This proposal is submitted as a competing continuation of NIH R01 AR49880-03, Hormone, Cytokine and Genetic Risks for RA in Women, in which we identified reproductive factors including breastfeeding, early menarche, and irregular menses, inflammatory markers including anti-CCP antibodies, and TNFR2 levels and a novel RA risk allele in the prolactin gene as significant risk factors for RA. Extending our work to develop clinical risk prediction models, this proposal builds on our strong track record of studying RA epidemiology in the Nurses'Health Studies, the largest prospective rheumatic disease cohorts in the world. Recent whole genome association studies in RA from our co-investigators have identified novel risk loci. However, despite rapid advances in understanding the genetic basis of RA, it is unclear how to utilize this information clinically for RA prediction. Identification of autoantibodies and cytokines present many years prior to RA onset provides an exciting opportunity to intervene during the pre-clinical phase. However, it is critical to understand the role of RA risk factors for the targeting of potentially toxic therapies at highest risk individuals. Predictive modeling is critical in the progress towards an RA prevention clinical trial. We propose to build a RA clinical risk prediction models incorporating RA genetic susceptibility alleles and environmental risk factors and their interactions, with validation in large U.S. and Swedish cohorts. Further validation in a unique high risk RA cohort, representing a target group for prevention trials, will lead to understanding of whether the models predict development of pre-clinical RA, essential information for future RA prevention trials. We propose the following aims: 1) Using validated RA susceptibility alleles, derive a Genetic Risk Score (GRS) and examine associations between GRS and RA risk in general, and with seropositive RA risk specifically, in 700 RA cases and 700 matched controls from the Nurses'Health Study (NHS) and in 2000 cases and 1150 matched controls from the Epidemiologic Investigation of RA (EIRA) cohort;2) Develop two RA clinical prediction models to predict 5-year RA risk for all RA and for subsets defined by sex, immune phenotype, and family history: (a) an """"""""environmental"""""""" model using behavioral factors, environmental exposures, and clinical factors , and (b) an """"""""environmental + genetic"""""""" model with environmental factors, GRS, and gene-environment interaction terms;and 3) Examine the goodness of fit of the prediction models developed and validated in Aim 2 for predicting an intermediate endpoint, pre-clinical RA defined autoantibodies, or RA symptoms, in a unique high risk RA cohort, the Studies of the Etiologies of Rheumatoid Arthritis (SERA) comprised of 2100 first-degree relatives of RA cases and of 800 individuals enriched with HLA-DR4 alleles (total N=2900). The ability to accurately predict an individual's 5-year risk of developing clinical RA based on a simple genetic risk score, behavioral, environmental and clinical risk factors would be an enormous advance, enabling risk factor modification and earlier introduction of effective therapies to abrogate the destruction and disability of this disease.

Public Health Relevance

This study will describe the characteristics of patients with rheumatoid arthritis (RA) who successfully engage in physical activity and those who do not. This information will be used to develop personally tailored physical activity counseling to promote health and reduce cardiovascular risk of patients with RA.

Agency
National Institute of Health (NIH)
Institute
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Type
Research Project (R01)
Project #
5R01AR049880-08
Application #
8125131
Study Section
Neurological, Aging and Musculoskeletal Epidemiology (NAME)
Program Officer
Wang, Yan Z
Project Start
2003-09-01
Project End
2014-08-31
Budget Start
2011-09-01
Budget End
2012-08-31
Support Year
8
Fiscal Year
2011
Total Cost
$439,071
Indirect Cost
Name
Brigham and Women's Hospital
Department
Type
DUNS #
030811269
City
Boston
State
MA
Country
United States
Zip Code
02115
Hu, Yang; Sparks, Jeffrey A; Malspeis, Susan et al. (2017) Long-term dietary quality and risk of developing rheumatoid arthritis in women. Ann Rheum Dis 76:1357-1364
Sparks, Jeffrey A; Iversen, Maura D; Yu, Zhi et al. (2017) 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) :
Bengtsson, Camilla; Malspeis, Susan; Orellana, Cecilia et al. (2017) Association Between Menopausal Factors and the Risk of Seronegative and Seropositive Rheumatoid Arthritis: Results From the Nurses' Health Studies. Arthritis Care Res (Hoboken) 69:1676-1684
Barbhaiya, Medha; Lu, Bing; Sparks, Jeffrey A et al. (2017) Influence of Alcohol Consumption on the Risk of Systemic Lupus Erythematosus Among Women in the Nurses' Health Study Cohorts. Arthritis Care Res (Hoboken) 69:384-392
Sparks, Jeffrey A; Lin, Tzu-Chieh; Camargo Jr, Carlos A et al. (2017) 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 :
Hu, Yang; Cui, Jing; Sparks, Jeffrey A et al. (2017) Circulating carotenoids and subsequent risk of rheumatoid arthritis in women. Clin Exp Rheumatol 35:309-312
Tedeschi, Sara K; Barbhaiya, Medha; Malspeis, Susan et al. (2017) Obesity and the risk of systemic lupus erythematosus among women in the Nurses' Health Studies. Semin Arthritis Rheum 47:376-383
Sparks, Jeffrey A; Chang, Shun-Chiao; Deane, Kevin D et al. (2016) Associations of Smoking and Age With Inflammatory Joint Signs Among Unaffected First-Degree Relatives of Rheumatoid Arthritis Patients: Results From Studies of the Etiology of Rheumatoid Arthritis. Arthritis Rheumatol 68:1828-38
Prescott, Jennifer; Karlson, Elizabeth W; Orr, Esther H et al. (2016) A Prospective Study Investigating Prediagnostic Leukocyte Telomere Length and Risk of Developing Rheumatoid Arthritis in Women. J Rheumatol 43:282-8
Ananthakrishnan, Ashwin N; Cagan, Andrew; Cai, Tianxi et al. (2016) Identification of Nonresponse to Treatment Using Narrative Data in an Electronic Health Record Inflammatory Bowel Disease Cohort. Inflamm Bowel Dis 22:151-8

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