Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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WITHDRAWN
OBSERVATIONAL
2023-07-01
2035-01-01
Brief Summary
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Specific research objectives of this cohort include:
1. Observe the response that immunosuppressive medications have on the immune cell population and cytokines in individuals with RA or Myositis.
2. Observe the role that the intestinal microbiome has on the immune cell population and cytokines in individuals with RA or Myositis.
3. Observe the connection between intestinal inflammation has on the immune cell population and cytokines in individuals with RA or Myositis.
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Detailed Description
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The human gastrointestinal tract is home to trillions of microorganisms including bacteria, viruses, fungi, and protozoa, which together are referred to as the gut microbiome. Research in recent years has underlined that the microorganisms can influence varying physiological aspects such as the immune system, metabolism, and behavior. The microbiome has further been implicated in the pathogenesis of autoimmune diseases. In Systematic Lupus Erythematosus for example, modifications in the intestinal flora have been documented while changes in gut commensal and periodontal diseases have been brought forth as factors for consideration in the development of Rheumatoid Arthritis. Similarly, autoimmune diseases such as Systematic Sclerosis, Sjogren's Syndrome, and Anti-phospholipid Syndrome have been noted to share alterations in the gut microbiome.
Emerging research on the gut microbiome has demonstrated that diet plays a critical role in the make-up of gut microbiome and several experiments have shown that dietary modifications can prompt significant changes in the gut microbial composition. However, little is presently understood about the precise mechanisms and unique interactions between the gut microbiome, diet, and the pathogenesis of autoimmune diseases.
To investigate the triangular link between a patient's diet, their microbiome, and their disease activity, the investigators are seeking to establish a registry to track patients with autoimmune disease diagnoses. Furthermore, the investigators are looking to track the changes in the microbiome, diet, and disease progression as patients are introduced and sustained on medication.
Conditions
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Study Design
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COHORT
PROSPECTIVE
Study Groups
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Patients with Rheumatoid Arthritis and/or Myositis
All patients 18 years or older who have been diagnosed with Rheumatoid Arthritis according to the 2010 ACR/EULAR Classification Criteria.
All patients 18 years or older who have been diagnosed with Myositis according to the 2017 European League Against Rheumatism/American College of Rheumatology Classification Criteria for Adult and Juvenile Idiopathic Inflammatory Myopathies Classification Criteria.
No interventions assigned to this group
Eligibility Criteria
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Inclusion Criteria
* Diagnosed RA by a rheumatologist determined by the 2010 ACR/EULAR Classification Criteria.
* Diagnosed Myositis by a rheumatologist determined by the 2017 American College of Rheumatology Classification Criteria for Adult and Juvenile Idiopathic Inflammatory Myopathies
* Able to read and write in English or Spanish
Exclusion Criteria
18 Years
ALL
No
Sponsors
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ONCOtracker Inc
INDUSTRY
Attune Health Research, Inc.
INDUSTRY
Responsible Party
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Swamy Venuturupalli
Principal Investigator
References
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Bethesda. National Institutes of Health Autoimmune Disease Coordinating Committee Report. The Institutes, 2002.
Services USDoHaH. Progress in Autoimmune Diseases and Research. National Institutes of Health: The autoimmune Diseases Coordinating Committee, 2005:1-126.
Wang L, Wang FS, Gershwin ME. Human autoimmune diseases: a comprehensive update. J Intern Med. 2015 Oct;278(4):369-95. doi: 10.1111/joim.12395. Epub 2015 Jul 25.
Xu J, Yang Y. Gut microbiome and its meta-omics perspectives: profound implications for cardiovascular diseases. Gut Microbes. 2021 Jan-Dec;13(1):1936379. doi: 10.1080/19490976.2021.1936379.
De Luca F, Shoenfeld Y. The microbiome in autoimmune diseases. Clin Exp Immunol. 2019 Jan;195(1):74-85. doi: 10.1111/cei.13158.
Singh RK, Chang HW, Yan D, Lee KM, Ucmak D, Wong K, Abrouk M, Farahnik B, Nakamura M, Zhu TH, Bhutani T, Liao W. Influence of diet on the gut microbiome and implications for human health. J Transl Med. 2017 Apr 8;15(1):73. doi: 10.1186/s12967-017-1175-y.
Vieira SM, Pagovich OE, Kriegel MA. Diet, microbiota and autoimmune diseases. Lupus. 2014 May;23(6):518-26. doi: 10.1177/0961203313501401.
Anderson J, Caplan L, Yazdany J, Robbins ML, Neogi T, Michaud K, Saag KG, O'Dell JR, Kazi S. Rheumatoid arthritis disease activity measures: American College of Rheumatology recommendations for use in clinical practice. Arthritis Care Res (Hoboken). 2012 May;64(5):640-7. doi: 10.1002/acr.21649.
Fransen J, van Riel PL. The Disease Activity Score and the EULAR response criteria. Rheum Dis Clin North Am. 2009 Nov;35(4):745-57, vii-viii. doi: 10.1016/j.rdc.2009.10.001.
Rider LG, Aggarwal R, Machado PM, Hogrel JY, Reed AM, Christopher-Stine L, Ruperto N. Update on outcome assessment in myositis. Nat Rev Rheumatol. 2018 May;14(5):303-318. doi: 10.1038/nrrheum.2018.33. Epub 2018 Apr 12.
Instruments available for use in Assessment Center . Secondary Instruments available for use in Assessment Center. https://www.assessmentcenter.net/documents/InstrumentLibrary.pdf.
Deyo RA, Katrina Ramsey, Buckley DI, Michaels L, Kobus A, Eckstrom E, Forro V, Morris C. Performance of a Patient Reported Outcomes Measurement Information System (PROMIS) Short Form in Older Adults with Chronic Musculoskeletal Pain. Pain Med. 2016 Feb;17(2):314-24. doi: 10.1093/pm/pnv046.
Bigaard J, Frederiksen K, Tjonneland A, Thomsen BL, Overvad K, Heitmann BL, Sorensen TI. Waist circumference and body composition in relation to all-cause mortality in middle-aged men and women. Int J Obes (Lond). 2005 Jul;29(7):778-84. doi: 10.1038/sj.ijo.0802976.
Konijn NP, van Tuyl LH, Bultink IE, Lems WF, Earthman CP, van Bokhorst-de van der Schueren MA. Making the invisible visible: bioelectrical impedance analysis demonstrates unfavourable body composition in rheumatoid arthritis patients in clinical practice. Scand J Rheumatol. 2014;43(4):273-8. doi: 10.3109/03009742.2013.852239. Epub 2014 Feb 7.
Chen YM, Chen HH, Hsieh CW, Hsieh TY, Lan JL, Chen DY. A close association of body cell mass loss with disease activity and disability in Chinese patients with rheumatoid arthritis. Clinics (Sao Paulo). 2011;66(7):1217-22. doi: 10.1590/s1807-59322011000700016.
Sciences NCIDoCCP. DHQIII Diet History Questionnaire Secondary DHQIII Diet History Questionnaire https://epi.grants.cancer.gov/dhq3/.
Thompson FE, Subar AF, Brown CC, Smith AF, Sharbaugh CO, Jobe JB, Mittl B, Gibson JT, Ziegler RG. Cognitive research enhances accuracy of food frequency questionnaire reports: results of an experimental validation study. J Am Diet Assoc. 2002 Feb;102(2):212-25. doi: 10.1016/s0002-8223(02)90050-7.
Subar AF, Thompson FE, Kipnis V, Midthune D, Hurwitz P, McNutt S, McIntosh A, Rosenfeld S. Comparative validation of the Block, Willett, and National Cancer Institute food frequency questionnaires : the Eating at America's Table Study. Am J Epidemiol. 2001 Dec 15;154(12):1089-99. doi: 10.1093/aje/154.12.1089.
Subar AF, Kipnis V, Troiano RP, Midthune D, Schoeller DA, Bingham S, Sharbaugh CO, Trabulsi J, Runswick S, Ballard-Barbash R, Sunshine J, Schatzkin A. Using intake biomarkers to evaluate the extent of dietary misreporting in a large sample of adults: the OPEN study. Am J Epidemiol. 2003 Jul 1;158(1):1-13. doi: 10.1093/aje/kwg092.
Other Identifiers
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RAMC2022
Identifier Type: -
Identifier Source: org_study_id
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