Altered Fecal Metabolomics and Potential Biomarkers of Psoriatic Arthritis Differing From Rheumatoid Arthritis

Treatment controversies in spondyloarthritis and psoriatic arthritis: focus on biologics and targeted therapies

INTRODUCTION

There are several treatment controversies that have emerged in spondyloarthritis and psoriatic arthritis. These are related to the nature of the conditions as well as to the use of medications.

AREAS COVERED

This review, which included a search of PubMed database as well as the references within the articles provides an overview of the nature of spondyloarthritis, controversy over the inclusion of psoriatic arthritis (PsA) as a peripheral spondyloarthritis, and a summary of current treatments for both PsA and axial spondyloarthritis (axSpA), with special emphasis on targeted therapy. The review highlights the differences in response to certain medications, particularly biologic therapy and summarizes the randomized controlled trials in psoriatic arthritis and axial spondyloarthritis providing data about the responses in table format.

EXPERT OPINION

There is a need for better outcome measures in axSpA. Currently, the measures are subjective. Imaging may be more appropriate but there is a need for research into the reliability and responsiveness of imaging techniques. In PsA, there may also be better response measures and research into the reliability and responsiveness of available measures is underway. There is also a need for novel therapies as well as biomarkers for response in both diseases.

IL-17A inhibitors alleviate Psoriasis with concomitant restoration of intestinal/skin microbiota homeostasis and altered microbiota function

Background

Disturbed gut microbiota and associated metabolic dysfunction exist in Psoriasis. Despite the growing use of interleukin-17 inhibitor (anti-IL17) therapy, the effect of anti-IL17 on gut/skin microbiota function is not fully understood in patients with Psoriasis.

Objective

Therefore, we explored whether Psoriasis is associated with alterations in selected gut/skin microbiota in a study cohort, and a longitudinal cohort study to reveal the effects of IL-17A inhibitor treatment on gut microbiota in Psoriasis.

Methods

In a case-control study, 14 patients with Psoriasis and 10 age, sex and body mass index-matched Healthy Controls were recruited. Longitudinal mapping of the gut microbiome was performed using 16S rRNA gene sequencing. Mouse models were used to further study and validate the interrelationship between the skin microbiome and the gut microbiome in Psoriasis. PICRUST2 was applied to predict the function of the bacterial community.

Results

In Psoriasis patients, gut microbiota dysbiosis was present with increased heterogeneity: decreased Bacteroidota and increased Firmicutes as well as Actinobacteriota predominating in Psoriasis. Escherichia-Shigella enrichment was associated with reduction in serum levels of total bile acid and markers in Apoptotic pathways. After IL-17A inhibitor treatment in Psoriasis patients, longitudinal studies observed a trend toward a normal distribution of the gut microbiome and modulation of apoptosis-related metabolic pathways. Results from a mouse model showed dysregulation of the skin microbiota in Psoriasis characterized by Staphylococcus colonization.

Conclusion

The psoriatic gut/skin microbiota exhibits loss of community stability and pathogen enrichment. IL-17A inhibitors restore microbiota homeostasis and metabolic pathways, reduce pro-inflammatory cytokine expression, and alleviate symptoms in patients with Psoriasis.

The impacts of biologic treatment on metabolic profiling in psoriasis

Psoriasis is an immune-mediated inflammatory disease commonly accompanied by various metabolic disorders. It is widely known that biologics could affect the metabolic status and comorbidities in psoriasis patients, however, the effects of biologics on metabolism in psoriasis patients remain poorly understood. The aim of this study was to elucidate the characteristic changes of metabolic profiling in psoriasis vulgaris (PsV) patients before and after applying biologics. Plasma samples were collected from a retrospective cohort of 43 PsV patients. Non-targeted metabolomics analyses were performed using liquid chromatography-mass spectrometry (LC-MS) to compare the metabolic profiles before and after applying adalimumab (ADA) or ixekizumab (IXE) for 4 weeks. Additionally, correlation analyses were conducted to investigate the associations between metabolite expression levels and clinical characteristics. The biologics significantly affected the metabolic profiles of PsV patients especially in glycerophospholipids (GPs). First, phosphatidylcholine (PC), unsaturated lysophosphatidylcholine (LPC), unsaturated lysophosphatidic acid (LPA) and unsaturated lysophosphatidylethanolamine (LPE) were significantly up-regulated, whereas phosphatidylethanolamine (PE), saturated LPC, saturated LPA and saturated LPE were predominantly down-regulated after biologic treatment. What is more, the changes in PE and LPA were mainly observed after applying IXE instead of ADA. Second, we also found GPs including PC, unsaturated LPC, unsaturated LPA and unsaturated LPE were primarily negatively correlated with disease severity, whereas, PE, saturated LPC, saturated LPA and saturated LPE displayed inverse correlations. Biologics could affect GP metabolism and facilitate the transition of metabolic status from a pro-inflammatory to an anti-inflammatory phenotype in PsV patients.

Metabolic influences on T cell in psoriasis: a literature review

Psoriasis is a systemic inflammatory disease that frequently coexists with various other conditions, such as essential hypertension, diabetes, metabolic syndrome, and inflammatory bowel disease. The association between these diseases may be attributed to shared inflammatory pathways and abnormal immunomodulatory mechanisms. Furthermore, metabolites also play a regulatory role in the function of different immune cells involved in psoriasis pathogenesis, particularly T lymphocytes. In this review, we have summarized the current research progress on T cell metabolism in psoriasis, encompassing the regulation of metabolites in glucose metabolism, lipid metabolism, amino acid metabolism, and other pathways within T cells affected by psoriasis. We will also explore the interaction and mechanism between psoriatic metabolites and immune cells. Moreover, we further discussed the research progress of metabolomics in psoriasis to gain a deeper understanding of its pathogenesis and identify potential new therapeutic targets through identification of metabolic biomarkers associated with this condition.

Small Intestinal Permeability and Metabolomic Profiles in Feces and Plasma Associate With Clinical Response in Patients With Active Psoriatic Arthritis Participating in a Fecal Microbiota Transplantation Trial: Exploratory Findings From the FLORA Trial

OBJECTIVE

We investigated intestinal permeability and fecal, plasma, and urine metabolomic profiles in methotrexate-treated active psoriatic arthritis (PsA) and how this related to clinical response following one sham or fecal microbiota transplantation (FMT).

METHODS

This exploratory study is based on the FLORA trial cohort, in which 31 patients with moderate-to-high peripheral PsA disease activity, despite at least 3 months of methotrexate-treatment, were included in a 26-week, double-blind, 1:1 randomized, sham-controlled trial. Participants were randomly allocated to receive either one healthy donor FMT (n = 15) or sham (n = 16) via gastroscopy. The primary trial end point was the proportion of treatment failures through 26 weeks. We performed a lactulose-to-mannitol ratio (LMR) test at baseline (n = 31) and at week 26 (n = 26) to assess small intestinal permeability. Metabolomic profiles in fecal, plasma, and urine samples collected at baseline, weeks 4, 12, and 26 were measured using 1 H Nuclear Magnetic Resonance.

RESULTS

Trial failures (n = 7) had significantly higher LMR compared with responders (n = 19) at week 26 (0.027 [0.017-0.33]) vs. 0.012 [0-0.064], P = 0.013), indicating increased intestinal permeability. Multivariate analysis revealed a significant model for responders (n = 19) versus failures (n = 12) at all time points based on their fecal (P < 0.0001) and plasma (P = 0.005) metabolomic profiles, whereas urine metabolomic profiles did not differ between groups (P = 1). Fecal N-acetyl glycoprotein GlycA correlated with Health Assessment Questionnaire Disability Index (coefficient = 0.50; P = 0.03) and fecal propionate correlated with American College of Rheumatology 20 response at week 26 (coefficient = 27, P = 0.02).

CONCLUSION

Intestinal permeability and fecal and plasma metabolomic profiles of patients with PsA were associated with the primary clinical trial end point, failure versus responder.

Raman spectroscopy as a promising diagnostic method for rheumatoid arthritis

Background: Diagnosis of rheumatoid arthritis (RA) basically relies on clinical symptoms and autoantibodies, especially anti-citrullinated protein antibodies (ACPAs) and rheumatoid factor (RF). However, the lack of autoantibodies is still a dilemma clinically in seronegative RA, especially in the early stage of the disease. This study aimed to provide a unique disease fingerprint with high diagnostic value to discriminate RA based on Raman spectroscopy. Methods: Raman spectroscopy provides a repertoire of biomolecules in serum from RA. Multivariate dimension-reducing methods and machine-learning algorithms were exploited to reveal the intrinsic differences and the potential discrimination power. The underlying differential biomolecules were retrieved by the assignment of Raman peaks. Moreover, the correlations between the spectral differences and RA patient's clinical and immunological manifestations were also analyzed. Results: RA patients exhibited unique Raman spectra characterized by biomolecular alterations during the disease progression. The discrimination power yielded 97.3% sensitivity and 94.8% specificity for RA diagnosis. In the recognition of ACPA-negative RA, the sensitivity and specificity also reached 95.6% and 92.8%, respectively. In particular, the differential Raman spectrum peaks of RA patients mainly represented lipids, amino acids, glycogen, and fatty acids. Further analysis showed that the different serum Raman spectra correlated with the clinical features of RA, including disease duration, RF, anticyclic citrullinated peptide antibodies (anti-CCPs), IgA, IgM, IgG, tender joint count, and swollen joint count (|rs| = 0.15-0.52, p < 0.05). Conclusions: Raman spectroscopy was revealed to be a promising diagnostic method for RA, especially for ACPA-negative patients.

Biomarkers in psoriatic arthritis: A meta-analysis and systematic review

Introduction

Psoriatic arthritis (PsA) is a chronic inflammatory disease that frequently develops in patients with psoriasis (PsO) but can also occur spontaneously. As a result, PsA diagnosis and treatment is commonly delayed, or even missed outright due to the manifold of clinical presentations that patients often experience. This inevitably results in progressive articular damage to axial and peripheral joints and entheses. As such, patients with PsA frequently experience reduced expectancy and quality of life due to disability. More recently, research has aimed to improve PsA diagnosis and prognosis by identifying novel disease biomarkers.

Methods

Here, we conducted a systematic review of the published literature on candidate biomarkers for PsA diagnosis and prognosis in MEDLINE(Pubmed), EMBase and the Cochrane library with the goal to identify clinically applicable PsA biomarkers. Meta-analyses were performed when a diagnostic bone and cartilage turnover biomarker was reported in 2 or moredifferent cohorts of PsA and control.

Results

We identified 1444 publications and 124 studies met eligibility criteria. We highlighted bone and cartilage turnover biomarkers, genetic markers, and autoantibodies used for diagnostic purposes of PsA, as well as acute phase reactant markers and bone and cartilage turnover biomarkers for activity or prognostic severity purposes. Serum cartilage oligometrix metalloproteinase levels were significantly increased in the PsA sera compared to Healthy Control (HC) with a standardized mean difference (SMD) of 2.305 (95%CI 0.795-3.816, p=0.003) and compared to osteoarthritis (OA) with a SMD of 0.783 (95%CI 0.015-1.551, p=0.046). The pooled serum MMP-3 levels were significantly higher in PsA patients than in PsO patients with a SMD of 0.419 (95%CI 0.119-0.719; p=0.006), but no significant difference was highlighted when PsA were compared to HC. While we did not identify any new genetic biomarkers that would be useful in the diagnosis of PsA, recent data with autoantibodies appear to be promising in diagnosis, but no replication studies have been published.

Conclusion

In summary, no specific diagnostic biomarkers for PsA were identified and further studies are needed to assess the performance of potential biomarkers that can distinguish PsA from OA and other chronic inflammatory diseases.

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.