A clinically based protein discovery strategy to identify potential biomarkers of response to anti-TNF-α treatment of psoriatic arthritis

Genomic, Proteomic, and Phenotypic Biomarkers of COVID-19 Severity: Protocol for a Retrospective Observational Study

BACKGROUND

Health organizations and countries around the world have found it difficult to control the spread of COVID-19. To minimize the future impact on the UK National Health Service and improve patient care, there is a pressing need to identify individuals who are at a higher risk of being hospitalized because of severe COVID-19. Early targeted work was successful in identifying angiotensin-converting enzyme-2 receptors and type II transmembrane serine protease dependency as drivers of severe infection. Although a targeted approach highlights key pathways, a multiomics approach will provide a clearer and more comprehensive picture of severe COVID-19 etiology and progression.

OBJECTIVE

The COVID-19 Response Study aims to carry out an integrated multiomics analysis to identify biomarkers in blood and saliva that could contribute to host susceptibility to SARS-CoV-2 and the development of severe COVID-19.

METHODS

The COVID-19 Response Study aims to recruit 1000 people who recovered from SARS-CoV-2 infection in both community and hospital settings on the island of Ireland. This protocol describes the retrospective observational study component carried out in Northern Ireland (NI; Cohort A); the Republic of Ireland cohort will be described separately. For all NI participants (n=519), SARS-CoV-2 infection has been confirmed by reverse transcription-quantitative polymerase chain reaction. A prospective Cohort B of 40 patients is also being followed up at 1, 3, 6, and 12 months postinfection to assess longitudinal symptom frequency and immune response. Data will be sourced from whole blood, saliva samples, and clinical data from the electronic care records, the general health questionnaire, and a 12-item general health questionnaire mental health survey. Saliva and blood samples were processed to extract DNA and RNA before whole-genome sequencing, RNA sequencing, DNA methylation analysis, microbiome analysis, 16S ribosomal RNA gene sequencing, and proteomic analysis were performed on the plasma. Multiomics data will be combined with clinical data to produce sensitive and specific prognostic models for severity risk.

RESULTS

An initial demographic and clinical profile of the NI Cohort A has been completed. A total of 249 hospitalized patients and 270 nonhospitalized patients were recruited, of whom 184 (64.3%) were female, and the mean age was 45.4 (SD 13) years. High levels of comorbidity were evident in the hospitalized cohort, with cardiovascular disease and metabolic and respiratory disorders being the most significant (P<.001), grouped according to the International Classification of Diseases 10 codes.

CONCLUSIONS

This study will provide a comprehensive opportunity to study the mechanisms of COVID-19 severity in recontactable participants.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/50733.

Spondyloarthritis with inflammatory bowel disease: the latest on biologic and targeted therapies

Spondyloarthritis (SpA) encompasses a heterogeneous group of chronic inflammatory diseases that can affect both axial and peripheral joints, tendons and entheses. Among the extra-articular manifestations, inflammatory bowel disease (IBD) is associated with considerable morbidity and effects on quality of life. In everyday clinical practice, treatment of these conditions requires a close collaboration between gastroenterologists and rheumatologists to enable early detection of joint and intestinal manifestations during follow-up and to choose the most effective therapeutic regimen, implementing precision medicine for each patient's subtype of SpA and IBD. The biggest issue in this field is the dearth of drugs that are approved for both diseases, as only TNF inhibitors are currently approved for the treatment of full-spectrum SpA-IBD. Janus tyrosine kinase inhibitors are among the most promising drugs for the treatment of peripheral and axial SpA, as well as for intestinal manifestations. Other therapies such as inhibitors of IL-23 and IL-17, phosphodiesterase 4 inhibitor, α4β7 integrin blockers and faecal microbiota transplantation seem to only be able to control some disease domains, or require further studies. Given the growing interest in the development of novel drugs to treat both conditions, it is important to understand the current state of the art and the unmet needs in the management of SpA-IBD.

Evaluation of the Synovial Effects of Biological and Targeted Synthetic DMARDs in Patients with Psoriatic Arthritis: A Systematic Literature Review and Meta-Analysis

The aims of this systematic literature review (SLR) were to identify the effects of approved biological and targeted synthetic disease modifying antirheumatic drugs (b/tsDMARDs) on synovial membrane of psoriatic arthritis (PsA) patients, and to determine the existence of histological/molecular biomarkers of response to therapy. A search was conducted on MEDLINE, Embase, Scopus, and Cochrane Library (PROSPERO:CRD42022304986) to retrieve data on longitudinal change of biomarkers in paired synovial biopsies and in vitro studies. A meta-analysis was conducted by adopting the standardized mean difference (SMD) as a measure of the effect. Twenty-two studies were included (19 longitudinal, 3 in vitro). In longitudinal studies, TNF inhibitors were the most used drugs, while, for in vitro studies, JAK inhibitors or adalimumab/secukinumab were assessed. The main technique used was immunohistochemistry (longitudinal studies). The meta-analysis showed a significant reduction in both CD3+ lymphocytes (SMD -0.85 [95% CI -1.23; -0.47]) and CD68+ macrophages (sublining, sl) (SMD -0.74 [-1.16; -0.32]) in synovial biopsies from patients treated for 4-12 weeks with bDMARDs. Reduction in CD3+ mostly correlated with clinical response. Despite heterogeneity among the biomarkers evaluated, the reduction in CD3+/CD68+sl cells during the first 3 months of treatment with TNF inhibitors represents the most consistent variation reported in the literature.

Phenotypic heterogeneity in psoriatic arthritis: towards tissue pathology-based therapy

Psoriatic arthritis (PsA) is a heterogeneous disease involving multiple potential tissue domains. Most outcome measures used so far in randomized clinical trials do not sufficiently reflect this domain heterogeneity. The concept that pathogenetic mechanisms might vary across tissues within a single disease, underpinning such phenotype diversity, could explain tissue-distinct levels of response to different therapies. In this Review, we discuss the tissue, cellular and molecular mechanisms that drive clinical heterogeneity in PsA phenotypes, and detail existing tissue-based research, including data generated using sophisticated interrogative technologies with single-cell precision. Finally, we discuss how these elements support the need for tissue-based therapy in PsA in the context of existing and new therapeutic modes of action, and the implications for future PsA trial outcomes and design.

Omics and Multi-Omics Analysis for the Early Identification and Improved Outcome of Patients with Psoriatic Arthritis

The definitive diagnosis and early treatment of many immune-mediated inflammatory diseases (IMIDs) is hindered by variable and overlapping clinical manifestations. Psoriatic arthritis (PsA), which develops in ~30% of people with psoriasis, is a key example. This mixed-pattern IMID is apparent in entheseal and synovial musculoskeletal structures, but a definitive diagnosis often can only be made by clinical experts or when an extensive progressive disease state is apparent. As with other IMIDs, the detection of multimodal molecular biomarkers offers some hope for the early diagnosis of PsA and the initiation of effective management and treatment strategies. However, specific biomarkers are not yet available for PsA. The assessment of new markers by genomic and epigenomic profiling, or the analysis of blood and synovial fluid/tissue samples using proteomics, metabolomics and lipidomics, provides hope that complex molecular biomarker profiles could be developed to diagnose PsA. Importantly, the integration of these markers with high-throughput histology, imaging and standardized clinical assessment data provides an important opportunity to develop molecular profiles that could improve the diagnosis of PsA, predict its occurrence in cohorts of individuals with psoriasis, differentiate PsA from other IMIDs, and improve therapeutic responses. In this review, we consider the technologies that are currently deployed in the EU IMI2 project HIPPOCRATES to define biomarker profiles specific for PsA and discuss the advantages of combining multi-omics data to improve the outcome of PsA patients.

ATRPred: A machine learning based tool for clinical decision making of anti-TNF treatment in rheumatoid arthritis patients

Rheumatoid arthritis (RA) is a chronic autoimmune condition, characterised by joint pain, damage and disability, which can be addressed in a high proportion of patients by timely use of targeted biologic treatments. However, the patients, non-responsive to the treatments often suffer from refractoriness of the disease, leading to poor quality of life. Additionally, the biologic treatments are expensive. We obtained plasma samples from N = 144 participants with RA, who were about to commence anti-tumour necrosis factor (anti-TNF) therapy. These samples were sent to Olink Proteomics, Uppsala, Sweden, where proximity extension assays of 4 panels, containing 92 proteins each, were performed. A total of n = 89 samples of patients passed the quality control of anti-TNF treatment response data. The preliminary analysis of plasma protein expression values suggested that the RA population could be divided into two distinct molecular sub-groups (endotypes). However, these broad groups did not predict response to anti-TNF treatment, but were significantly different in terms of gender and their disease activity. We then labelled these patients as responders (n = 60) and non-responders (n = 29) based on the change in disease activity score (DAS) after 6 months of anti-TNF treatment and applied machine learning (ML) with a rigorous 5-fold nested cross-validation scheme to filter 17 proteins that were significantly associated with the treatment response. We have developed a ML based classifier ATRPred (anti-TNF treatment response predictor), which can predict anti-TNF treatment response in RA patients with 81% accuracy, 75% sensitivity and 86% specificity. ATRPred may aid clinicians to direct anti-TNF therapy to patients most likely to receive benefit, thus save cost as well as prevent non-responsive patients from refractory consequences. ATRPred is implemented in R.

Integrating imaging and biomarker assessment to better define psoriatic arthritis and predict response to biologic therapy

The treatment options for PsA have substantially expanded over the last decade. Approximately 40% of patients will not respond to first-line anti-TNF-α therapies. There is limited data to help clinicians select the most appropriate biologic therapy for PsA patients, including guidance for decisions on biologic therapy switching. In this review we will examine the current understanding of predictors of response to treatment. Imaging technology has evolved to allow us to better study psoriatic disease and define disease activity, including synovitis and enthesitis. Enthesitis is implicated in the pathogenesis, diagnosis and prognosis of PsA. It appears to be a common thread among all of the various PsA clinical presentations. Enthesitis mainly manifests as tenderness, which is difficult to distinguish from FM, chronic pain and mechanically associated enthesopathy, and it might be relevant for understanding the apparent 40% failure of existing therapy. Excess adipose tissue makes if more difficult to detect joint swelling clinically, as many PsA patients have very high BMIs. Integrating imaging and clinical assessment with biomarker analysis could help to deliver stratified medicine in PsA and allow better treatment decision making. This could include which patients require ongoing biologic therapy, which class of biologic therapy that should be, and who alternatively requires management of non-inflammatory disease.

Unraveling the complexities of psoriatic arthritis by the use of -Omics and their relevance for clinical care

-Omic technologies represent a novel approach to unravel ill-defined aspects of psoriatic arthritis (PsA). Large-scale information can be acquired from analysis of affected tissues in PsA via high-throughput studies in the domains of genomics, transcriptomics, epigenetics, proteomics and metabolomics. This is a critical overview of the current knowledge of -omics in PsA, with emphasis on the pathophysiological insights of diagnostic and therapeutic relevance, the advent of novel biomarkers and their potential use for precision medicine in PsA.

From Bed to Bench and Back: TNF-α, IL-23/IL-17A, and JAK-Dependent Inflammation in the Pathogenesis of Psoriatic Synovitis

Psoriatic arthritis (PsA) is a chronic inflammatory immune-mediated disease with a burdensome impact on quality of life and substantial healthcare costs. To date, pharmacological interventions with different mechanisms of action, including conventional synthetic (cs), biological (b), and targeted synthetic (ts) disease-modifying antirheumatic drugs (DMARDs), have been proven efficacious, despite a relevant proportion of failures. The current approach in clinical practice and research is typically "predictive": the expected response is based on stratification according to clinical, imaging, and laboratory data, with a "heuristic" approach based on "trial and error". Several available therapeutic options target the TNF-α pathway, while others are directed against the IL-23/IL-17A axis. Janus kinase inhibitors (JAKis), instead, simultaneously block different pathways, endowing these drugs with a potentially "broad-spectrum" mechanism of action. It is not clear, however, whether targeting a specific pathway (e.g., TNF-α or the IL-23/IL-17 axis) could result in discordant effects over other approaches. In particular, in the case of "refractory to a treatment" patients, other pathways might be hyperactivated, with opposing, synergistic, or redundant biological significance. On the contrary, refractory states could be purely resistant to treatment as a whole. Since chronic synovitis is one of the primary targets of inflammation in PsA, synovial biomarkers could be useful in depicting specific biological characteristics of the inflammatory burden at the single-patient level, and despite not yet being implemented in clinical practice, these biomarkers might help in selecting the proper treatment. In this narrative review, we will provide an up-to-date overview of the knowledge in the field of psoriatic synovitis regarding studies investigating the relationships among different activated proinflammatory processes suitable for targeting by different available drugs. The final objective is to clarify the state of the art in the field of personalized medicine for psoriatic disease, aiming at moving beyond the current treatment schedules toward a patient-centered approach.

Unmet needs in psoriatic arthritis

Psoriatic arthritis (PsA) is a chronic inflammatory arthritis with a highly variable clinical presentation that does not have a validated molecular or imaging test, making accurate diagnosis a challenge. Consequences of diagnostic delay include irreversible joint damage and significant morbidity. Over the past few decades, there have been major advances in the understanding and treatment of PsA, leading to more targeted therapies. However, there is no current method to predict optimal treatment strategy to achieve minimal disease activity and prevent medication-related adverse events in the management of early disease. PsA is also associated with other comorbidities that include metabolic syndrome and psychosocial burden; two areas that are often unaddressed in the clinical setting and have associated sequelae. This chapter focuses on key domains of unmet needs, which include diagnostic challenges, delay in diagnosis, prognostication systems and stratified medicine approaches and precision medicine strategies for established and emerging therapies.

Biomarkers predictive of treatment response in psoriasis and psoriatic arthritis: a systematic review

AIMS

The ability to predict response to treatment remains a key unmet need in psoriatic disease. We conducted a systematic review of studies relating to biomarkers associated with response to treatment in either psoriasis vulgaris (PsV) or psoriatic arthritis (PsA).

METHODS

A search was conducted in PubMed, Embase and the Cochrane library from their inception to 2 September 2020, and conference proceedings from four major rheumatology conferences. Original research articles studying pre-treatment biomarker levels associated with subsequent response to pharmacologic treatment in either PsV or PsA were included.

RESULTS

A total of 765 articles were retrieved and after review, 44 articles (22 relating to PsV and 22 to PsA) met the systematic review's eligibility criteria. One study examined the response to methotrexate, one the response to tofacitinib and all the other studies to biologic disease-modifying antirheumatic drugs (DMARDs). Whilst several studies examined the HLA-C*06 allele in PsV, the results were conflicting. Interleukin (IL)-12 serum levels and polymorphisms in the IL-12B gene show promise as biomarkers of treatment response in PsV. Most, but not all, studies found that higher baseline levels of C-reactive protein (CRP) were associated with a better clinical response to treatment in patients with PsA.

CONCLUSION

Several studies have identified biomarkers associated with subsequent response to treatment in psoriatic disease. However, due to the different types of biomarkers, treatments and outcome measures used, firm conclusions cannot be drawn. Further validation is needed before any of these biomarkers translate to clinical practice.

The growing role of precision medicine for the treatment of autoimmune diseases; results of a systematic review of literature and Experts' Consensus

Autoimmune diseases (AIDs) share similar serological, clinical, and radiological findings, but, behind these common features, there are different pathogenic mechanisms, immune cells dysfunctions, and targeted organs. In this context, multiple lines of evidence suggest the application of precision medicine principles to AIDs to reduce the treatment failure. Precision medicine refers to the tailoring of therapeutic strategies to the individual characteristics of each patient, thus it could be a new approach for management of AIDS which considers individual variability in genes, environmental exposure, and lifestyle. Precision medicine would also assist physicians in choosing the right treatment, the best timing of administration, consequently trying to maximize drug efficacy, and, possibly, reducing adverse events. In this work, the growing body of evidence is summarized regarding the predictive factors for drug response in patients with AIDs, applying the precision medicine principles to provide high-quality evidence for therapeutic opportunities in improving the management of these patients.

Applying precision medicine to unmet clinical needs in psoriatic disease

Psoriatic disease (PsD) is a heterogeneous condition that can affect peripheral and axial joints (arthritis), entheses, skin (psoriasis) and other structures. Over the past decade, considerable advances have been made both in our understanding of the pathogenesis of PsD and in the treatment of its diverse manifestations. However, several major areas of continued unmet need in the care of patients with PsD have been identified. One of these areas is the prediction of poor outcome, notably radiographic outcome in patients with psoriatic arthritis, so that stratified medicine approaches can be taken; another is predicting response to the numerous current and emerging therapies for PsD, so that precision medicine can be applied to rapidly improve clinical outcome and reduce the risk of toxicity. In order to address these needs, novel approaches, including imaging, tissue analysis and the application of proteogenomic technologies, are proposed as methodological solutions that will assist the dissection of the critical immune-metabolic pathways in this complex disease. Learning from advances made in other inflammatory diseases, it is time to address these unmet needs in a multi-centre partnership aimed at improving short-term and long-term outcomes for patients with PsD.

Not your average joint: Towards precision medicine in psoriatic arthritis

Precision medicine, propelled by advances in multi-omics methods and analytics, aims to revolutionize patient care by using clinically-actionable molecular markers to guide diagnostic and therapeutic decisions. We describe the applications of precision medicine in risk stratification, drug selection, and treatment response prediction in psoriatic arthritis, for which targeted, personalized approaches are steadily emerging.

Serum MicroRNA Signature as a Diagnostic and Therapeutic Marker in Patients with Psoriatic Arthritis

OBJECTIVE

MicroRNA (miRNA) are small endogenous regulatory RNA molecules that have emerged as potential therapeutic targets and biomarkers in autoimmunity. Here, we investigated serum miRNA levels in patients with psoriatic arthritis (PsA) and further assessed a serum miRNA signature in therapeutic responder versus nonresponder PsA patients.

METHODS

Serum samples were collected from healthy controls (HC; n = 20) and PsA patients (n = 31), and clinical demographics were obtained. To examine circulatory miRNA in serum from HC and PsA patients, a focused immunology miRNA panel was analyzed utilizing a miRNA Fireplex assay (FirePlex Bioworks Inc.). MiRNA expression was further assessed in responders versus nonresponders according to the European League Against Rheumatism response criteria.

RESULTS

Six miRNA (miR-221-3p, miR-130a-3p, miR-146a-5p, miR-151-5p, miR-26a-5p, and miR-21-5p) were significantly higher in PsA compared to HC (all P < 0.05), with high specificity and sensitivity determined by receiver-operating characteristic curve analysis. Analysis of responder versus nonresponders demonstrated higher baseline levels of miR-221-3p, miR-130a-3p, miR-146a-5p, miR-151-5p, and miR-26a-5p were associated with therapeutic response.

CONCLUSION

This study identified a 6-serum microRNA signature that could be attractive candidates as noninvasive markers for PsA and may help to elucidate the disease pathogenesis.

Proteomic analysis of synovial fluid: current and potential uses to improve clinical outcomes

INTRODUCTION

Synovial fluid (SF) is in close proximity to tissues which are primarily altered during articular disease and has significant potential to better understand the underlying disease pathogeneses of articular pathologies and biomarker discovery. Although development of mass spectrometry-based methods has allowed faster and higher sensitivity techniques, interrogation of the SF proteome has been hindered by its large protein concentration dynamic range, impeding quantification of lower abundant proteins. Areas covered: Recent advances have developed methodologies to reduce the large protein concentration dynamic range of SF and subsequently allow deeper exploration of the SF proteome. This review concentrates on methods to overcome biofluid complexity, mass spectrometry proteomics methodologies, extracellular vesicles proteomics and the application of advances within the field in clinical disease, including osteoarthritis, rheumatoid arthritis, spondyloarthritis and juvenile arthritis. A narrative review was conducted with articles searched using PubMed, 1991-2018. Expert opinion: The SF proteomics field faces various challenges, including the requirement for rigorous and standardised methods of sample collection/storage, the sensitivity and specificity of proteomic assays, techniques to combat the large protein concentration dynamic range and comprehensive data analysis to reduce falsely identified markers. Additionally, there are challenges in developing multi 'omic' integration techniques, with computational integration enhancing analysis.

The use of biomarkers as a tool for novel psoriatic disease drug discovery

INTRODUCTION

Psoriatic disease is a relatively new term which encompasses psoriatic arthritis, psoriasis, and associated comorbidities. In this heterogeneous condition, the study of biomarkers is necessary to direct best therapy. Resulting in significant disability and socioeconomic burden, recent recommendations stress the need for tight control in psoriatic disease. Areas covered: The authors outline recent advances in the understanding of psoriatic disease pathogenesis which has highlighted multiple biomarkers that have been pursued as drug targets with varying degrees of success. Current drugs targeting biomarkers and therapies in development are evaluated. The methods of biomarker discovery through genomics, transcriptomics, proteomics, metabolomics, and study of the microbiome are also discussed. Expert opinion: Targeting biomarkers for therapeutic benefit appears to a promising field with multiple success stories, notably those associated with signaling through T-helper-17 cells. The use of genomics, transcriptomics, proteomics, and more recently metabolomics will help individualize targeted biomarker therapies, assist in monitoring therapeutic success, and ultimately yield novel therapeutic targets. Advances in the development of novel biologic molecules targeting more than one cytokine may offer additional gains in therapeutic response.

Exploring the Psoriatic Arthritis Proteome in Search of Novel Biomarkers

Psoriatic arthritis (PsA) is an inflammatory arthritis which develops in up to one-third of patients suffering from the cutaneous disorder, psoriasis. The complex and heterogeneous nature of PsA renders it difficult to diagnose, leading to poor outcomes and, therefore, warrants an examination into soluble biomarkers, which may facilitate early detection of the disease. Protein biomarkers are a dynamic resource of pathophysiological information able to provide an immediate reflection of pathological changes caused by disease. Investigations of the serum and synovial fluid of PsA patients has provided new insights into the molecular basis of this disease and led to the identification of sensitive diagnostic and prognostic biomarkers. The collection of novel PsA biomarkers identified through proteomic studies has been reviewed below.

Urinary proteomics can define distinct diagnostic inflammatory arthritis subgroups

Current diagnostic tests applied to inflammatory arthritis lack the necessary specificity to appropriately categorise patients. There is a need for novel approaches to classify patients with these conditions. Herein we explored whether urinary proteomic biomarkers specific for different forms of arthritis (rheumatoid arthritis (RA), psoriatic arthritis (PsA), osteoarthritis (OA)) or chronic inflammatory conditions (inflammatory bowel disease (IBD)) can be identified. Fifty subjects per group with RA, PsA, OA or IBD and 50 healthy controls were included in the study. Two-thirds of these populations were randomly selected to serve as a training set, while the remaining one-third was reserved for validation. Sequential comparison of one group to the other four enabled identification of multiple urinary peptides significantly associated with discrete pathological conditions. Classifiers for the five groups were developed and subsequently tested blind in the validation test set. Upon unblinding, the classifiers demonstrated excellent performance, with an area under the curve between 0.90 and 0.97 per group. Identification of the peptide markers pointed to dysregulation of collagen synthesis and inflammation, but also novel inflammatory markers. We conclude that urinary peptide signatures can reliably differentiate between chronic arthropathies and inflammatory conditions with discrete pathogenesis.

Contribution of Mass Spectrometry-Based Proteomics to the Understanding of TNF-α Signaling

NF-κB is a family of ubiquitous dimeric transcription factors that play a role in a myriad of cellular processes, ranging from differentiation to stress response and immunity. In inflammation, activation of NF-κB is mediated by pro-inflammatory cytokines, in particular the prototypic cytokines IL-1β and TNF-α, which trigger the activation of complex signaling cascades. In spite of decades of research, the system level understanding of TNF-α signaling is still incomplete. This is partially due to the limited knowledge at the proteome level. The objective of this review is to summarize and critically evaluate the current status of the proteomic research on TNF-α signaling. We will discuss the merits and flaws of the existing studies as well as the insights that they have generated into the proteomic landscape and architecture connected to this signaling pathway. Besides delineating past and current trends in TNF-α proteomic research, we will identify research directions and new methodologies that can further contribute to characterize the TNF-α associated proteome in space and time.