Program Official

Principal Investigator

Su-Hsin
Chang
Awardee Organization

Washington University
United States

Fiscal Year
2022
Activity Code
R01
Early Stage Investigator Grants (ESI)
Not Applicable
Project End Date

Addressing racial disparities in monoclonal gammopathy of undetermined significance and progression to multiple myeloma from a prevention perspective

Multiple myeloma (MM) is a lethal neoplasm and a common hematologic malignancy. MM is uniformly preceded by monoclonal gammopathy of undetermined significance (MGUS). Unlike MM, patients with MGUS are asymptomatic. The current management for MGUS is watchful waiting for disease progression. A marked racial disparity in this disease area is long-established with a 2 to 3-fold increased risk in African Americans (AAs) compared to Caucasians. Moreover, obesity is a risk factor for MM independent of race. Obesity is prevalent in U.S. adults, and particularly more prevalent among AAs than Caucasians. As a result, without any intervention, racial disparities in this disease will continue to worsen. Metformin, a widely-used, safe, welltolerated, and inexpensive medication, induces weight loss and has been found to be more effective in glycemic control in AAs compared to Caucasians. It has also been used in prospective trials for non-diabetes indications and solid tumor malignancies. We therefore hypothesize that metformin use in MGUS patients will prevent MM and reduce MM disparities. This project plans to focus on the precursor condition of MM – MGUS. The findings from the proposed project will inform biological mechanism studies and MGUS/MM prevention trials. The long-term goal is to identify intervention strategies to prevent the progression of MGUS to MM, reduce the overall burden of MM, and reduce MM disparities. We plan to identify whether high body mass index (BMI) and/or significant change in BMI over the life course are risk factors for MGUS by race (Aim 1), utilizing linked databases with nearly lifelong follow-up of BMI and other health measures ,as well as utilizing artificial intelligence, i.e., machine learning approaches, to perform big data analyses. We will then assess racial differences in the M-protein trajectory after MGUS diagnosis in metformin versus non-metformin users in a subgroup of MGUS patients diagnosed with diabetes mellitus (Aim 2.1) and the association of metformin use with the progression of MGUS to MM (Aim 2.2). Last, we will assess racial differences in the M-protein trajectory in the subgroup of MGUS patients without diabetes mellitus (Aim 3). This project is significant in its capability to 1) identify perhaps the only modifiable risk factor (high BMI) to inform interventions to prevent MM; 2) identify a dynamic marker for disease progression by race (M-protein concentration), where these biomarkers can be a surrogate for MM diagnosis in future prevention trials; and 3) reduce MM health disparities by a) identifying race-specific biomarkers for MGUS and MGUS progression, available through clinical encounters (as opposed to expensive genetic testing); and b) exploring metformin use as a chemopreventive measure. It is innovative in its 1) focus on MM prevention rather than treatment and 2) utilization of artificial intelligence to analyze big data. Successful completion of this study will provide evidence for a paradigm shift in current clinical practice of MGUS management and help prevent MM, an incurable and costly disease. More importantly, it will provide evidence to guide interventions to reduce MM disparities.

Publications

  • Yu YC, Zhang W, O'Gara D, Li JS, Chang SH. A moment kernel machine for clinical data mining to inform medical decision making. Scientific reports. 2023 Jun 28;13(1):10459. PMID: 37380721
  • Ji M, Huber JH, Schoen MW, Sanfilippo KM, Colditz GA, Wang SY, Chang SH. Mortality in the US Populations With Monoclonal Gammopathy of Undetermined Significance. JAMA oncology. 2023 Sep 1;9(9):1293-1295. PMID: 37498610
  • Liu LW, Wang M, Grandhi N, Schroeder MA, Thomas T, Vargo K, Gao F, Sanfilippo KM, Chang SH. The Association of Agent Orange (AO) Exposure with Monoclonal Gammopathy of Undetermined Significance (MGUS) to Multiple Myeloma (MM) Progression: A Population-based Study of Vietnam War Era Veterans. Research square. 2023 Oct 9. PMID: 37886452
  • Huber JH, Ji M, Shih YH, Wang M, Colditz G, Chang SH. Disentangling age, gender, and racial/ethnic disparities in multiple myeloma burden: a modeling study. Nature communications. 2023 Sep 20;14(1):5768. PMID: 37730703
  • Wang M, Yu YC, Liu L, Schoen MW, Kumar A, Vargo K, Colditz G, Thomas T, Chang SH. Natural Language Processing-Assisted Classification Models to Confirm Monoclonal Gammopathy of Undetermined Significance and Progression in Veterans' Electronic Health Records. JCO clinical cancer informatics. 2023 Sep;7:e2300081. PMID: 38048516
  • Liu LW, Wang M, Grandhi N, Schroeder MA, Thomas T, Vargo K, Gao F, Sanfilippo KM, Chang SH. The Association of Agent Orange Exposure with the progression of monoclonal gammopathy of undetermined significance to multiple myeloma: a population-based study of Vietnam War Era Veterans. Journal of hematology & oncology. 2024 Jan 8;17(1):3. PMID: 38191467