Urinary proteomics can define distinct diagnostic inflammatory arthritis subgroups

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.

Progress in multi-omics studies of osteoarthritis

Osteoarthritis (OA), a ubiquitous degenerative joint disorder, is marked by pain and disability, profoundly impacting patients' quality of life. As the population ages, the global prevalence of OA is escalating. Omics technologies have become instrumental in investigating complex diseases like OA, offering comprehensive insights into its pathogenesis and progression by uncovering disease-specific alterations across genomics, transcriptomics, proteomics, and metabolomics levels. In this review, we systematically analyzed and summarized the application and recent achievements of omics technologies in OA research by scouring relevant literature in databases such as PubMed. These studies have shed light on new potential therapeutic targets and biomarkers, charting fresh avenues for OA diagnosis and treatment. Furthermore, in our discussion, we highlighted the immense potential of spatial omics technologies in unraveling the molecular mechanisms of OA and in the development of novel therapeutic strategies, proposing future research directions and challenges. Collectively, this study encapsulates the pivotal advances in current OA research and prospects for future investigation, providing invaluable references for a deeper understanding and treatment of OA. This review aims to synthesize the recent progress of omics technologies in the realm of OA, aspiring to furnish theoretical foundations and research orientations for more profound studies of OA in the future.

Proteomics appending a complementary dimension to precision oncotherapy

Recent advances in high-throughput proteomic profiling technologies have facilitated the precise quantification of numerous proteins across multiple specimens concurrently. Researchers have the opportunity to comprehensively analyze the molecular signatures in plentiful medical specimens or disease pattern cell lines. Along with advances in data analysis and integration, proteomics data could be efficiently consolidated and employed to recognize precise elementary molecular mechanisms and decode individual biomarkers, guiding the precision treatment of tumors. Herein, we review a broad array of proteomics technologies and the progress and methods for the integration of proteomics data and further discuss how to better merge proteomics in precision medicine and clinical settings.

Quantitative urinary proteome analysis reveals potential biomarkers for disease activity of Behcet's disease uveitis

PURPOSE

Behçet's disease-associated uveitis (BDU) is a severe, recurrent inflammatory condition affecting the eye and is part of a systemic vasculitis with unknown etiology, making biomarker discovery essential for disease management. In this study, we intend to investigate potential urinary biomarkers to monitor the disease activity of BDU.

METHODS

Firstly, label-free data-dependent acquisition (DDA) and tandem mass tag (TMT)-labeled quantitative proteomics methods were used to profile the proteomes of urine from active and quiescent BDU patients, respectively. For further exploration, the remaining fifty urine samples were analyzed by a data-independent acquisition (DIA) quantitative proteomics method.

RESULTS

Twenty-nine and 21 differential proteins were identified in the same urine from BDU patients by label-free DDA and TMT-labeled analyses, respectively. Seventy-nine differentially expressed proteins (DEPs) were significantly changed in other active BDU urine samples compared to those in quiescent BDU urine samples by IDA analysis. Gene Ontology (GO) and protein-protein interaction (PPI) analyses revealed that the DEPs were associated with multiple functions, including the immune and neutrophil activation responses. Finally, seven proteins were identified as candidate biomarkers for BDU monitoring and recurrence prediction, namely, CD38, KCRB, DPP4, FUCA2, MTPN, S100A8 and S100A9.

CONCLUSIONS

Our results showed that urine can be a good source of biomarkers for BDU. These dysregulated proteins provide potential urinary biomarkers for BDU activity monitoring and provide valuable clues for the analysis of the pathogenic mechanisms of BDU.

Recent progress in mass spectrometry-based urinary proteomics

Serum or plasma is frequently utilized in biomedical research; however, its application is impeded by the requirement for invasive sample collection. The non-invasive nature of urine collection makes it an attractive alternative for disease characterization and biomarker discovery. Mass spectrometry-based protein profiling of urine has led to the discovery of several disease-associated biomarkers. Proteomic analysis of urine has not only been applied to disorders of the kidney and urinary bladder but also to conditions affecting distant organs because proteins excreted in the urine originate from multiple organs. This review provides a progress update on urinary proteomics carried out over the past decade. Studies summarized in this review have expanded the catalog of proteins detected in the urine in a variety of clinical conditions. The wide range of applications of urine analysis-from characterizing diseases to discovering predictive, diagnostic and prognostic markers-continues to drive investigations of the urinary proteome.

Systematic Review: Urine Biomarker Discovery for Inflammatory Bowel Disease Diagnosis

Inflammatory bowel diseases (IBDs) are chronic, heterogeneous, and inflammatory conditions mainly affecting the gastrointestinal tract. Currently, endoscopy is the gold standard test for assessing mucosal activity and healing in clinical practice; however, it is a costly, time-consuming, invasive, and uncomfortable procedure for the patients. Therefore, there is an urgent need for sensitive, specific, fast and non-invasive biomarkers for the diagnosis of IBD in medical research. Urine is an excellent biofluid for discovering biomarkers because it is non-invasive to sample. In this review, we aimed to summarize proteomics and metabolomics studies performed in both animal models of IBD and humans that identify urinary biomarkers for IBD diagnosis. Future large-scale multi-omics studies should be conducted in collaboration with clinicians, researchers, and industry to make progress toward the development of sensitive and specific diagnostic biomarkers, thereby making personalized medicine possible.

Psoriasis to Psoriatic Arthritis: The Application of Proteomics Technologies

Psoriatic disease (PsD) is a spectrum of diseases that affect both skin [cutaneous psoriasis (PsC)] and musculoskeletal features [psoriatic arthritis (PsA)]. A considerable number of patients with PsC have asymptomatic synovio-entheseal inflammations, and approximately one-third of those eventually progress to PsA with an enigmatic mechanism. Published studies have shown that early interventions to the very early-stage PsA would effectively prevent substantial bone destructions or deformities, suggesting an unmet goal for exploring early PsA biomarkers. The emergence of proteomics technologies brings a complete view of all involved proteins in PsA transitions, offers a unique chance to map all potential peptides, and allows a direct head-to-head comparison of interaction pathways in PsC and PsA. This review summarized the latest development of proteomics technologies, highlighted its application in PsA biomarker discovery, and discussed the possible clinical detectable PsA risk factors in patients with PsC.

Quantitative Proteomic Analysis of Synovial Tissue Reveals That Upregulated OLFM4 Aggravates Inflammation in Rheumatoid Arthritis

Tandem mass tag (TMT)-coupled liquid chromatography coupled with tandem mass spectrometry is a powerful method to investigate synovial tissue protein profiles in patients with rheumatoid arthritis (RA) and osteoarthritis (OA). Protein was isolated from synovial tissue samples of 22 patients and labeled with a TMT kit. Over 500 proteins were identified as the differential expression protein on comparing RA and OA synovial tissue, including 239 upregulated and 271 downregulated proteins. Data are available via ProteomeXchange with identifier PXD027703. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis showed that the majority participated in the developmental processes and protein processing in the endoplasmic reticulum. Olfactomedin 4 (OLFM4), a secreted glycoprotein, in joint inflammation of RA was explored. OLFM4 was upregulated in RA synovial tissue samples. In fibroblast-like synoviocytes (FLS), inflammation cytokines, TNF-α, interleukin (IL)-1β, and LPS can upregulate OLFM4. After OLFM4 knockdown under TNF-α stimulation, RA FLS proliferation was inhibited and the expression of CXCL9, CXCL11, and MMP-1 was decreased. Overall, the RA synovial tissue protein expression profile by proteomic analysis shows some unique targets in RA pathophysiology, and OLFM4 in FLS plays an important role in RA joint inflammation. OLFM4 can be a promising therapeutic target in RA synovial tissue.

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.

Proteomic Biomarkers in the Cardiorenal Syndrome: Toward Deciphering Molecular Pathophysiology

Cardiorenal syndrome (CRS) is defined by coexisting heart and renal dysfunctions. Malfunction of 1 organ may cause dysfunction of the other with variable causative disease that defines the type of CRS (1-5). Numerous studies showed that the prevalence of cardiovascular disease is increased in patients with chronic kidney disease (CKD). Similarly, CKD affects a large proportion of patients with heart failure. This overlap between primary heart or primary kidney disease blurs cause-effect inferences of the initiator/target organ. The classical subdivision of CRS in 5 categories does not provide pathophysiological suggestions for targeted intervention. It seems timely to revisit the value of CRS biomarkers in a pathophysiology-centered approach. We systematically reviewed the literature in CRS, which revealed 53 clinical studies describing the use of 44 biomarkers and 4 proteomic panels. All biomarkers are involved in at least one of the CRS comorbidities. Among the pathways affected, inflammation, aberrant glucose metabolism, neurohormonal activation, and oxidative stress are well described. There is growing evidence that fibrosis may be the "cornerstone" that unifies most of the pathways leading to CRS. Formation of excess fibrous connective tissue antedates CRS in many cases. This review highlights that biomarkers reflecting fibrosis may be of substantial clinical value in the early detection, prognostication, and guiding treatment of CRS. Biomarkers detecting changes in collagen turnover in the extracellular matrix of heart and kidney appear able to depict subclinical changes in the fibrotic remodeling of tissues and constitute a promising approach toward personalized intervention in CRS.

Identification and Evaluation of Serum Protein Biomarkers Which Differentiate Psoriatic from Rheumatoid Arthritis

OBJECTIVES

To identify serum protein biomarkers which might separate early inflammatory arthritis (EIA) patients with psoriatic arthritis (PsA) from those with rheumatoid arthritis (RA) and may be used to support appropriate early intervention.

METHODS

The serum proteome of patients with PsA and RA was interrogated using nano-flow liquid chromatography mass spectrometry (nLC-MS/MS) (n=64 patients), an aptamer-based assay (SOMAscan) targeting 1,129 proteins (n=36 patients) and a multiplexed antibody assay (Luminex) for 48 proteins (n=64 patients). Multiple reaction monitoring assays (MRM) were developed to evaluate the performance of putative markers using the discovery cohort (n=60) and subsequently an independent cohort of PsA and RA patients (n=167).

RESULTS

Multivariate machine learning analysis of the protein discovery data from the three platforms revealed that it was possible to discriminate PsA from RA patients with an area under the curve (AUC) of 0.94 for nLC-MS/MS, 0.69 for bead based immunoassay measurements and 0.73 for aptamer based analysis. Subsequently in the separate verification and evaluation studies, random forest models revealed that a subset of proteins measured by MRM could differentiate PsA and RA patients with AUCs of 0.79 and 0.85 respectively.

CONCLUSION

We report a serum protein biomarker panel which can separate EIA patients with PsA from those with RA. With continued evaluation and refinement using additional and larger patient cohorts including those with other arthropathies we suggest the panel identified here could contribute toward improved clinical decision making.

Bioinformatic Analysis of the Wound Peptidome Reveals Potential Biomarkers and Antimicrobial Peptides

Wound infection is a common and serious medical condition with an unmet need for improved diagnostic tools. A peptidomic approach, aided by mass spectrometry and bioinformatics, could provide novel means of identifying new peptide biomarkers for wound healing and infection assessment. Wound fluid is suitable for peptidomic analysis since it is both intimately tied to the wound environment and is readily available. In this study we investigate the peptidomes of wound fluids derived from surgical drainages following mastectomy and from wound dressings following facial skin grafting. By applying sorting algorithms and open source third party software to peptidomic label free tandem mass spectrometry data we provide an unbiased general methodology for analyzing and differentiating between peptidomes. We show that the wound fluid peptidomes of patients are highly individualized. However, differences emerge when grouping the patients depending on wound type. Furthermore, the abundance of peptides originating from documented antimicrobial regions of hemoglobin in infected wounds may contribute to an antimicrobial wound environment, as determined by in silico analysis. We validate our findings by compiling literature on peptide biomarkers and peptides of physiological significance and cross checking the results against our dataset, demonstrating that well-documented peptides of immunological significance are abundant in infected wounds, and originate from certain distinct regions in proteins such as hemoglobin and fibrinogen. Ultimately, we have demonstrated the power using sorting algorithms and open source software to help yield insights and visualize peptidomic data.

Urinary Proteomics Associates with COVID-19 Severity: Pilot Proof-of-Principle Data and Design of a Multicentric Diagnostic Study

SARS-CoV-2 infection results in a mild-to-moderate disease course in most patients, allowing outpatient self-care and quarantine. However, in approx. 10% of cases a two- or three-phasic critical disease course with starting from day 7 to 10 is observed. To facilitate and plan outpatient care, biomarkers prognosing such worsening at an early stage appear of outmost importance. In this accelerated article, we report on the identification of urinary peptides significantly associated with SARS-CoV-2 infection, and the development of a multi-marker urinary peptide based test, COVID20, that may enable prognosis of critical and fatal outcomes in COVID-19 patients. COVID20 is composed of 20 endogenous peptides mainly derived from various collagen chains that enable differentiating moderate or severe disease from critical state or death with 83% sensitivity at 100% specificity. Based on the performance in this pilot study, testing in a prospective study on 1000 patients has been initiated. This article is protected by copyright. All rights reserved.

Bile and urine peptide marker profiles: access keys to molecular pathways and biological processes in cholangiocarcinoma

Background

Detection of cholangiocarcinoma (CCA) remains a diagnostic challenge. We established diagnostic peptide biomarkers in bile and urine based on capillary electrophoresis coupled to mass spectrometry (CE-MS) to detect both local and systemic changes during CCA progression. In a prospective cohort study we recently demonstrated that combined bile and urine proteome analysis could further improve diagnostic accuracy of CCA diagnosis in patients with unknown biliary strictures. As a continuation of these investigations, the aim of the present study was to investigate the pathophysiological mechanisms behind the molecular determinants reflected by bile and urine peptide biomarkers.

Methods

Protease mapping and gene ontology cluster analysis were performed for the previously defined CE-MS based biomarkers in bile and urine. For that purpose, bile and urine peptide profiles (from samples both collected at the date of endoscopy) were investigated from a representative cohort of patients with benign (n = 76) or CCA-associated (n = 52) biliary strictures (verified during clinical follow-up). This was supplemented with a literature search for the association of the individual biomarkers included in the proteomic patterns with CCA or cancer progression.

Results

For most of the peptide markers, association to CCA has been described in literature. Protease mapping revealed ADAMTS4 activity in cleavage of both bile and urine CCA peptide biomarkers. Furthermore, increased chymase activity in bile points to mast cell activation at the tumor site. Gene ontology cluster analysis indicates cellular response to chemical stimuli and stress response as local and extracellular matrix reorganization by tissue destruction and repair as systemic events. The analysis further supports that the mapped proteases are drivers of local and systemic events.

Conclusions

The study supports connection of the CCA-associated peptide biomarkers to the molecular pathophysiology and indicates an involvement in epithelial-to-mesenchymal transition, generation of cancer-associated fibroblasts and activation of residual immune cells. Proteases, extracellular matrix components, inflammatory cytokines, proangiogenic, growth and vasoactive factors released from the tumor microenvironment are drivers of systemic early events during CCA progression.

Proteomics and phosphoproteomics in precision medicine: applications and challenges

Recent advances in proteomics allow the accurate measurement of abundances for thousands of proteins and phosphoproteins from multiple samples in parallel. Therefore, for the first time, we have the opportunity to measure the proteomic profiles of thousands of patient samples or disease model cell lines in a systematic way, to identify the precise underlying molecular mechanism and discover personalized biomarkers, networks and treatments. Here, we review examples of successful use of proteomics and phosphoproteomics data sets in as well as their integration other omics data sets with the aim of precision medicine. We will discuss the bioinformatics challenges posed by the generation, analysis and integration of such large data sets and present potential reasons why proteomics profiling and biomarkers are not currently widely used in the clinical setting. We will finally discuss ways to contribute to the better use of proteomics data in precision medicine and the clinical setting.

Proteomic profiling of urine: implications for lupus nephritis

INTRODUCTION

Lupus nephritis (LN) is a common and significant manifestation, affecting 60% of adults and 80% of children with systemic lupus erythematosus, with up to 30% of patients progressing to end stage renal disease. There remains an unmet need for non-invasive markers of disease activity, damage, and response to therapy. In addition, non-invasive biomarkers that predict therapeutic efficacy are needed to enable cost-effective clinical trials of novel agents. Areas covered: This review examines the methodological aspects of urinary proteomics, the role of proteome profiling in identifying promising urinary biomarkers in LN, and the translation of research findings into clinically useful tools in the management of LN. Expert opinion: Targeted and unbiased proteomics have identified several promising urinary biomarkers that predict LN activity, damage (chronicity), and response to therapy. In particular, a combination of biologically plausible urinary biomarkers termed as RAIL (Renal Activity Index for Lupus) has emerged as an excellent predictor of LN activity as well as response to therapy, being able to predict efficacy within 3 months of therapy. If validated in additional large prospective studies, the RAIL biomarkers will transform the care of patients with LN, allowing for a personalized and predictive approach and improved outcomes.

Potential candidate biomarkers associated with osteoarthritis: Evidence from a comprehensive network and pathway analysis

Osteoarthritis (OA) is one of the most common forms of arthritis world widely. Some key genes and diagnostic markers have been reported due to the development of modern molecular biology technologies. However, the etiology and pathogenesis of OA remains unknown. In this study, an integrated network and pathway analysis towards the biological function of OA-associated genes was conducted to provide valuable information to further explore the etiology and pathogenesis of OA. A total of 2,548 genes which reported a statistically significant association with OA were screened. An integrated network and pathway analysis was performed to identify the pathways and genes most associated to OA. Moreover, OA-specific protein-protein interaction (PPI) network was constructed by cytocluster based on the Molecular Complex Detection Algorithm (MCODE) to screen its candidate biomarkers. Quantitative real-time polymerase chain reaction was used to confirm the expression levels and to validate the results of MCODE cluster analysis by six genes. The pathway networks suggested that extracellular matrix (ECM) organization, collagen degradation and collagen formation showed important associations with OA. In top two PPI clusters, 61 of the OA-associated genes were included in the OA-specific PPI network, which also included 23 candidate genes that are likely to be highly associated with OA based on MCODE clusters. Analysis of mRNA showed that the expression levels of COL9A1, COL9A2, ITGA3, COL9A3, ITGA2, and LAMA1 in the peripheral blood mononuclear cells of OA patients were significantly lower than those of the normal controls (p<0.005). To our knowledge, this is the first comprehensive and systematic report based on OA-related genes demonstrating that the functional destruction of collagen in cartilage may be a very important contributing factor to OA. Quantitative detection of collagen synthesis may be of great help in early identification and prediction of OA. Maintaining the quality and quantity of collagen can be a potential target for clinical treatment of OA in the future practice.

Molecular Network Analysis of the Urinary Proteome of Alzheimer's Disease Patients

Background/Aims

The identification of predictive biomarkers for Alzheimer's disease (AD) from urine would aid in screening for the disease, but information about biological and pathophysiological changes in the urine of AD patients is limited. This study aimed to explore the comprehensive profile and molecular network relations of urinary proteins in AD patients.

Methods

Urine samples collected from 18 AD patients and 18 age- and sex-matched cognitively normal controls were analyzed by mass spectrometry and semiquantified with the normalized spectral index method. Bioinformatics analyses were performed on proteins which significantly increased by more than 2-fold or decreased by less than 0.5-fold compared to the control (p < 0.05) using DAVID bioinformatics resources and KeyMolnet software.

Results

The levels of 109 proteins significantly differed between AD patients and controls. Among these, annotation clusters related to lysosomes, complement activation, and gluconeogenesis were significantly enriched. The molecular relation networks derived from these proteins were mainly associated with pathways of lipoprotein metabolism, heat shock protein 90 signaling, matrix metalloproteinase signaling, and redox regulation by thioredoxin.

Conclusion

Our findings suggest that changes in the urinary proteome of AD patients reflect systemic changes related to AD pathophysiology.

Soluble biochemical markers of osteoarthritis: Are we close to using them in clinical practice?

Osteoarthritis (OA) is the most common form of arthritis and a major cause of pain and disability. Recent work suggests that the global burden of OA is increasing, and costs associated with treatment are expected to increase dramatically as the aging human population expands. OA is currently diagnosed using radiography, but this technique is an indirect and insensitive measure of alterations in articular cartilage and fails to measure dynamic inflammatory processes in the joint. Radiographic changes detected overtime are small and occur in only a subset (progressors) of patients with OA. Therefore, we diagnose patients with OA on the basis of a diagnostic classification that is outdated. We also use the same tools and approaches for assessing the efficacy of new pharmacological and nonpharmacological interventions. In this review, we discuss the utility of soluble biochemical markers as biomarkers of OA and discuss whether we are close to using them in clinical practice. Combining patient information, functional imaging and carefully selected panels of biomarkers can help in achieving enhanced patient stratification and lead to better designed clinical trials. Biomarkers can be used for molecular endotyping and for developing more effective and more personalized treatments that will enhance clinical care for patients with OA.

Reprint of: Proteomics in cardiovascular diseases: Unveiling sex and gender differences in the era of precision medicine

Cardiovascular diseases (CVDs) represent the most important cause of mortality in women and in men. Contrary to the long-standing notion that the effects of the major risk factors on CVD outcomes are the same in both sexes, recent evidence recognizes new, potentially independent, sex/gender-related risk factors for CVDs, and sex/gender-differences in the clinical presentation of CVDs have been demonstrated. Furthermore, some therapeutic options may not be equally effective and safe in men and women. In this context, proteomics offers an extremely useful and versatile analytical platform for biomedical researches that expand from the screening of early diagnostic and prognostic biomarkers to the investigation of the molecular mechanisms underlying CDVs. In this review, we summarized the current applications of proteomics in the cardiovascular field, with emphasis on sex and gender-related differences in CVDs.

SIGNIFICANCE

Increasing evidence supports the profound effect of sex and gender on cardiovascular physio-pathology and the response to drugs. A clear understanding of the mechanisms underlying sexual dimorphisms in CVDs would not only improve our knowledge of the etiology of these diseases, but could also inform health policy makers and guideline committees in tailoring specific interventions for the prevention, treatment and management of CVDs in both men and women.

Osteoarthritis biomarkers: year in review

OBJECTIVE

To summarise important findings from biomarker studies relevant to osteoarthritis (OA), published between April 2016 and March 2017; to consider these findings in the context of new discoveries and technologies, and clinical and scientific need in OA.

DESIGN

Studies were selected by PubMed search, conducted between 01/04/2016 and 01/03/2017. MeSH terms [biomarker] AND [OA] were used; the search was restricted to Human, English language and Full Text Available publications, which yielded 50 eligible publications. Any biomarker was considered, including non-proteins and other clinical measurements.

RESULTS

Three main areas are overviewed: 1) Studies examining highly validated biomarkers, in the FNIH OA Biomarkers Consortium and elsewhere, particularly their ongoing application and validation. Control reference intervals, work on predictive validity and other longitudinal studies examining prognostic value of biomarkers in large cohorts are reviewed. 2) Novel studies relating to biomarkers of inflammation are discussed, including complement, the performance of markers of so-called 'cold inflammation' and results from clinical trials including biomarkers. 3) Discovery studies, including whole blood RNA, proteomics and metabolomics are reviewed, with an emphasis on new technologies.

CONCLUSIONS

Discovery, characterisation and qualification of various biomarkers is ongoing; several novel protein and non-protein candidate biomarkers have been reported this year. Biomarkers provide us with an opportunity to better diagnose and stratify the disease, via established panels or new discovery approaches. Improving quality of sampling and testing, and measuring large numbers of markers simultaneously in large cohorts would seem likely to identify new clinically applicable biomarkers, which are still much needed in this disease.

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.

Proteomics in cardiovascular diseases: Unveiling sex and gender differences in the era of precision medicine

Cardiovascular diseases (CVDs) represent the most important cause of mortality in women and in men. Contrary to the long-standing notion that the effects of the major risk factors on CVD outcomes are the same in both sexes, recent evidence recognizes new, potentially independent, sex/gender-related risk factors for CVDs, and sex/gender-differences in the clinical presentation of CVDs have been demonstrated. Furthermore, some therapeutic options may not be equally effective and safe in men and women. In this context, proteomics offers an extremely useful and versatile analytical platform for biomedical researches that expand from the screening of early diagnostic and prognostic biomarkers to the investigation of the molecular mechanisms underlying CDVs. In this review, we summarized the current applications of proteomics in the cardiovascular field, with emphasis on sex and gender-related differences in CVDs.

SIGNIFICANCE

Increasing evidence supports the profound effect of sex and gender on cardiovascular physio-pathology and the response to drugs. A clear understanding of the mechanisms underlying sexual dimorphisms in CVDs would not only improve our knowledge of the etiology of these diseases, but could also inform health policy makers and guideline committees in tailoring specific interventions for the prevention, treatment and management of CVDs in both men and women.

Pathogenetic insights from the treatment of rheumatoid arthritis

Rheumatoid arthritis is a chronic autoimmune disease that causes progressive articular damage, functional loss, and comorbidity. The development of effective biologics and small-molecule kinase inhibitors in the past two decades has substantially improved clinical outcomes. Just as understanding of pathogenesis has led in large part to the development of drugs, so have mode-of-action studies of these specific immune-targeted agents revealed which immune pathways drive articular inflammation and related comorbidities. Cytokine inhibitors have definitively proven a critical role for tumour necrosis factor α and interleukin 6 in disease pathogenesis and possibly also for granulocyte-macrophage colony-stimulating factor. More recently, clinical trials with Janus kinase (JAK) inhibitors have shown that cytokine receptors that signal through the JAK/STAT signalling pathway are important for disease, informing the pathogenetic function of additional cytokines (such as the interferons). Finally, successful use of costimulatory blockade and B-cell depletion in the clinic has revealed that the adaptive immune response and the downstream events initiated by these cells participate directly in synovial inflammation. Taken together, it becomes apparent that understanding the effects of specific immune interventions can elucidate definitive molecular or cellular nodes that are essential to maintain complex inflammatory networks that subserve diseases like rheumatoid arthritis.