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| Name | Class |
|---|---|
| Harvard Medical School (HMS and HSDM) | OTHER |
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The investigators are interested in enrolling patients with rheumatoid arthritis (RA) who had a difficult time getting their disease under control even after trying multiple RA therapies. The investigators believe that there may be common patterns in the genes of this group of RA patients compared to those with more "textbook RA." Understanding genetic factors can help doctors to know in advance who may not respond to conventional therapies and start with treatments that work. Learning about underlying genes that influence treatment may help the investigators to identify new targets for therapy, to ultimately improve the lives of patients with RA and inflammatory arthritis.
The investigators are looking for patients with rheumatoid arthritis (RA) with an inadequate response to tumor necrosis factor inhibitor (TNFi) and another biologic disease modifying anti-rheumatic drug (bDMARD) or small molecule approved for treating RA. The investigators are conducting this research to learn more about RA and the genetic patterns associated with patients whose RA cannot be well controlled with most RA treatments. Investigators anticipate that these patients will differ from "classic" RA patients in their biomarker and genetic composition and that they represent a mixed group of individuals who may be similar in ways that are not currently being measured.
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| Measure | Description | Time Frame |
|---|---|---|
| Whole genome sequencing | Genomic data will be applied in an established bioinformatics pipeline to screen for uncommon variants and test association with exceptional treatment non-responders compared with TNFi responders. | Through study completion, averaging 1 year |
| Measure | Description | Time Frame |
|---|---|---|
| Subgroup analyses of treatment non-responders | Patients who eventually find a therapy that controls their RA. The investigators will use prospective questionnaire data to subgroup patients into those who eventually find a treatment that works vs those who do not. | 1 year |
| Measure | Description | Time Frame |
|---|---|---|
| Other potential predictors of poor response to biologic therapies | Electronic health data will be used to assess for common features of patients who have poor response to therapy compared to TNFi responders. | Retrospective data up to 10 years prior to enrollment |
Inclusion Criteria:
Exclusion Criteria:
Participant eligibility is based on self-representation of gender identity
Patients diagnosed with rheumatoid arthritis (RA) that have failed TNFi therapy and another bDMARD or small molecule approved for RA.
TNFi= adalimumab (Humira), certolizumab (Cimzia), etanercept (Enbrel), infliximab (Remicade), golimumab (Simponi)
bDMARDs or small molecules for RA in addition to TNFi above: abatacept (Orencia), baricitinib (Olumiant), sarilumab (Kevzara), tocilizumab (Actemra), rituximab (Rituxan), tofacitinib (Xeljanz), upadacitinib (Rinvoq)
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Brigham and Women's Hospital | Boston | Massachusetts | 02115 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 40669748 | Derived | McDermott GC, Jeffway M, Seyok T, Zhang H, Myasoedova E, Davis JM 3rd, Giles J, Coblyn J, Helfgott S, Massarotti E, Sands R, Weinblatt ME, Johansson T, Schmajuk G, Michaud K, Perry C, Churchill S, Liao KP. Rationale and design of the rheumatoid arthritis non-responders to treatment (RANT) study: Use of a bioinformatics platform and "decentralized" clinical recruitment design. Contemp Clin Trials. 2025 Sep;156:108000. doi: 10.1016/j.cct.2025.108000. Epub 2025 Jul 14. |
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| ID | Term |
|---|---|
| D001172 | Arthritis, Rheumatoid |
| ID | Term |
|---|---|
| D001168 | Arthritis |
| D007592 | Joint Diseases |
| D009140 | Musculoskeletal Diseases |
| D012216 | Rheumatic Diseases |
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One-time blood draw to measure proteomics and conduct whole genome sequencing.
| D003240 |
| Connective Tissue Diseases |
| D017437 | Skin and Connective Tissue Diseases |
| D001327 | Autoimmune Diseases |
| D007154 | Immune System Diseases |