Clay‐Gilmour, Alyssa

AbstractGene expression profiling can be used for predicting survival in multiple myeloma (MM) and identifying patients who will benefit from particular types of therapy. Some germline single nucleotide polymorphisms (SNPs) act as expression quantitative trait loci (eQTLs) showing strong associations with gene expression levels. We performed an association study to test whether eQTLs of genes reported to be associated with prognosis of MM patients are directly associated with measures of adverse outcome. Using the genotype‐tissue expression portal, we identified a total of 16 candidate genes with at least one eQTL SNP associated with their expression with P < 10−7 either in EBV‐transformed B‐lymphocytes or whole blood. We genotyped the resulting 22 SNPs in 1327 MM cases from the International Multiple Myeloma rESEarch (IMMEnSE) consortium and examined their association with overall survival (OS) and progression‐free survival (PFS), adjusting for age, sex, country of origin and disease stage. Three polymorphisms in two genes (TBRG4‐rs1992292, TBRG4‐rs2287535 and ENTPD1‐rs2153913) showed associations with OS at P < .05, with the former two also associated with PFS. The associations of two polymorphisms in TBRG4 with OS were replicated in 1277 MM cases from the International Lymphoma Epidemiology (InterLymph) Consortium. A meta‐analysis of the data from IMMEnSE and InterLymph (2579 cases) showed that TBRG4‐rs1992292 is associated with OS (hazard ratio = 1.14, 95% confidence interval 1.04‐1.26, P = .007). In conclusion, we found biologically a plausible association between a SNP in TBRG4 and OS of MM patients.

Abstract Inherited genetic risk factors play a role in multiple myeloma (MM), yet considerable missing heritability exists. Rare risk variants at genome-wide association study (GWAS) loci are a new avenue to explore. Pleiotropy between lymphoid neoplasms (LNs) has been suggested in family history and genetic studies, but no studies have interrogated sequencing for pleiotropic genes or rare risk variants. Sequencing genetically enriched cases can help discover rarer variants. We analyzed exome sequencing in familial or early-onset MM cases to identify rare, functionally relevant variants near GWAS loci for a range of LNs. A total of 149 distinct and significant LN GWAS loci have been published. We identified six recurrent, rare, potentially deleterious variants within 5 kb of significant GWAS single nucleotide polymorphisms in 75 MM cases. Mutations were observed in BTNL2, EOMES, TNFRSF13B, IRF8, ACOXL and TSPAN32. All six genes replicated in an independent set of 255 early-onset MM or familial MM or precursor cases. Expansion of our analyses to the full length of these six genes resulted in a list of 39 rare and deleterious variants, seven of which segregated in MM families. Three genes also had significant rare variant burden in 733 sporadic MM cases compared with 935 control individuals: IRF8 (P = 1.0 × 10−6), EOMES (P = 6.0 × 10−6) and BTNL2 (P = 2.1 × 10−3). Together, our results implicate six genes in MM risk, provide support for genetic pleiotropy between LN subtypes and demonstrate the utility of sequencing genetically enriched cases to identify functionally relevant variants near GWAS loci.

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.

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 available 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.

Background: Multiple myeloma (MM) treatment has advanced considerably with proteasome inhibitors, immunomodulatory drugs (IMiDs), and, most recently, monoclonal antibodies. However, treatment response is quite heterogeneous, and many patients still progress even with novel combination therapies. Thus, understanding the factors that underlie response to treatment is a priority. Several somatic genomic aberrations and mutations predict poor response to therapy. However, germline variation has not previously been investigated as a predictor of treatment response in MM. We used genome-wide association and transcriptome-wide association approaches to identify germline genetic predictors of treatment response in MM. Methods: We included 510 MM patients from Mayo Clinic and 324 MM patients from UCSF diagnosed from 1999-2015. Basic demographics, laboratory values and pathology at diagnosis, type of initial therapy, duration of therapy, and follow-up were ascertained by chart review. Patients were grouped into categories of treatment based on their first line therapy: proteasome inhibitor-based regimen, IMiD based regimen, combination proteasome and IMiD based regimen, or other. Response was assessed using International Myeloma Working Group (IMWG) response criteria after 4-6 cycles of induction. As such, response was categorized into progressive disease (PD), minimal response (MR), partial response (PR), very good partial response (VGPR), or complete response (CR). Germline samples were genotyped using Illumina or Affymetrix arrays and were imputed based on the Haplotype Reference Consortium (HRC). For the genome-wide association study (GWAS), we included all SNPs with minor allele frequency >0.01 and imputation r2 of >0.5. We tested each SNP for association with treatment response using a linear regression model that adjusted for age, gender, and genetic ancestry (from principal components analysis (PCA)). To perform the transcriptome-wide association study (TWAS), we calculated predicted gene expression data using PREDIXCAN software on a reference cohort of 922 individuals with genotype and RNA expression data from peripheral blood. We then tested the association between predicted gene expression and response to therapy using linear regression models. Both the GWAS and TWAS were performed on subgroups of patients who received either proteasome inhibitors or IMiD therapies. The analyses of patients on proteasome inhibitors were adjusted for IMiD use as a covariate and analyses of patients on IMiDs were adjusted for proteasome inhibitor use. The threshold for genome-wide significance loci was set at P = 5 x 10-8 and the threshold for suggestive loci was set at P = 10-6. The threshold for significance for TWAS was set at P = 4 x 10-6 by using a Bonferroni correction for the number of genes for which genetic models of expression could be developed by PREDIXCAN. Results: Overall, 42.7% (59 of 138) of patients on proteasome inhibitors alone, 32.5% (66 of 203) of patients on IMiDs alone, and 58.1% (50 of 86) of patients on combination achieved at least a VGPR. There were no significant differences in response across centers in analyses that adjusted for age, sex and types of therapy. There were no genome wide significant loci to predict for response. We identified 8 suggestive SNPs associated with proteasome inhibitor response and 4 suggestive SNPs associated with IMiD response. TWAS identified ZNF622 as a candidate genetic modifier of proteasome inhibitor effect that was significant after correction for multiple hypothesis testing (P = 1.6 x 10-6). Higher genetically predicted expression was associated with improved response to proteasome inhibitor therapy. Among patients above the median of predicted expression of ZNF622 on proteasome inhibitors, 62.6% achieved at least VGPR; among patients at or below the median of expression, only 37.6% achieved at least VGPR. Conclusions: We identified an association between predicted expression of ZNF622 and clinical response to proteasome inhibitor therapy among MM patients. ZNF622 is a zinc finger binding protein which is known to be co-activator of B Myb activity and to affect apoptosis in response to oxidative stress. Our work highlights the potential importance of pharmacogenetic modifiers of treatment response in MM. Disclosures Shah: Nkarta: Consultancy, Membership on an entity's Board of Directors or advisory committees; Indapta Therapeutics: Equity Ownership; University of California, San Francisco: Employment; Celgene, Janssen, Bluebird Bio, Sutro Biopharma: Research Funding; Genentech, Seattle Genetics, Oncopeptides, Karoypharm, Surface Oncology, Precision biosciences GSK, Nektar, Amgen, Indapta Therapeutics, Sanofi: Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Poseida: Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Kite: Consultancy, Membership on an entity's Board of Directors or advisory committees; Teneobio: Consultancy, Membership on an entity's Board of Directors or advisory committees. Wong:Celgene: Research Funding; Janssen: Research Funding; Roche: Research Funding; Fortis: Research Funding. Martin:Roche and Juno: Consultancy; Amgen, Sanofi, Seattle Genetics: Research Funding. Kumar:Celgene: Consultancy, Research Funding; Takeda: Research Funding; Janssen: Consultancy, Research Funding.

Abstract The first two authors and last two authors contributed equally. Genome-wide association studies (GWAS) have identified risk loci for Acute Lymphoblastic Leukemia (ALL), Chronic Lymphoblastic Leukemia (CLL) and Non-Hodgkin Lymphoma, however an Acute Myeloid Leukemia (AML) GWAS has not been published to date. We performed a GWAS to identify AML and Myelodysplastic Syndrome (MDS) risk loci using a nested case-control study design in the DISCOVeRY-BMT cohorts which includes almost 2000 AML and MDS patients as cases and 2813 unrelated donors as controls. Genotyping was performed using the Illumina Human OmniExpress BeadChip and imputed using the Haplotype Reference Consortium, yielding > 8 million high-quality variants for statistical analysis. Logistic regression models with AML (de novo AML with normal cytogenetics, de novo AML with abnormal cytogenetics and therapy-related AML) and MDS cases and European American healthy donor controls adjusted for age and sex were used to test the association of each SNP with disease status. To identify the strongest association signal with disease we conducted a summary statistic SNP-based association analysis (ASSET) using non-overlapping AML and MDS cases implemented in R statistical software. ASSET uses an exhaustive search for SNPs with small but common pleiotropic effects across groups of traits while accounting for the multiple tests required by the subset search, as well as any shared controls between groups. This approach allowed us to further investigate the heterogeneity within AML subtypes and to gain increased power by pooling subtypes that show pleiotropic effects. ASSET genome wide (GW) significance is defined as P<5.0x10-8, however, we present results of each subset analysis. ASSET analyses identified an association of T allele at rs12203592, Interferon Regulatory Factor 4 (IRF4), with increased risk of de novo AML and MDS (Figure 1) (OR=1.37; 95% CI, 1.25-1.51, Pmeta=1.59x10-10). The variant has been reported significant in GWAS of skin pigmentation, hair color, non-melanoma skin cancer, squamous cell carcinoma, actinic keratosis, and childhood ALL; GW case-control studies of neuroblastoma and breast cancer show suggestive association signals (P<5 x 10-6). IRF4 belongs to the IRF family of transcription factors and is a key regulator of differentiation stages in hematopoiesis. The T allele at rs12203592 is associated with significantly increased expression of IRF4 in whole blood and lung tissue and in vitro mouse studies have shown the T allele to be associated with higher levels of IRF4 transcription. rs12203592 is <80bp from an IRF4 transcription start site and in an important position within NF-κB motifs in multiple blood and immune cell lines, supporting the hypothesis that this SNP modulates NF-κB repression of IRF4 expression. Another variant in the IRF4 regulatory region, rs62389423 (A allele), showed a putative association with subsets of de novo AML and MDS (OR=1.36; 95% CI,1.21-1.52, Pmeta=1.2x10-7). Although not in linkage disequilibrium with rs12203592, the A allele has also been previously associated with susceptibility to skin cancer and melanoma in multiple GWAS. Analysis of 596 UKbiobank CLL cases and >300,000 controls, shows the A allele correlates with a 50% increased risk of CLL (95% CI, 1.32-1.73, P= 2.4x10-9).Several other GWAS also show an association between additional IRF4 variants and CLL. Analyses in individual subtypes also revealed an intronic variant, rs10098598, in RAD21 to be associated with de novo AML (OR=2.18; 95% CI, 1.60-2.97; Pmeta=8.9x10-7). RAD21, on8q24, a region known to be associated with multiple cancer types, is involved in DNA double-stranded break repair and in chromatid cohesion in mitotic cells. Loss of function would theoretically lead to chromosomal instability and tumorigenesis. Components of the cohesion complex (including RAD21) are somatically mutated in ~12% of de novo AML and MDS patients, where it is frequently an early event. We provide the first GW evidence of association between a common variant and AML susceptibility. This SNP has been shown to be associated with multiple phenotypes, suggesting that there are pleiotropic effects at work. Our RAD21 finding is consistent with the role of cohesion in leukemogenesis and provides some evidence of its role in de novo AML susceptibility. Replication and further subset analyses with genome-wide data in >2000 AML cases are ongoing. Disclosures Griffiths: Alexion Inc.: Honoraria, Research Funding; Astex/Otsuka Pharmaceuticals: Honoraria, Research Funding; Celgene, Inc: Honoraria, Research Funding; Novartis, Inc.: Research Funding; Pfizer, Inc.: Research Funding. McCarthy:Bristol Myers Squibb: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Karyopharm: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Janssen: Consultancy, Honoraria.

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 Both genome wide association studies (GWAS) of common variation and exome wide association studies (EXWAS) of rare variation have successfully identified disease susceptibility variants for a variety of diseases. One GWAS of inherited susceptibility to Acute Myeloid Leukemia (AML) has been conducted, but no EXWAS have been performed to measure risk of AML attributable to low-frequency constitutional genetic variation. We performed the first EXWAS of risk of AML as a nested case-control study in the DISCOVeRY-BMT (Determining the Influence of Susceptibility Conveying Variants Related to one-Year mortality after BMT) cohorts. The DISCOVeRY-BMT parent study examined transplant-related mortality in leukemia patients undergoing unrelated donor allogeneic BMT. To identify low frequency variants and genes contributing to increased susceptibility to AML we used genotype data from the Illumina HumanExome BeadChip typed in the DISCOVeRY-BMT cohorts; the HumanExome BeadChip contains 242,901 variants, which are mainly protein-coding variants. The optimal sequence kernel association test (SKAT-O) was used to analyze gene-level associations with risk of AML. These gene-based tests evaluate the cumulative effects of multiple single gene variants on risk of AML. Analyses were performed in all European American AML cases and two subtypes: 1) de novo AML, 2) de novo AML with normal cytogenetics. Models were adjusted for age at transplant and principal components to control for population stratification. For gene-based tests at least 2 variants with minor allele frequency (MAF) ≤ 5%, were required to be present in the gene. This yielded a total of 13,687 genes tested, and a Bonferroni corrected significance level of P<3.65 x 10-6. Association tests were performed in 1,189 AML cases reported to CIBMTR 2000-08 (Cohort 1) and 327 AML cases reported to CIBMTR from 2009-11 (Cohort 2). Controls in Cohorts 1 (n=1,986) and 2 (n= 515) were 10/10 HLA-matched unrelated donors who passed a comprehensive medical exam and deemed healthy. We used metaSKAT to combine Cohorts 1 and 2 and obtain p-values of association with AML. We present the results of gene-level tests significant in both cohorts. The likely pathogenicity of these variants was determined in silico using SIFT, PolyPhen and MutationTaster. Patient characteristics are in Table 1. DNMT3A, on chromosome 2, was associated in the gene-based test with risk of AML (Pmeta=1.70x10-9, Table 2). Three missense variants at MAF <1% comprise both overall AML and de novo AML gene-based association: exm177559 (Asn->Ser), exm177507 (Arg->His), and exm177543 (Arg->Trp). Normal cytogenetics de novo AML gene-based assocations consisted of only 2 of these variants: exm177559 and exm177507 (Table 2). While prevalence of exm177507 is <1% for all AML cases, in de novo AML with normal cytogenetics the MAF was higher at 3%. The other 2 variants had a MAF<1% irrespective of subtype. Somatically, DNMT3A is most frequently mutated in hematologic malignancies, with >30% of de novo AML cases with a normal karyotype and >10% of MDS patients having DNMT3A mutations. Although these are germline gene associations all three of the variants found have been reported somatically in hematologic malignancies. In 200 AML cases from The Cancer Genome Atlas (TCGA) p.R882H (represented as exm177507 on the exome chip) was a frequent somatic mutation (25%). Exm177543 (p.R635W) and exm177559 (p.N501S) are reported in the Catalogue of Somatic Mutations in Cancer (COSMIC) as somatic mutations involved in hematopoietic and lymphoid tissue in both cell lines and humans. Exm177507 and exm177543 show evidence of pathogenicity in all three in silico tools, while exm177559 was reported as deleterious and disease causing by Sift and MutationTaster, respectively. Our results show that multiple potentially pathogenic missense germline variants in DNMT3A comprise the gene-based association with AML, specifically de novo AML with normal cytogenetics. Given the functional nature of these variants it is possible germline risk stratification could be informative in determining AML risk, and subsequently development of AML harboring DNMT3A mutations. Confirmation of these findings in additional cohorts could have implications for individualized risk screening, prediction and prognosis. Additional cytogenetic subgroup analyses, including treatment-related AML, are underway. Disclosures Hahn: Novartis: Equity Ownership; NIH: Research Funding. McCarthy:Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Onyx: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; The Binding Site: Honoraria, Membership on an entity's Board of Directors or advisory committees; Karyopharm: Honoraria, Membership on an entity's Board of Directors or advisory committees; Gamida Cell: Honoraria, Membership on an entity's Board of Directors or advisory committees. Sucheston-Campbell:NIH/NCI: Research Funding.

Abstract We and others previously demonstrated an increased risk of monoclonal gammopathy of undetermined significance (MGUS) in first-degree relatives of multiple myeloma (MM) and MGUS patients, underscoring a familial component to this disease. However, MM is known to be a collection of cytogenetically distinct diseases, with 40-50% of MM cases having a reciprocal translocation involving the IgH locus on chromosome 14q32 and in many of the remaining patients, trisomies. In a small proportion of cases, both IgH abnormalities and trisomies are found in the same clone. These MM cytogenetic subtypes are associated with differential prognosis. Whether there are differences in familial risk by cytogenetic subtypes is not known. Patients with MM were recruited from the Mayo Clinic Hematology practice in Rochester, Minnesota (MN) between 2005 and 2015. Serum samples were collected from first-degree relatives and subjected to electrophoresis and immunofixation for MGUS determination. Age- and sex-specific rates of MGUS from the population-based Olmsted County, MN, prevalence study were used as expected rates for the calculation of risk ratios (RRs) for comparisons of first-degree relatives. Cytogenetic subtypes were classified by FISH testing performed in the clinic and categorized into groups defined by IgH translocation , trisomy, intermediate/ high-risk disease (t(4;14), t(14;16), t(14;20), and del17p). Further, the distribution of cytogenetic subtypes was compared between MM cases with and without evidence of MGUS in first degree relatives using Chi square tests. Analyses were also subset to MM probands diagnosed in MN. There were a total of 442 MM probands, with 1235 first-degree relatives recruited and eligible for the study. MGUS was detected in 78 relatives, for an age- and sex-adjusted prevalence of 6.1% (4.7%-7.5%). Analyses comparing prevalence of MGUS in first degree relatives to population-based rates from Olmsted County showed a 2.5-fold (95% CI=1.9-3.0) increased prevalence. When performing analyses among MN probands only (RR=2.9; 95% CI=2.1-3.8), results were similar. Of the 442 probands, 310 had FISH performed on plasma cells (identified by cIG staining; cIg-FISH) at diagnosis. Of these cases, 49% had a trisomy, 23% had an IgH translocation, and 9% had both. Although the proportion of trisomies and IgH translocations were 4-6% higher among MM probands with a relative with MGUS compared to those without, these differences were not statistically significant (Table 1). MM probands with a first degree relative with MGUS also had a similar proportion of cytogenetic subtypes that are considered of intermediate or high risk compared to those MM without a family history (26.9% vs 25.2%) (p=0.79) (Table 1). When restricted to MM probands from MN, results remained non-statistically significant (Table 1). We showed an increased risk of MGUS in first-degree relatives of MM cases, implying shared environment and/or genetics underlying this malignancy. However, we did not find an association between family history of MGUS in MM probands and the cytogenetic subtypes examined. Larger cohorts are needed to examine if a relationship exists between cytogenetic subtypes of MM and familial risk. Disclosures Kumar: Noxxon Pharma: Consultancy, Research Funding; Array BioPharma: Consultancy, Research Funding; AbbVie: Research Funding; Onyx: Consultancy, Research Funding; Millennium: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Glycomimetics: Consultancy; Kesios: Consultancy; Janssen: Consultancy, Research Funding; Skyline: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Consultancy, Research Funding; BMS: Consultancy.

Abstract #the authors contributed equally to this work While survival outcomes after HLA-matched unrelated donor (URD) blood and marrow transplant (BMT) have significantly improved over the last two decades, about 40% of patients die before 1-year post URD BMT. Previously we performed a genome-wide association study (GWAS) named DISCOVeRY-BMT (Determining the Influence of Susceptibility COnveying Variants Related to one-Year mortality after BMT) to investigate the contributions of common genetic variants on survival outcomes. To address the specific contributions of low frequency (≤ 1%) exonic variants on survival outcomes, we used the DISCOVeRY-BMT cohorts typed with the Illumina HumanExome BeadChip containing 242,901 variants, which are mainly protein-coding variants. We used a gene-based test (the optimal sequence kernel association test (SKAT-O)) to evaluate the cumulative effects of multiple genetic variants within a gene on overall survival (OS), transplant-related mortality (TRM), and disease-related mortality (DRM) 1 year after URD BMT. SKAT-O measures the overall significance of the gene and allows the variants to have different directions and magnitude of effects. We used a 2-stage study design: SKAT-O analysis was carried out in Cohort 1 consisting of 1,972 AML, ALL or MDS patients reported to the Center for International Blood and Marrow Transplant Research from 2000 to 2008 and their 2,006 10/10 HLA-matched URD. Genes with a suggestive association with each outcome (P < 1×10-3) entered the final meta-analysis including Cohort 1 and an independent cohort (Cohort 2), consisting of 503 recipients and 520 10/10 HLA-matched URD from 2009 to 2011. The analysis included recipients and URD of European descent due to the low frequency of other populations. All association models included age at BMT, diagnosis (AML, ALL, MDS), disease status at BMT, cell source (peripheral blood, marrow), year of BMT, and principal components from EIGENSTRAT to control for population stratification. Only coding variants (missense and nonsense) with minor allele frequency ≤ 1% were included in our analysis, which resulted in > 12,000 genes tested in our gene-based analysis in recipients and donors. Exome-wide significance was set at Pmeta< 4.10×10-6 after Bonferroni correction for the total number of genes tested. The likely pathogenicity of these variants was determined in silico using SIFT and PolyPhen. In recipients, we identified OR51D1, a member of the olfactory receptor gene family, as significantly associated with both OS and TRM. The OS association with ORD51D1 is driven by TRM as the same six missense variants contribute to both TRM and OS, but not to DRM. In donors, four (ALPP, EMID1, SLC44A5, LRP1), one (HHAT), and two (LYZL4, NT5E) genes were significantly associated with OS, TRM, and DRM, respectively (Table). ALPP encodes an alkaline phosphatase. SLC44A5 is a member of the solute carrier gene family. LRP1 (low density lipoprotein receptor-related protein 1) encodes an endocytic receptor involved in several cellular processes, including intracellular signaling, lipid homeostasis, and clearance of apoptotic cells. HHAT encodes an enzyme that acts within the hedgehog secretory pathway, which is involved in hematologic malignancy. LYZL4 is a member of a family of lysozyme-like genes, which have a protective role in host defense. The encoded protein of NT5E, CD270, is used as a determinant of lymphocyte differentiation. The likely pathogenicity of several of the functional variants in all significant genes identified was predicted to be both (possibly or probably) damaging and deleterious (Table), thus indicating that the amino acid substitution of the variant may not be well tolerated. One damaging variant in LRP1 has been identified as a somatic mutation in hematopoietic and lymphoid tissue. Our study is the first analysis of the low-frequency coding variant contribution to URD BMT survival outcomes. We found that the missense variants contributing to many of these significant gene associations shows evidence of pathogenicity and thus it is biologically plausible these variants are contributing to survival outcomes. Further confirmation of these findings, and studies of the functional consequences of protein-coding changes in these genes, may provide more individualized risk prediction and prognosis as well as alternative donor selection strategies. Table. Table. Disclosures McCarthy: Gamida Cell: Honoraria, Membership on an entity's Board of Directors or advisory committees; Onyx: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Karyopharm: Honoraria, Membership on an entity's Board of Directors or advisory committees; The Binding Site: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees. Hahn:Novartis: Equity Ownership; NIH: Research Funding. Sucheston-Campbell:NIH/NCI: Research Funding.