Rheumatoid Arthritis (RA) is a chronic inflammatory and autoimmune disorder characterized by high morbidity and mortality, and profound disability. During the prior cycles of this award, we discovered that RA patients are significantly more likely to develop cardiovascular (CV) disease (i.e., myocardial infarction and heart failure) and have significantly worse outcomes after CV disease, compared to the general population. Moreover, CV disease in persons with RA showed a markedly different risk profile, with traditional CV risk factors playing a relatively less important (and sometimes paradoxical) role, and markers of inflammation/immune dysfunction playing a much greater role. Indeed, we demonstrated that CV risk prediction tools developed for the general population (e.g., Framingham) were of little value in RA, due to poor calibration (i.e., ability to predict absolute risk), and poor discrimination (i.e., ability to distinguish low from high risk). Thus, we introduced, in the current grant cycle, a novel phenotypic biomarker, immune response signatures, which (in cross sectional studies) significantly improved identification of RA subjects with silent myocardial dysfunction. The objective of this renewal application is to improve CV risk prediction for persons with RA. We propose to: 1) establish (in longitudinal studies) the utility of immune response signatures, when combined with our rich epidemiological data, for predicting myocardial function in RA, examining the impact of disease activity and biological treatment; and 2) create and validate a new, RA-specific, CV risk assessment tool.
In Aim 1 we will repeat assessment of myocardial function and test the hypothesis that the 11 cytokine immune response signature (developed in the current grant cycle) is a significant predictor of future myocardial dysfunction after adjusting for demographic, disease features and CV characteristics. We will compare immune response signatures measured at 2 time points and test the hypotheses that improvement in signature is associated with lower risk for myocardial dysfunction, as well as investigating the impact of biological therapies.
In Aim 2 we will devise a new, RA-specific, CV risk score by re-calibrating the Framingham, and other available CV risk scores to more accurately predict CV risk for RA; and by systematically evaluating RA disease characteristics, laboratory measures and immune response signatures for inclusion into the new CV risk score, in order to maximize discrimination. To ensure generalizability of the new score, external validation will be conducted using the large (n=25,977) and well established National Databank for Rheumatic Diseases. The creation of effective CV risk prediction tools and biomarkers will enable targeting of screening and prevention strategies towards those who could benefit the most, thereby reducing CV morbidity, mortality, and healthcare costs in persons with RA.

Public Health Relevance

Heart disease is the #1 cause of death in the US. People suffering from RA have an increased risk of heart disease. Early identification of persons at high risk for heart disease is necessary for effective prevention. There is currently no way of accurately identifying which of the 1.5 million persons with RA are at high risk for heart disease. The goal of this study is to develop special risk scores and new blood tests that will identify RA patients who are at high risk for heart disease.

Agency
National Institute of Health (NIH)
Institute
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Type
Research Project (R01)
Project #
4R01AR046849-15
Application #
9062382
Study Section
Neurological, Aging and Musculoskeletal Epidemiology (NAME)
Program Officer
Witter, James
Project Start
2000-09-01
Project End
2017-02-28
Budget Start
2016-03-01
Budget End
2017-02-28
Support Year
15
Fiscal Year
2016
Total Cost
$639,388
Indirect Cost
$215,292
Name
Mayo Clinic, Rochester
Department
Type
DUNS #
006471700
City
Rochester
State
MN
Country
United States
Zip Code
55905
Myasoedova, Elena; Gabriel, Sherine E; Matteson, Eric L et al. (2017) Decreased Cardiovascular Mortality in Patients with Incident Rheumatoid Arthritis (RA) in Recent Years: Dawn of a New Era in Cardiovascular Disease in RA? J Rheumatol 44:732-739
Crowson, Aaron D; Colligan, Robert C; Matteson, Eric L et al. (2017) Explanatory Style in Patients with Rheumatoid Arthritis: An Unrecognized Predictor of Mortality. J Rheumatol 44:170-173
Davis 3rd, John M; Lin, Grace; Oh, Jae K et al. (2017) Five-year changes in cardiac structure and function in patients with rheumatoid arthritis compared with the general population. Int J Cardiol 240:379-385
Bois, John P; Crowson, Cynthia S; Khullar, Tamanna et al. (2017) Progression rate of severity of aortic stenosis in patients with rheumatoid arthritis. Echocardiography 34:1410-1416
Richter, Michael; Crowson, Cynthia S; Matteson, Eric L et al. (2017) Orthopedic Surgery among Patients with Rheumatoid Arthritis: A Population-based study to Identify Risk factors, Sex differences, and Time trends. Arthritis Care Res (Hoboken) :
Scanlon, Erin M; Mankad, Rekha; Crowson, Cynthia S et al. (2017) Cardiovascular risk assessment in patients with rheumatoid arthritis: a correlative study of noninvasive arterial health testing. Clin Rheumatol 36:763-771
Ni Mhuircheartaigh, Orla; Crowson, Cynthia S; Gabriel, Sherine E et al. (2017) Fragility Fractures Are Associated with an Increased Risk for Cardiovascular Events in Women and Men with Rheumatoid Arthritis: A Population-based Study. J Rheumatol 44:558-564
Myasoedova, Elena; Chandran, Arun; Ilhan, Birkan et al. (2016) The role of rheumatoid arthritis (RA) flare and cumulative burden of RA severity in the risk of cardiovascular disease. Ann Rheum Dis 75:560-5
Zamora-Legoff, Jorge A; Myasoedova, Elena; Matteson, Eric L et al. (2016) Drug prescribing trends in adults with rheumatoid arthritis: a population-based comparative study from 2005 to 2014. Clin Rheumatol 35:2427-36
Crowson, Cynthia S; Atkinson, Elizabeth J; Therneau, Terry M (2016) Assessing calibration of prognostic risk scores. Stat Methods Med Res 25:1692-706

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