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 Genome-wide association studies (GWAS) conducted in populations of European ancestry (EA) have identified and confirmed 23 germline susceptibility loci for multiple myeloma (MM). The effect sizes of single nucleotide polymorphisms (SNPs) at these loci are small, therefore combining them into a single summary measure, known as a polygenic risk score (PRS), may provide a more meaningful risk factor. We have previously shown a PRS comprised of the 23 SNPs for MM contributes to increased risk of MM, with a 2.7-fold increase for highest vs. lowest PRS quintiles. Whether the MM-PRS is also associated with overall survival (OS) in MM cases has not been evaluated. We examined the association between MM-PRS and OS in two EA studies. Methods The first study consisted of 2,179 EA MM cases from ten studies included in the Multiple Myeloma Working Group within the International Lymphoma Consortium (InterLymph). Cases were diagnosed between 1970 and 2015 and genotyped using multiple platforms (Oncoarray, Affymetrix, Human660W-quad Beadchip, and Illumina arrays); 885 cases also had stage [based on International Staging System (ISS)] available. Each of the GWAS was subjected to rigorous standard quality control independently (prior to imputation via the Michigan imputation server based on the Haplotype Reference Consortium (HRC). The second study consisted of 515 newly diagnosed EA MM cases from CoMMpass (Relating Clinical Outcomes in Multiple Myeloma to Personal Assessment of Genetic Profile), diagnosed from 2011-2013, who had whole genome sequencing (WGS) performed on germline DNA. The WGS data was used to call common germline genetic variants through the Mayo Clinic bioinformatics pipeline. Briefly, genetic variants were detected with GenomeGPS, aligned to the hg19 reference genome, called using the GATK (V3.6) Haplotype Caller, and merged for multiple-sample joint calling. To reduce the false positive variants, variant quality score recalibration (VQSR) was applied for both SNPs and INDELs. After quality control, 458 EA samples remained. Follow-up was av ailable for both studies and consisted of time from MM diagnosis date until death or date of last known follow-up. The PRS was constructed from the 23 MM SNPs using the published per allele odds ratio associated with MM risk. The published log odds ratios for each SNP were multiplied by the number of risk alleles (0, 1, 2) for the corresponding SNP, and summed, resulting in a unique score per person. Kaplan-Meier curves and Cox proportional hazard models were used to assess the association between PRS with MM OS considering two models: 1) adjusted for age, sex, study and 2) additional adjustment by stage (ISS). Hazard ratios (OR) and 95% confidence intervals (CI) were estimated. The PRS was evaluated both as a continuous variable, per standard deviation (SD), and as a categorical variable (quintiles). Results MM cases (N=2,179) in the InterLymph study were 59% male and 41% female and the median age was 61.0 years (26-90 years). Median follow-up time was 57.2 months (1.0-509.0 months) with 868 reported deaths. MM cases with stage information available consisted of 20% stage I (n=178), 53% stage II (n=466), and 27% stage III (n=241). No association was observed between PRS and OS in MM patients regardless of adjustment for stage (continuous PRS (HR: 1.03, 95% CI: 0.83-1.28, P=0.80) or by quintile PRS (p 〉 0.05)) (Table). The CoMMpass EA MM cases (n=458) had similar distributions for sex (61% male and 39% females) but were slightly older 65 years (27-93 years) and had shorter follow-up time (median=39.75 months (0.13-77.2)) with 117 deaths. Stage was available for 96% of CoMMpass cases including 36% stage I (n=159), 33% stage II (n=146), and 31% stage III (n=134). We also observed no association of PRS and OS in the CoMMpass study (HR=1.02, 95% CI: 0.72 -1.46, P= 0.89), adjusted for age, sex, and stage (Table). Discussion A PRS score for MM risk is not associated with OS for MM cases in two EA populations. Given that prior studies have shown association of genetic variation with MM survival, efforts to identify additional loci associated with OS or MM specific survival are warranted. Future studies should also consider germline variants impact on molecular subtypes, specific therapies, and outcomes. Disclosures Kumar: Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding.

Abstract: What's new? Multiple myeloma (MM) remains incurable for most patients, although recent therapeutic advances have extended survival. MM is highly heterogeneous, but gene expression profiling can identify patients with poor outcomes and classify patients by how they will respond to drugs. Here, the authors evaluate certain genetic loci that influence the amount of RNA transcript produced, called expression quantitative trait loci (eQTLs). They found two eQTLs of genes associated with MM prognosis that were directly associated with adverse outcomes. These results provide a proof‐of‐concept that eQTLs can serve as a surrogate for gene expression profile as a predictor of survival, and they are much easier to measure.

Abstract: Chronic lymphocytic leukemia (CLL) and its precursor, monoclonal B-cell lymphocytosis (MBL), are heritable. Serumfree light-chain (sFLC) measures are a prognostic factor for CLL, but their role in susceptibility to CLL is not clear. We investigated differences between sFLC measurements in pre-treatment serum from five groups to inform the association of sFLC with familial and sporadic CLL: (1) familial CLL ( n  = 154), (2) sporadic CLL ( n  = 302), (3) familial MBL ( n  = 87), (4) unaffected first-degree relatives from CLL/MBL families ( n  = 263), and (5) reference population ( n  = 15,396). The percent of individuals having elevated monoclonal and polyclonal sFLCs was compared using age-stratified and age- and sex-adjusted logistic regression models. In age groups 〉 50 years, monoclonal sFLC elevations were increased in sporadic and familial CLL cases compared to the reference population ( p ’s  〈  0.05). However, there were no statistically significant differences in sFLC monoclonal or polyclonal elevations between familial and sporadic CLL cases ( p ’s  〉  0.05). Unaffected relatives and MBL cases from CLL/MBL families, ages 〉 60 years, showed elevated monoclonal sFLC, compared to the reference population ( p ’s  〈  0.05). This is the first study to demonstrate monoclonal sFLC elevations in CLL cases compared to controls. Monoclonal sFLC levels may provide additional risk information in relatives of CLL probands.

Abstract: The first three authors contributed equally. The last three authors share senior authorship. Background: Although there has been an increased recognition of the contribution of germline variants to development of myeloid neoplasms, only two large-scale case-control genome-wide association studies (GWASs) have been conducted to identify variants that predispose to AML. Importantly, these studies were dedicated to AML predisposition in general, without investigation of molecularly distinct AML subtypes. Thus, we performed the first dedicated meta-analysis combining the two GWASs to investigate predisposing variants to cytogenetic AML subsets characterized by recurrent translocations and inversions. Methods: Two sets of adult de novo AML patients treated on Alliance for Clinical Trials in Oncology (Alliance) protocols, and two sets of adult de novo AML patients reported to CIBMTR (2000-11) from DISCOVeRY-BMT cohorts were compared with four sets of population-matched non-leukemic individuals of European ancestry. Illumina Infinium arrays were used for genotyping. The haplotype reference consortium was used for imputation and comparisons were performed using SNPtest and METAL with fixed-effects, for CBF-AML (n=251, including t(8;21), n=115; inv(16), n=136) and AML with 11q23/KMT2A translocations (n=177). Blood or bone marrow samples from subsets of these patients and additional AML patients with other cytogenetic abnormalities were used for total transcriptome RNA sequencing with Illumina instruments. Results: Two risk loci reached genome-wide significance in AML patients with 11q23/KMT2A translocations (Fig 1A). The most significant single nucleotide polymorphism (SNP) in the 4q21.3 risk locus, rs17668899[A] (P = 2.32 x 10-8, odds ratio [OR] = 3.92 [2.43-6.32]) is in intron 6 of the AFF1 gene (also called AF4) (Fig 1B), within an enhancer that interacts with the AFF1 transcription start site (Fig 1C, left). KMT2A-translocated AML patients with the risk allele had higher blast expression of AFF1 compared to those homozygous for the non-risk allele, although the trend did not reach significance (Fig 1D). Notably, AFF1 encodes a subunit of the super-elongation-complex (SEC) that acts as Pol II-associated master regulator of global transcription elongation. AFF1 is a common translocation partner of KMT2A in patients with acute lymphoblastic leukemia with t(4;11)(q21;q23), and is required for KMT2A-mediated leukemogenesis. We observed significantly higher AFF1 expression in both KMT2A-translocated AML and cytogenetically normal (CN) AML compared to CBF-AML (Fig 1E). The suggested role of AFF1/SEC is consistent with recent studies showing an important role for DOT1L, H3K79 methylation, and transcriptional elongation in NPM1-mutant AML (the most common subtype of CN-AML). Outcome analysis showed higher expression of AFF1 associated with shorter disease-free (DFS) in patients & lt; 60 years treated on Alliance studies (hazard ratio [HR] = 1.36, P=0.04; Fig 1F). The second KMT2A-translocated AML risk locus was located at 22q13.31, and the most significant SNP was rs62231468[A] (P = 4.95 x 10-9, OR = 3.25). rs62231468 is immediately 5' of the LDOC1L gene (a retrotransposon GAG-related gene, also called RTL6), and analysis of expression quantitative trait loci (eQTL) showed association of rs62231468[A] with higher LDOC1L expression, consistent with its location in an active enhancer (Fig 1C, right). The association between rs62231468[A] and higher LDOC1L expression was validated in leukemic blast expression from a set of 449 AML patients of any cytogenetic subset (Fig 1G). Notably, higher LDOC1L expression was associated with shorter DFS and overall survival (OS) in Alliance patients & lt; 60 years (DFS, HR = 1.25, P=0.03; OS, HR = 1.46, P & lt;0.001; Fig 1H-I). Analysis of patients with CBF-AML identified rs71568004[C] as more common in CBF-AML patients compared to controls (P = 3.84 x 10-8 , OR = 3.05 [2.05-4.53] ). This SNP is ~50kb 5' of the MARCKS gene located at 6q21, but genomic context analysis did not reveal any clear associations with MARCKS expression. Conclusions: Our first assessment of risk alleles for cytogenetic subsets of AML identified two novel independent risk loci associated with 11q23/KMT2A-translocated AML, and one risk locus associated with CBF-AML. These data suggest an important, subtype-specific role for transcriptional elongation in AML and that functional studies of retro transposition elements should be undertaken in leukemogenesis. Figure Disclosures Walker: Karyopharm: Current Employment, Current equity holder in publicly-traded company; Vigeo Therapeutics: Consultancy. Powell:Rafael Pharmaceuticals: Consultancy, Other: Advisor, Research Funding; Jazz Pharmaceuticals: Consultancy, Other: Advisor, Research Funding; Genentech: Research Funding; Novartis: Research Funding; Pfizer: Research Funding. Kolitz:Pfizer: Membership on an entity's Board of Directors or advisory committees; Magellan: Membership on an entity's Board of Directors or advisory committees. Pasquini:Bristol Myers Squibb: Consultancy; BMS: Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Other; Novartis: Research Funding; Kite: Research Funding. McCarthy:Karyopharm: Consultancy, Honoraria; Magenta: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Advisory Board; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Advisory Board; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Advisory Board; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Advisory Board; Genentech: Consultancy, Honoraria; Starton: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Advisory Board; Juno Therapeutics, a Bristol-Myers Squibb Company: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Advisory Board , Research Funding is to Roswell Park, Research Funding. Stone:AbbVie: Consultancy, Research Funding; Actinium: Consultancy; Agios: Consultancy, Research Funding; Argenx: Consultancy, Other: Data and safety monitoring board; Arog: Research Funding; Astellas: Consultancy, Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Consultancy; Biolinerx: Consultancy; Celgene: Consultancy, Other: Data and safety monitoring board; Jazz: Consultancy; Novartis: Consultancy, Research Funding; Otsuka: Consultancy; Pfizer: Consultancy; Trovagene: Consultancy; Takeda: Consultancy; Daiichi-Sankyo: Consultancy; Elevate: Consultancy; Gemoab: Consultancy; Janssen: Consultancy; Macrogenics: Consultancy; Hoffman LaRoche: Consultancy; Stemline: Consultancy; Syndax: Consultancy; Syntrix: Consultancy; Syros: Consultancy. Byrd:Trillium: Research Funding; Novartis: Research Funding; Kartos Therapeutics: Research Funding; Syndax: Research Funding; Vincera: Research Funding; Acerta Pharma: Research Funding; Janssen: Consultancy; Leukemia and Lymphoma Society: Other; Pharmacyclics LLC, an AbbVie Company, Gilead, TG Therapeutics, BeiGene: Research Funding; Pharmacyclics LLC, an AbbVie Company, Janssen, Novartis, Gilead, TG Therapeutics: Other; Pharmacyclics LLC, an AbbVie Company, Gilead, TG Therapeutics, Novartis, Janssen: Speakers Bureau. Eisfeld:Karyopharm: Current Employment, Current equity holder in publicly-traded company; Vigeo Therapeutics: Consultancy.

Abstract: Introduction Multiple myeloma (MM) is a result of a malignant transformation of plasma cells that is preceded by the presence of an asymptomatic clonal plasma cell expansion, a condition referred to as monoclonal gammopathy of undetermined significance (MGUS). We and others have shown familial aggregation of MM and MGUS. Evidence from epidemiologic, family and genome-wide association studies (GWAS) suggests a genetic component underlying MM etiology. GWAS have successfully established 17 common genetic risk loci for MM to date and recently, rare inherited susceptibility variants in the LSD1 / KDM1A and USP45 genes were identified in familial MM / MGUS kindreds. Family-based approaches may be used to elucidate genetic variation contributing to familial MM. Genetic linkage analysis has historically been used to detect the chromosomal location of disease genes. The objective of this study was to conduct a linkage analysis of MM / MGUS families to identify genomic regions for MM / MGUS. Methods Linkage analysis was performed on whole exome sequencing (WES) data generated from germline DNA extracted from peripheral blood from MM / MGUS families ascertained at four sites, of which 79 were selected with 2 or more affected members with any combination of MM or MGUS. Whole exome capture was performed using Agilent SureSelect 38 Mb paired end sequencing and ran on Illumina HiSeq 2000s/2500s; standard analyses for alignment (GRCh37) and quality control were conducted. The Genome Analysis Toolkit's (GATK) HaplotypeCaller in per-sample mode was used to jointly call all the samples together. Quality control included removing variants that had 〈 75% call rate, 〈 8x coverage, or minor allele frequency 〈 0.01 (1KGenomes). The jointly called WES data from the 79 families consisted of 230 individuals, including 119 MM, 93 MGUS and 18 unaffected relatives. Additional early onset (defined as age 〈 60) MM cases (n=400), sporadic MM cases (n=879) and controls (n=2389) were also included in the joint calling to be used for follow-up of linkage regions. We included independent variants defined as linkage disequilibrium (LD) r2 〈 0.05 using both PLINK 1.07's LD based variant pruner and also MERLIN's pairwise r2 cluster marker-marker modeling to ensure variant independence. After quality control and LD filtering: 12,946 variants remained. We conducted multipoint linkage analysis using MERLIN (Multipoint Engine for Rapid Likelihood Inference using the Lander-Green approach) and considered both non-parametric and parametric (dominant and recessive) models to test for co-segregation of chromosomal regions with MM / MGUS. A logarithm of the odds (LOD) score greater than 3.3 was significant evidence for linkage. Within the same families, we interrogated any suggestive regions by performing gene-level association tests using the PEDGENE R package to calculate burden and kernel statistics, accounting for family relationships. Follow-up of these genes in the early onset and sporadic MM cases and controls and interrogation of single variants driving the associations of these genes is ongoing. Results Among the 79 families, 28 consisted of two or more MM, 41 had two or more MM and MGUS cases and 10 had two or more MGUS. Analyses of the 79 MM / MGUS families identified chromosome 6 at 123420001-149070000 BP region, with evidence for linkage by the non-parametric model (LOD score=3.3) and supportive evidence for linkage by the dominant parametric model (LOD=2.5) (Figure). The chromosome 6 region, which is outside the HLA-region, contains a total of 72 genes. Using gene-level association tests, we identified four genes within the region (MOXD1, TRDN, ADAT2, LTV1) that were associated within MM / MGUS in the family cases (p 〈 0.05). Discussion We found evidence for a locus on chromosome 6 linked to MM / MGUS. Four genes in this region may be associated with MM / MGUS in these families. Follow-up of these genes/variants in high-risk individuals (early-onset / age 〈 60), sporadic cases and controls will help elucidate genetic mechanisms contributing to familial MM / MGUS. In addition, we demonstrate the benefit of applying a linkage analysis framework to familial WES data for discovery of genomic regions influencing MM / MGUS. Disclosures Dumontet: Roche: Research Funding; Merck: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria; Sanofi: Honoraria. Kumar:AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Roche: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding.

Abstract: Acute myeloid leukemia (AML) is a hematological malignancy with an undefined heritable risk. Here we perform a meta-analysis of three genome-wide association studies, with replication in a fourth study, incorporating a total of 4018 AML cases and 10488 controls. We identify a genome-wide significant risk locus for AML at 11q13.2 (rs4930561; P  = 2.15 × 10 −8 ; KMT5B ). We also identify a genome-wide significant risk locus for the cytogenetically normal AML sub-group (N = 1287) at 6p21.32 (rs3916765; P  = 1.51 × 10 −10 ; HLA ). Our results inform on AML etiology and identify putative functional genes operating in histone methylation ( KMT5B ) and immune function ( HLA ).

Abstract: IKZF1 associations with high-risk B-ALL may differ by age and sex. A novel variant on chromosome 14, rs189434316, is associated with over a 3.5-fold risk of normal cytogenetic B-ALL.