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Rheumatoid Arthritis Inflammatory Subtypes, Treatment Responses Uncovered in Synovial Tissue Study

NEW YORK – With a combination of single-cell sequencing strategies, a team led by investigators at Brigham and Women's Hospital, Harvard Medical School, and the Broad Institute has teased out synovial tissue inflammatory subtypes that coincide with distinct patient phenotypes in individuals with rheumatoid arthritis.

"[W]e were also able to demonstrate that certain cell states track together," co-senior and corresponding author Soumya Raychaudhuri, director of the BWH Center for Data Sciences, who is also affiliated with Harvard and the Broad, said in an email. "That is to say there are some key synovial inflammatory phenotypes — and each of those phenotypes tend to have more of certain cell states."

For a study appearing in Nature on Wednesday, he and his colleagues turned to multi-modal, single-cell RNA sequencing and single-cell CITE-seq-based profiling on 58 surface proteins to assess more than 314,000 individual cells in samples from 79 donor individuals, highlighting combinations of cell states behind half a dozen rheumatoid arthritis-related inflammatory subtypes.

The participants included 28 treatment-naïve rheumatoid arthritis patients, 27 rheumatoid arthritis patients who showed poor responses to methotrexate, and 15 rheumatoid arthritis patients with inadequate anti-tumor necrosis factor (TNF) antibody treatment response, as well as nine individuals with osteoarthritis.

"This comprehensive atlas and molecular, tissue-based stratification of rheumatoid arthritis synovial tissue reveal new insights into rheumatoid arthritis pathology and heterogeneity that could inform novel treatment targets," the authors wrote.

Findings from the study expand on past research linking the state of T cells, B cells, fibroblasts and other synovial cells with rheumatoid arthritis features and outcomes, pointing to the possibility of tissue stratification based on so-called "cell-type abundance phenotypes" (CTAPs) associated with rheumatoid arthritis.

"The CTAP paradigm provides a tissue classification system that captures coarse cell-type and fine cell-state heterogeneity," the authors wrote. Now that such subtypes have been unearthed, they noted that CTAPs "can be inferred from single-cell RNA-seq, bulk RNA-seq, or flow cytometry data" in the future "to provide cellular and molecular insights into clinical trials."

The CTAPs were "each characterized by selectively enriched cell states," they explained, noting that the phenotypes found "demonstrate the diversity of synovial inflammation in rheumatoid arthritis, ranging from samples enriched for T and B cells to those largely lacking lymphocytes."

In addition, Raychaudhuri noted that the inflammatory phenotypes found point to the possibility of targeting cell states within CTAPs found in rheumatoid arthritis patients with distinct inflammatory features and rheumatoid arthritis symptoms.

"[T]here may be value in paying attention to which inflammatory phenotype a particular patient has," Raychaudhuri noted. "Given the inflammatory phenotype, it is possible that a patient may respond better to drugs that target the relevant cell states associated with that patient’s phenotype."

In the current study, for example, the researchers saw ties between CTAPs and responses to rituximab (Genentech's Rituxan) or tocilizumab (Genentech's Actemra) treatments in a clinical trial dubbed R4RA that included 133 rheumatoid arthritis cases.

"We applied our CTAP classification algorithm to bulk RNA-seq profiles from the R4RA clinical trial comparing rituximab and tocilizumab for the treatment of patients with rheumatoid arthritis with inadequate response to TNF inhibitor therapy," the authors explained.

Although CTAP features shifted over time in a subset of rheumatoid arthritis patients with available synovial tissue data, the team found that pre-treatment CTAP features provided clues to treatment response in R4RA participants receiving either treatment.

The authors noted that additional longitudinal studies will offer a more refined look at the CTAP subtypes and shifts that correspond to response to other treatment types, and suggested that a similar strategy may offer clinically relevant insights in other autoimmune conditions.

"As rheumatoid arthritis shares disease-associated tissue cell states and genetic risk loci with other autoimmune diseases, these analyses may offer insights into other diseases that feature tissue inflammation," they wrote, adding that a "deeper understanding of the heterogeneity of tissue inflammation in rheumatoid arthritis and other autoimmune diseases may provide new insights into disease pathogenesis and reveal new treatment targets, and key elements of precision medicine."