Molecular profiling of rheumatoid arthritis patients reveals an association between innate and adaptive cell populations and response to anti-tumor necrosis factor

Abstract

BackgroundThe goal of this study is to use comprehensive molecular profiling to characterize clinical response to anti-TNF therapy in a real-world setting and identify reproducible markers differentiating good responders and non-responders in rheumatoid arthritis (RA).MethodsWhole-blood mRNA, plasma proteins, and glycopeptides were measured in two cohorts of biologic-naïve RA patients (n = 40 and n = 36) from the Corrona CERTAIN (Comparative Effectiveness Registry to study Therapies for Arthritis and Inflammatory coNditions) registry at baseline and after 3 months of anti-TNF treatment. Response to treatment was categorized by EULAR criteria. A cell type-specific data analysis was conducted to evaluate the involvement of the most common immune cell sub-populations. Findings concordant between the two cohorts were further assessed for reproducibility using selected NCBI-GEO datasets and clinical laboratory measurements available in the CERTAIN database.ResultsA treatment-related signature suggesting a reduction in neutrophils, independent of the status of response, was indicated by a high level of correlation (ρ = 0.62; p < 0.01) between the two cohorts. A baseline, response signature of increased innate cell types in responders compared to increased adaptive cell types in non-responders was identified in both cohorts. This result was further assessed by applying the cell type-specific analysis to five other publicly available RA datasets. Evaluation of the neutrophil-to-lymphocyte ratio at baseline in the remaining patients (n = 1962) from the CERTAIN database confirmed the observation (odds ratio of good/moderate response = 1.20 [95% CI = 1.03–1.41, p = 0.02]).ConclusionDifferences in innate/adaptive immune cell type composition at baseline may be a major contributor to response to anti-TNF treatment within the first 3 months of therapy.

Molecular Biomarkers of Anti-TNF Response in Patients with Rheumatoid Arthritis

“…This nding corroborates a recent study which showed that patients treated with anti-TNF in combination with methotrexate decreased the blood neutrophil counts regardless of their clinical response to therapy [48,49]. Additionally, our results also corroborate with earlier studies showing an induction of B cells and NK cells in whole blood following anti-TNF treatment [50]. Along with these changes we also see an upregulation of the proportion of activated NK cells (NKp44+) in responders that express the inhibitory protein NKG2A.…”

Inference of an integrative, executable network for Rheumatoid Arthritis combining data-driven machine learning approaches and a state-of-the-art mechanistic disease map

“…Patients who do not respond to conventional DMARDs usually initiate therapy with TNF inhibitors. However, approximately 30-40% of RA patients fail to respond to anti-TNF therapy and are usually obliged to go several rounds of drug combinations (Farutin et al, 2019). Due to the complex nature of the disease, systems biology and integrative approaches are needed in order to gain insight into the disease pathogenesis and progression.…”

“…Patients who do not respond to conventional DMARDs usually initiate therapy with TNF inhibitors. However, approximately 30–40% of RA patients fail to respond to antiTNF therapy and are usually obliged to undergo several rounds of drug combinations [9].…”

Current status of use of high throughput nucleotide sequencing in rheumatology

“…The most represented assay is RNA-Seq (n=457, 65%) for the identification of biomarkers in blood or synovial tissue, for example, to distinguish active versus inactive/low disease activity states, 27 to examine response to anti-TNF therapy in RA, 34 to identify gene expression signatures correlating with disease phenotype, 35 for longitudinal analysis of peripheral blood TCR diversity in patients with SLE, 36 as well as for subgrouping patients with SLE with common clinical characteristics, 28 characterisation of circulating memory stem T cells in RA, 37 as well as to examine the BCR repertoire in patients with RA to identify B cell clones associated with autoreactivity. 38 In addition to messenger RNA, a wide range of RNA types can be measured, such as microRNAs (miRNAs) in RA, 39 JIA, 40 SLE and Sjögren’s syndrome, 41 long non coding RNA (lncRNA) in SLE 42 as well as myositis, 43 and finally circular RNA as biomarker in SLE 44 .…”