The promise of precision medicine in rheumatology

Rheumatoid arthritis patients harbour aberrant enteric bacteriophages with autoimmunity-provoking potential: a paired sibling study

OBJECTIVES

Viruses have been considered as important participants in the development of rheumatoid arthritis (RA). However, the profile of enteric virome and its role in RA remains elusive. This study aimed to investigate the atlas and involvement of virome in RA pathogenesis.

METHODS

Faecal samples from 30 pairs of RA and healthy siblings that minimise genetic interferences were collected for metagenomic sequencing. The α and β diversity of the virome and the virome-bacteriome interaction were analysed. The differential bacteriophages were identified, and their correlations with clinical and immunological features of RA were analysed. The potential involvement of these differential bacteriophages in RA pathogenesis was further investigated by auxiliary metabolic gene annotation and molecular mimicry study. The responses of CD4+ T cells and B cells to the mimotopes derived from the differential bacteriophages were systemically studied.

RESULTS

The composition of the enteric bacteriophageome was distorted in RA. The differentially presented bacteriophages correlated with the immunological features of RA, including anti-CCP autoantibody and HLA-DR shared epitope. Intriguingly, the glycerolipid and purine metabolic genes were highly active in the bacteriophages from RA. Moreover, peptides of RA-enriched phages, in particular Prevotella phage and Oscillibacter phage could provoke the autoimmune responses in CD4+ T cells and plasma cells via molecular mimicry of the disease-associated autoantigen epitopes, especially those of Bip.

CONCLUSIONS

This study provides new insights into enteric bacteriophageome in RA development. In particular, the aberrant bacteriophages demonstrated autoimmunity-provoking potential that would promote the occurrence of the disease.

A Network-Based Framework to Discover Treatment-Response-Predicting Biomarkers for Complex Diseases

Precision medicine's potential to transform complex autoimmune disease treatment is often challenged by limited data availability and inadequate sample size when compared with the number of molecular features found in high-throughput multi-omics data sets. Addressing this issue, the novel framework PRoBeNet (Predictive Response Biomarkers using Network medicine) was developed. ProBeNet operates under the hypothesis that the therapeutic effect of a drug propagates through a protein-protein interaction network to reverse disease states. ProBeNet prioritizes biomarkers by considering the following: i) therapy-targeted proteins, ii) disease-specific molecular signatures, and iii) an underlying network of interactions among cellular components (the human interactome). With ProBeNet, biomarkers were discovered predicting patient responses to both an established autoimmune therapy (infliximab) and an investigational compound (a mitogen-activated protein kinase 3/1 inhibitor). The predictive power of ProBeNet biomarkers was validated with retrospective gene-expression data from patients with ulcerative colitis and rheumatoid arthritis and prospective data from patient-derived tissues from patients with ulcerative colitis and Crohn disease. Machine-learning models using ProBeNet biomarkers significantly outperformed models using either all genes or randomly selected genes, especially when data were limited (<20 samples). These results illustrate the value of ProBeNet for reducing features and for constructing robust machine-learning models when limited data are available. ProBeNet may be used to develop companion and complementary diagnostic assays for complex autoimmune disease therapies, which may help stratify suitable patient subgroups in clinical trials, approve new drugs, and improve patient outcomes.

Hurdles in new drug development in rheumatic diseases

INTRODUCTION

Rheumatic diseases are heterogenous conditions with multifactorial underlying physiologic pathogeneses. Despite recent progress in the identification and development of advanced therapies primarily focusing on disrupting the immunological abnormalities that cause these conditions, rheumatic disease management remains challenging in a notable proportion of patients, with many exhibiting uncontrolled or refractory disease activity. New and improved therapies are needed to respond to this treatment gap. However, there are important hurdles that can affect the expedited identification and assessment of new treatments.

METHODS

We present a review of key hurdles in the development of antirheumatic agents, as well as possible solutions to these obstacles.

RESULTS

We highlight the challenges presented by incomplete understanding of the complexity of rheumatic disease pathophysiology and the resultant difficulties in the identification, development, and evaluation of new therapies. We further explore the diversity of the underlying disease processes leading to heterogeneity in patient response to treatment, necessitating the re-design of clinical trials of antirheumatic agents to detect efficacy signals and better inform clinical disease management. Finally, emergent strategies and methodologies with potential to improve upon these hurdles are presented.

CONCLUSION

New and modified study designs and research tools that leverage ongoing advancements in the elucidation of rheumatic disease pathogenesis coupled with progress in methods to mine available data will be instrumental in overcoming current hurdles in antirheumatic drug development.

Engineered immune cells as therapeutics for autoimmune diseases

Current treatment options for autoimmune disease (AID) are essentially immunosuppressive, inhibiting the inflammatory cascade, without curing the disease. Therapeutic monoclonal antibodies (mAbs) that target B cells showed efficacy, emphasizing the importance of B lymphocytes in autoimmune pathogenesis. Treatments that eliminate more potently B cells would open a new therapeutic era for AID. Immune cells can now be bioengineered to express constructs that enable them to specifically eradicate pathogenic B lymphocytes. Engineered immune cells (EICs) have shown therapeutic promise in both experimental models and in clinical trials in AID. Next-generation platforms are under development to optimize their specificity and improve safety. The profound and durable B cell depletion achieved reinforces the view that this biotherapeutic option holds promise for treating AID.

Engineering Innervated Musculoskeletal Tissues for Regenerative Orthopedics and Disease Modeling

Musculoskeletal (MSK) disorders significantly burden patients and society, resulting in high healthcare costs and productivity loss. These disorders are the leading cause of physical disability, and their prevalence is expected to increase as sedentary lifestyles become common and the global population of the elderly increases. Proper innervation is critical to maintaining MSK function, and nerve damage or dysfunction underlies various MSK disorders, underscoring the potential of restoring nerve function in MSK disorder treatment. However, most MSK tissue engineering strategies have overlooked the significance of innervation. This review first expounds upon innervation in the MSK system and its importance in maintaining MSK homeostasis and functions. This will be followed by strategies for engineering MSK tissues that induce post-implantation in situ innervation or are pre-innervated. Subsequently, research progress in modeling MSK disorders using innervated MSK organoids and organs-on-chips (OoCs) is analyzed. Finally, the future development of engineering innervated MSK tissues to treat MSK disorders and recapitulate disease mechanisms is discussed. This review provides valuable insights into the underlying principles, engineering methods, and applications of innervated MSK tissues, paving the way for the development of targeted, efficacious therapies for various MSK conditions.

Molecular portrait of chronic joint diseases: Defining endotypes toward personalized medicine

Joint diseases affect hundreds of millions of people worldwide, and their prevalence is constantly increasing. To date, despite recent advances in the development of therapeutic options for most rheumatic conditions, a significant proportion of patients still lack efficient disease management, considerably impacting their quality of life. Through the spectrum of rheumatoid arthritis (RA), psoriatic arthritis (PsA), and osteoarthritis (OA) as quintessential and common rheumatic diseases, this review first provides an overview of their epidemiological and clinical features before exploring how the better definition of clinical phenotypes has helped their clinical management. It then discusses the recent progress in understanding the diversity of endotypes underlying disease phenotypes. Finally, this review highlights the current challenges of implementing molecular endotypes towards the personalized management of RA, PsA and OA patients in the future.

The diagnosis and management of systemic autoimmune rheumatic disease-related interstitial lung disease: British Society for Rheumatology guideline scope

Interstitial lung disease (ILD) is a significant complication of many systemic autoimmune rheumatic diseases (SARDs), although the clinical presentation, severity and outlook may vary widely between individuals. Despite the prevalence, there are no specific guidelines addressing the issue of screening, diagnosis and management of ILD across this diverse group. Guidelines from the ACR and EULAR are expected, but there is a need for UK-specific guidelines that consider the framework of the UK National Health Service, local licensing and funding strategies. This article outlines the intended scope for the British Society for Rheumatology guideline on the diagnosis and management of SARD-ILD developed by the guideline working group. It specifically identifies the SARDs for consideration, alongside the overarching principles for which systematic review will be conducted. Expert consensus will be produced based on the most up-to-date available evidence for inclusion within the final guideline. Key issues to be addressed include recommendations for screening of ILD, identifying the methodology and frequency of monitoring and pharmacological and non-pharmacological management. The guideline will be developed according to methods and processes outlined in Creating Clinical Guidelines: British Society for Rheumatology Protocol version 5.1.

Myocardial DNA Damage Predicts Heart Failure Outcome in Various Underlying Diseases

BACKGROUND

Reliable predictors of treatment efficacy in heart failure have been long awaited. DNA damage has been implicated as a cause of heart failure.

OBJECTIVES

The purpose of this study was to investigate the association of DNA damage in myocardial tissue with treatment response and prognosis of heart failure.

METHODS

The authors performed immunostaining of DNA damage markers poly(ADP-ribose) (PAR) and γ-H2A.X in endomyocardial biopsy specimens from 175 patients with heart failure with reduced ejection fraction (HFrEF) of various underlying etiologies. They calculated the percentage of nuclei positive for each DNA damage marker (%PAR and %γ-H2A.X). The primary outcome was left ventricular reverse remodeling (LVRR) at 1 year, and the secondary outcome was a composite of cardiovascular death, heart transplantation, and ventricular assist device implantation.

RESULTS

Patients who did not achieve LVRR after the optimization of medical therapies presented with significantly higher %PAR and %γ-H2A.X. The ROC analysis demonstrated good performance of both %PAR and %γ-H2A.X for predicting LVRR (AUCs: 0.867 and 0.855, respectively). There was a negative correlation between the mean proportion of DNA damage marker-positive nuclei and the probability of LVRR across different underlying diseases. In addition, patients with higher %PAR or %γ-H2A.X had more long-term clinical events (PAR HR: 1.63 [95% CI: 1.31-2.01]; P < 0.001; γ-H2A.X HR: 1.48 [95% CI: 1.27-1.72]; P < 0.001).

CONCLUSIONS

DNA damage determines the consequences of human heart failure. Assessment of DNA damage is useful to predict treatment efficacy and prognosis of heart failure patients with various underlying etiologies.

Anti-Acidification and Immune Regulation by Nano-Ceria-Loaded Mg-Al Layered Double Hydroxide for Rheumatoid Arthritis Therapy

Rheumatoid arthritis (RA) is a chronic autoimmune disease featuring an abnormal immune microenvironment and resultant accumulation of hydrogen ions (H+ ) produced by activated osteoclasts (OCs). Currently, clinic RA therapy can hardly achieve sustained or efficient therapeutic outcomes due to the failures in generating sufficient immune modulation and manipulating the accumulation of H+ that deteriorates bone damage. Herein, a highly effective immune modulatory nanocatalytic platform, nanoceria-loaded magnesium aluminum layered double hydroxide (LDH-CeO2 ), is proposed for enhanced immune modulation based on acid neutralization and metal ion inherent bioactivity. Specifically, the mild alkaline LDH initiates significant M2 repolarization of macrophages triggered by the elevated antioxidation effect of CeO2 via neutralizing excessive H+ in RA microenvironment, thus resulting in the efficient recruitment of regulatory T cell (Treg) and suppressions on T helper 17 cell (Th 17) and plasma cells. Moreover, the osteogenic activity is stimulated by the Mg ion released from LDH, thereby promoting the damaged bone healing. The encouraging therapeutic outcomes in adjuvant-induced RA model mice demonstrate the high feasibility of such a therapeutic concept, which provides a novel and efficient RA therapeutic modality by the immune modulatory and bone-repairing effects of inorganic nanocatalytic material.

Immune and molecular landscape behind non-response to Mycophenolate Mofetil and Azathioprine in lupus nephritis therapy

Lupus nephritis (LN) represents one of the most severe complications of systemic lupus erythematosus, leading to end-stage kidney disease in worst cases. Current first-line therapies for LN, including mycophenolate mofetil (MMF) and azathioprine (AZA), fail to induce long-term remission in 60-70% of the patients, evidencing the urgent need to delve into the molecular knowledge-gap behind the non-response to these therapies. A longitudinal cohort of treated LN patients including clinical, cellular and transcriptomic data, was analyzed. Gene-expression signatures behind non-response to different drugs were revealed by differential expression analysis. Drug-specific non-response mechanisms and cell proportion differences were identified. Blood cell subsets mediating non-response were described using single-cell RNASeq data. We show that AZA and MMF non-response implicates different cells and regulatory functions. Mechanistic models were used to suggest add-on therapies to improve their current performance. Our results provide new insights into the molecular mechanisms associated with treatment failures in LN.

Extracting immunological and clinical heterogeneity across autoimmune rheumatic diseases by cohort-wide immunophenotyping

OBJECTIVE

Extracting immunological and clinical heterogeneity across autoimmune rheumatic diseases (AIRDs) is essential towards personalised medicine.

METHODS

We conducted large-scale and cohort-wide immunophenotyping of 46 peripheral immune cells using Human Immunology Protocol of comprehensive 8-colour flow cytometric analysis. Dataset consisted of >1000 Japanese patients of 11 AIRDs with deep clinical information registered at the FLOW study, including rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). In-depth clinical and immunological characterisation was conducted for the identified RA patient clusters, including associations of inborn human genetics represented by Polygenic Risk Score (PRS).

RESULTS

Multimodal clustering of immunophenotypes deciphered underlying disease-cell type network in immune cell, disease and patient cluster resolutions. This provided immune cell type specificity shared or distinct across AIRDs, such as close immunological network between mixed connective tissue disease and SLE. Individual patient-level clustering dissected patients with AIRD into several clusters with different immunological features. Of these, RA-like or SLE-like clusters were exclusively dominant, showing immunological differentiation between RA and SLE across AIRDs. In-depth clinical analysis of RA revealed that such patient clusters differentially defined clinical heterogeneity in disease activity and treatment responses, such as treatment resistance in patients with RA with SLE-like immunophenotypes. PRS based on RA case-control and within-case stratified genome-wide association studies were associated with clinical and immunological characteristics. This pointed immune cell type implicated in disease biology such as dendritic cells for RA-interstitial lung disease.

CONCLUSION

Cohort-wide and cross-disease immunophenotyping elucidate clinically heterogeneous patient subtypes existing within single disease in immune cell type-specific manner.

Recent advances in strategies to target the behavior of macrophages in wound healing

Chronic wounds and scar formation are widespread due to limited suitable remedies. The macrophage is a crucial regulator in wound healing, controlling the onset and termination of inflammation and regulating other processes related to wound healing. The current breakthroughs in developing new medications and drug delivery methods have enabled the accurate targeting of macrophages in oncology and rheumatic disease therapies through clinical trials. These successes have cleared the way to utilize drugs targeting macrophages in various disorders. This review thus summarizes macrophage involvement in normal and pathologic wound healing. It further details the targets available for macrophage intervention and therapeutic strategies for targeting the behavior of macrophages in tissue repair and regeneration.

Skin Gene Expression Profiles in Systemic Sclerosis: From Clinical Stratification to Precision Medicine

Systemic sclerosis, also known as scleroderma or SSc, is a condition characterized by significant heterogeneity in clinical presentation, disease progression, and response to treatment. Consequently, the design of clinical trials to successfully identify effective therapeutic interventions poses a major challenge. Recent advancements in skin molecular profiling technologies and stratification techniques have enabled the identification of patient subgroups that may be relevant for personalized treatment approaches. This narrative review aims at providing an overview of the current status of skin gene expression analysis using computational biology approaches and highlights the benefits of stratifying patients upon their skin gene signatures. Such stratification has the potential to lead toward a precision medicine approach in the management of SSc.

Artificial intelligence-driven drug development against autoimmune diseases

Artificial intelligence (AI)-based predictive models are being used to foster a precision medicine approach to treat complex chronic diseases such as autoimmune and autoinflammatory disorders (AIIDs). In the past few years the first models of systemic lupus erythematosus (SLE), primary Sjögren syndrome (pSS), and rheumatoid arthritis (RA) have been produced by molecular profiling of patients using omic technologies and integrating the data with AI. These advances have confirmed a complex pathophysiology involving multiple proinflammatory pathways and also provide evidence for shared molecular dysregulation across different AIIDs. I discuss how models are used to stratify patients, assess causality in pathophysiology, design drug candidates in silico, and predict drug efficacy in virtual patients. By relating individual patient characteristics to the predicted properties of millions of drug candidates, these models can improve the management of AIIDs through more personalized treatments.

Analysis of serum proteomics data identifies a quantitative association between beta-defensin 2 at baseline and clinical response to IL-17 blockade in psoriatic arthritis

OBJECTIVES

Despite several effective targeted therapies, biomarkers that predict whether a patient with psoriatic arthritis (PsA) will respond to a particular treatment are currently lacking.

METHODS

We analysed proteomics data from serum samples of nearly 2000 patients with PsA in placebo-controlled phase-III clinical trials of the interleukin-17 inhibitor secukinumab. To discover predictive biomarkers of clinical response, we used statistical learning with controlled feature selection. The top candidate was validated using an ELISA and was separately assessed in a trial of almost 800 patients with PsA treated with secukinumab or the tumour necrosis factor inhibitor adalimumab.

RESULTS

Serum levels of beta-defensin 2 (BD-2) at baseline were found to be robustly associated with subsequent clinical response (eg, American College of Rheumatology definition of 20%, 50% and 70% improvement) to secukinumab, but not to placebo. This finding was validated in two independent clinical studies not used for discovery. Although BD-2 is known to be associated with psoriasis severity, the predictivity of BD-2 was independent of baseline Psoriasis Area and Severity Index. The association between BD-2 and response to secukinumab was observed as early as 4 weeks and maintained up to 52 weeks. BD-2 was also found to predict response to treatment with adalimumab. Unlike in PsA, BD-2 was not predictive of response to secukinumab in rheumatoid arthritis.

CONCLUSIONS

In PsA, BD-2 at baseline is quantitatively associated with clinical response to secukinumab. Patients with high levels of BD-2 at baseline reach and sustain higher rates of clinical response after treatment with secukinumab.

Autoantibodies testing in autoimmunity: Diagnostic, prognostic and classification value

Diagnosis of autoimmune diseases is in most cases challenging for clinicians as there is not a single specific laboratory or histological marker to diagnose or exclude the presence of the conditions. This review focused on the current knowledge of the role of autoantibodies' testing in various diseases, such as systemic lupus erythematosus, rheumatoid arthritis, antiphospholipid syndrome, undifferentiated connective tissues disease, primary biliary cirrhosis and primary sclerosing cholangitis. Similarly, the prognostic and diagnostic values of autoantibodies testing in patients with interstitial lung disease have been reviewed. In-depth research on the molecular action of these autoantibodies on immune regulation and diseases pathogenesis has been explored beyond their correlation with disease phenotypes, highlighting the impact of autoantibodies targeting on disease outcomes and etiopathogenesis.

Stratified distribution of Th17 and Treg cells in patients with multi-stage rheumatoid arthritis

OBJECTIVE

Rheumatoid arthritis (RA) is a typical, progressive autoimmune disease. Its occurrence and development are associated with dysregulation of T and B cell numbers. However, the specific immune characteristics of different RA courses remain incompletely defined. Here, we describe the peripheral blood lymphocyte subsets, particularly CD4 + T subsets, of different RA courses with a focus on early RA (Ea-RA).

METHODS

In all, 131 patients with Ea-RA, 117 with advanced RA (Ad-RA), and 109 with treated RA (Tr-RA) were enrolled. We collected general clinical data. Whole blood samples obtained from the patients and 97 healthy controls (HCs) were analysed via flow cytometry.

RESULTS

Decreased absolute NK cell numbers and increased CD4/CD8 T cell ratios were observed in different RA groups, including Ea-RA, compared to healthy controls. In Ea-RA patients, the Th17 and Treg cell numbers were similar to those in HCs. We performed k-means clustering based on the profiles of Th17 and Treg cells for patients with multi-stage of RA. We identified three patient types: type A characterised by relatively low Treg and Th17 cell numbers, type B with moderate levels of Treg cells and levels of Th17 cells similar to that of type C patients, and type C with high levels of Treg cells and levels of Th17 cells similar to that of type B patients.

CONCLUSION

The immune characteristics of Ea-RA patients differ from those of HCs; an immune system disorder is apparent although no differences in Th17 and Treg levels were evident between Ea-RA patients and HCs. We found distributional heterogeneities of Th17 and Treg cells in patients with multi-stage of RA. Stratified management based on such heterogeneity may serve as a useful novel immunotherapy allowing of early intervention.

Biomarker-driven development of new therapies for autoimmune diseases: current status and future promises

INTRODUCTION

Auto-immune diseases are complex and heterogeneous. Various types of biomarkers can be used to support precision medicine approaches to autoimmune diseases, ensuring that the right patient receives the most appropriate therapy to improve treatment outcomes.

AREAS COVERED

We review the recent progress made in modeling several autoimmune diseases such as Systemic Lupus Erythematosus, primary Sjogren Syndrome, and Rheumatoid Arthritis following extensive molecular profiling of large cohorts of patients. From this knowledge, BMKs are being identified which support diagnostic as well as patient stratification and prediction of response to treatment. The identification of biomarkers should be initiated early in drug development and properly validated during subsequent clinical trials. To ensure the robustness and reproducibility of biomarkers, the PERMIT Consortium recently established recommendations highlighting the importance of relevant study design, sample size, and appropriate validation of analytical methods.

EXPERT OPINION

The integration by AI-powered analytics of massive data provided by multi-omics technologies, high-resolution medical imaging and sensors borne by patients will eventually allow the identification of clinically relevant BMKs, likely in the form of combinatorial predictive algorithms, to support future drug development for autoimmune diseases.

Bioinformatics analyses of combined databases identify shared differentially expressed genes in cancer and autoimmune disease

BACKGROUND

Inadequate immunity caused by poor immune surveillance leads to tumorigenesis, while excessive immunity due to breakdown of immune tolerance causes autoimmune genesis. Although the function of immunity during the onset of these two processes appears to be distinct, the underlying mechanism is shared. To date, gene expression data for large bodies of clinical samples are available, but the resemblances of tumorigenesis and autoimmune genesis in terms of immune responses remains to be summed up.

METHODS

Considering the high disease prevalence, we chose invasive ductal carcinoma (IDC) and systemic lupus erythematosus (SLE) to study the potential commonalities of immune responses. We obtained gene expression data of IDC/SLE patients and normal controls from five IDC databases (GSE29044, GSE21422, GSE22840, GSE15852, and GSE9309) and five SLE databases (GSE154851, GSE99967, GSE61635, GSE50635, and GSE17755). We intended to identify genes differentially expressed in both IDC and SLE by using three bioinformatics tools including GEO2R, the limma R package, and Weighted Gene Co-expression Network Analysis (WGCNA) to perform function enrichment, protein-protein network, and signaling pathway analyses.

RESULTS

The mRNA levels of signal transducer and activator of transcription 1 (STAT1), 2'-5'-oligoadenylate synthetase 1 (OAS1), 2'-5'-oligoadenylate synthetase like (OASL), and PML nuclear body scaffold (PML) were found to be differentially expressed in both IDC and SLE by using three different bioinformatics tools of GEO2R, the limma R package and WGCNA. From the combined databases in this study, the mRNA levels of STAT1 and OAS1 were increased in IDC while reduced in SLE. And the mRNA levels of OASL and PML were elevated in both IDC and SLE. Based on Kyoto Encyclopedia of Genes and Genomes pathway analysis and QIAGEN Ingenuity Pathway Analysis, both IDC and SLE were correlated with the changes of multiple components involved in the Interferon (IFN)-Janus kinase (JAK)-signal transducer and activator of transcription (STAT) signaling pathway.

CONCLUSION

The expression levels of STAT1 and OAS1 manifest the opposite expression tendency across cancer and autoimmune disease. They are components in the IFN-JAK-STAT signaling pathway related to both tumorigenesis and autoimmune genesis. STAT1 and OAS1-associated IFN-JAK-STAT signaling could explain the commonalities during tumorigenesis and autoimmune genesis and render significant information for more precise treatment from the point of immune homeostasis.

Myositis with prominent B cell aggregates may meet classification criteria for sporadic inclusion body myositis

The objective of this study was to report the clinical, serological and pathological features of patients with autoimmune myositis other than dermatomyositis, who displayed both muscle weakness on physical examination and prominent B cell aggregates on muscle pathology, defined as ≥ 30 CD20+ cells/aggregate. Specifically, the presence of a brachio-cervical inflammatory myopathies or a sporadic inclusion body myositis (sIBM) phenotype was recorded. Over a three-year period, eight patients were identified from two university neuropathology referral centers. Seven of 8 (88%) patients had an associated connective tissue disease (CTD): rheumatoid arthritis (n=3), systemic sclerosis (n=2), Sjögren's syndrome (n=1) and systemic lupus erythematosus (n=1), while one patient died on initial presentation without a complete serological and cancer investigation. A brachio-cervical phenotype, i.e. neck weakness, proximal weakness more than distal and shoulder abduction weakness greater than hip flexors, was seen in two patients (25%), while one patient had both proximal and diaphragmatic weakness. In contrast, an IBM-like clinical phenotype was seen in the last five patients (63%), who either had finger flexor weakness and/or quadriceps weakness ≤ 4 on the manual muscle testing MRC-5 scale. Although these 5 patients met at least one set of classification criteria for sIBM, an integrated clinico-sero-pathological approach argued against a diagnosis of sIBM. In summary, in a weak patient with myositis plus an associated CTD and lymphoid aggregates at muscle pathology, B cell predominant aggregates may represent a morphological biomarker against a diagnosis of sIBM.

From Bench to Bedside in Rheumatoid Arthritis from the "2022 GISEA International Symposium"

While precision medicine is still a challenge in rheumatic disease, in recent years many advances have been made regarding pathogenesis, the treatment of inflammatory arthropathies, and their interaction. New insight into the role of inflammasome and synovial tissue macrophage subsets as predictors of drug response give hope for future tailored therapeutic strategies and a personalized medicine approach in inflammatory arthropathies. Here, we discuss the main pathogenetic mechanisms and therapeutic approaches towards precision medicine in rheumatoid arthritis from the 2022 International GISEA/OEG Symposium.

Association of the serological status of rheumatoid arthritis patients with two circulating protein biomarkers: A useful tool for precision medicine strategies

Rheumatoid arthritis (RA) is an autoimmune disease characterized by chronic inflammation of the joints and presence of systemic autoantibodies, with a great clinical and molecular heterogeneity. Rheumatoid Factor (RF) and anti-citrullinated protein antibodies (ACPA) are routinely used for the diagnosis of RA. However, additional serological markers are needed to improve the clinical management of this disease, allowing for better patient stratification and the desirable application of precision medicine strategies. In the present study, we investigated those systemic molecular changes that are associated with the RF and ACPA status of RA patients. To achieve this objective, we followed a proteomic biomarker pipeline from the discovery phase to validation. First, we performed an iTRAQ-based quantitative proteomic experiment on serum samples from the RA cohort of the Hospital of Santiago de Compostela (CHUS). In this discovery phase, serum samples from the CHUS cohort were pooled according to their RF/ACPA status. Shotgun analysis revealed that, in comparison with the double negative group (RF-/ACPA-), the abundance of 12 proteins was altered in the RF+/ACPA+ pool, 16 in the RF+/ACPA- pool and 10 in the RF-/ACPA+ pool. Vitamin D binding protein and haptoglobin were the unique proteins increased in all the comparisons. For the verification phase, 80 samples from the same cohort were analyzed individually. To this end, we developed a Multiple Reaction Monitoring (MRM) method that was employed in a comprehensive targeted analysis with the aim of verifying the results obtained in the discovery phase. Thirty-one peptides belonging to 12 proteins associated with RF and/or ACPA status were quantified by MRM. In a final validation phase, the serum levels of alpha-1-acid glycoprotein 1 (A1AG1), haptoglobin (HPT) and retinol-binding protein 4 (RET4) were measured by immunoassays in the RA cohort of the Hospital of A Coruña (HUAC). The increase of two of these putative biomarkers in the double seropositive group was validated in 260 patients from this cohort (p = 0.009 A1AG1; p = 0.003 HPT). The increased level of A1AG1 showed association with RF rather than ACPA (p = 0.023), whereas HPT showed association with ACPA rather than RF (p = 0.013). Altogether, this study has allowed a further classification of the RA seropositive patients into two novel clusters: RF+A1AG+ and ACPA+HPT+. The determination of A1AG1 and HPT in serum would provide novel information useful for RA patient stratification, which could facilitate the effective implementation of personalized medicine in routine clinical practice.