Quantitative tandem mass-spectrometry of skin tissue reveals putative psoriatic arthritis biomarkers

Differences between psoriatic arthritis and psoriasis in multi-omics

We aim to systemically review the genomics, transcriptomics, epigenetics, proteomics, metabonomics and microbiota of psoriatic arthritis and psoriasis, illustrating the differences of these two diseases, broadening our understanding of the pathogenesis of them and providing important clues for valuable biomarkers of earlier diagnosis and treatments. To our knowledge, this is the first study that combine all omics studies from genomics to microbiota and may serve as a reference for future studies to identify the key underlying pathways in psoriatic arthritis.

Differences in transcriptional changes in psoriasis and psoriatic arthritis skin with immunoglobulin gene enrichment in psoriatic arthritis

OBJECTIVES

Approximately 20% of people with psoriasis develop PsA. Although genetic, clinical and environmental risk factors have been identified, it is not known why some people with psoriasis develop PsA. The skin disease is traditionally considered the same in both. This study compares transcriptional changes in psoriasis and PsA skin for the first time.

METHODS

Skin biopsies were collected from healthy controls (HC), and uninvolved and lesional skin from patients with PsA. Bulk tissue sequencing was performed and analysed using the pipeline Searchlight 2.0. Transcriptional changes in PsA skin were compared with existing sequencing data from participants with psoriasis without PsA (GSE121212). Psoriasis and PsA datasets could not be directly compared as different analysis methods were used. Data from participants with PsA in the GSE121212 dataset were used for validation.

RESULTS

Skin samples from 9 participants with PsA and 9 HC were sequenced, analysed and compared with available transcriptomic data for 16 participants with psoriasis compared with 16 HC. Uninvolved skin in psoriasis shared transcriptional changes with lesional skin in psoriasis, but uninvolved skin in PsA did not. Most transcriptional changes in psoriasis and PsA lesional skin were shared, but immunoglobulin genes were upregulated in PsA lesional skin specifically. The transcription factor POU2F1, which regulates immunoglobulin gene expression, was enriched in PsA lesional skin. This was confirmed in the validation cohort.

CONCLUSIONS

Immunoglobulin genes are upregulated in PsA but not in psoriasis skin lesions. This may have implications for the spread from the cutaneous compartment to other tissues.

Investigating the gut microbiota's influence on psoriasis and psoriatic arthritis risk: a Mendelian randomization analysis

Background

Numerous investigations have revealed the interplay between gut microbiota (GM) and psoriasis (Ps) and psoriatic arthritis (PsA). However, the causal relationship between them remains unknown.

Methods

We curated a collection of genetic variants (P < 1 × 10-5) associated with GM (n = 18 340) derived from the MiBioGen study. To explore the intricate relationship between GM and Ps as well as PsA, we harnessed the comprehensive resources of the FinnGen database, encompassing a vast cohort of individuals, including 4510 Ps cases and 212 242 controls and 1637 PsA cases and 212 242 controls. Mendelian randomization (MR) was used, including an inverse variance weighting method, followed by a sensitivity analysis to verify the robustness of the results.

Results

For Ps, some bacterial taxa, including Lactococcus, Ruminiclostridium 5, and Eubacterium fissicatena, were identified as risk factors; but Odoribacter demonstrated a protective effect against Ps. In the case of PsA, Lactococcus, Verrucomicrobiales, Akkermansia, Coprococcus 1, and Verrucomicrobiaceae were identified as risk factors; Odoribacter and Rikenellaceae exhibited a protective effect against the development of PsA.

Conclusion

Our study establishes a causal link between the GM and Ps and PsA. These findings provide insights into the underlying mechanisms and suggest potential therapeutic targets.

Construction of a fecal immune-related protein-based biomarker panel for colorectal cancer diagnosis: a multicenter study

Purpose

To explore fecal immune-related proteins that can be used for colorectal cancer (CRC) diagnosis.

Patients and methods

Three independent cohorts were used in present study. In the discovery cohort, which included 14 CRC patients and 6 healthy controls (HCs), label-free proteomics was applied to identify immune-related proteins in stool that could be used for CRC diagnosis. Exploring potential links between gut microbes and immune-related proteins by 16S rRNA sequencing. The abundance of fecal immune-associated proteins was verified by ELISA in two independent validation cohorts and a biomarker panel was constructed that could be used for CRC diagnosis. The validation cohort I included 192 CRC patients and 151 HCs from 6 different hospitals. The validation cohort II included 141 CRC patients, 82 colorectal adenoma (CRA) patients, and 87 HCs from another hospital. Finally, the expression of biomarkers in cancer tissues was verified by immunohistochemistry (IHC).

Results

In the discovery study, 436 plausible fecal proteins were identified. And among 67 differential fecal proteins (|log2 fold change| > 1, P< 0.01) that could be used for CRC diagnosis, 16 immune-related proteins with diagnostic value were identified. The 16S rRNA sequencing results showed a positive correlation between immune-related proteins and the abundance of oncogenic bacteria. In the validation cohort I, a biomarker panel consisting of five fecal immune-related proteins (CAT, LTF, MMP9, RBP4, and SERPINA3) was constructed based on the least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression. The biomarker panel was found to be superior to hemoglobin in the diagnosis of CRC in both validation cohort I and validation cohort II. The IHC result showed that protein expression levels of these five immune-related proteins were significantly higher in CRC tissue than in normal colorectal tissue.

Conclusion

A novel biomarker panel consisting of fecal immune-related proteins can be used for the diagnosis of CRC.

Cutaneous lesions in psoriatic arthritis are enriched in chemokine transcriptomic pathways

OBJECTIVES

Skin from people with psoriasis has been extensively studied and is assumed to be identical to skin from those with psoriatic arthritis (PsA). Chemokines and the CC chemokine scavenger receptor ACKR2 are upregulated in uninvolved psoriasis. ACKR2 has been proposed as a regulator of cutaneous inflammation in psoriasis. The aim of this study was to compare the transcriptome of PsA skin to healthy control (HC) skin and evaluate ACKR2 expression in PsA skin.

METHODS

Full-thickness skin biopsies from HC, lesional and uninvolved skin from participants with PsA were sequenced on NovaSeq 6000. Findings were validated using qPCR and RNAscope.

RESULTS

Nine HC and nine paired PsA skin samples were sequenced. PsA uninvolved skin was transcriptionally similar to HC skin, and lesional PsA skin was enriched in epidermal and inflammatory genes. Lesional PsA skin was enriched in chemokine-mediated signalling pathways, but uninvolved skin was not. ACKR2 was upregulated in lesional PsA skin but had unchanged expression in uninvolved compared with HC skin. The expression of ACKR2 was confirmed by qPCR, and RNAscope demonstrated strong expression of ACKR2 in the suprabasal layer of the epidermis in PsA lesions.

CONCLUSION

Chemokines and their receptors are upregulated in lesional PsA skin but relatively unchanged in uninvolved PsA skin. In contrast to previous psoriasis studies, ACKR2 was not upregulated in uninvolved PsA skin. Further understanding of the chemokine system in PsA may help to explain why inflammation spreads from the skin to the joints in some people with psoriasis.

Follicular fluid biomarkers for prediction of human IVF outcome in women with poor ovarian response

Background

The aim of controlled ovarian stimulation is to achieve an optimal number of mature oocytes to obtain good-quality embryos. High follicular fluid (FF) concentrations of FSH, hCG, and LH promote oocyte maturation and are associated with a higher probability of fertilization. LH concentrations in FF are consistently higher in follicles that will lead to a successful IVF outcome. The levels of some of these FF biomarkers may vary among different ovarian stimulation schemes; however, the effects of corifollitropin alfa, recombinant FSH (rFSH), LH (rLH), and highly purified urinary menotropins uhMG on these biomarkers are still unknown. The objective of this study was to characterize the profile of FF biomarkers (leptin, vascular endothelial growth factor (VEGF), metalloproteinases (MMPs), and NO2−/NO3−) according to three different protocols of controlled ovarian stimulation (COS) in poor ovarian responders (POR) and to evaluate the association between these profiles and clinical outcomes. Three groups of POR patients were examined according to the protocols used.

Results

Group C showed significant higher levels in all biomarkers (p < 0001). FF samples from Group B had the lowest levels of VEGF and Pro-MMP-9. Group A showed the lowest concentration of pro-MMP-2. The VEGF level and number of captured oocytes were positively correlated in Group C (r = 0.534, p = 0.01). MMP-9 and fertilization rate were negatively correlated in Group C (r = −0.476, p = 0.02). We found negative correlations between proMMP-2 and serum estradiol levels on the day of rhCG administration.

Conclusion

We found significant variations in the biomarker concentrations between the different controlled ovarian stimulation schemes used in POR patients. These differences can be potentially explained by the nature and composition of the gonadotropins. Our results support the hypothesis that some of these molecules should be thoroughly investigated as noninvasive predictors of egg quality.

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.

Hallmarks of aging-based dual-purpose disease and age-associated targets predicted using PandaOmics AI-powered discovery engine

Aging biology is a promising and burgeoning research area that can yield dual-purpose pathways and protein targets that may impact multiple diseases, while retarding or possibly even reversing age-associated processes. One widely used approach to classify a multiplicity of mechanisms driving the aging process is the hallmarks of aging. In addition to the classic nine hallmarks of aging, processes such as extracellular matrix stiffness, chronic inflammation and activation of retrotransposons are also often considered, given their strong association with aging. In this study, we used a variety of target identification and prioritization techniques offered by the AI-powered PandaOmics platform, to propose a list of promising novel aging-associated targets that may be used for drug discovery. We also propose a list of more classical targets that may be used for drug repurposing within each hallmark of aging. Most of the top targets generated by this comprehensive analysis play a role in inflammation and extracellular matrix stiffness, highlighting the relevance of these processes as therapeutic targets in aging and age-related diseases. Overall, our study reveals both high confidence and novel targets associated with multiple hallmarks of aging and demonstrates application of the PandaOmics platform to target discovery across multiple disease areas.

Proteomic Studies of Psoriasis

In this review paper, we discuss the contribution of proteomic studies to the discovery of disease-specific biomarkers to monitor the disease and evaluate available treatment options for psoriasis. Psoriasis is one of the most prevalent skin disorders driven by a Th17-specific immune response. Although potential patients have a genetic predisposition to psoriasis, the etiology of the disease remains unknown. During the last two decades, proteomics became deeply integrated with psoriatic research. The data obtained in proteomic studies facilitated the discovery of novel mechanisms and the verification of many experimental hypotheses of the disease pathogenesis. The detailed data analysis revealed multiple differentially expressed proteins and significant changes in proteome associated with the disease and drug efficacy. In this respect, there is a need for proteomic studies to characterize the role of the disease-specific biomarkers in the pathogenesis of psoriasis, develop clinical applications to choose the most efficient treatment options and monitor the therapeutic response.

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.

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.

Analytical approaches to assess metabolic changes in psoriasis

Psoriasis is one of the most common human skin diseases, although its development is not limited to one tissue, but is associated with autoimmune reactions throughout the body. Overproduction of pro-inflammatory cytokines and growth factors systemically stimulates the proliferation of skin cells, which manifests as excessive exfoliation of the epidermis, and/or arthritis, as well as other comorbidities such as insulin resistance, metabolic syndrome, hypertension, and depression. Thus, there is a great need for a thorough analysis of the pathophysiology of psoriatic patients, including classical methods, such as spectrophotometry, chromatography, or Western blot, and also novel omics approaches such as lipidomics and proteomics. Moreover, the extensive pathophysiology forces increased research examining biological changes in both skin cells, and systemically. A wide range of techniques involved in lipidomic research based on a combination of mass spectrometry and different types of chromatography (RP-LC-QTOF-MS/MS, HILIC-QTOF-MS/MS or RP-LC-QTRAP-MS/MS), have allowed comprehensive assessment of lipid modification in psoriatic skin and provided new insight into the role of lipids and their mechanism of action in psoriasis. Moreover, proteomic analysis using gel-nanoLC-OrbiTrap-MS/MS, as well as MALDI-TOF/TOF techniques facilitates the description of panels of enzymes involved in lipidome modifications, and the response of the endocannabinoid system to metabolic changes. Psoriasis is known to alter the expression of proteins that are involved in the inflammatory and antioxidant response, as well as protein biosynthesis, degradation, as well as cell proliferation and apoptosis. Knowledge of changes in the lipidomic and proteomic profile will not only allow the understanding of psoriasis pathophysiology, but also facilitate proper and early diagnosis and effective pharmacotherapy.

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.

Early Origins of Psoriatic Arthritis: Clinical, Genetic and Molecular Biomarkers of Progression From Psoriasis to Psoriatic Arthritis

Greater than 90% of patients with psoriatic arthritis (PsA) first develop their arthritis on a background of known psoriasis (Pso). Thus, having skin/nail Pso certainly is an important risk factor for PsA but as PsA develops in <30% of those affected with Pso, the presence of Pso alone is insufficient as a means of identifying which patients with Pso will develop PsA. It is hoped that with further molecular assessment of Pso patients who do not have any evidence of inflammatory musculoskeletal disease compared to those with early PsA features, that the “at risk” profile of Pso patients destined to develop PsA can be refined such that disease prevention studies can be designed and a new era of treatment for PsA can emerge. In this article, the early stages in the development of PsA are outlined and what is currently known about clinical features, genetic factors and soluble or tissue biomarkers associated with the development of PsA in patients with Pso is reviewed in detail. Finally, proposals are outlined regarding the approaches required in order to address this important research area.

Translational Research Studies Unraveling the Origins of Psoriatic Arthritis: Moving Beyond Skin and Joints

Patients with psoriatic arthritis (PsA) are suffering from a decreased quality of life despite currently available treatments. In the latest years, novel therapies targeting the IL-17/IL-23 and TNF pathways improved clinical outcome. Despite this, remission of disease is not achieved in a considerable group of patients, continuous treatment is very often required to reach clinical remission, and prevention of PsA in patients with psoriasis (PsO) is currently impossible. A better understanding of PsA pathogenesis is required to develop novel treatment strategies that target inflammation and destruction more effectively and at an early stage of the disease, or even before clinically manifest disease. The skin is considered as one of the sites of onset of immune activation, triggering the inflammatory cascade in PsA. PsO develops into PsA in 30% of the PsO patients. Influenced by environmental and genetic factors, the inflammatory process in the skin, entheses, and/or gut may evolve into synovial tissue inflammation, characterized by influx of immune cells. The exact role of the innate and adaptive immune cells in disease pathogenesis is not completely known. The involvement of activated IL-17A+ T cells could implicate early immunomodulatory events generated in lymphoid organs thereby shaping the pathogenic inflammatory response leading to disease. In this perspective article, we provide the reader with an overview of the current literature regarding the immunological changes observed during the earliest stages of PsA. Moreover, we will postulate future areas of translational research aimed at increasing our knowledge on the molecular mechanisms driving disease development, which will aid the identification of novel potential therapeutic targets to limit the progression of PsA.

Identification of proteins associated with development of psoriatic arthritis in peripheral blood mononuclear cells: a quantitative iTRAQ-based proteomics study

Background

Biomarkers for distinguishing psoriatic arthritis (PsA) from psoriasis without arthritis (PsO) are still lacking.

Methods

We applied isobaric tags for relative and absolute quantification (iTRAQ) and LC–MS/MS to analyze the proteome profile of peripheral blood mononuclear cells (PBMCs) collected from patients with PsO, patients with PsA, and healthy controls. Bioinformatics analysis and western blotting were performed to identify and validate differentially expressed proteins.

Results

We identified 389, 199, 291, and 60 significantly differentially expressed proteins (adj.p < 0.05) in the comparison of all psoriatic patients versus healthy controls, PsO group versus healthy controls, PsA group versus healthy controls, and PsA group versus PsO group, respectively. Among these proteins, 14 proteins may represent promising biomarkers for PsA: SIRT2, NAA50, ARF6, ADPRHL2, SF3B6, SH3KBP1, UBA3, SCP2, RPS5, NUDT5, NCBP1, SYNE1, NDUFB7, HTATSF1. Furthermore, western blotting confirmed that SIRT2 expression was significantly higher in PBMCs from PsA patients than PsO and healthy controls, and was negatively correlated with the phosphorylation of p38 mitogen-activated protein kinase (p-p38MAPK; p = 0.006, r = − 0.582).

Conclusions

This pilot study provided a broad characterization of the proteome of PBMCs in PsA as compared to PsO and healthy controls, which may help to provide prospective strategies for PsA diagnosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-03006-x.

Clinical, laboratory, and genetic markers for the development or presence of psoriatic arthritis in psoriasis patients: a systematic review

Twenty to thirty percent of psoriasis (Pso) patients will develop psoriatic arthritis (PsA). Detection of Pso patients that are (at risk for) developing PsA is essential to prevent structural damage. We conducted a systematic search of five bibliographic databases, up to May 2020. We searched for studies assessing markers (clinical, laboratory, genetic) associated with the development or presence of PsA in Pso patients. Study selection and quality assessment of the included studies was performed, followed by a qualitative best evidence synthesis to determine the level of evidence for a marker and its association with concomitant/developing PsA in Pso. Overall, 259 possible markers were identified in 119 studies that met the inclusion criteria. Laboratory markers related to inflammation and bone metabolism reached a strong level of evidence for the association (not prediction) of PsA in Pso. Only CXCL10 showed strong evidence for a positive predictive value for PsA in Pso. The importance of timely detecting PsA in a Pso population, and finding more (bio)markers contributing to early detection, remains high.

Quantitative Proteomic Profile of Psoriatic Epidermis Identifies OAS2 as a Novel Biomarker for Disease Activity

Psoriasis is a common chronic inflammatory systemic disease. Epidermal proteins are considered to be important in maintaining skin barrier function, innate immunity, and inflammation. To define more possible roles of the epidermis in the pathogenesis of psoriasis, quantified proteomic analysis was used to screen and analyze the differentially expressed epidermal proteins between 16 psoriasis patients and 15 healthy controls. Upregulated differential expression proteins (DEPs) include several significant functional protein clusters, including antimicrobial peptides (AMPs) and antiviral proteins (AVPs). The levels of 2–5-oligoadenylate synthase 2 (OAS2) in both epidermis and serum levels were significantly elevated in psoriasis and were also positively correlated with Psoriasis Area Severity Index (PASI) scores and Body Surface Area (BSA) scores. Moreover, OAS2 expression in psoriatic skin significantly decreased after IL-17R mono-antibody treatment. It has been clarified that inflamed keratinocytes were the main source of abnormally increased OAS2 in psoriasis skin by immunofluorescence and primary cell cultures. Keratinocyte-derived OAS2 can be induced by not only IFNβ, but also psoriasis associated cytokines like IL-17A and IL-6. This study revealed that AMPs and AVPs are two important functional protein clusters altering innate immune in psoriatic epidermis. OAS2 is a novel potential sensitive biomarker, which could predict the severity and activity of psoriasis, and could also be used as an indicator to evaluate or monitor the efficacy of clinical treatment.

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.

Mechanisms of innate events during skin reaction following intradermal injection of seasonal influenza vaccine

The skin plays a crucial role in host defences against microbial attack and the innate cells must provide the immune system with sufficient information to organize these defences. This unique feature makes the skin a promising site for vaccine administration. Although cellular innate immune events during vaccination have been widely studied, initial events remain poorly understood. Our aim is to determine molecular biomarkers of skin innate reaction after intradermal (i.d.) immunization. Using an ex vivo human explant model from healthy donors, we investigated by NanoLC-MS/MS analysis and MALDI-MSI imaging, to detect innate molecular events (lipids, metabolites, proteins) few hours after i.d. administration of seasonal trivalent influenza vaccine (TIV). This multimodel approach allowed to identify early molecules differentially expressed in dermal and epidermal layers at 4 and 18 h after TIV immunization compared with control PBS. In the dermis, the most relevant network of proteins upregulated were related to cell-to-cell signalling and cell trafficking. The molecular signatures detected were associated with chemokines such as CXCL8, a chemoattractant of neutrophils. In the epidermis, the most relevant networks were associated with activation of antigen-presenting cells and related to CXCL10. Our study proposes a novel step-forward approach to identify biomarkers of skin innate reaction. SIGNIFICANCE: To our knowledge, there is no study analyzing innate molecular reaction to vaccines at the site of skin immunization. What is known on skin reaction is based on macroscopic (erythema, redness…), microscopic (epidermal and dermal tissues) and cellular events (inflammatory cell infiltrate). Therefore, we propose a multimodal approach to analyze molecular events at the site of vaccine injection on skin tissue. We identified early molecular networks involved biological functions such cell migration, cell-to-cell interaction and antigen presentation, validated by chemokine expression, in the epidermis and dermis, then could be used as early indicator of success in immunization.

LC-MS Analysis of Serum for the Metabolomic Investigation of the Effects of Pulchinenoside b4 Administration in Monosodium Urate Crystal-Induced Gouty Arthritis Rat Model

Gouty arthritis (GA) is commonly caused by deposition of monosodium urate (MSU) crystals within the joint capsule, bursa, cartilage, bone, or other periarticular tissues after chronic hyperuricemia. Clinically, GA is characterized by acute episodes of joint inflammation, which is most frequently encountered in the major joints, and also has a significant impact on quality of life. Pulchinenoside b4(P-b4) has a wide range of biological activities, including antitumor, anti-inflammatory, antiviral and immunomodulatory activities. Currently, the anti-GA activity and metabolomic profiles after being treated by P-b4 have not been reported. In this paper, for the first time, we have performed a non-targeted metabolomics analysis of serum obtained from an MSU crystal-induced GA rat model intervened by P-b4, using ultra-performance liquid chromatography coupled to quadrupole time-of-flight tandem mass spectrometry. In this study, the main pharmacodynamics of different dosing methods and dosages of P-b4 was firstly investigated. Results have shown that P-b4 possesses high anti-inflammatory activity. These results demonstrated changes in serum metabolites with 32 potential biomarkers. Arachidonic acid, sphingolipid, and glycerophospholipid metabolism are considered to be the most relevant metabolic pathway with P-b4 treatment effect in this study. Moreover, the changes of metabolites and the self-extinction of model effects within 24 h reveals important information for GA diagnostic criteria: The regression of clinical symptoms or the decline of some biochemical indicators cannot be regarded as the end point of GA treatment. Furthermore, our research group plans to conduct further metabolomics research on the clinical course of GA.

Elucidating the endogenous synovial fluid proteome and peptidome of inflammatory arthritis using label-free mass spectrometry

Background

Inflammatory arthritis (IA) is an immunological disorder in which loss of immune tolerance to endogenous self-antigens perpetuates synovitis and eventual destruction of the underlying cartilage and bone. Pathological changes in the joint are expected to be represented by synovial fluid (SF) proteins and peptides. In the present study, a mass spectrometry-based approach was utilized for the identification of key protein and peptide mediators of IA.

Methods

Age-matched SF samples from 10 rheumatoid arthritis patients, 10 psoriatic arthritis patients and 10 cadaveric controls were subjected to an integrated proteomic and peptidomic protocol using liquid chromatography tandem mass spectrometry. Significant differentially abundant proteins and peptides were identified between cohorts according to the results of a Mann-Whitney U test coupled to the Benjamini-Hochberg correction for multiple hypothesis testing. Fold change ratios were computed for each protein and peptide according to their log-transformed extracted ion current. Pathway analysis and antimicrobial peptide (AMP) prediction were conducted to clarify the pathophysiological relevance of identified proteins and peptides to IA.

Results

We determined that 144 proteins showed significant differential abundance between the IA and control SF proteomes, of which 11 protein candidates were selected for future follow-up studies. Similar analyses applied to our peptidomic data identified 15 peptide sequences, originating from 4 protein precursors, to have significant differential abundance in IA compared to the control SF peptidome. Pathway enrichment analysis of the IA SF peptidome along with AMP prediction suggests a possible mechanistic role of microbes in eliciting an immune response which drives the development of IA.

Conclusions

The discovery-phase data generated herein has provided a basis for the identification of candidates with the greatest potential to serve as novel serum biomarkers specific to inflammatory arthritides. Moreover, these findings facilitate the understanding of possible disease mechanisms specific to each subtype.

Differentiating Psoriatic Arthritis From Psoriasis Without Psoriatic Arthritis Using Novel Serum Biomarkers

OBJECTIVE

There is a high prevalence of undiagnosed psoriatic arthritis (PsA) in patients with psoriasis. Identifying soluble biomarkers for PsA will help in screening psoriasis patients for appropriate rheumatology referral. We therefore aimed to investigate whether serum levels of novel markers previously discovered by quantitative mass spectrometric analysis of synovial fluid and skin biopsies performs better than the C-reactive protein (CRP) level in differentiating PsA patients from those with psoriasis without PsA (PsC).

METHODS

In this case-control study, serum samples were obtained from 100 subjects with PsA, 100 with PsC, and 100 healthy controls. Patients with PsA and PsC were group matched for age, sex, psoriasis duration, and Psoriasis Area and Severity Index and were not currently receiving biologic treatment. Using enzyme-linked immunosorbent assay, 4 high-priority markers (Mac-2-binding protein [M2BP], CD5-like protein [CD5L], myeloperoxidase [MPO], and integrin β5 [ITGβ5]), as well as previously established markers (matrix metalloproteinase 3 [MMP-3] and CRP level) were assayed. Data were analyzed using logistic regression. Receiver operating characteristic (ROC) curves were plotted.

RESULTS

In comparisons to controls, CD5L, ITGβ5, M2BP, MPO, MMP-3, and CRP level were independently associated with PsA, while only CD5L, M2BP, and MPO were independently associated with PsC alone. In comparisons to PsC, ITGβ5, M2BP, and CRP level were independently associated with PsA. ROC analysis of this model shows an area under the curve (AUC) of 0.85 (95% confidence interval [95% CI] 0.80-0.90). The model that included CRP level alone had an AUC of 0.71 (95% CI 0.64-0.78).

CONCLUSION

CD5L, ITGβ5, M2BP, MPO, MMP-3, and CRP level are markers for PsA. The combination of ITGβ5, M2BP, and CRP level differentiates PsA from PsC, and performs better than CRP level alone.

Sample Treatment for Tissue Proteomics in Cancer, Toxicology, and Forensics

Since the birth of proteomics science in the 1990, the number of applications and of sample preparation methods has grown exponentially, making a huge contribution to the knowledge in life science disciplines. Continuous improvements in the sample treatment strategies unlock and reveal the fine details of disease mechanisms, drug potency, and toxicity as well as enable new disciplines to be investigated such as forensic science.This chapter will cover the most recent developments in sample preparation strategies for tissue proteomics in three areas, namely, cancer, toxicology, and forensics, thus also demonstrating breath of application within the domain of health and well-being, pharmaceuticals, and secure societies.In particular, in the area of cancer (human tumor biomarkers), the most efficient and multi-informative proteomic strategies will be covered in relation to the subsequent application of matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) and liquid extraction surface analysis (LESA), due to their ability to provide molecular localization of tumor biomarkers albeit with different spatial resolution.With respect to toxicology, methodologies applied in toxicoproteomics will be illustrated with examples from its use in two important areas: the study of drug-induced liver injury (DILI) and studies of effects of chemical and environmental insults on skin, i.e., the effects of irritants, sensitizers, and ionizing radiation. Within this chapter, mainly tissue proteomics sample preparation methods for LC-MS/MS analysis will be discussed as (i) the use of LC-MS/MS is majorly represented in the research efforts of the bioanalytical community in this area and (ii) LC-MS/MS still is the gold standard for quantification studies.Finally, the use of proteomics will also be discussed in forensic science with respect to the information that can be recovered from blood and fingerprint evidence which are commonly encountered at the scene of the crime. The application of proteomic strategies for the analysis of blood and fingerprints is novel and proteomic preparation methods will be reported in relation to the subsequent use of mass spectrometry without any hyphenation. While generally yielding more information, hyphenated methods are often more laborious and time-consuming; since forensic investigations need quick turnaround, without compromising validity of the information, the prospect to develop methods for the application of quick forensic mass spectrometry techniques such as MALDI-MS (in imaging or profiling mode) is of great interest.

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.

Targeted Proteomics for Multiplexed Verification of Markers of Colorectal Tumorigenesis

Targeted proteomic methods can accelerate the verification of multiple tumor marker candidates in large series of patient samples. We utilized the targeted approach known as selected/multiple reaction monitoring (S/MRM) to verify potential protein markers of colorectal adenoma identified by our group in previous transcriptomic and quantitative shotgun proteomic studies of a large cohort of precancerous colorectal lesions. We developed SRM assays to reproducibly detect and quantify 25 (62.5%) of the 40 selected proteins in an independent series of precancerous and cancerous tissue samples (19 adenoma/normal mucosa pairs; 17 adenocarcinoma/normal mucosa pairs). Twenty-three proteins were significantly up-regulated (n = 17) or downregulated (n = 6) in adenomas and/or adenocarcinomas, as compared with normal mucosa (linear fold changes ≥ ±1.3, adjusted p value <0.05). Most changes were observed in both tumor types (up-regulation of ANP32A, ANXA3, SORD, LDHA, LCN2, NCL, S100A11, SERPINB5, CDV3, OLFM4, and REG4; downregulation of ARF6 and PGM5), and a five-protein biomarker signature distinguished neoplastic tissue from normal mucosa with a maximum area under the receiver operating curve greater than 0.83. Other changes were specific for adenomas (PPA1 and PPA2 up-regulation; KCTD12 downregulation) or adenocarcinoma (ANP32B, G6PD, RCN1, and SET up-regulation; downregulated AKR1B1, APEX1, and PPA1). Some changes significantly correlated with a few patient- or tumor-related phenotypes. Twenty-two (96%) of the 23 proteins have a potential to be released from the tumors into the bloodstream, and their detectability in plasma has been previously reported. The proteins identified in this study expand the pool of biomarker candidates that can be used to develop a standardized precolonoscopy blood test for the early detection of colorectal tumors.

Comprehensive Metaproteomic Analyses of Urine in the Presence and Absence of Neutrophil-Associated Inflammation in the Urinary Tract

Inflammation in the urinary tract results in a urinary proteome characterized by a high dynamic range of protein concentrations and high variability in protein content. This proteome encompasses plasma proteins not resorbed by renal tubular uptake, renal secretion products, proteins of immune cells and erythrocytes derived from trans-urothelial migration and vascular leakage, respectively, and exfoliating urothelial and squamous epithelial cells. We examined how such proteins partition into soluble urine (SU) and urinary pellet (UP) fractions by analyzing 33 urine specimens 12 of which were associated with a urinary tract infection (UTI). Using mass spectrometry-based metaproteomic approaches, we identified 5,327 non-redundant human proteins, 2,638 and 4,379 of which were associated with SU and UP fractions, respectively, and 1,206 non-redundant protein orthology groups derived from pathogenic and commensal organisms of the urogenital tract. Differences between the SU and UP proteomes were influenced by local inflammation, supported by respective comparisons with 12 healthy control urine proteomes. Clustering analyses showed that SU and UP fractions had proteomic signatures discerning UTIs, vascular injury, and epithelial cell exfoliation from the control group to varying degrees. Cases of UTI revealed clusters of proteins produced by activated neutrophils. Network analysis supported the central role of neutrophil effector proteins in the defense against invading pathogens associated with subsequent coagulation and wound repair processes. Our study expands the existing knowledge of the urinary proteome under perturbed conditions, and should be useful as reference dataset in the search of biomarkers.

Recent advances in understanding and managing psoriatic arthritis

This article reviews recent advances in psoriatic arthritis (PsA) over the past several years with emphasis on early diagnosis, better understanding of pathogenesis, and new therapeutic approaches. Early diagnosis is important, since people who present late do not fare as well. There are a number of clinical, laboratory, and ultrasound features that can help identify patients destined to develop PsA, and several screening tools have been developed. It is recognized that genetic and epigenetic factors, as well as T cells and cytokines, play a role in the pathogenesis of PsA, and several targets have been identified for therapeutic interventions. New therapies have been developed and tested in PsA and have been found to be highly effective for both skin and joint manifestations of the disease. The expectation is that, in the future, PsA patients will be treated early and more aggressively and that there will not be significant progression of joint damage. Moreover, with effective treatment of the skin and joint disease and management of risk factors for the comorbidities, we can expect to reduce their occurrence and further reduce the excess mortality and reduced quality of life and function in these patients.

Hydrogel Micropatch and Mass Spectrometry-Assisted Screening for Psoriasis-Related Skin Metabolites

BACKGROUND

Psoriasis is a chronic, immune-mediated inflammatory skin disease. Screening skin metabolites could unravel the pathophysiology of psoriasis and provide new diagnostic approaches. Due to the lack of suitable methodologies for collecting scarce amounts of skin excretions, the psoriatic skin metabolome has not been extensively studied.

METHODS

We implemented biocompatible hydrogel micropatch probes combined with mass spectrometry to investigate the skin metabolome. This noninvasive approach was applied to examine samples obtained from 100 psoriatic patients and 100 healthy individuals. We also developed custom data treatment tools and used chemometric and statistical tools to reveal the alterations in the skin metabolome caused by psoriasis.

RESULTS

The proposed methodology enabled us to capture alterations in the composition of skin excretions caused by the disease. Chemometric analysis revealed the major differences between the metabolomes of psoriatic skin and healthy skin. Several polar metabolites were positively (choline and glutamic acid) or negatively (urocanic acid and citrulline) correlated with the plaque severity scores. The amounts of these metabolites in the excretions sampled from psoriatic skin were significantly different (P < 0.001) from the excretions sampled from healthy skin. The role of biological variability and various confounding factors, which might affect the skin metabolome, was also investigated.

CONCLUSIONS

Sampling lesional and healthy skin with the hydrogel micropatch probes and subsequent direct mass spectrometry scanning provided information on the alterations in the skin metabolome caused by psoriasis, increasing the understanding of the complex pathophysiology of this disease.

Clinical Utility of a Plasma Protein Classifier for Indeterminate Lung Nodules

Evaluation of indeterminate pulmonary nodules is a complex challenge. Most are benign but frequently undergo invasive and costly procedures to rule out malignancy. A plasma protein classifier was developed that identifies likely benign nodules that can be triaged to CT surveillance to avoid unnecessary invasive procedures. The clinical utility of this classifier was assessed in a prospective-retrospective analysis of a study enrolling 475 patients with nodules 8-30 mm in diameter who had an invasive procedure to confirm diagnosis at 12 sites. Using this classifier, 32.0 % (CI 19.5-46.7) of surgeries and 31.8 % (CI 20.9-44.4) of invasive procedures (biopsy and/or surgery) on benign nodules could have been avoided. Patients with malignancy triaged to CT surveillance by the classifier would have been 24.0 % (CI 19.2-29.4). This rate is similar to that described in clinical practices (24.5 % CI 16.2-34.4). This study demonstrates the clinical utility of a non-invasive blood test for pulmonary nodules.