In """"""""Novel biomarkers and Risk Prediction Modeling in RA"""""""" we propose to study metabolites and metabolic profiles as new biomarkers of RA risk. The hypothesis underlying this proposal is that concentrations of certain metabolites involving the activation of multiple enzymatic pathways are highly discriminatory for a population at high risk for developing RA. We have validated RA risk prediction models and demonstrated the improvement in accuracy with addition of genetic risk scores and gene-environment interactions to environmental factors. We have demonstrated associations for novel autoantibodies and cytokines with RA risk. Our team has expertise in epidemiology, genetics, predictive modeling, biomarker analysis, and network and pathway analysis.
Specific Aims are to: 1) identify individual metabolites and metabolic profiles associated with RA risk in both untargeted and candidate approaches with discovery analyses in the Nurses'Health Study cohorts and replication analyses in the Department of Defense military cohort;we will use advanced biostatistical techniques to identify novel RA risk metabolic patterns, as well as to investigate whether validated metabolic profiles, previously associated with the gastrointestinal microbiota and inflammation, atherosclerosis and cardiovascular disease are also associated with RA risk;2) examine whether intermediate biomarkers of RA (IL-6, TNFR2, MCP-1, anti-citrullinated protein antibodies) are associated with distinct metabolic profiles and whether biomarkers mediate the relationship of metabolites to RA risk;3) investigate whether relationships between both lifestyle factors and genetic risk scores and RA risk are mediated by individual metabolites and metabolic profiles. We will use our epidemiologic expertise to build comprehensive models that include environmental factors, cytokines, autoantibodies, metabolic profiles, and genetic predictors that can be used to identify high risk populations for targeted prevention therapy. The discovery of novel metabolic biomarkers associated with a greater likelihood of RA would provide an important public health benefit to subjects at high risk of RA due to family history and genetics.

Public Health Relevance

Changes in blood metabolites, such as sugars, amino acids, and lipids, have been linked to increased risk of several chronic diseases. Our goal is to comprehensively examine metabolites in the blood among people who later develop rheumatoid arthritis (RA), a disabling autoimmune disease of unknown cause, comparing them to people who do not develop RA. The discovery of novel metabolic biomarkers for RA risk would provide an important public health benefit to people at high risk of RA due to family history and genetics.

Agency
National Institute of Health (NIH)
Institute
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Type
Research Project (R01)
Project #
2R01AR049880-11
Application #
8721627
Study Section
Neurological, Aging and Musculoskeletal Epidemiology Study Section (NAME)
Program Officer
Wang, Yan Z
Project Start
2003-09-01
Project End
2019-08-31
Budget Start
2014-09-01
Budget End
2015-08-31
Support Year
11
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Brigham and Women's Hospital
Department
Type
DUNS #
City
Boston
State
MA
Country
United States
Zip Code
02115
Sparks, Jeffrey A; Chang, Shun-Chiao; Nguyen, Uyen-Sa et al. (2018) Weight Change During the Early Rheumatoid Arthritis Period and Risk of Subsequent Mortality in Women With Rheumatoid Arthritis and Matched Comparators. Arthritis Rheumatol 70:18-29
Sparks, Jeffrey A; Costenbader, Karen H (2018) Rheumatoid arthritis in 2017: Protective dietary and hormonal factors brought to light. Nat Rev Rheumatol 14:71-72
Sparks, Jeffrey A; Barbhaiya, Medha; Tedeschi, Sara K et al. (2018) Inflammatory dietary pattern and risk of developing rheumatoid arthritis in women. Clin Rheumatol :
Sparks, Jeffrey A; Lin, Tzu-Chieh; Camargo Jr, Carlos A et al. (2018) Rheumatoid arthritis and risk of chronic obstructive pulmonary disease or asthma among women: A marginal structural model analysis in the Nurses' Health Study. Semin Arthritis Rheum 47:639-648
Kreps, David J; Halperin, Florencia; Desai, Sonali P et al. (2018) Association of weight loss with improved disease activity in patients with rheumatoid arthritis: A retrospective analysis using electronic medical record data. Int J Clin Rheumtol 13:1-10
Prado, Maria G; Iversen, Maura D; Yu, Zhi et al. (2018) Effectiveness of a Web-Based Personalized Rheumatoid Arthritis Risk Tool With or Without a Health Educator for Knowledge of Rheumatoid Arthritis Risk Factors. Arthritis Care Res (Hoboken) 70:1421-1430
Li, Jun; Rice, Megan S; Huang, Tianyi et al. (2018) Circulating prolactin concentrations and risk of type 2 diabetes in US women. Diabetologia 61:2549-2560
Barbhaiya, Medha; Tedeschi, Sara K; Lu, Bing et al. (2018) Cigarette smoking and the risk of systemic lupus erythematosus, overall and by anti-double stranded DNA antibody subtype, in the Nurses' Health Study cohorts. Ann Rheum Dis 77:196-202
Sparks, Jeffrey A; Iversen, Maura D; Yu, Zhi et al. (2018) Disclosure of Personalized Rheumatoid Arthritis Risk Using Genetics, Biomarkers, and Lifestyle Factors to Motivate Health Behavior Improvements: A Randomized Controlled Trial. Arthritis Care Res (Hoboken) 70:823-833
Sparks, Jeffrey A; Chang, Shun-Chiao; Nguyen, Uyen-Sa D T et al. (2018) Smoking Behavior Changes in the Early Rheumatoid Arthritis Period and Risk of Mortality During Thirty-Six Years of Prospective Followup. Arthritis Care Res (Hoboken) 70:19-29

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