Waller, Rosalie G.

7011 Background: Monoclonal B-cell lymphocytosis (MBL) is a precursor to chronic lymphocytic leukemia (CLL) but also a risk factor for other lymphoid malignancies. Clonal hematopoiesis (CH), originally defined as the presence of mutations in myeloid driver genes, is a precursor to myeloid malignancies. Recently, CH that includes genes associated with lymphoid malignancies has been reportedly associated with risk of lymphoid malignancies, and particularly CLL. Little is known about the association between CH and MBL and their joint effects on risk of hematological malignancies (HM). Methods: Study participants were from the Mayo Clinic Biobank, a large-scale biorepository of patients who provided a peripheral blood sample. CH at enrollment was determined using whole-exome sequencing (50x coverage). Myeloid-CH (M-CH) was based on mutations located in 56 genes associated with myeloid malignancies. Lymphoid-CH (L-CH) was based on 235 genes associated with lymphoid malignancies. Individuals were screened for MBL using eight-color flow cytometry in two different cohorts of Biobank participants. Cohort 1 (N=3883) included participants who had available sample for MBL screening at enrollment. Cohort 2 (N=5684) were participants recontacted to provide a sample for MBL screening. Incident HM were identified using ICD codes and confirmed via medical record review. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI). Cox regression was used to estimate hazard ratios (HR), with time defined as date between MBL sample and the first of incident HM, death, or 9/30/2023. Analyses were adjusted for age at MBL screening and sex. Results: In total, 9567 individuals (39% male, median age 66 years) were screened for MBL with available CH, of whom 17% were positive for MBL, 7% were positive for M-CH, and 2% were positive for L-CH. We found no evidence of an association between M-CH and MBL (OR=1.11, 95% CI:0.91-1.34) nor L-CH and MBL (OR=1.05, 95% CI:0.70-1.55). When subset to Cohort 1, where the same sample was used for both CH and MBL screening, the results held (M-CH OR=1.11, 95% CI: 0.83-1.48; L-CH OR=0.82, 95% CI:0.40-1.53). Next, we investigated the effect of each of these precursors with incident HM. Median follow-up was 4 years, and 78 individuals developed incident HM (31 myeloid, 49 lymphoid overall, 8 CLL). When modeling both precursors, both L-CH (HR=6.23, 95% CI:2.46-15.79) and MBL (HR=3.89, 95% CI:2.17-6.99) were independently associated with incident lymphoid malignancy. When excluding CLL events, the association held (L-CH: HR=5.94, 95% CI:2.11-16.77; MBL: HR=2.95, 95% CI:1.54-5.66). Only M-CH was significantly associated with incident myeloid malignancies. Conclusions: In the largest cohort with MBL and CH precursors measured, we found no evidence of an association between them. However, both MBL and L-CH were strong independent risk factors for incident lymphoid malignancies.

Abstract Chronic Lymphocytic Leukemia (CLL) exhibits a substantial familial risk that extends beyond CLL to other B-cell lymphomas (including follicular lymphoma and diffuse large B-cell lymphoma). Monoclonal B-cell Lymphocytosis (MBL), a precursor to CLL, is also associated with a significant risk for hematologic malignancies overall and for lymphoid malignancies, specifically. Moreover, previous research has shown an association between the CLL polygenic risk score (CLL-PRS) and common lymphoma subtypes. This study aims to further evaluate CLL-PRS associations with hematological cancer overall and by lineage while also considering MBL status a strong risk factor for lymphoid malignancies. Utilizing the Mayo Clinic Biobank, we selected individuals aged 40 years or older, residing in proximal counties, who had no prior hematologic malignancies, and with available biospecimens. MBL screening was done using 8-color flow cytometry, and MBL with CLL (CD5+/CD20dim) or atypical CLL (CD5+/CD20+) immunophenotype were included. CLL-PRS was calculated from 41 known susceptibility variants, with weights being the log of the odds ratios from the largest CLL genome-wide association study. Incident hematologic malignancies were ascertained through ICD codes and confirmed via medical record review. Hazard ratios (HR) and 95% confidence intervals (CIs) for associations with hematologic malignancies were estimated through Cox regression. Of 7,332 participants, 1,150 (16%) screened positive for MBL; median age was 67 years (range 40-101), and 37% male. Median follow-up was 2.9 years (range 0-13), and 56 hematologic cancers were identified. After adjusting for age and sex, the CLL-PRS was associated with increased risk of developing hematologic (HR=1.49, 95%CI=1.12-1.98, P=0.006) which was all attributable to lymphoid cancers (HR=1.79, 95%CI=1.26-2.56, P=0.001). When adjusting for baseline MBL status in the models, the CLL-PRS associations remained significant but were attenuated for hematological (HR=1.33, 95%CI=0.99-1.79, P=0.058) and lymphoid (HR=1.56, 95%CI=1.07-2.26, P=0.020) malignancies, while MBL status was also significantly associated with risk of hematologic (HR=2.76, 95%CI=1.55-4.91, P=0.001) and lymphoid (HR=3.61, 95%CI=1.78-3.32, P<0.001) malignancies. In this prospective cohort study of individuals screened for MBL, CLL-PRS was associated with an elevated risk of hematologic malignancies overall and within the lymphoid lineage, underscoring a shared genetic etiology across many B-cell lymphomas. However, the associations between CLL-PRS and hematologic malignancies were attenuated when accounting for MBL status or when analyzing among MBL-positive individuals, highlighting the role of MBL status in these associations. Further research with expanded cohorts is needed to unravel these complex genetic and clinical interactions. Citation Format: Raphael Mwangi, Dennis P. Robinson, Sara J. Achenbach, Geffen Kleinstern, Aaron D. Norman, Kari G. Rabe, Janet E. Olson, Neil E. Kay, Rosalie Griffin, Nicholas J. Boddicker, Esteban Braggio, Sameer A. Parikh, Curtis A. Hanson, Celine M. Vachon, James R. Cerhan, Tait D. Shanafelt, Susan L. Slager. Genetic associations with hematologic malignancies: An evaluation of CLL polygenic risk score and MBL status in the Mayo Clinic Biobank Cohort [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6152.

Abstract High-count monoclonal B-cell lymphocytosis (HCMBL) is a precursor condition to chronic lymphocytic leukemia (CLL). We have shown that among individuals with HCMBL, the CLL-International Prognostic Index (CLL-IPI) is prognostic for time-to-first therapy (TTFT). Little is known about the prognostic impact of somatically mutated genes among individuals with HCMBL. We sequenced DNA from 371 individuals with HCMBL using a targeted sequencing panel of 59 recurrently mutated genes in CLL to identify high-impact mutations. We compared the sequencing results with that of our treatment-naïve CLL cohort (N = 855) and used Cox regression to estimate hazard ratios and 95% confidence intervals (CIs) for associations with TTFT. The frequencies of any mutated genes were lower in HCMBL (52%) than CLL (70%). At 10 years, 37% of individuals with HCMBL with any mutated gene had progressed requiring treatment compared with 10% among individuals with HCMBL with no mutations; this led to 5.4-fold shorter TTFT (95% CI, 2.6-11.0) among HCMBL with any mutated gene vs none, independent of CLL-IPI. When considering individuals with low risk of progression according to CLL-IPI, those with HCMBL with any mutations had 4.3-fold shorter TTFT (95% CI, 1.6-11.8) vs those with none. Finally, when considering both CLL-IPI and any mutated gene status, we observed individuals with HCMBL who were high risk for both prognostic factors had worse prognosis than patients with low-risk CLL (ie, 5-year progression rate of 32% vs 21%, respectively). Among HCMBL, the frequency of somatically mutated genes at diagnosis is lower than that of CLL. Accounting for both the number of mutated genes and CLL-IPI can identify individuals with HCMBL with more aggressive clinical course.

Background: Monoclonal B-cell lymphocytosis (MBL) is a precursor condition to chronic lymphocytic leukemia (CLL) characterized by the presence of circulating monoclonal B-cell populations in the peripheral blood of otherwise healthy individuals. MBL increases risk of several adverse clinical outcomes, including development of hematological malignancies. Mosaic chromosomal alterations (mCAs) are a form of clonal hematopoiesis which affect large segments of DNA and include gains, losses, and copy number neutral loss of heterozygosity events. mCAs can be detected from SNP-array genotyping. Prior work has suggested mCAs as a potent risk factor for hematological malignancies. However, the nature of the relationship between mCAs and MBL is unknown. We sought to determine 1) the association between mCAs and MBL and 2) their combined effect on risk of hematological malignancies, in a large, prospectively collected, and well-annotated cohort of individuals with known MBL, mCA, and clinical outcomes. Methods: We examined the prevalence of mCA in a cohort of individuals from the Mayo Clinic Biobank who were screened for MBL using a sensitive eight-color flow cytometry assay. We classified MBL by the size of the clone relative to total B-cells, with high count (HC) defined as those individuals who had a percent clonal B-cell count ≥85% out of total B-cell count and low-count (LC) otherwise. Autosomal mCAs were detected from whole blood DNA collected at the time of MBL screening using a SNP-array-based assay. The MoChA pipeline was used to identify mCA events. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CIs). To examine incident hematological cancers, we identified and validated all hematological cancers through medical record abstraction using the International Statistical Classification of Diseases codes. Cox regression was used to calculate hazard ratios (HR) and 95% CIs, stratified by MBL status or autosomal mCA status. All models were adjusted for age and sex. Results: We evaluated the prevalence of autosomal mCA in 3,764 individuals (792 individuals with MBL of whom 64 had HC-MBL and 2,972 without MBL). The prevalence of autosomal mCA was 7.7% ( n=288) with a median mCA cell fraction of 0.09 (range 0.01-1). Among those with and without MBL overall, the prevalence of mCA was 15.5% ( n=123) and 5.6% ( n=165), respectively (Figure 1). Compared to those without an autosomal mCA, individuals with an autosomal mCA were 2.4-fold more likely to have MBL (95% CI 1.9-3.2; P =2.0x10 -11; Figure 1). CLL-associated mCA (i.e., those commonly altered in CLL including trisomy 12 and deletion of 6q, 11q, 13q, and 17p) were present in 42 individuals, of whom 38 (90.5%) had MBL overall and 30 (71.4%) individuals had HC-MBL. Compared to those without a CLL-associated mCA, individuals with a CLL-associated mCA were 539.39-fold more likely to have HC-MBL (95% CI 190.3-1975.9; P <2.0x10 -16) and 6.7-fold more likely to have LC-MBL (95% CI 2.0-26.5; P =0.0031; Figure 1). Next, we evaluated the relationship between MBL and mCA with risk of developing a hematologic malignancy in 3,009 individuals with follow-up data (median 10 years). Forty-one individuals developed an incident hematological malignancy (68.3% lymphoid). When we evaluated the effect of autosomal mCA stratified by MBL status we observed elevated but non-significant risk of hematological malignancies (Figure 2). When we evaluated the effect of MBL stratified by autosomal mCA status we observed elevated and significant increased risk of developing a hematological malignancy (Figure 2). Conclusions: We found that the presence of an autosomal mCA is highly associated with having MBL. In particular, >90% of CLL-associated mCA carriers had MBL with ~7- and ~540-fold increased association for LC- and HC-MBL, respectively. These results suggest that almost all individuals in large biobanks with CLL-associated mCAs have undiagnosed MBL. However, not all individuals with MBL have an mCA. When evaluating risk of hematological malignancies, we found autosomal mCAs had >2-fold elevated but non-significant effects when stratified by MBL status while MBL remained a significant risk factor regardless of autosomal mCA status. Collectively these results support that MBL remains an important risk factor and suggests that mCAs hold potential to identify a subgroup of individuals at greater risk of developing a hematological malignancy.

Background: CLL is the most prevalent adult leukemia with a highly heterogenous genetic landscape leading to extremely varied clinical outcomes. Previously, CLL patients with immunoglobulin heavy chain variable region ( IGHV) mutated status and presence of deletion 13q14 [del(13q)] were identified as favorable-risk with most patients remaining on lifetime observation. However, other intrinsic factors contributing to CLL disease progression and leading to treatment initiation remain unknown. Our goal was to identify patients at high-risk of progression with added predictive value (APV) beyond IGHV-status and presence of del(13q). Methods: Flow cytometry was used to sort CD19+CD5+ malignant cells in peripheral blood from CLL patients at Huntsman Cancer Institute at University of Utah and triple sequencing generated (tumor whole transcriptome and paired tumor-normal whole exome data). We used SPECTRA, a novel dimension reduction transcriptome approach, to derive a set of independent, intrinsic, quantitative transcriptome tumor variables from 249 CLL patients with quality-controlled transcriptome sequence data. From this set, 182 treatment-naïve (TN) patients with quality-controlled clinical variables were used as a discovery cohort set to derive a SPECTRA-based risk score for TTFT using multivariable Cox proportional hazards modeling. Event time was date of patient specimen acquisition to initiation of frontline therapy with patients censored at last follow-up or death. Gaussian mixture modeling (GMM) was performed to identify evidence for distinct risk groups within the quantitative risk score. GMM-risk groups, and further stratifications by IGHV mutational and del(13q) status, were used in hazard ratios (HR) and to illustrate differences in Kaplan-Meier time-to-event curves. An independent publicly available dataset of 548 TN CLL patients with clinical and transcriptome data for CD19+ enriched cells was used for replication. Results: SPECTRA produced 19 quantitative spectra variables to describe most of the expression variation across the 249 CLL patients. In multivariable Cox modeling for TTFT, 7 spectra were significant and retained in a final model, which GMM separated into a bi-modal distribution and defined high (N=83) and low-risk (N=99) groups (HR=5.7, 95% confidence interval [CI] 3.4-9.7). In a post-hoc model including IGHV mutational and del(13q) status, the spectra-risk score showed significant APV beyond both factors (p<0.001 for both). The discovery study timeframe was 6.3 years (y) and included 109 IGHV-mutated and 75 del(13q) patients. In the IGHV-mutated patients, median TTFT (mTTFT) was significantly shorter for spectra-high risk patients (3.1y) vs. spectra-low risk patients (median not reached [NR]; p<0.001). Similarly, in the del(13q) patients, mTTFT was significantly shorter in high-risk patients (3.3y) compared to median NR for spectra-low (p<0.001) ( Figure). Importantly, stratification of patients into low- and high-risk SPECTRA scores provided significant additional information for prediction of TTFT than IGHV mutational and del(13q) status ( Figure). For validation, we applied the same spectra-risk score to the independent data set containing 301 IGHV-mutated and 278 del(13q) CLL patients. In the replication set, the mTTFT in the IGHV-mutated patients who were spectra-high was 3.3y vs. 11.2y in spectra-low (p<0.001). Similarly, in the replication set of del(13q) patients, spectra-high-risk patients had a mTTFT of 2.7y vs. 10.7y for spectra-low (p<0.001). Conclusion: A transcriptome risk score utilizing novel SPECTRA variables identified a substantial subset of CLL patients with IGHV-mutated status and presence of del(13q) who have uncharacteristically short TTFT, but who would be classified as favorable risk under current best practice stratification. Future directions include validating our results with external patient cohorts from Mayo Clinic and investigating the genetic and transcriptomic profile of SPECTRA low- and high-risk cohorts to determine targetable pathways for treatment.

Background: Tumor mutational burden (TMB), defined as the number of nonsynonymous mutations per megabase (Mb) in the coding regions of a tumor genome, has been associated with improved response to immune checkpoint blockade treatments and more broadly with overall survival (OS) in many cancers. Limited prior studies have found that TMB is higher in diffuse large B-cell lymphoma (DLBCL) compared to many other cancers. However, only two studies have evaluated TMB and prognosis in newly diagnosed DLBCL patients. The prognostic role of TMB in diffuse large B-cell lymphoma (DLBCL) remains unclear as prior studies have been limited to panel sequencing of cancer genes and/or lacked matched germline-tumor samples for filtering. Methods: We characterized TMB from whole exome sequencing (WES) in newly diagnosed DLBCL patients with matched diagnostic tumor-normal samples prior to treatment with standard immunochemotherapy (IC). Tumor DNA was extracted from formalin-fixed, paraffin embedded tissue sections and germline DNA from peripheral blood. We evaluated the association between TMB and event-free (EFS) and OS using Cox regression adjusted for the international prognostic index (IPI) and other factors including cell of origin (COO), MYC double hit (DH) with BLC2 or BCL6 by FISH, and TP53 mutation status. EFS and OS were defined as time from diagnosis to earliest of treatment failure (EFS only), death, or last follow-up; EFS at 24 months (EFS24) was also modeled as a marker of early aggressive DLBCL. An optimal high/low TMB cutpoint was determined based on EFS using maximally selected rank statistics; sensitivity analyses used an 20/80 percentile to define the threshold. We also evaluated the association of driver tumor mutational load (driverTML) with EFS and OS, defined as the total number of mutations in 292 DLBCL driver genes. Results: In the analysis cohort of 394 DLBCL patients, the median age at diagnosis was 65 years (interquartile range: 56-73), 43% were female, 62.2% had IPI 0-2, and 57.4% germinal center B-cell COO. MYC was DH in 7.5% and TP53 was mutated in 16.2% of patients. Through a median follow-up of 7.5 years, there were 141 events and 122 deaths. EFS24 was achieved in 75.1% of the cohort; 5-year EFS was 69% (95% CI 64-74%) and 5-year OS was 75% (95% CI 71-80%). Median TMB in our cohort of DLBCL patients was 3.6 mutations/Mb, which was the fifth highest compared with 32 cancers in The Cancer Genome Atlas. As a continuous variable, increasing TMB (mutation/Mb) was associated with superior EFS (HR=0.89, 95% CI 0.81-0.98) and OS (HR=0.89, 95% CI 0.81-0.99) after adjustment for IPI. Spline analyses confirmed linear associations of TMB with EFS and OS. The optimal modeled cutpoint based on EFS was 4.5 mutations/Mb, with 31% classified as high TMB (>4.5). No significant ( P >.05) differences were observed between high and low TMB patients with clinical (i.e., age, sex, IPI category) or molecular (cell of origin, MYC DH, TP53 mutated) factors. In Cox regression, high-TMB was significantly protective for EFS and for OS compared to low-TMB after adjustment for each clinical factor ( Figure 1), with simultaneous adjustment for all these factors associated with superior EFS (HR=0.52, 95% CI 0.33-0.84) and OS (HR=0.59, 95% CI 0.36-1.00). TMB (high/low) combined with IPI (0-2, 3-5) was significantly ( P =.001) associated with EFS in Kaplan-Meier analysis ( Figure 2). Among patients with IPI 3-5, high TMB was significantly associated with superior EFS (HR=0.47, 95% CI 0.27-0.81) and OS (HR=0.57, 95% CI 0.33-0.99). Among patients with IPI 0-2, we also observed longer EFS (HR=0.62, 95% CI 0.34-1.11) and OS (HR=0.62, 95% CI 0.32-1.20) in high TMB patients, although the associations were not statistically significant ( P >.05). In sensitivity analyses, a 20/80 percentile TMB threshold found similar results for EFS (HR=0.64, 95% CI 0.41-1.03) and OS (HR=0.69, 95% CI 0.42-1.12) as in our main analyses. TMB and driverTML were significantly correlated ( R=0.65, P <10 -16) and we found similar effect sizes for EFS (HR=0.45, 95% CI 0.22-0.91) and OS (HR=0.55, 95% 0.27-1.13) as in our main analyses. Conclusions: In a large and well-defined cohort of IC treated DLBCL patients, we found DLBCL patients with higher TMB had superior EFS and OS after adjustment for other clinical and molecular prognostic factors, and the prognostic association for TMB was robust to threshold and gene set.

Abstract TP53 aberrations, including mutations and deletion of 17p13, are important adverse prognostic markers in chronic lymphocytic leukemia (CLL) but are less studied in high count monoclonal B-cell lymphocytosis (HCMBL), an asymptomatic pre-malignant stage of CLL. Here we estimated the prevalence and impact of TP53 aberrations in 1,230 newly diagnosed treatment-naïve individuals (849 CLL, 381 HCMBL). We defined TP53 state as: wild-type (no TP53 mutations and normal 17p), single-hit (del(17p) or one TP53 mutation), or multi-hit (TP53 mutation and del(17p), TP53 mutation and loss of heterozygosity, or multiple TP53 mutations). Cox regression was used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for time to first treatment and overall survival by TP53 state. We found 64 (7.5%) CLL patients and 17 (4.5%) HCMBL individuals had TP53 mutations with variant allele fraction >10%. Del(17p) was present in 58 (6.8%) of CLL and 11 (2.9%) of HCMBL cases. Most individuals had wild-type (N=1,128, 91.7%) TP53 state, followed by multi-hit (N=55, 4.5%) and then single-hit (N=47, 3.8%) TP53 state. The risk of shorter time to therapy and death increased with the number of TP53 abnormalities. Compared to wild-type patients, multi-hit patients had 3-fold and single-hit patients had 1.5-fold increased risk of requiring therapy. Multi-hit patients also had 2.9-fold increased risk of death compared to wild-type. These results remained stable after accounting for other known poor prognostic factors. Both TP53 mutations and del(17p) may provide important prognostic information for HCMBL and CLL that would be missed if only one were measured.

Abstract Background: Transcriptome studies are gaining momentum in genomic epidemiology, and the need to incorporate these data in multivariable models alongside other risk factors brings demands for new approaches. Methods: Here we describe SPECTRA, an approach to derive quantitative variables that capture the intrinsic variation in gene expression of a tissue type. We applied the SPECTRA approach to bulk RNA sequencing from malignant cells (CD138+) in patients from the Multiple Myeloma Research Foundation CoMMpass study. Results: A set of 39 spectra variables were derived to represent multiple myeloma cells. We used these variables in predictive modeling to determine spectra-based risk scores for overall survival, progression-free survival, and time to treatment failure. Risk scores added predictive value beyond known clinical and expression risk factors and replicated in an external dataset. Spectrum variable S5, a significant predictor for all three outcomes, showed pre-ranked gene set enrichment for the unfolded protein response, a mechanism targeted by proteasome inhibitors which are a common first line agent in multiple myeloma treatment. We further used the 39 spectra variables in descriptive modeling, with significant associations found with tumor cytogenetics, race, gender, and age at diagnosis; factors known to influence multiple myeloma incidence or progression. Conclusions: Quantitative variables from the SPECTRA approach can predict clinical outcomes in multiple myeloma and provide a new avenue for insight into tumor differences by demographic groups. Impact: The SPECTRA approach provides a set of quantitative phenotypes that deeply profile a tissue and allows for more comprehensive modeling of gene expression with other risk factors.

AbstractPleiotropy, which consists of a single gene or allelic variant affecting multiple unrelated traits, is common across cancers, with evidence for genome‐wide significant loci shared across cancer and noncancer traits. This feature is particularly relevant in multiple myeloma (MM) because several susceptibility loci that have been identified to date are pleiotropic. Therefore, the aim of this study was to identify novel pleiotropic variants involved in MM risk using 28 684 independent single nucleotide polymorphisms (SNPs) from GWAS Catalog that reached a significant association (P < 5 × 10−8) with their respective trait. The selected SNPs were analyzed in 2434 MM cases and 3446 controls from the International Lymphoma Epidemiology Consortium (InterLymph). The 10 SNPs showing the strongest associations with MM risk in InterLymph were selected for replication in an independent set of 1955 MM cases and 1549 controls from the International Multiple Myeloma rESEarch (IMMEnSE) consortium and 418 MM cases and 147 282 controls from the FinnGen project. The combined analysis of the three studies identified an association between DNAJB4‐rs34517439‐A and an increased risk of developing MM (OR = 1.22, 95%CI 1.13‐1.32, P = 4.81 × 10−7). rs34517439‐A is associated with a modified expression of the FUBP1 gene, which encodes a multifunctional DNA and RNA‐binding protein that it was observed to influence the regulation of various genes involved in cell cycle regulation, among which various oncogenes and oncosuppressors. In conclusion, with a pleiotropic scan approach we identified DNAJB4‐rs34517439 as a potentially novel MM risk locus.

Abstract Background: Genome-wide association studies (GWAS) of multiple myeloma in populations of European ancestry (EA) identified and confirmed 24 susceptibility loci. For other cancers (e.g., colorectum and melanoma), risk loci have also been associated with patient survival. Methods: We explored the possible association of all the known risk variants and their polygenic risk score (PRS) with multiple myeloma overall survival (OS) in multiple populations of EA [the International Multiple Myeloma rESEarch (IMMEnSE) consortium, the International Lymphoma Epidemiology consortium, CoMMpass, and the German GWAS] for a total of 3,748 multiple myeloma cases. Cox proportional hazards regression was used to assess the association between each risk SNP with OS under the allelic and codominant models of inheritance. All analyses were adjusted for age, sex, country of origin (for IMMEnSE) or principal components (for the others) and disease stage (ISS). SNP associations were meta-analyzed. Results: SNP associations were meta-analyzed. From the meta-analysis, two multiple myeloma risk SNPs were associated with OS (P &lt; 0.05), specifically POT1-AS1-rs2170352 [HR = 1.37; 95% confidence interval (CI) = 1.09–1.73; P = 0.007] and TNFRSF13B-rs4273077 (HR = 1.19; 95% CI = 1.01–1.41; P = 0.04). The association between the combined 24 SNP MM-PRS and OS, however, was not significant. Conclusions: Overall, our results did not support an association between the majority of multiple myeloma risk SNPs and OS. Impact: This is the first study to investigate the association between multiple myeloma PRS and OS in multiple myeloma.