Metabolomics Studies in Psoriatic Disease: A Review

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.

Challenges in the Metabolomics-Based Biomarker Validation Pipeline

As end-products of the intersection between the genome and environmental influences, metabolites represent a promising approach to the discovery of novel biomarkers for diseases. However, many potential biomarker candidates identified by metabolomics studies fail to progress beyond analytical validation for routine implementation in clinics. Awareness of the challenges present can facilitate the development and advancement of innovative strategies that allow improved and more efficient applications of metabolite-based markers in clinical settings. This minireview provides a comprehensive summary of the pre-analytical factors, required analytical validation studies, and kit development challenges that must be resolved before the successful translation of novel metabolite biomarkers originating from research. We discuss the necessity for strict protocols for sample collection, storage, and the regulatory requirements to be fulfilled for a bioanalytical method to be considered as analytically validated. We focus especially on the blood as a biological matrix and liquid chromatography coupled with tandem mass spectrometry as the analytical platform for biomarker validation. Furthermore, we examine the challenges of developing a commercially viable metabolomics kit for distribution. To bridge the gap between the research lab and clinical implementation and utility of relevant metabolites, the understanding of the translational challenges for a biomarker panel is crucial for more efficient development of metabolomics-based precision medicine.

Classifying patients with psoriatic arthritis according to their disease activity status using serum metabolites and machine learning

INTRODUCTION

Psoriatic arthritis (PsA) is a heterogeneous inflammatory arthritis, affecting approximately a quarter of patients with psoriasis. Accurate assessment of disease activity is difficult. There are currently no clinically validated biomarkers to stratify PsA patients based on their disease activity, which is important for improving clinical management.

OBJECTIVES

To identify metabolites capable of classifying patients with PsA according to their disease activity.

METHODS

An in-house solid-phase microextraction (SPME)-liquid chromatography-high resolution mass spectrometry (LC-HRMS) method for lipid analysis was used to analyze serum samples obtained from patients classified as having low (n = 134), moderate (n = 134) or high (n = 104) disease activity, based on psoriatic arthritis disease activity scores (PASDAS). Metabolite data were analyzed using eight machine learning methods to predict disease activity levels. Top performing methods were selected based on area under the curve (AUC) and significance.

RESULTS

The best model for predicting high disease activity from low disease activity achieved AUC 0.818. The best model for predicting high disease activity from moderate disease activity achieved AUC 0.74. The best model for classifying low disease activity from moderate and high disease activity achieved AUC 0.765. Compounds confirmed by MS/MS validation included metabolites from diverse compound classes such as sphingolipids, phosphatidylcholines and carboxylic acids.

CONCLUSION

Several lipids and other metabolites when combined in classifying models predict high disease activity from both low and moderate disease activity. Lipids of key interest included lysophosphatidylcholine and sphingomyelin. Quantitative MS assays based on selected reaction monitoring, are required to quantify the candidate biomarkers identified.

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.

A Solid-Phase Microextraction-Liquid Chromatography-Mass Spectrometry Method for Analyzing Serum Lipids in Psoriatic Disease

Approximately 25% of psoriasis patients have an inflammatory arthritis termed psoriatic arthritis (PsA). There is strong interest in identifying and validating biomarkers that can accurately and reliably predict conversion from psoriasis to PsA using novel technologies such as metabolomics. Lipids, in particular, are of key interest in psoriatic disease. We sought to develop a liquid chromatography-mass spectrometry (LC-MS) method to be used in conjunction with solid-phase microextraction (SPME) for analyzing fatty acids and similar molecules. A total of 25 chromatographic methods based on published lipid studies were tested on two LC columns. As a proof of concept, serum samples from psoriatic disease patients (n = 27 psoriasis and n = 26 PsA) were processed using SPME and run on the selected LC-MS method. The method that was best for analyzing fatty acids and fatty acid-like molecules was optimized and applied to serum samples. A total of 18 tentatively annotated features classified as fatty acids and other lipid compounds were statistically significant between psoriasis and PsA groups using both multivariate and univariate approaches. The SPME-LC-MS method developed and optimized was capable of detecting fatty acids and similar lipids that may aid in differentiating psoriasis and PsA patients.

Psoriasis immunometabolism: progress on metabolic biomarkers and targeted therapy

Psoriasis is a common inflammatory disease that affects mainly the skin. However, the moderate to severe forms have been associated with several comorbidities, such as psoriatic arthritis, Crohn's disease, metabolic syndrome and cardiovascular disease. Keratinocytes and T helper cells are the dominant cell types involved in psoriasis development via a complex crosstalk between epithelial cells, peripheral immune cells and immune cells residing in the skin. Immunometabolism has emerged as a potent mechanism elucidating the aetiopathogenesis of psoriasis, offering novel specific targets to diagnose and treat psoriasis early. The present article discusses the metabolic reprogramming of activated T cells, tissue-resident memory T cells and keratinocytes in psoriatic skin, presenting associated metabolic biomarkers and therapeutic targets. In psoriatic phenotype, keratinocytes and activated T cells are glycolysis dependent and are characterized by disruptions in the TCA cycle, the amino acid metabolism and the fatty acid metabolism. Upregulation of the mammalian target of rapamycin (mTOR) results in hyperproliferation and cytokine secretion by immune cells and keratinocytes. Metabolic reprogramming through the inhibition of affected metabolic pathways and the dietary restoration of metabolic imbalances may thus present a potent therapeutic opportunity to achieve long-term management of psoriasis and improved quality of life with minimum adverse effects.

Metabolomics analysis reveals cytotoxic effects of ouabain towards psoriatic keratinocytes via impairment of glutathione metabolism

Ouabain is a cardiac glycoside long studied for treating heart diseases, but the attempts to evaluate its anti-psoriatic activity have not been reported. We aimed to explore the effects of ouabain on proliferation and metabolism towards psoriatic keratinocytes. In human HaCaT keratinocytes, ouabain potently decreased viability, promoted apoptosis and caused G2/M cycle arrest. Metabolomics analysis indicated that ouabain markedly impaired glutathione metabolism. The solute carrier family 7 member 11 (SLC7A11) is an amino acid transporter highly specific to cysteine, which is critical for glutathione synthesis. Ouabain downregulated SLC7A11, reduced cysteine uptake and subsequently inhibited glutathione synthesis, probably through inhibiting Akt/mTOR/beclin axis that regulate protein activity of SLC7A11. The impaired glutathione synthesis and oxidative stress caused by ouabain may contribute to its cytotoxicity towards psoriatic keratinocytes. Our results provide experimental evidence supporting further study of ouabain as a potential anti-psoriatic agent.

Dysregulation of Bile Acids, Lipids, and Nucleotides in Psoriatic Arthritis Revealed by Unbiased Profiling of Serum Metabolites

OBJECTIVE

The transition from psoriasis to psoriatic arthritis (PsA) occurs in 20-30% of patients; however, the mechanisms underlying the emergence of musculoskeletal disease are not well understood. Metabolic disease is prevalent in psoriasis patients, but whether metabolic factors, other than obesity, increase arthritis risk in psoriasis patients is not known. This study was undertaken to investigate the link between metabolic changes and disease progression in psoriasis patients.

METHODS

To characterize the metabolic alterations during the progression of arthritis in psoriasis patients, we analyzed cross-sectional healthy controls and PsA samples and longitudinal psoriasis serum samples, before and after PsA onset. Nontargeted metabolomic profiling was performed using liquid chromatography mass spectrometry.

RESULTS

We identified several serum metabolites that differed between PsA patients, psoriasis patients, and healthy controls. Differentially abundant bile acids, purines, pyrimidines, glutathione, lipids, and amino acid metabolites were noted in these 3 groups. We also noted differences between psoriasis patients who progressed and those who did not progress to PsA. Bile acid and butyrate levels were depressed in those who progressed to PsA compared to those who did not, and the level of inflammatory lipid mediators increased following PsA diagnosis. In particular, the combination of leukotriene B4 and glycoursodeoxycholic acid sulfate were sensitive and specific predictors of PsA progression.

CONCLUSION

We observed notable differences in bile acid, purine, lipid, and amino acid-derived metabolites, among the healthy controls, psoriasis patients, and PsA patients and identified changes during the transition from psoriasis to PsA. The decreased bile acid and butyrate levels and elevated guanine levels in psoriasis patients at risk for PsA were particularly striking and may reflect gut microbial dysbiosis and dysregulated hepatic metabolism, leading to altered proliferation of immune cells and enhanced cytokine expression.

Current and future approaches for in vitro hit discovery in diabetes mellitus

Type 2 diabetes mellitus (T2DM) is a serious public health problem. In this review, we discuss current and promising future drugs, targets, in vitro assays and emerging omics technologies in T2DM. Importantly, we open the perspective to image-based high-content screening (HCS), with the focus of combining it with metabolomics or lipidomics. HCS has become a strong technology in phenotypic screens because it allows comprehensive screening for the cell-modulatory activity of small molecules. Metabolomics and lipidomics screen for perturbations at the molecular level. The combination of these data-intensive comprehensive technologies is enabled by the rapid development of artificial intelligence. It promises a deep cellular and molecular phenotyping directly linked to chemical information about the applied drug candidates or complex mixtures.

Metabolic Profiling in Rheumatoid Arthritis, Psoriatic Arthritis, and Psoriasis: Elucidating Pathogenesis, Improving Diagnosis, and Monitoring Disease Activity

Immune-mediated inflammatory diseases (IMIDs), such as rheumatoid arthritis (RA), psoriatic arthritis (PsA), and psoriasis (Ps), represent autoinflammatory and autoimmune disorders, as well as conditions that have an overlap of both categories. Understanding the underlying pathogeneses, making diagnoses, and choosing individualized treatments remain challenging due to heterogeneous disease phenotypes and the lack of reliable biomarkers that drive the treatment choice. In this review, we provide an overview of the low-molecular-weight metabolites that might be employed as biomarkers for various applications, e.g., early diagnosis, disease activity monitoring, and treatment-response prediction, in RA, PsA, and Ps. The literature was evaluated, and putative biomarkers in different matrices were identified, categorized, and summarized. While some of these candidate biomarkers appeared to be disease-specific, others were shared across multiple IMIDs, indicating common underlying disease mechanisms. However, there is still a long way to go for their application in a routine clinical setting. We propose that studies integrating omics analyses of large patient cohorts from different IMIDs should be performed to further elucidate their pathomechanisms and treatment options. This could lead to the identification and validation of biomarkers that might be applied in the context of precision medicine to improve the clinical outcomes of these IMID patients.

Metabolomics: An Emerging Approach to Understand Pathogenesis and to Assess Diagnosis and Response to Treatment in Spondyloarthritis

Spondyloarthritis (SpA) is a group of rheumatic diseases whose pathogenesis relies on a complex interplay between genetic and environmental factors. Over the last several years, the importance of the alteration of the gut microbiota, known as dysbiosis, and the interaction of bacterial products with host immunity have been highlighted as intriguing key players in SpA development. The recent advent of the so called “-omics” sciences, that include metabolomics, opened the way to a new approach to SpA through a deeper characterisation of the pathogenetic mechanisms behind the disease. In addition, metabolomics can reveal potential new biomarkers to diagnose and monitor SpA patients. The aim of this review is to highlight the most recent advances concerning the application of metabolomics to SpA, in particular focusing attention on Ankylosing Spondylitis and Psoriatic Arthritis.