Interactions between rheumatoid arthritis antibodies are associated with the response to anti-tumor necrosis factor therapy.

BACKGROUND: Blocking of the Tumor Necrosis Factor (TNF) activity is a successful therapeutic approach for 50-60% of rheumatoid arthritis (RA) patients. However, there are yet no biomarkers to stratify patients for anti-TNF therapy. Rheumatoid factor (RF) and anti-cyclic-citrullinated antibodies (anti-CCP) have been evaluated as biomarkers of response but the results have shown limited consistency. Anti-carbamylated protein (anti-CarP) and anti-peptidylarginine deiminase type 4 (anti-PAD4) antibodies have been much less studied. Despite being linked to common immune processes, the interaction between these markers has not been evaluated yet. Our aim was to analyze the interaction between these four antibodies in relation to the response to anti-TNF therapy. METHODS: For this objective, a prospective cohort of n = 80 RA patients starting anti-TNF therapy was recruited. Serum determinations at baseline were performed for RF, anti-CCP, anti-CarP and anti-PAD4 antibodies using enzyme-linked immunosorbent assays (ELISA). The clinical response to anti-TNF therapy was determined at week 12 using the change in DAS28 score. Association was performed using multivariate linear regression adjusting for baseline DAS28, sex and age. RESULTS: The interaction between pairs of antibodies was tested by the addition of an interaction term. We found two highly significant antibody interactions associated with treatment response: anti-CarP with anti-PAD4 (p = 0.0062), and anti-CCP with RF (p = 0.00068). The latter antibody interaction was replicated in an independent retrospective cohort of RA patients (n = 199, p = 0.04). CONCLUSIONS: The results of this study suggest that antibody interaction effects are important factors in the response to anti-TNF therapy in RA.

Efficacy, safety and cost-effectiveness of a web-based platform delivering the results of a biomarker-based predictive model of biotherapy response for rheumatoid arthritis patients: a protocol for a randomized multicenter single-blind active controlled clinical trial (PREDIRA).

BACKGROUND: Rheumatoid arthritis (RA) is one of the leading chronic inflammatory rheumatism. First-line therapy with synthetic disease-modifying antirheumatic drugs (sDMARD) is insufficiently effective in 40% of cases and these patients are treated with biotherapies. The increased use of these drugs each year is becoming a public health issue with considerable economic burden. This cost is 20 times higher than that of sDMARD. However, among patients treated with biotherapies, clinical practice shows that about one third will not respond to the selected drug. In nonresponse cases, practitioners currently have no choice but to perform an empirical switching between different treatments, because no tool capable of predicting the response or nonresponse to these molecules is currently available. METHODS: The study is a prospective, phase III, controlled, multicenter, and randomized, single-blind (patient) clinical trial, including RA patients with a previous failure to anti-TNF therapies. The main objective is the analysis of the clinical and pharmacoeconomic impact after 6 months of treatment. Intervention arm: prescription of biotherapy (rituximab, adalimumab, abatacept) using SinnoTest® software, a prediction software based on proteomic biomarkers. Control arm: prescription of biotherapy based on current practice, without the SinnoTest® software (any biotherapy). In addition, a substudy will be carried out within this trial to generate a biobank and further analyze the proteomic profile of the patients and their modification throughout the study. DISCUSSION: This clinical trial study will be the first validation study of a biotherapy response prediction software, bringing personalized medicine into the management of RA. We expect that the findings from this study will bring several benefits for the patient and the Health Care System. TRIAL REGISTRATION: ClincalTrials.gov NCT04147026 . Registered on 31 October, 2019.

A Combined Transcriptomic and Genomic Analysis Identifies a Gene Signature Associated With the Response to Anti-TNF Therapy in Rheumatoid Arthritis.

Background: Rheumatoid arthritis (RA) is the most frequent autoimmune disease involving the joints. Although anti-TNF therapies have proven effective in the management of RA, approximately one third of patients do not show a significant clinical response. The objective of this study was to identify new genetic variation associated with the clinical response to anti-TNF therapy in RA. Methods: We performed a sequential multi-omic analysis integrating different sources of molecular information. First, we extracted the RNA from synovial biopsies of 11 RA patients starting anti-TNF therapy to identify gene coexpression modules (GCMs) in the RA synovium. Second, we analyzed the transcriptomic association between each GCM and the clinical response to anti-TNF therapy. The clinical response was determined at week 14 using the EULAR criteria. Third, we analyzed the association between the GCMs and anti-TNF response at the genetic level. For this objective, we used genome-wide data from a cohort of 348 anti-TNF treated patients from Spain. The GCMs that were significantly associated with the anti-TNF response were then tested for validation in an independent cohort of 2,706 anti-TNF treated patients. Finally, the functional implication of the validated GCMs was evaluated via pathway and cell type epigenetic enrichment analyses. Results: A total of 149 GCMs were identified in the RA synovium. From these, 13 GCMs were found to be significantly associated with anti-TNF response (P < 0.05). At the genetic level, we detected two of the 13 GCMs to be significantly associated with the response to adalimumab (P = 0.0015) and infliximab (P = 0.021) in the Spain cohort. Using the independent cohort of RA patients, we replicated the association of the GCM associated with the response to adalimumab (P = 0.0019). The validated module was found to be significantly enriched for genes involved in the nucleotide metabolism (P = 2.41e-5) and epigenetic marks from immune cells, including CD4+ regulatory T cells (P = 0.041). Conclusions: These findings show the existence of a drug-specific genetic basis for anti-TNF response, thereby supporting treatment stratification in the search for response biomarkers in RA.

A genome-wide association study identifies SLC8A3 as a susceptibility locus for ACPA-positive rheumatoid arthritis.

OBJECTIVE: RA patients with serum ACPA have a strong and specific genetic background. The objective of the study was to identify new susceptibility genes for ACPA-positive RA using a genome-wide association approach. METHODS: A total of 924 ACPA-positive RA patients with joint damage in hands and/or feet, and 1524 healthy controls were genotyped in 582 591 single-nucleotide polymorphisms (SNPs) in the discovery phase. In the validation phase, the most significant SNPs in the genome-wide association study representing new candidate loci for RA were tested in an independent cohort of 863 ACPA-positive patients with joint damage and 1152 healthy controls. All individuals from the discovery and validation cohorts were Caucasian and of Southern European ancestry. RESULTS: In the discovery phase, 60 loci not previously associated with RA risk showed evidence for association at P < 5×10(-4) and were tested for replication in the validation cohort. A total of 12 loci were replicated at the nominal level (P < 0.05, same direction of effect as in the discovery phase). When combining the discovery and validation cohorts, an intronic SNP in the Solute Carrier family 8 gene (SLC8A3) was found to be associated with ACPA-positive RA at a genome-wide level of significance RA [odds ratio (95% CI): 1.42 (1.25, 1.6), Pcombined = 3.19×10(-8)]. CONCLUSIONS: SLC8A3 was identified as a new risk locus for ACPA-positive RA. This study demonstrates the advantage of analysing relevant subsets of RA patients to identify new genetic risk variants.

Discovery of serum proteomic biomarkers for prediction of response to infliximab (a monoclonal anti-TNF antibody) treatment in rheumatoid arthritis: an exploratory analysis.

Biologics such as TNF antagonists are a new class of drugs that have greatly improved Rheumatoid Arthritis (RA) treatment. However, for unknown reasons, individual patients with RA respond to one of these drugs but not to others even those targeting the same molecule. Methods to predict response are sorely needed because these drugs are currently selected by trial and error, what is very inefficient and prejudicial for the patient and the healthcare system. Here, we have explored the discovery of protein biomarkers in serum from patients treated with infliximab, one of the major anti-TNF drugs. The study was based in a quantitative proteomics approach using 8-plex iTRAQ labeling. It combined depletion of the most abundant serum proteins, two-dimensional LC fractionation, protein identification and relative quantification with a hybrid Orbitrap mass spectrometer. This approach allowed the identification of 315 proteins of which 237 were confidently quantified with two or more peptides. The detection range covered up to 6 orders of magnitude including multiple proteins at the ng/mL level. A new set of putative biomarkers was identified comprising 14 proteins significantly more abundant in the non-responder patients. The differential proteins were enriched in apolipoproteins, components of the complement system and acute phase reactants. These results show the feasibility of this approach and provide a set of candidates for validation as biomarkers for the classification of RA patients before the beginning of treatment, so that anticipated non-responders could be treated with an alternative drug.

Diagnóstico de osteoporosis mediante la radiografía lateral de tórax / Diagnosis of osteoporosis by lateral chest X-ray

FUNDAMENTO: La radiografía lateral de tórax, mediante la detección de deformidades vertebrales, puede ayudar a identificar tempranamente a los enfermos con esteoporosis. En este trabajo hemos querido ver con qué frecuencia los radiólogos refieren en sus informes de radiografías laterales de tórax algún dato que permita al clínico sospechar una osteoporosis, y en qué porcentaje de casos el clínico, ante estos informes, llega a diagnosticar la enfermedad. PACIENTES Y MÉTODO: Se han revisado los informes de las radiografías laterales de tórax de 3.500 pacientes consecutivos, así como sus informes de alta. RESULTADOS: Los informes radiológicos hicieron referencia a la existencia de osteoporosis sólo en un 20 por ciento de los casos potencialmente diagnosticables; los informes clínicos lo hicieron en un 6,3 por ciento (un tercio de los casos con informe radiológico positivo); sólo se trató adecuadamente al 4 por ciento (dos tercios de los casos diagnosticados por el clínico). CONCLUSIONES: La osteoporosis es una enfermedad desatendida por radiólogos y clínicos. Las radiografías laterales de tórax constituyen una herramienta diagnóstica desaprovechada en la identificación de pacientes con osteoporosis (AU)