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

Proteomic biomarkers in psoriatic arthritis

Psoriasis (PsO) is a chronic inflammatory skin disease that affects 2-3% of the adult population worldwide. Psoriatic arthritis (PsA) is a chronic inflammatory arthropathy that occurs in 20-30% of PsO patients. PsA is characterized by a heterogeneous clinical phenotype that makes diagnosis and treatment challenging. Currently, diagnosis is predominantly based on clinical findings, highlighting the need for reliable biomarkers to improve diagnostic precision, refine prognostic evaluations, and guide personalized therapeutic strategies. Recent advances in proteomic methodologies have provided novel insights into the pathophysiology and diagnosis of PsA. This review synthesizes the current evidence on protein biomarkers associated with PsA, focusing on non-targeted chromatographic proteomic approaches. These methodologies can enable comprehensive analysis of diverse biological specimens, facilitating the identification of candidate proteins that could be incorporated into targeted enzymatic and immunological panels for routine clinical practice in the future. Our review identified 72 isolated proteins and one protein combination with potential diagnostic utility for PsA, with particular emphasis on biomarkers such as NAD-dependent sirtuin-2 deacetylase (SIRT2), stress-induced phosphoprotein 1 (STIP1), and thymosin β4 (TMSB4X). Despite the growing interest in proteomic approaches for PsA, additional investigations with larger, well-stratified patient cohorts are necessary to validate these findings, establish robust diagnostic biomarkers, and facilitate their clinical implementation.

Algorithms and tools for data-driven omics integration to achieve multilayer biological insights: a narrative review

Systems biology is a holistic approach to biological sciences that combines experimental and computational strategies, aimed at integrating information from different scales of biological processes to unravel pathophysiological mechanisms and behaviours. In this scenario, high-throughput technologies have been playing a major role in providing huge amounts of omics data, whose integration would offer unprecedented possibilities in gaining insights on diseases and identifying potential biomarkers. In the present review, we focus on strategies that have been applied in literature to integrate genomics, transcriptomics, proteomics, and metabolomics in the year range 2018-2024. Integration approaches were divided into three main categories: statistical-based approaches, multivariate methods, and machine learning/artificial intelligence techniques. Among them, statistical approaches (mainly based on correlation) were the ones with a slightly higher prevalence, followed by multivariate approaches, and machine learning techniques. Integrating multiple biological layers has shown great potential in uncovering molecular mechanisms, identifying putative biomarkers, and aid classification, most of the time resulting in better performances when compared to single omics analyses. However, significant challenges remain. The high-throughput nature of omics platforms introduces issues such as variable data quality, missing values, collinearity, and dimensionality. These challenges further increase when combining multiple omics datasets, as the complexity and heterogeneity of the data increase with integration. We report different strategies that have been found in literature to cope with these challenges, but some open issues still remain and should be addressed to disclose the full potential of omics integration.

The Role of Artificial Intelligence in the Diagnosis and Management of Rheumatoid Arthritis

Background and Objectives: Artificial intelligence has emerged as a transformative tool in healthcare, offering capabilities such as early diagnosis, personalised treatment, and real-time patient monitoring. In the context of rheumatoid arthritis, a chronic autoimmune disease that demands timely intervention, artificial intelligence shows promise in overcoming diagnostic delays and optimising disease management. This study examines the role of artificial intelligence in the diagnosis and management of rheumatoid arthritis, focusing on perceived benefits, challenges, and acceptance levels among healthcare professionals and patients. Materials and Methods: A cross-sectional study was conducted using a detailed questionnaire distributed to 205 participants, including rheumatologists, general practitioners, and rheumatoid arthritis patients from Romania. The study used descriptive statistics, chi-square tests, and logistic regression to analyse AI acceptance in rheumatology. Data visualisation and multiple imputations addressed missing values, ensuring accuracy. Statistical significance was set at p < 0.05 for hypothesis testing. Results: Respondents with prior experience in artificial intelligence perceived it as more useful for early diagnosis and personalised management of RA (p < 0.001). Familiarity with artificial intelligence concepts positively correlated with acceptance in routine rheumatology practice (ρ = 1.066, p < 0.001). The main barriers identified were high costs (36%), lack of medical staff training (37%), and concerns regarding diagnostic accuracy (21%). Although less frequently mentioned, data privacy concerns remained relevant for a subset of respondents. The study revealed that artificial intelligence could improve diagnostic accuracy and rheumatoid arthritis monitoring, being perceived as a valuable tool by professionals familiar with digital technologies. However, 42% of participants cited the lack of data standardisation across medical systems as a major barrier, underscoring the need for effective interoperability solutions. Conclusions: Artificial intelligence has the potential to revolutionise rheumatoid arthritis management through faster and more accurate diagnoses, personalised treatments, and optimised monitoring. Nevertheless, challenges such as costs, staff training, and data privacy need to be addressed to ensure efficient integration into clinical practice. Educational programmes and interdisciplinary collaboration are essential to increase artificial intelligence adoption in rheumatology.

Clinical, genetic and omics-based biomarkers that might support the identification of the development of psoriatic arthritis in individuals with psoriasis: a narrative review of the literature

It is known that 25%-30% of individuals with cutaneous psoriasis (PsC) will develop psoriatic arthritis (PsA). To date, the reasons for the development of PsA in individuals with PsC have not been identified. Furthermore, there are considerable delays in the diagnosis and treatment of PsA, which lead to joint and bone deformation and chronic pain. It is therefore important to develop more precise diagnostic and screening tools. In this narrative review of the literature, clinical risk factors and novel molecular biomarkers (genetic markers, blood and inflammatory markers, lipid, metabolite and protein biomarkers) have been evaluated. The review included 38 publications that were reported between May 2020 and May 2024. Similar to previous reviews, nail involvement was one of the strongest clinical risk factors for the development of PsA, while molecular biomarkers did not provide a clear and robust differentiation between PsC and PsA groups. The seemingly poor performance of molecular markers may be largely attributed to small study populations and heterogeneity in study designs. Data and sample sharing in large consortia such as HIPPOCRATES (Health initiatives in Psoriasis and PsOriatic arthritis ConsoRTium European States) could help to overcome the limitations of small studies and enable the development of more robust diagnostic and screening tools for PsA.

Proteomic Signatures of Multisystem Inflammatory Syndrome in Children (MIS-C) Associated with COVID-19: A Narrative Review

BACKGROUND/OBJECTIVES

Multisystem Inflammatory Syndrome in Children (MIS-C) is a post-infectious complication of COVID-19. MIS-C has overlapping features with other pediatric inflammatory disorders including Kawasaki Disease (KD), Macrophage Activation Syndrome (MAS), Toxic Shock Syndrome and sepsis. The exact mechanisms responsible for the clinical overlap between MIS-C and these conditions remain unclear, and biomarkers that could distinguish MIS-C from its clinical mimics are lacking. This study aimed to provide an overview of how proteomic methods, like Mass Spectrometry (MS) and affinity-based proteomics, can offer a detailed understanding of pathophysiology and aid in the diagnosis and prognosis of MIS-C.

METHODS

A narrative review of relevant studies published up to July 2024 was conducted.

RESULTS

We identified 15 studies and summarized their key proteomic findings. These studies investigated the serum or plasma proteome of MIS-C patients using MS, Proximity Extension, or Aptamer-based assays. The studies associated the proteomic profile of MIS-C with laboratory and clinical parameters and/or compared it with that of other diseases including acute COVID-19, KD, MAS, pediatric rheumatic diseases, sepsis and myocarditis or pericarditis following COVID-19 mRNA immunization. Depending on the method and the control group, different proteins were increased or decreased in the MIS-C group. The limitations and challenges in MIS-C proteomic research are also discussed, and future research recommendations are provided.

CONCLUSIONS

Although proteomics appear to be a promising approach for understanding the pathogenesis and uncovering candidate biomarkers in MIS-C, proteomic studies are still needed to recognize and validate biomarkers that could accurately discriminate MIS-C from its clinical mimics.

Early psoriatic arthritis: clinical and therapeutic challenges

INTRODUCTION

Psoriatic arthritis (PsA) is a chronic immunoinflammatory disease of the enthesis and adjacent synovium, skin, and nail, which early diagnosis may be crucial for starting a prompt therapeutic intervention. Theoretically, early treatment offers the advantage of acting on the reduction of the articular damage progression since initial phases of the disease.

AREAS COVERED

This review explores the challenges of clinical-diagnostic aspects and the underlying pathophysiology of early PsA phases, as well as the evidence evaluating the impact of early intervention on disease outcomes.

EXPERT OPINION

Main instruments for early PsA diagnosis include recognizing synovial-entheseal inflammatory signs at onset, improving screening PsA high-risk subjects, and increasing disease knowledge of physicians and patients with psoriasis or familial history. PsA continues to significantly impact on the Quality of Life of patients affected by the disease, making necessary to deeply study clinical manifestations, risk factors, and underlying immunoinflammatory mechanisms, as well as to identify biomarkers for early identification. Additionally, it remains a need to increase more evidence on understanding how early treatment of PsA and of psoriasis might influence the course of the disease.

Biomarkers of heart failure: advances in omics studies

Heart failure is a complex syndrome characterized by progressive circulatory dysfunction, manifesting clinically as pulmonary and systemic venous congestion, alongside inadequate tissue perfusion. The early identification of HF, particularly at the mild and moderate stages (stages B and C), presents a clinical challenge due to the overlap of signs, symptoms, and natriuretic peptide levels with other cardiorespiratory pathologies. Nonetheless, early detection coupled with timely pharmacological intervention is imperative for enhancing patient outcomes. Advances in high-throughput omics technologies have enabled researchers to analyze patient-derived biofluids and tissues, discovering biomarkers that are sensitive and specific for HF diagnosis. Due to the diversity of HF etiology, it is insufficient to study the diagnostic data of early HF using a single omics technology. This study reviewed the latest progress in genomics, transcriptomics, proteomics, and metabolomics for the identification of HF biomarkers, offering novel insights into the early clinical diagnosis of HF. However, the validity of biomarkers depends on the disease status, intervention time, genetic diversity and comorbidities of the subjects. Moreover, biomarkers lack generalizability in different clinical settings. Hence, it is imperative to conduct multi-center, large-scale and standardized clinical trials to enhance the diagnostic accuracy and utility of HF biomarkers.

Investigating causal associations among gut microbiota, metabolites, and psoriatic arthritis: a Mendelian randomization study

BACKGROUND

Currently, there has been observed a significant alteration in the composition of the gut microbiome (GM) and serum metabolites in patients with psoriatic arthritis (PsA) compared to healthy individuals. However, previous observational studies have shown inconsistent results regarding the alteration of gut microbiota/metabolites. In order to shed light on this matter, we utilized Mendelian randomization to determine the causal effect of GM/metabolites on PsA.

METHODS

We retrieved summary-level data of GM taxa/metabolites and PsA from publicly available GWAS statistics. Causal relationships between GM/metabolites and PsA were determined using a two-sample MR analysis, with the IVW approach serving as the primary analysis method. To ensure the robustness of our findings, we conducted sensitivity analyses, multivariable MR analysis (MVMR), and additional analysis including replication verification analysis, LDSC regression, and Steiger test analysis. Furthermore, we investigated reverse causality through a reverse MR analysis. Finally, we conducted an analysis of expression quantitative trait loci (eQTLs) involved in the metabolic pathway to explore potential molecular mechanisms of metabolism.

RESULTS

Our findings reveal that eight GM taxa and twenty-three serum metabolites are causally related to PsA (P < 0.05). Notably, a higher relative abundance of Family Rikenellaceae (ORIVW: 0.622, 95% CI: 0.438-0.883, FDR = 0.045) and elevated serum levels of X-11538 (ORIVW: 0.442, 95% CI: 0.250-0.781, FDR = 0.046) maintain significant causal associations with a reduced risk of PsA, even after adjusting for multiple testing correction and conducting MVMR analysis. These findings suggest that Family Rikenellaceae and X-11538 may have protective effects against PsA. Our sensitivity analysis and additional analysis revealed no significant horizontal pleiotropy, reverse causality, or heterogeneity. The functional enrichment analysis revealed that the eQTLs examined were primarily associated with glycerolipid metabolism and the expression of key metabolic factors influenced by bacterial infections (Vibrio cholerae and Helicobacter pylori) as well as the mTOR signaling pathway.

CONCLUSION

In conclusion, our study demonstrates that Family Rikenellaceae and X-11538 exhibit a strong and negative causal relationship with PsA. These particular GM taxa and metabolites have the potential to serve as innovative biomarkers, offering valuable insights into the treatment and prevention of PsA. Moreover, bacterial infections and mTOR-mediated activation of metabolic factors may play an important role in this process.

Chronic Pelvic Pain, Vulvar Pain Disorders, and Proteomics Profiles: New Discoveries, New Hopes

Chronic pelvic pain (CPP) is generally defined as non-cyclic pain perceived in the pelvic area that has persisted from three to six months or longer and is unrelated to pregnancy. The etiology of CPP is complex, multifactorial, with heterogeneous presentation, and includes several diseases such as endometriosis, adenomyosis, and interstitial cystitis/bladder pain syndrome. It may also be associated with sexual dysfunction, musculoskeletal disorders, and comorbid psychiatric symptoms. Vulvar pain disorders (VPDs) are typically categorized separately from chronic pelvic pain; among all VPDs, vulvodynia is a chronic vulvar pain of unknown etiology, lasting at least 3 months and that might be associated with other potentially linked factors. Proteomics represents a useful approach to study the proteome profiles of clinical samples. In this review, we have considered a selection of articles that have analyzed the protein abundance and novel protein species from various biological samples, including eutopic/ectopic endometrium, urine, serum, follicular, peritoneal fluid, and cervical mucus, potentially involved in the pathogenesis and progression of CPP and VPDs. These findings could represent valuable targets for paving the way for the differential diagnosis and therapeutic management of CPP and VDPs, thereby optimizing both the prevention and treatment of these conditions.

Management of psoriatic arthritis: a consensus opinion by expert rheumatologists

Background

Psoriatic arthritis (PsA) is a chronic inflammatory musculoskeletal disease involving several articular and extra-articular structures. Despite the important progresses recently made in all of the aspects of this disease, its management is still burdened by unresolved issues. The aim of this exercise was to provide a set of statements that may be helpful for the management of PsA.

Methods

A group of 38 Italian rheumatologists with recognized expertise in PsA selected and addressed the following four topics: "early PsA," "axial-PsA," "extra-articular manifestations and comorbidities," "therapeutic goals." Relevant articles from the literature (2016-2022) were selected by the experts based on a PubMed search. A number of statements for each topic were elaborated.

Results

Ninety-four articles were selected and evaluated, 68 out of the 1,114 yielded by the literature search and 26 added by the Authors. Each of the four topic was subdivided in themes as follows: transition from psoriasis to PsA, imaging vs. CASPAR criteria in early diagnosis, early treatment for "early PsA"; axial-PsA vs. axialspondyloarthritis, diagnosis, clinical evaluation, treatment, standard radiography vs. magnetic resonance imaging for "axial PsA"; influence of inflammatory bowel disease on the therapeutic choice, cardiovascular comorbidity, bone damage, risk of infection for "comorbidities and extra-articular manifestations"; target and tools, treat-to-target strategy, role of imaging for "therapeutic goals." The final document consisted of 49 statements.

Discussion

The final product of this exercise is a set of statements concerning the main issues of PsA management offering an expert opinion for some unmet needs of this complex disease.

Application of clinical and molecular profiling data to improve patient outcomes in psoriatic arthritis

Achieving a good outcome for a person with Psoriatic Arthritis (PsA) is made difficult by late diagnosis, heterogenous clinical disease expression and in many cases, failure to adequately suppress inflammatory disease features. Single-centre studies have certainly contributed to our understanding of disease pathogenesis, but to adequately address the major areas of unmet need, multi-partner, collaborative research programmes are now required. HIPPOCRATES is a 5-year, Innovative Medicines Initiative (IMI) programme which includes 17 European academic centres experienced in PsA research, 5 pharmaceutical industry partners, 3 small-/medium-sized industry partners and 2 patient-representative organizations. In this review, the ambitious programme of work to be undertaken by HIPPOCRATES is outlined and common approaches and challenges are identified. It is expected that, when completed, the results will ultimately allow for changes in the approaches to diagnosing, managing and treating PsA allowing for better short-term and long-term outcomes.

Association between biological immunotherapy for psoriasis and time to incident inflammatory arthritis: limitations and opportunities

Psoriatic arthritis (PsA) is a chronic inflammatory immune-mediated disease that affects approximately 30% of psoriasis patients. In most cases, skin disease clearly precedes the musculoskeletal disease. Some studies suggest that targeted treatment may intercept the disease course and prevent psoriasis patients from developing PsA. A recent population-based retrospective analysis in 15 501 psoriasis patients evaluated the association between different biological treatment strategies and time to incident inflammatory arthritis based on data in a US electronic health records database. A cumulative incidence of 2.6 PsA cases per 100 person-years was determined. The multivariable regression analysis revealed a significantly lower risk of developing inflammatory arthritis in patients who had been prescribed interleukin (IL)-12/23 or IL-23 inhibitors compared with tumour necrosis factor (TNF) inhibitor-treated patients, whereas there was no significant difference in risk for patients prescribed inhibitors of IL-17 versus TNF. Although the analysis was based on a large set of clinical data and the findings were rigorously evaluated, there are some limitations in interpretation due to the study design. Prospective clinical trials are missing, and retrospective data analyses from clinical trials or population-based studies show conflicting results. Overall, the recent data on prevention of PsA in patients with psoriasis support the high need to characterise biomarkers of increased risk and perform prospective clinical trials to give a clear guidance on possibilities for disease interception in psoriatic disease.

Managing psoriatic arthritis in different clinical scenarios

INTRODUCTION

Psoriatic arthritis (PsA) is a chronic, immune-mediated disease characterized by synovio-entheseal inflammation. It is estimated to affect around 30% of patients with psoriasis and significantly reduces patients' physical function and quality of life. There is a growing number of treatment options for PsA, but due to the heterogeneous clinical features of the disease and prevalence of comorbidities, managing PsA can be challenging.

AREAS COVERED

In this article, we review current understanding of the disease and available pharmacological options. Based on published treatment guidelines, emerging evidence and clinical experience, we provide our expert opinion on treatment strategies, taking into consideration the predominant disease domain and the presence of comorbidities, which can impact treatment decisions and clinical outcomes.

EXPERT OPINION

Biological and targeted synthetic disease-modifying agents are dramatically improving the lives of patients with PsA. Biosimilar TNF inhibitors offer a particularly versatile and cost-effective option, whilst newer biologics and targeted synthetic molecules that can be used to treat most domains of psoriatic disease are an attractive alternative to TNF inhibitors. Despite a lack of consensus on treatment sequencing and tapering, it is important that PsA patients, especially those with comorbidities, are looked after by a multidisciplinary team to optimize their care.

Clinical Blood Metabogram: Application to Overweight and Obese Patients

Recently, the concept of a mass spectrometric blood metabogram was introduced, which allows the analysis of the blood metabolome in terms of the time, cost, and reproducibility of clinical laboratory tests. It was demonstrated that the components of the metabogram are related groups of the blood metabolites associated with humoral regulation; the metabolism of lipids, carbohydrates, and amines; lipid intake into the organism; and liver function, thereby providing clinically relevant information. The purpose of this work was to evaluate the relevance of using the metabogram in a disease. To do this, the metabogram was used to analyze patients with various degrees of metabolic alterations associated with obesity. The study involved 20 healthy individuals, 20 overweight individuals, and 60 individuals with class 1, 2, or 3 obesity. The results showed that the metabogram revealed obesity-associated metabolic alterations, including changes in the blood levels of steroids, amino acids, fatty acids, and phospholipids, which are consistent with the available scientific data to date. Therefore, the metabogram allows testing of metabolically unhealthy overweight or obese patients, providing both a general overview of their metabolic alterations and detailing their individual characteristics. It was concluded that the metabogram is an accurate and clinically applicable test for assessing an individual's metabolic status in disease.

Psoriatic Arthritis: Pathogenesis and Targeted Therapies

Psoriatic arthritis (PsA), a heterogeneous chronic inflammatory immune-mediated disease characterized by musculoskeletal inflammation (arthritis, enthesitis, spondylitis, and dactylitis), generally occurs in patients with psoriasis. PsA is also associated with uveitis and inflammatory bowel disease (Crohn's disease and ulcerative colitis). To capture these manifestations as well as the associated comorbidities, and to recognize their underlining common pathogenesis, the name of psoriatic disease was coined. The pathogenesis of PsA is complex and multifaceted, with an interplay of genetic predisposition, triggering environmental factors, and activation of the innate and adaptive immune system, although autoinflammation has also been implicated. Research has identified several immune-inflammatory pathways defined by cytokines (IL-23/IL-17, TNF), leading to the development of efficacious therapeutic targets. However, heterogeneous responses to these drugs occur in different patients and in the different tissues involved, resulting in a challenge to the global management of the disease. Therefore, more translational research is necessary in order to identify new targets and improve current disease outcomes. Hopefully, this may become a reality through the integration of different omics technologies that allow better understanding of the relevant cellular and molecular players of the different tissues and manifestations of the disease. In this narrative review, we aim to provide an updated overview of the pathophysiology, including the latest findings from multiomics studies, and to describe current targeted therapies.

The vitamin D receptor gene polymorphism rs1544410 T/T genotype as a predictor of factor vitamin D thresholds deficiency in patients with psoriasis vulgaris-A preliminary study

BACKGROUND

Many clinical features of psoriasis include a rash with itchy, scaly patches, most frequently on the knees, elbows, trunk, and scalp. By studying genes involved with psoriasis receptivity, the pathologic pathways of psoriasis become clearer and more understood.

AIM

To predict the participation of rs1544410 in serum vitamin D levels (SDL) in psoriasis, psoriasis susceptibility, and severity.

PATIENTS/METHODS

One hundred five patients with psoriasis were categorized by body surface area as mild, moderate, and severe. SDL and genetic analysis of rs1544410 were performed using polymerase chain reaction and standard Sanger methods.

RESULT

Our findings revealed that SDL were higher in healthy subjects than in patients. The rs1544410 genotype TT was more prevalent in patients, while CT was more prevalent in controls. Our findings revealed that the T alleles were frequently more in the patient group than in the controls. (p ≤ 0.001). While in healthy normal individuals, the C alleles were frequently more (p ≤ 0.001). SDL are lower in patients with the TT genotype. Patients with moderate form of psoriasis have higher SDL than those with mild or severe form.

CONCLUSION

rs1544410 polymorphism has been linked to a higher probability of psoriasis and SDL deficiency. However, grander scale studies in a larger number of people are necessary.

Current State and Future Perspectives on Personalized Metabolomics

Metabolomics is one of the most promising 'omics' sciences for the implementation in medicine by developing new diagnostic tests and optimizing drug therapy. Since in metabolomics, the end products of the biochemical processes in an organism are studied, which are under the influence of both genetic and environmental factors, the metabolomics analysis can detect any changes associated with both lifestyle and pathological processes. Almost every case-controlled metabolomics study shows a high diagnostic accuracy. Taking into account that metabolomics processes are already described for most nosologies, there are prerequisites that a high-speed and comprehensive metabolite analysis will replace, in near future, the narrow range of chemical analyses used today, by the medical community. However, despite the promising perspectives of personalized metabolomics, there are currently no FDA-approved metabolomics tests. The well-known problem of complexity of personalized metabolomics data analysis and their interpretation for the end-users, in addition to a traditional need for analytical methods to address the quality control, standardization, and data treatment are reported in the review. Possible ways to solve the problems and change the situation with the introduction of metabolomics tests into clinical practice, are also discussed.