Habib El-Khoury1, David J Lee2, Jean-Baptiste Alberge3, Robert Redd4, Christian J Cea-Curry1, Jacqueline Perry1, Hadley Barr1, Ciara Murphy1, Dhananjay Sakrikar5, David Barnidge5, Mark Bustoros6, Houry Leblebjian7, Anna Cowan8, Maya I Davis1, Julia Amstutz1, Cody J Boehner1, Elizabeth D Lightbody1, Romanos Sklavenitis-Pistofidis3, Mark C Perkins9, Stephen Harding9, Clifton C Mo1, Prashant Kapoor10, Joseph Mikhael11, Ivan M Borrello12, Rafael Fonseca13, Scott T Weiss14, Elizabeth Karlson15, Lorenzo Trippa16, Timothy R Rebbeck17, Gad Getz18, Catherine R Marinac19, Irene M Ghobrial20. 1. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Harvard Medical School, Boston, MA, USA. 2. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Department of Medicine, Massachusetts General Hospital, Boston, MA, USA. 3. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA. 4. Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA, USA. 5. The Binding Site, Rochester, MN, USA. 6. Department of Medical Oncology, Weill Cornell Medicine, New York, NY, USA. 7. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Pharmacy, Dana-Farber Cancer Institute, Boston, MA, USA. 8. Alix School of Medicine, The Mayo Clinic, Rochester, MN, USA. 9. The Binding Site Group, Birmingham, UK. 10. The Mayo Clinic, Rochester, MN, USA. 11. Translational Genomics Research Institute, City of Hope Cancer Center, Phoenix, AZ, USA; International Myeloma Foundation, North Hollywood, CA, USA. 12. Department of Medical Oncology, Johns Hopkins University School of Medicine, Baltimore, MD, USA. 13. Department of Medical Oncology, The Mayo Clinic, Phoenix, AZ, USA. 14. Harvard Medical School, Boston, MA, USA; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA. 15. Harvard Medical School, Boston, MA, USA; Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA. 16. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA. 17. The Center for Prevention of Progression of Blood Cancer, Dana-Farber Cancer Institute, Boston, MA, USA. 18. Harvard Medical School, Boston, MA, USA; Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA. 19. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; The Center for Prevention of Progression of Blood Cancer, Dana-Farber Cancer Institute, Boston, MA, USA; Harvard Medical School, Boston, MA, USA. 20. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; The Center for Prevention of Progression of Blood Cancer, Dana-Farber Cancer Institute, Boston, MA, USA; Harvard Medical School, Boston, MA, USA. Electronic address: irene_ghobrial@dfci.harvard.edu.
Abstract
BACKGROUND: Prevalence estimates for monoclonal gammopathy of undetermined significance (MGUS) are based on predominantly White study populations screened by serum protein electrophoresis supplemented with immunofixation electrophoresis. A prevalence of 3% is reported for MGUS in the general population of European ancestry aged 50 years or older. MGUS prevalence is two times higher in individuals of African descent or with a family history of conditions related to multiple myeloma. We aimed to evaluate the prevalence and clinical implications of monoclonal gammopathies in a high-risk US population screened by quantitative mass spectrometry. METHODS: We used quantitative matrix-assisted laser desorption ionisation-time of flight (MALDI-TOF) mass spectrometry and EXENT-iQ software to screen for and quantify monoclonal gammopathies in serum from 7622 individuals who consented to the PROMISE screening study between Feb 26, 2019, and Nov 4, 2021, and the Mass General Brigham Biobank (MGBB) between July 28, 2010, and July 1, 2021. M-protein concentrations at the monoclonal gammopathy of indeterminate potential (MGIP) level were confirmed by liquid chromatography mass spectrometry testing. 6305 (83%; 2211 from PROMISE, 4094 from MGBB) of 7622 participants in the cohorts were at high risk for developing a monoclonal gammopathy on the basis of Black race or a family history of haematological malignancies and fell within the eligible high-risk age range (30 years or older for PROMISE cohort and 18 years or older for MGBB cohort); those over 18 years were also eligible if they had two or more family members with a blood cancer (PROMISE cohort). Participants with a plasma cell malignancy diagnosed before screening were excluded. Longitudinal clinical data were available for MGBB participants with a median follow-up time from serum sample screening of 4·5 years (IQR 2·4-6·7). The PROMISE study is registered with ClinicalTrials.gov, NCT03689595. FINDINGS: The median age at time of screening was 56·0 years (IQR 46·8-64·1). 5013 (66%) of 7622 participants were female, 2570 (34%) male, and 39 (<1%) unknown. 2439 (32%) self-identified as Black, 4986 (65%) as White, 119 (2%) as other, and 78 (1%) unknown. Using serum protein electrophoresis with immunofixation electrophoresis, the MGUS prevalence was 6% (101 of 1714) in high-risk individuals aged 50 years or older. Using mass spectrometry, we observed a total prevalence of monoclonal gammopathies of 43% (1788 of 4207) in this group. We termed monoclonal gammopathies below the clinical immunofixation electrophoresis detection level (<0·2 g/L) MGIPs, to differentiate them from those with higher concentrations, termed mass-spectrometry MGUS, which had a 13% (592 of 4207) prevalence by mass spectrometry in high-risk individuals aged 50 years or older. MGIP was predominantly of immunoglobulin M isotype, and its prevalence increased with age (19% [488 of 2564] for individuals aged <50 years, 29% [1464 of 5058] for those aged ≥50 years, and 37% [347 of 946] for those aged ≥70 years). Mass-spectrometry MGUS prevalence increased with age (5% [127 of 2564] for individuals aged <50 years, 13% [678 of 5058] for those aged ≥50 years, and 18% [173 of 946] for those aged ≥70 years) and was higher in men (314 [12%] of 2570) compared with women (485 [10%] 5013; p=0·0002), whereas MGIP prevalence did not differ significantly by gender. In those aged 50 years or older, the prevalence of mass spectrometry was significantly higher in Black participants (224 [17%] of 1356) compared with the controls (p=0·0012) but not in those with family history (368 [13%] of 2851) compared with the controls (p=0·1008). Screen-detected monoclonal gammopathies correlated with increased all-cause mortality in MGBB participants (hazard ratio 1·55, 95% CI 1·16-2·08; p=0·0035). All monoclonal gammopathies were associated with an increased likelihood of comorbidities, including myocardial infarction (odds ratio 1·60, 95% CI 1·26-2·02; p=0·00016 for MGIP-high and 1·39, 1·07-1·80; p=0·015 for mass-spectrometry MGUS). INTERPRETATION: We detected a high prevalence of monoclonal gammopathies, including age-associated MGIP, and made more precise estimates of mass-spectrometry MGUS compared with conventional gel-based methods. The use of mass spectrometry also highlighted the potential hidden clinical significance of MGIP. Our study suggests the association of monoclonal gammopathies with a variety of clinical phenotypes and decreased overall survival. FUNDING: Stand Up To Cancer Dream Team, the Multiple Myeloma Research Foundation, and National Institutes of Health.
BACKGROUND: Prevalence estimates for monoclonal gammopathy of undetermined significance (MGUS) are based on predominantly White study populations screened by serum protein electrophoresis supplemented with immunofixation electrophoresis. A prevalence of 3% is reported for MGUS in the general population of European ancestry aged 50 years or older. MGUS prevalence is two times higher in individuals of African descent or with a family history of conditions related to multiple myeloma. We aimed to evaluate the prevalence and clinical implications of monoclonal gammopathies in a high-risk US population screened by quantitative mass spectrometry. METHODS: We used quantitative matrix-assisted laser desorption ionisation-time of flight (MALDI-TOF) mass spectrometry and EXENT-iQ software to screen for and quantify monoclonal gammopathies in serum from 7622 individuals who consented to the PROMISE screening study between Feb 26, 2019, and Nov 4, 2021, and the Mass General Brigham Biobank (MGBB) between July 28, 2010, and July 1, 2021. M-protein concentrations at the monoclonal gammopathy of indeterminate potential (MGIP) level were confirmed by liquid chromatography mass spectrometry testing. 6305 (83%; 2211 from PROMISE, 4094 from MGBB) of 7622 participants in the cohorts were at high risk for developing a monoclonal gammopathy on the basis of Black race or a family history of haematological malignancies and fell within the eligible high-risk age range (30 years or older for PROMISE cohort and 18 years or older for MGBB cohort); those over 18 years were also eligible if they had two or more family members with a blood cancer (PROMISE cohort). Participants with a plasma cell malignancy diagnosed before screening were excluded. Longitudinal clinical data were available for MGBB participants with a median follow-up time from serum sample screening of 4·5 years (IQR 2·4-6·7). The PROMISE study is registered with ClinicalTrials.gov, NCT03689595. FINDINGS: The median age at time of screening was 56·0 years (IQR 46·8-64·1). 5013 (66%) of 7622 participants were female, 2570 (34%) male, and 39 (<1%) unknown. 2439 (32%) self-identified as Black, 4986 (65%) as White, 119 (2%) as other, and 78 (1%) unknown. Using serum protein electrophoresis with immunofixation electrophoresis, the MGUS prevalence was 6% (101 of 1714) in high-risk individuals aged 50 years or older. Using mass spectrometry, we observed a total prevalence of monoclonal gammopathies of 43% (1788 of 4207) in this group. We termed monoclonal gammopathies below the clinical immunofixation electrophoresis detection level (<0·2 g/L) MGIPs, to differentiate them from those with higher concentrations, termed mass-spectrometry MGUS, which had a 13% (592 of 4207) prevalence by mass spectrometry in high-risk individuals aged 50 years or older. MGIP was predominantly of immunoglobulin M isotype, and its prevalence increased with age (19% [488 of 2564] for individuals aged <50 years, 29% [1464 of 5058] for those aged ≥50 years, and 37% [347 of 946] for those aged ≥70 years). Mass-spectrometry MGUS prevalence increased with age (5% [127 of 2564] for individuals aged <50 years, 13% [678 of 5058] for those aged ≥50 years, and 18% [173 of 946] for those aged ≥70 years) and was higher in men (314 [12%] of 2570) compared with women (485 [10%] 5013; p=0·0002), whereas MGIP prevalence did not differ significantly by gender. In those aged 50 years or older, the prevalence of mass spectrometry was significantly higher in Black participants (224 [17%] of 1356) compared with the controls (p=0·0012) but not in those with family history (368 [13%] of 2851) compared with the controls (p=0·1008). Screen-detected monoclonal gammopathies correlated with increased all-cause mortality in MGBB participants (hazard ratio 1·55, 95% CI 1·16-2·08; p=0·0035). All monoclonal gammopathies were associated with an increased likelihood of comorbidities, including myocardial infarction (odds ratio 1·60, 95% CI 1·26-2·02; p=0·00016 for MGIP-high and 1·39, 1·07-1·80; p=0·015 for mass-spectrometry MGUS). INTERPRETATION: We detected a high prevalence of monoclonal gammopathies, including age-associated MGIP, and made more precise estimates of mass-spectrometry MGUS compared with conventional gel-based methods. The use of mass spectrometry also highlighted the potential hidden clinical significance of MGIP. Our study suggests the association of monoclonal gammopathies with a variety of clinical phenotypes and decreased overall survival. FUNDING: Stand Up To Cancer Dream Team, the Multiple Myeloma Research Foundation, and National Institutes of Health.
Authors: Ola Landgren; S Vincent Rajkumar; Ruth M Pfeiffer; Robert A Kyle; Jerry A Katzmann; Angela Dispenzieri; Qiuyin Cai; Lynn R Goldin; Neil E Caporaso; Joseph F Fraumeni; William J Blot; Lisa B Signorello Journal: Blood Date: 2010-04-26 Impact factor: 22.113
Authors: Ola Landgren; Gloria Gridley; Ingemar Turesson; Neil E Caporaso; Lynn R Goldin; Dalsu Baris; Thomas R Fears; Robert N Hoover; Martha S Linet Journal: Blood Date: 2005-10-06 Impact factor: 22.113
Authors: Robert A Kyle; Terry M Therneau; S Vincent Rajkumar; Dirk R Larson; Matthew F Plevak; Janice R Offord; Angela Dispenzieri; Jerry A Katzmann; L Joseph Melton Journal: N Engl J Med Date: 2006-03-30 Impact factor: 91.245
Authors: David L Murray; Justin L Seningen; Angela Dispenzieri; Melissa R Snyder; Robert A Kyle; S Vincent Rajkumar; Jerry A Katzmann Journal: Am J Clin Pathol Date: 2012-10 Impact factor: 2.493
Authors: Celine M Vachon; Robert A Kyle; Terry M Therneau; Barbara J Foreman; Dirk R Larson; Colin L Colby; Tara K Phelps; Angela Dispenzieri; Shaji K Kumar; Jerry A Katzmann; S Vincent Rajkumar Journal: Blood Date: 2009-01-29 Impact factor: 22.113
Authors: Ola Landgren; Robert A Kyle; Ruth M Pfeiffer; Jerry A Katzmann; Neil E Caporaso; Richard B Hayes; Angela Dispenzieri; Shaji Kumar; Raynell J Clark; Dalsu Baris; Robert Hoover; S Vincent Rajkumar Journal: Blood Date: 2009-01-29 Impact factor: 22.113
Authors: Henry T Lynch; Kelly Ferrara; Bart Barlogie; Elizabeth A Coleman; Jane F Lynch; Dennis Weisenburger; Warren Sanger; Patrice Watson; Henry Nipper; Vinetta Witt; Stephan Thomé Journal: N Engl J Med Date: 2008-07-10 Impact factor: 91.245
Authors: Ola Landgren; Jerry A Katzmann; Ann W Hsing; Ruth M Pfeiffer; Robert A Kyle; Edward D Yeboah; Richard B Biritwum; Yao Tettey; Andrew A Adjei; Dirk R Larson; Angela Dispenzieri; L Joseph Melton; Lynn R Goldin; Mary L McMaster; Neil E Caporaso; S Vincent Rajkumar Journal: Mayo Clin Proc Date: 2007-12 Impact factor: 7.616
Authors: Benjamin A Derman; Andrew T Stefka; Ken Jiang; Amanda McIver; Tadeusz Kubicki; Jagoda K Jasielec; Andrzej J Jakubowiak Journal: Blood Cancer J Date: 2021-02-05 Impact factor: 11.037