Vachon, Celine M.

Introduction: First degree relatives of patients with monoclonal gammopathy of undetermined significance (MGUS) or multiple myeloma (MM), and African Americans, have an increased risk of having MGUS and MM compared to the general population. However, current guidelines do not advocate for screening family members of MM for plasma cell disorders (PCD). Understanding the epidemiology of familial plasma cell disorders (PCDs) is essential in order to identify people at highest risk of developing PCDs who may benefit from targeted screening strategies. The aims of this study were to assess the prevalence of MM patients with a family history of PCD, and the implications of a family history of PCD on the overall survival (OS) of MM patients. Methods: We retrospectively reviewed the electronic medical records of patients with symptomatic MM followed at Mayo Clinic and diagnosed between January 1989 and June 2019. Clinical notes were reviewed for documentation pertaining to family history of PCDs. Kaplan Meier survival analysis was used to assess the OS, where OS was calculated from the date of diagnosis of symptomatic MM until death; patients were censored if they were alive at the date of last follow up. A Cox proportional hazards model was used to provide risk estimates for OS. Results: A total of 8403 patients with symptomatic MM were included in this study. Family history was documented in 1521 patients, and 291 patients (3.5% of all patients, 19% of those with any documented family history) had a documented family member with a PCD. The median age at diagnosis of symptomatic MM was significantly lower in patients with (n=291) versus without (n= 8112) a family history of PCD (60.9 versus 63.6 years, p<0.0001). The median OS of MM patients with a family history of PCD was significantly longer than MM patients without a family history of PCD (8.1 versus 4.9 years, respectively, with p<0.0001, see figure 1). Using a multivariable Cox proportional hazards model, MM patients with a family history of PCD had a significantly lower risk of death compared to those without a family history of PCD (HR 0.66, 95% CI 0.55-0.78, p<0.0001) even after adjusting for sex, age at diagnosis (above versus below age 65), self-reported race (African American versus not African American), or date of diagnosis (before versus after 2010). When restricting the analyses to the 1521 patients with clearly documented family history, the survival benefit amongst patients with versus without a family history of PCD was similar. In probands with a PCD family history, 182 (63%) had a first degree relative with PCD, whereas 109 (37%) had a second degree relative with PCD. The most common reported PCD amongst family members was MM (figure 2). Nineteen (6.5%) probands with a family history of PCD had 2 or more relatives with a PCD (6 MM patients had 2 or more first degree relatives, 5 MM patients had at least 1 first and 1 second degree relative, and 8 MM patients had 2 or more second degree relatives with a PCD history). There was no significant difference in the median OS between MM patients with a first degree versus second degree relative with PCD (HR 1.03, 95% CI 0.74-1.46, p=0.837), or MM patients with 1 versus 2 or more relatives with PCD (HR 1.01, 95% CI 0.53-1.96, p=0.962). Conclusion: We reviewed patients with symptomatic MM seen at Mayo Clinic over the last 30 years and found that the prevalence of patients with a documented family history of PCD was 3.5%. MM patients with a family history of PCD were diagnosed with MM at a younger age and survived longer than patients without a family history of PCD. Further work is needed to understand factors underlying the survival benefit in patients with a family history of PCD, and whether they present with less aggressive or less advanced disease at diagnosis. Disclosures Dispenzieri: Intellia: Research Funding; Alnylam: Research Funding; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Janssen: Research Funding. Kapoor:Sanofi: Consultancy, Research Funding; Cellectar: Consultancy; Janssen: Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; GlaxoSmithKline: Research Funding; Celgene: Honoraria. Gertz:Spectrum: Other: personal fee, Research Funding; Janssen: Other: personal fee; Abbvie: Other; Amgen: Other: personal fee; Physicians Education Resource: Other: personal fee; Medscape: Other: personal fee, Speakers Bureau; Prothena: Other: personal fee; Teva: Speakers Bureau; Celgene: Other; Research to Practice: Other; Sanofi: Other; DAVA oncology: Speakers Bureau; Annexon: Other: personal fee; Appellis: Other: personal fee; Ionis/Akcea: Other: personal fee; Alnylam: Other: personal fee; Aurora Bio: Other; Proclara: Other; Johnson and Johnson: Speakers Bureau; Springer Publishing: Patents & Royalties. Kumar:Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Novartis: Research Funding; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Carsgen: Other, Research Funding; Cellectar: Other; Dr. Reddy's Laboratories: Honoraria; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; BMS: Consultancy, Research Funding; Karyopharm: Consultancy; MedImmune: Research Funding; Sanofi: Research Funding; Tenebio: Other, Research Funding; Kite Pharma: Consultancy, Research Funding; Adaptive Biotechnologies: Consultancy; Genecentrix: Consultancy; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Merck: Consultancy, Research Funding; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments.

Introduction Monoclonal gammopathy of undetermined significance (MGUS) is a premalignant clonal disorder, which progresses at a rate of 1% per year to multiple myeloma (MM), or other plasma-cell or lymphoid disorders. MGUS is common and occurs in approximately 3% and 5% of persons 50 and 70 years of age or older, respectively. Clinical factors reported to be associated with MGUS progression include MGUS isotype, abnormal serum free light-chain ratio (FLCr), and high serum monoclonal protein (M protein) level (>=1.5 g per deciliter). Body mass index (BMI) has also been seen associated with MGUS progression, but has not been evaluated in context of established clinical prognostic factors. Here, we evaluate the contribution of BMI to MGUS progression beyond clinical prognostic factors in a population-based study and examine differential associations by sex. Methods We studied 594 patients residing in Olmsted County Minnesota, who were identified with MGUS in a screening study conducted between1995 through 2003. Patients with light-chain MGUS were not included. Patients were screened for M-protein [normal (<1.5 g/dl) or high (≥1.5 g/dl)], FLCr [normal (0.26-1.65) or abnormal (<0.26 and/or >1.65)], and isotype (IgG, IgM, IgA, bi-clonal). Follow-up time was calculated from date of MGUS screening to date of last follow-up, death, or progression to MM or another plasma-cell or lymphoid disorder. BMI (kg/m2) was calculated using height and weight values reported close to sample date (80% of patients within 2 years), and then categorized into BMI<25 and BMI≥25. We used Cox regression to estimate the association of BMI with risk of MGUS progression to MM or another plasma-cell or lymphoid disorder, univariately, and accounting for clinical factors. Analyses were also stratified by sex. We report hazard ratios (HR) and 95% confidence intervals (CI). Results Of the 594 patients, 51% were male, and the median age at screening date was 73 (range:50-98 years). The immunoglobulin type was IgG in 71% of patients, IgM in 17%, IgA in 10%, and bi-clonal in 2%. High M protein level was observed in 22% and abnormal FLCr in 28%. BMI≥25 was observed in 67% of patients. The median follow-up time was 10.5 years (range:0-25). Over a median of 6,846 person-years, 465 patients (78%) died and 57 patients progressed and developed MM (N=39), amyloidosis (N=8), lymphoma (N=5), or Waldenstrom macroglobulinemia (N=5). The overall rate of progression was 0.87 events (CI:0.67-1.12) per 100 person-years, and higher among males (1.01, CI:0.73-1.42) than in females (0.72, CI:0.48-1.08), however, the difference was not statistically significant (P=0.24). In univariate analyses, BMI≥25 (HR=2.14, CI:1.05-4.36, P=0.04), non-IgG isotype (HR=2.84, CI:1.68-4.80, P=0.0001), high M protein (HR=2.57, CI: 1.50-4.42, P=0.001), and abnormal FLCr (HR=3.39, CI:1.98-5.82, P<0.0001) were associated with increased risk of progression (Table 1.A). These four factors were independently associated with MGUS progression in a multivariable model, with a c-statistic=0.75 (CI:0.68-0.82). When stratifying by sex, associations of BMI with progression were stronger among females than males (Table 1.B) [c-statistic=0.81 (CI:0.72-0.90) vs 0.71 (CI:0.60-0.82) for females vs. males respectively], however, a test for interaction between BMI and sex was not statistically significant (P=0.15). Conclusions In this study we found evidence that high BMI is a prognostic factor independent of isotype, M protein, and FLC ratio in the full cohort, however, this was mainly driven by the effect in females rather than males. Future studies should further investigate sex differences in evaluating prognostic factors among MGUS patients. Disclosures Dispenzieri: Intellia: Research Funding; Pfizer: Research Funding; Alnylam: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Janssen: Research Funding. Kumar:Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Cellectar: Other; Kite Pharma: Consultancy, Research Funding; Tenebio: Other, Research Funding; BMS: Consultancy, Research Funding; Karyopharm: Consultancy; MedImmune: Research Funding; Sanofi: Research Funding; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Merck: Consultancy, Research Funding; Adaptive Biotechnologies: Consultancy; Genecentrix: Consultancy; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Dr. Reddy's Laboratories: Honoraria; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Novartis: Research Funding; Carsgen: Other, Research Funding; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member.

Abstract Antimullerian hormone (AMH) is a promising biomarker for ovarian reserve. In this study, we assessed AMH before and 1 year after initiation of adjuvant chemotherapy on National Surgical Adjuvant Breast and Bowel Project (NSABP)/NRG Oncology B-47 in female participants aged 42 years and younger (median age = 39 years). At baseline, median AMH was 1.2 ng/mL; 13 (4.7%) values were less than 0.1 ng/mL (the threshold for detectable levels, in the perimenopause and menopause range), and 57 values (20.6%) were less than 0.5 ng/mL. At 1 year, 215 (77.6%) were less than 0.1 ng/mL, and 264 (95.3%) were less than 0.5 ng/mL. Postchemotherapy menses were reported by 46.2% of participants. Multivariable logistic regression found that the odds of having postchemotherapy menses increased with younger age, higher body mass index, and higher prechemotherapy AMH, but not by trastuzumab administration or by the choice of chemotherapy (doxorubicin-cyclophosphamide followed by paclitaxel vs docetaxel-cyclophosphamide). We conclude that higher prechemotherapy AMH predicts a lower risk of chemotherapy-induced amenorrhea and that AMH 1 year after chemotherapy initiation is not informative in this setting because it is likely to be very low.

Abstract Endocrine therapy is underutilized to reduce breast cancer incidence among women at increased risk. Polygenic risk scores (PRSs) assessing 77 breast cancer genetic susceptibility loci personalizes risk estimates. We examined effect of personalized PRS breast cancer risk prediction on intention to take and endocrine therapy uptake among women at increased risk. Eligible participants had a 10-year breast cancer risk ≥5% by Tyrer–Cuzick model [International Breast Cancer Intervention Study (IBIS)] or ≥3.0 % 5-year Gail Model risk with no breast cancer history or hereditary breast cancer syndrome. Breast cancer risk was estimated, endocrine therapy options were discussed, and endocrine therapy intent was assessed at baseline. After genotyping, PRS-updated breast cancer risk estimates, endocrine therapy options, and intent to take endocrine therapy were reassessed; endocrine therapy uptake was assessed during follow-up. From March 2016 to October 2017, 151 patients were enrolled [median (range) age, 56.1 (36.0–76.4 years)]. Median 10-year and lifetime IBIS risks were 7.9% and 25.3%. Inclusion of PRS increased lifetime IBIS breast cancer risk estimates for 81 patients (53.6%) and reduced risk for 70 (46.4%). Of participants with increased breast cancer risk by PRS, 39 (41.9%) had greater intent to take endocrine therapy; of those with decreased breast cancer risk by PRS, 28 (46.7%) had less intent to take endocrine therapy (P < 0.001). On multivariable regression, increased breast cancer risk by PRS was associated with greater intent to take endocrine therapy (P < 0.001). Endocrine therapy uptake was greater among participants with increased breast cancer risk by PRS (53.4%) than with decreased risk (20.9%; P < 0.001). PRS testing influenced intent to take and endocrine therapy uptake. Assessing PRS effect on endocrine therapy adherence is needed. Prevention Relevance: Counseling women at increased breast cancer risk using polygenic risk score (PRS) risk estimates can significantly impact preventive endocrine therapy uptake. Further development of PRS testing to personalize breast cancer risk assessments and endocrine therapy counselling may serve to potentially reduce the incidence of breast cancer in the future.

Abstract Immune dysfunction is a hallmark of CLL/MBL; ~25% individuals with newly diagnosed CLL have hypogammaglobulinemia at diagnosis. In this study of newly diagnosed CLL/MBL, we sought to a) investigate the association between serum immunoglobulins and specific mutations identified by next generation sequencing, and b) determine if serum immunoglobulin levels predict TFT, independent of the CLL-International Prognostic Index (CLL-IPI) and tumor mutational load (TML). We used the Mayo Clinic CLL Resource to identify newly diagnosed CLL/MBL individuals consented within 2 years of diagnosis. Baseline clinical characteristics and the CLL-IPI score was ascertained on all individuals. DNA was extracted from peripheral blood CD5+/CD19+ clonal B-cells; and the entire coding regions of 60 somatically recurring mutated CLL driver genes were enriched using a customized Agilent SureSelect gene panel and sequenced in Illumina Hiseq4000. Serum immunoglobulins were quantitated by radial immunodiffusion using Immunoplates. The relationship between serum immunoglobulins was assessed: a) with individual gene mutations (mutated vs. not); and b) using the TML score (using a value of 0, 1, and 2 or greater [2+] mutated genes). The impact of serum immunoglobulin levels on TFT was analyzed for all individuals. Of 356 individuals identified, 80 (22%) had MBL, median age was 63 years (28-87), 261 (73%) were male, and the CLL-IPI distribution was: low risk (n=149, 42%), intermediate risk (n=112, 32%), and high/very high risk (n=94, 26%). We observed 43%, 39%, and 18% individuals with 0, 1, or 2+ mutated genes, respectively. The most commonly mutated genes were NOTCH1 (13%), SF3B1 (13%), TP53 (8%), ATM (8%), BIRC3 (7%), and NFKBIE (7%). Using standard cutoffs, 135 (38%) individuals had low serum IgG, 73 (21%) had low serum IgA, and 154 (44%) had low serum IgM at diagnosis. There were no differences in individual gene mutation frequencies between individuals with low and normal serum IgG. In contrast, individuals with low serum IgA were more likely to have mutations in NOTCH1 (25% vs 10%) and ATM (14% vs 7%) compared to those with normal IgA, and individuals with low serum IgM were more likely to have mutations in NOTCH1 (19% vs 9%) and BIRC3 (11% vs 4%) compared to those with normal IgM (all p-values <0.05). There were no significant differences in individuals with low serum IgG based on TML scores of 0, 1, and 2+ (31%, 35%, 40%, respectively, p=0.28). However, individuals with low serum IgA and low serum IgM were more likely to have a higher TML (8%, 20%, 36% for IgA, p<0.0001; and 35%, 45%, 54% for IgM, p<0.0001, for TML scores of 0, 1, and 2+, respectively). After a median follow-up of 6.9 years, 157 individuals required CLL therapy. After adjusting for CLL-IPI and TML, low serum IgG, low serum IgA, and low serum IgM (hazard ratio [HR]: 1.8, 2.3, and 2.4, respectively, all p-values <0.05) were independently associated with a shorter TFT. Our study shows that individuals with CLL/MBL who harbor mutations in NOTCH1, ATM and BIRC3 are more likely to have low serum IgA and IgM at diagnosis. Serum IgA and IgM (but not serum IgG) levels decrease with an increase in the TML score. Finally, low serum immunoglobulins can predict TFT, independent of the CLL-IPI and TML, which has important implications for risk stratification in newly diagnosed CLL/MBL. Citation Format: Sameer A. Parikh, Cristine Allmer, Geffen Kleinstern, Nicholas J. Boddicker, Shulan Tian, Cecilia B. De Campos, Laura A. Bruins, Daniel R. o"brien, Brian F. Kabat, Kari G. Rabe, Aaron D. Norman, Huihuang Yan, Xing Li, Timothy G. Call, Wei Ding, Jose F. Leis, Saad J. Kenderian, Celine M. Vachon, James R. Cerhan, Neil E. Kay, Susan L. Slager, Esteban Braggio. Serum immunoglobulins are an independent prognostic marker of time to first therapy in newly diagnosed chronic lymphocytic leukemia (CLL) and monoclonal B-cell lymphocytosis (MBL) [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 6466.

Abstract Background: Biopsy diagnosis of benign breast disease (BBD) based on the most severe lesion in a sample predicts future breast cancer risk and has implications for screening and management. Lobules are the functional unit of the breast and the structures from which BBD arises. We developed and preliminarily validated an automated computational pathology algorithm to discriminate normal from BBD breast lobules as a step toward automated comprehensive characterization of benign biopsies. Methods: 152 BBD biopsies (27 training, 125 validation) from the Mayo Clinic were examined using scanned digital images of H&E stained sections. For each image, a pathologist annotated up to 10 representative lobules as normal or BBD using standard pathology criteria. A deep learning algorithm to quantify lobular features was developed using 129 lobules from 27 subjects. Nine features were identified that discriminate normal vs BBD lobules, expressing lobule size, acini size and number, acinar lumen size, proportion of lobular stroma, and capillaries. Here, we validate their performance to discriminate normal vs BBD lobules in a set of 1250 lobules from 125 subjects using area under the ROC curve (AUC) analysis. Random forest analysis was used for multivariable modeling; model performance was assessed with a tenfold cross-validation approach. Results: Median subject age was 52 years. Among the 125 validation subjects, BBD findings were nonproliferative in 39%, proliferative in 45%, and atypical hyperplasia in 16%. Sections included 552 (44%) normal lobules and 698 BBD (56%) lobules, with representation of both lobule types on each section. In univariate analyses, four individual features showed good discrimination between normal vs. BBD lobules, yielding the following AUCs: lobule size= 0.74, mean acini size= 0.75, epithelial area= 0.75, and number of acini with large lumens= 0.76. Lobule size and epithelial area were highly correlated (Spearman rank correlation r = 0.95), but both of these features showed lower correlation with mean acini size and number of acini with large lumens (each r < 0.5). With random forest modeling, number of acini with large lumens was the strongest discriminating feature, followed by mean acini size, lobule size, and epithelial area. With ten-fold cross validation of the multivariable random forest model, the overall AUC was 0.82 (95% CI: 0.79-0.85). Conclusion: Our validation showed that automated quantitative computational pathology assessment of breast lobules can discriminate normal versus BBD on a per lobule basis. This finding supports the feasibility of developing automated algorithms to classify every lesion in breast biopsies, expanding beyond visual assessment. Further studies using deep learning may reveal novel pathology features for classifying BBD biopsies with the potential to strengthen estimation of breast cancer risk. Citation Format: Amy C. Degnim, Thomas de Bel, Mark E. Sherman, Derek C. Radisky, Stacey J. Winham, Tanya L. Hoskin, Melody L. Stallings Mann, Marlene Frost, Robert A. Vierkant, Brendan T. Broderick, Ethan P. Heinzen, Rushin Brahmbhatt, Muhammad Arshad, Celine M. Vachon, Jodi M. Carter, Lori A. Denison, Daniel W. Visscher, Jeroen van der Laak. Discrimination of benign breast disease from normal lobules using an automated computational pathology algorithm [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2113.

1061 Background: Benign breast disease (BBD) is a significant risk factor for breast cancer (BC); however little is known about the aggressiveness of the BCs these patients develop. Shared features between select atypias and low-grade DCIS have led some to speculate that a history of BBD portends the development of well-differentiated BCs. Methods: The Mayo BBD cohort includes 9,376 women who had benign breast biopsies from 1967–1991. Data on BC events were obtained from medical records and questionnaires. Tissue from the BCs was reviewed by a single breast pathologist (DWV). Results: Our cohort included 6,244 patients with nonproliferative disease (NP), 2,801 women with proliferative disease without atypia (PDWA), and 331 with atypical hyperplasias (AH). With a median of 18 years of follow-up, 799 patients with BBD have developed breast cancer, 416 initially had NP, 313 had PDWA, and 70 AH. BC tissue was available for 703 of the women. The cancers were invasive ductal in 76.1% (n = 535), invasive lobular in 9.4% (n = 66), and DCIS alone in 14.5% (n = 102) patients. Grade is currently available for 500 women, and is well differentiated in 29.4% (n = 150), moderately differentiated in 42.7% (n = 218) and poorly differentiated in 27.8% (n = 142). In 537 cases the malignant tissue had a concurrent benign component consisting of NP in 24% (n = 129), PDWA in 25.1% (n = 135), and AH in 50.8% (n = 273). In regards to tumor size, 69.6% had T1 tumors, 24.9% T2 tumors, and 5.5% T3 disease. Metastasis to lymph nodes occurred in 25% of patients. Median time to BC was 12.3 years and did not differ across the different benign entities. Breast cancer developed within 5 years from the initial BBD in 163 women (20%). In this group, tumor size was greater (p = 0.02), and there were more poorly differentiated tumors (p = 0.006) than in those who later developed BC. Conclusions: In the BCs that have developed in our BBD cohort, we do not see a preponderance of well-differentiated, good-risk BCs. Patients diagnosed within 5 years of BBD appear to have BCs with more aggressive features. No significant financial relationships to disclose.

Abstract Over one million women in the United States receive biopsy diagnoses of benign breast disease (BBD) each year, which confer a 1.5–4.0-fold increase in breast cancer risk. Studies in the general population suggest that nonsteroidal anti-inflammatory agents (NSAID) lower breast cancer risk; however, associations among women with BBD are unknown. We assessed whether NSAID use among women diagnosed with BBD is associated with lower breast cancer risk. Participants included 3,080 women (mean age = 50.3 ± 13.5 years) in the Mayo BBD surgical biopsy cohort diagnosed between January 1, 1992 and December 31, 2001 who completed breast cancer risk factor questionnaires that assessed NSAID use, and whose biopsies underwent detailed pathology review, masked to outcome. Women were followed from date of BBD biopsy to breast cancer diagnosis (main outcome) or censoring (death, prophylactic mastectomy, reduction mammoplasty, lobular carcinoma in situ or last contact). Median follow-up time was 16.4 ± 6.0 years. Incident breast cancer was diagnosed among 312 women over a median follow-up of 9.9 years. Regular non-aspirin NSAID use was associated with lower breast cancer risk [HR = 0.63; 95% confidence interval (CI) = 0.46–0.85; P = 0.002] with trends of lower risk (highest tertiles of use vs. nonuse) for greater number of years used [HR = 0.55; 95% CI = 0.31–0.97; Ptrend = 0.003), days used per month (HR = 0.51; 95% CI = 0.33–0.80; Ptrend = 0.001) and lifetime number of doses taken (HR = 0.53; 95% CI = 0.31–0.89; Ptrend = 0.003). We conclude that nonaspirin NSAID use is associated with statistically significant lower breast cancer risk after a BBD biopsy, including a dose–response effect, suggesting a potential role for NSAIDs in breast cancer prevention among patients with BBD.

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.