate Cancer Consortium (AAPC) and African Ancestry Breast Cancer Consortium (AABC) using the Illumina 1M-Duo. In the second study, 95 additional AAMMS cases and 435 AA MM cases from the University of Arkansas for Medical Sciences (UAMS) were genotyped using the Illumina MegaBead Chip and compared to 2,390 AA controls from the Multiethnic Cohort. The Haplotype Reference Consortium (HRC) was used to impute the overlapping typed SNPS from each GWAS case and control set together. Per-allele risk associations were tested for 8,715,278 overlapping genotyped and imputed variants with & gt;1% frequency and & gt;0.8 imputation score using unconditional logistic regression in both sets, and the combined effects were estimated using a fixed-effect meta-analysis. Of the 16 reported risk loci discovered in EA, directional consistency was present for 15 variants; eight of these replicated at nominal significance p & lt;0.05, with the most statistically significant variant being rs4487645 at 7p15.3 (OR=1.38, p=3.56×10-6). AA individuals with polygenic risk scores from these 16 variants (PRS) in the top 10% stratum had a 1.44-fold increased MM risk compared to those with a PRS in the 25th -75th percentiles. Additionally, we identified three suggestive novel loci located at 12q12, 9p24.3 and 9p13.1 at p & lt;1×10-6, with ORs ranging from 1.25-1.55, but none reached genome-wide significance. The variant at 9p24.3 is located in an intron in the KANK1 gene and a correlated SNP in EAs (r2=0.5) is strongly associated with gene expression in neoplastic plasma cells (unpublished, Weinhold and Morgan). Our study replicated most of the reported risk loci discovered among EA, demonstrated that a PRS constructed using the 16 reported risk alleles was associated with MM risk, and provides suggestive evidence for additional loci associated with MM risk in AAs. Citation Format: Zhaohui Du, Chi Song, Kristin Rand, Niels Weinhold, David Van Den Berg, Amie Hwang, Xin Sheng, Victor Hom, Sikander Ailawadhi, Ajay K. Nooka, Seema Singhal, Karen Pawlish, Edward S. Peters, Cathryn Bock, Ann Mohrbacher, Alexander Stram, Sonja I. Berndt, William Blot, John David Carpten, Antoinette Stroup, Andrew Olshan, Wei Zhang, African Ancestry Breast & Prostate Consortium, Stephen Chanock, Jayesh Mehta, Graham A. Colditz, Jeffrey Wolf, Thomas G. Martin, Michael Tomasson, Mark A. Fiala, Howard Terebelo, Nalini Janakiraman, Laurence Kolonel, Loic LeMarchand, Elad Ziv, Daniel Stram, Ravi Vij, Leon Bernal-Mizrachi, Gareth J. Morgan, Jeffrey A. Zonder, Carol Ann Huff, Sagar Lonial, Robert Z. Orlowski, David V. Conti, Christopher A. Haiman, Wendy Cozen. A meta-analysis of genome-wide association studies of multiple myeloma among African Americans [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 223.

Abstract: African-American ethnicity, male sex, older age and obesity are accepted risk factors for multiple myeloma (MM). Obesity early in life is a risk factor for many cancers, including MM; most studies have focused on populations of European origin. African-Americans have a higher prevalence of obesity than other populations, and may have a distinct genetic contribution to this condition. We established a multi-center study to investigate possible explanations for the excess risk of MM among African-Americans. The aim of the present case-case analysis was to determine whether body mass index (BMI) was associated with clinical characteristics at presentation in African-American MM patients. 1,065 patients diagnosed with active MM from January 1, 2009 through September 30, 2013 were recruited through nine outpatient centers at academic medical centers and 3 SEER population-based cancer registries. Information on weight and height at 20 years of age and at 5 years prior to diagnosis was obtained from questionnaires. Clinical information collected from the medical records and interviews included age at diagnosis, stage, percent plasmacytosis on bone marrow biopsy, B2 microglobulin level, immunoglobulin class and presence of lytic bone lesions. Molecular profiling abstracted from pathology reports included chromosomal gain/deletions (1P-, 1Q+, +3, +5, +7, +9, +11, 12P-, Del(13), +15, Del(17P), Del(17P13)), translocations (4;14), (11;14), and (14;16 ). Analysis of Variance (ANOVA) was used to test the null hypothesis that age at diagnosis was similar across BMI categories. A T-test was used to test the null hypothesis that the mean age at diagnosis in underweight/normal patients was not different than that for overweight and obese patients. The Mantel-Haenszel Chi square test for trend was used to test the null hypothesis that the proportion of cytogenetic and molecular abnormalities was similar across BMI categories. The study population consists of 306 African American male and 396 African American female MM patients. In both, obesity at 20 years of age was associated with younger age at diagnosis, compared to a normal/underweight (p=0.0015). Among males only, obesity at 5 years prior to diagnosis was also associated with younger age at diagnosis (p=0.03). A trend between increasing BMI and molecular characteristics associated with a poor prognosis was suggested. We observed a strong association between obesity at age 20 and younger age at diagnosis among males and females, and in males only at 5 years prior to diagnosis. Obesity is one of the few known potentially modifiable risk factors for MM. Younger age at diagnosis reflects an earlier accumulation of either or both genetic and environmental risk factors. We also observed a link between obesity at each of the two time points and specific molecular markers of poor prognosis. Additional studies are needed to determine biological significance of the results. Citation Format: Amie E. Hwang, Sikander Ailwadhi, Carol Ann Huff, Leon Bernal-Mizrachi, Christopher A. Haiman, Edward Peters, Seema Singhal, Karen Pawlish, Cathryn Bock, Todd Zimmerman, David J. Van Den Berg, David V. Conti, Brenda B. Birmann, Jayesh Mehta, John J. Graff, Daniel O. Stram, Niquelle Brown, Yang Yu, Moosa Azadian, Laurence Kolonel, Brian E. Henderson, Ann Mohrbacher, Graham Colditz, Brian-C Chiu, Michael Tomasson, Jeffrey Zonder, Robert Z. Orlowski, Sagar Lonial, Wendy Cozen. Obesity is associated with clinical characteristics in African American multiple myeloma patients. [abstract] . In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3852. doi:10.1158/1538-7445.AM2014-3852

Abstract: African-American ethnicity, male sex, older age and obesity are accepted risk factors for multiple myeloma (MM). Obesity early in life is a risk factor for many cancers, including MM; most studies have focused on populations of European origin. African-Americans have a higher prevalence of obesity than other populations, and may have a distinct genetic contribution to this condition. We established a multi-center collaborative study to investigate possible explanations for the excess risk of MM among African-Americans. The aim of the present case-case analysis was to determine whether body mass index (BMI) was associated with risk factors and clinical characteristics at presentation in African-American MM patients. Methods Patients diagnosed with active MM since January 1, 2009 were recruited from nine outpatient centers and three Surveillance, Epidemiology, End-Results Program (SEER) population-based cancer registries. Information on weight and height at 20 years of age and at 5 years prior to diagnosis was obtained from questionnaires. Clinical information collected included age at diagnosis, stage, percent plasmacytosis on bone marrow biopsy, β2 microglobulin level, Ig serotype, light vs. heavy chain disease, and presence of lytic bone lesions. BMI (ht/wt2) was categorized into 3 levels (normal 〈 25, overweight 25-29, obese 〉 30) according to World Health Organization standard. The Pearson chi-square test was used to test the association between BMI category, and risk factors and clinical characteristics. Mean ages at diagnosis across BMI categories were compared using linear regression and a t-test for trend calculated. Results To date, 1,044 African-American MM patients have been enrolled and of those, 1,014 provided a DNA sample. At present, 970 patients have completed a questionnaire, clinical records have been abstracted for 823 patients, and 509 patients have some information on gender, age at diagnosis, weight, height and clinical characteristics.The mean age at diagnosis was 59. Increasing BMI at age 20 was associated with younger age at diagnosis (p= 0.0004), whereas BMI at 5 years prior to diagnosis was not associated with age at diagnosis (p=0.9477). Among men, mean age at diagnosis decreased with increasing BMI at age 20 (p= 0.0125) (Table 1a) and at 5 years prior to diagnosis (p=0.0252) (Table 1b). Among women, the trend was signficant at age 20 (p=0.0018) (Table 1a) but not at 5 years prior to diagnosis (p= 0.7094) (Table 1b). Increasing BMI was not significantly associated with any other clinical characteristics. Conclusion/Discussion In a large collection of African-American MM patients, we observed a strong association between increasing BMI at age 20 and younger age at diagnosis. A similar trend was observed in men only at 5 years prior to diagnosis, consistent with previous reports. Obesity is one of the few known potentially modifiable risk factors for MM. Younger age at diagnosis reflects an earlier accumulation of either or both genetic and environmental risk factors. Obesity at an early age may influence MM risk through shared biological pathways such as interleukin-6 and insulin-like growth factor, by contributing to chronic B-cell activation, thereby increasing susceptibilty for MM later in life. The significance of the gender difference for the association closer to diagnosis is unclear and requires additional study. Disclosures: Terebelo: Amgen: Honoraria; Millennium: Honoraria. Mehta:Celgene: Speakers Bureau; Millennium: Speakers Bureau. Zonder:Skyline: Consultancy. Orlowski:Bristol-Myers Squibb: Honoraria, Membership on an entity’s Board of Directors or advisory committees, Research Funding; Celgene: Honoraria, Membership on an entity’s Board of Directors or advisory committees, Research Funding; Millennium: The Takeda Oncology Company: Honoraria, Membership on an entity’s Board of Directors or advisory committees, Research Funding; Onyx: Honoraria, Membership on an entity’s Board of Directors or advisory committees, Research Funding; Resverlogix: Research Funding; Array Biopharma: Honoraria, Membership on an entity’s Board of Directors or advisory committees; Genentech: Honoraria, Membership on an entity’s Board of Directors or advisory committees; Merck: Membership on an entity’s Board of Directors or advisory committees. Lonial:Celgene Corporation: Consultancy; Millennium: Consultancy; Novartis: Consultancy; Bristol Myers Squibb: Consultancy; Sanofi: Consultancy; Onyx: Consultancy.