# Risk Prediction and Inflammatory Biomarkers of Cardiovascular Disease in Myelodysplastic Syndrome > **NIH NIH P20** · UNIVERSITY OF VERMONT & ST AGRIC COLLEGE · 2024 · $218,007 ## Abstract Myelodysplastic syndromes (MDS) are hematologic cancers caused by mutations in hematopoietic cells which also cause vascular inflammation and increased risk of cardiovascular disease (CVD). CVD in MDS is an important source of morbidity and mortality, the most common non-cancer cause of death, and mediated by mutation-driven inflammation. Despite these mechanistic and clinical links, common risk prediction tools for CVD are not accurate in MDS and there are also no studies of circulating inflammatory proteins as CVD biomarkers in MDS. The objectives of this application are: 1) to use the largest MDS clinical registry in the U.S. (Surveillance, Epidemiology, and End Results [SEER]-Medicare) to develop a risk assessment model (RAM) for CVD in MDS patients, and 2) to characterize inflammatory circulating proteins in MDS patients using functional proteomics and define their potential value as CVD biomarkers by establishing biological variation. To achieve these goals, we propose two specific aims: 1) Develop and validate a RAM to assess CVD risk and cardiovascular mortality risk in MDS, and 2) Recruit and longitudinally follow a 30 patient MDS cohort and assess the within- and between-person biovariability over 6 months and explore the stability of an inflammation proteome. To complete Aim 1, we will harness clinical data from SEER-Medicare to define differential associations of traditional CVD risk factors in MDS and non-MDS patients and build a CVD RAM in this population. We will then externally validate the RAM in an independent cohort from 2 diverse academic hospitals. To complete Aim 2, we will enroll MDS patients in a pilot study at the University of Vermont (UVM) Medical Center and measure 92 inflammation proteins weekly for 4 consecutive weeks at 2 time-points 6 months. This will characterize within- and between-person biologic variation of these proteins to assess their reliability as candidate CVD biomarkers for use in epidemiologic research. Support for study design, RAM modelling and statistical analysis in Aim 1 and operating procedures for processing, storage, and proteomic assays in Aim 2 will be provided by the VCCBH Study Design and Molecular Epidemiology Core. Inflammatory biomarkers of CVD constitute an area of research expertise at UVM and an ongoing interest of the VCCBH. The proposed research is significant because: 1) an MDSspecific CVD RAM that can be integrated into clinical practice can be implemented in larger studies to guide preventive CVD measures in patients at greatest risk, and 2) biologic variation of inflammation proteins through proteomics is the first step necessary to translate this novel technology into large-scale observational research to predict CVD or measure CVD mitigation in MDS. Ultimately, the results of this research will inform future clinical and translational research to address cardiovascular health as a means of improving quality and quantity of life in patients with MDS... ## Key facts - **NIH application ID:** 11220188 - **Project number:** 5P20GM135007-05 - **Recipient organization:** UNIVERSITY OF VERMONT & ST AGRIC COLLEGE - **Principal Investigator:** Diego Adrianzen Herrera - **Activity code:** P20 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $218,007 - **Award type:** 5 - **Project period:** 2024-06-01 → 2026-05-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/11220188 ## Citation > US National Institutes of Health, RePORTER application 11220188, Risk Prediction and Inflammatory Biomarkers of Cardiovascular Disease in Myelodysplastic Syndrome (5P20GM135007-05). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/11220188. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*