Integrated metabolomic analysis and cytokine profiling define clusters of immuno-metabolic correlation in new-onset psoriasis

Exploration of circulating metabolic signature of erythrodermic psoriasis based on LC-MS metabolomics

Erythrodermic psoriasis (EP) is a rare and life-threatening disease, the pathogenesis of which remains to be largely unknown. Metabolomics analysis can provide global information on disease pathophysiology, candidate biomarkers, and potential intervention strategies. To gain a better understanding of the mechanisms of EP and explore the serum metabolic signature of EP, we conducted an untargeted metabolomics analysis from 20 EP patients and 20 healthy controls. Furthermore, targeted metabolomics for focused metabolites were identified in the serum samples of 30 EP patients and 30 psoriasis vulgaris (PsV) patients. In the untargeted analysis, a total of 2992 molecular features were extracted from each sample, and the peak intensity of each feature was obtained. Principal component analysis (PCA), orthogonal partial least squares-discriminant analysis (OPLS-DA) revealed significant difference between groups. After screening, 98 metabolites were found to be significantly dysregulated in EP, including 67 down-regulated and 31 up-regulated. EP patients had lower levels of L-tryptophan, L-isoleucine, retinol, lysophosphatidylcholine (LPC), and higher levels of betaine and uric acid. KEGG analysis showed differential metabolites were enriched in amino acid metabolism and glycerophospholipid metabolism. The targeted metabolomics showed lower L-tryptophan in EP than PsV with significant difference and L-tryptophan levels were negatively correlated with the PASI scores. The serum metabolic signature of EP was discovered. Amino acid and glycerophospholipid metabolism were dysregulated in EP. The metabolite differences provide clues for pathogenesis of EP and they may provide insights for therapeutic interventions.

Development of metabolome extraction strategy for metabolite profiling of skin tissue

INTRODUCTION

Changes in skin phenotypic characteristics are based on skin tissue. The study of the metabolic changes in skin tissue can help understand the causes of skin diseases and identify effective therapeutic interventions.

OBJECTIVES

We aimed to establish and optimize a non-targeted skin metabolome extraction system for skin tissue metabolomics with high metabolite coverage, recovery, and reproducibility using gas chromatography/mass spectrometry.

METHODS

The metabolites in skin tissues were extracted using eleven different extraction systems, which were designed using reagents with different polarities based on sequential solid-liquid extraction employing a two-step strategy and analyzed using gas chromatograph/mass spectrometry. The extraction efficiency of diverse solvents was evaluated by coefficient of variation (CV), multivariate analysis, metabolites coverage, and relative peak area analysis.

RESULTS

We identified 119 metabolites and the metabolite profiles differed significantly between the eleven extraction systems. Metabolites with high abundances in the organic extraction systems, followed by aqueous extraction, were involved in the biosynthesis of unsaturated fatty acids, while metabolites with high abundances in the aqueous extraction systems, followed by organic extraction, were involved in amino sugar and nucleotide sugar metabolism, and glycerolipid metabolism. MeOH/chloroform-H2O and MeOH/H2O-chloroform were the extraction systems that yielded the highest number of metabolites, while MeOH/acetonitrile (ACN)-H2O and ACN/H2O-IPA exhibited superior metabolite recoveries.

CONCLUSION

Our results demonstrated that our research facilitates the selection of an appropriate metabolite extraction approach based on the experimental purpose for the metabolomics study of skin tissue.

The causal relationship between serum metabolites and the risk of psoriasis: a Mendelian randomization and meta-analysis study

Objective

To explore the influence of serum metabolites on the risk of psoriasis.

Methods

In the initial stage, we applied Mendelian randomization to evaluate the association between 1,400 serum metabolites and the risk of psoriasis. Causal effects were primarily assessed through the Inverse-Variance Weighted method and Wald Ratio's odds ratios, and 95% confidence intervals. False Discovery Rate was used for multiple comparison corrections. Sensitivity analyses were conducted using Cochran's Q Test, MR-PRESSO. MR-Steiger Test was employed to check for reverse causality. In the validation stage, we sought other sources of psoriasis GWAS data to verify the initial results and used meta-analysis to combine the effect sizes to obtain robust causal relationships. In addition, we also conducted metabolic pathway enrichment analysis on known metabolites that have a causal relationship with the risk of psoriasis in both stages.

Results

In the initial stage, we identified 112 metabolites causally associated with psoriasis, including 32 metabolite ratios and 80 metabolites (69 known and 11 unknown). In the validation stage, 24 metabolites (16 known, 1 unknown, and 7 metabolite ratios) were confirmed to have a causal relationship with psoriasis onset. Meta-analysis results showed that the overall effect of combined metabolites was consistent with the main analysis in direction and robust in the causal relationship with psoriasis onset. Of the 16 known metabolites, most were attributed to lipid metabolism, with 5 as risk factors and 8 as protective factors for psoriasis. Peptidic metabolite Gamma-glutamylvaline levels had a negative causal relationship with psoriasis, while exogenous metabolite Catechol sulfate levels and amino acid 3-methylglutaconate levels had a positive causal relationship with the disease onset. The metabolites associated with psoriasis risk in the two stages are mainly enriched in the following metabolic pathways: Glutathione metabolism, Alpha Linolenic Acid and Linoleic Acid Metabolism, Biosynthesis of unsaturated fatty acids, Arachidonic acid metabolism, Glycerophospholipid metabolism.

Conclusion

Circulating metabolites may have a potential causal relationship with psoriasis risk, and targeting specific metabolites may benefit psoriasis diagnosis, disease assessment, and treatment.

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.

Non-Invasive Assessment of Skin Surface Proteins of Psoriasis Vulgaris Patients in Response to Biological Therapy

Measurements of skin surface biomarkers have enormous value for the detailed assessment of skin conditions, both for clinical application and in skin care. The main goals of the current study were to assess whether expression patterns of skin surface hBD-1, hBD-2, IL-1α, CXCL-1, and CXCL-8, examples of proteins known to be involved in psoriasis pathology, are associated with disease severity and whether expression patterns of these proteins on the skin surface can be used to measure pharmacodynamic effects of biological therapy. In this observational study using transdermal analysis patch (TAP), levels of skin surface IL-1α, hBD-1, hBD-2, CXCL-1/2, and CXCL-8 of psoriasis vulgaris (PV) patients over biological therapy were assessed. The Psoriasis Area Severity Index (PASI) and local score for erythema, induration, and desquamation were determined from the exact same skin area as FibroTx TAP measurements. Thirty-seven adult PV patients were included, of which twenty-three were subjected to anti-TNF-α, seven to anti-IL-17A, and seven to anti-IL12/IL-23 therapy. Significantly higher levels of hBD-1, hBD-2, CXCL-1/2, and CXCL-8 were detected on lesional skin compared to the non-lesional skin of the PV patients. In contrast, lower levels of IL-1α were found in lesional skin compared to non-lesional skin. In addition, we observed that the biomarker expression levels correlate with disease severity. Further, we confirmed that changes in the expression levels of skin surface biomarkers during biological therapy correlate with treatment response. Biomarker expression patterns in response to treatment differed somewhat between treatment subtypes. We observed that, in the case of anti-TNF-α therapy, an increase after a steady decrease in the expression levels of CXCL-1/2 and CXCL-8 occurred before the change in clinical scores. Moreover, response kinetics of skin surface proteins differs between the applied therapies-hBD2 expression responds quickly to anti-IL-17A therapy, CXCL-1/2 to anti-IL-12/23, and levels of CXCL-8 are rapidly down-regulated by IL-17A and IL-12/23 therapy. Our findings confirm that the skin surface hBD-2, IL-1α, CXCL-1/2, and CXCL-8 are markers for the psoriasis severity. Further, data obtained during this study give the basis for the conclusion that skin surface proteins CXCL-1/2 and CXCL-8 may have value as therapeutic biomarkers, thus confirming that measuring the 'molecular root' of inflammation appears to have value in scoring disease severity on its own.

Molecular interaction analysis of anti-IL-8 scFv-10F8-6His against IL-8 monomer through molecular docking and molecular dynamic simulations

Elevated interleukin 8 (IL-8) expression has been linked to unfavorable outcomes in a range of inflammatory conditions, such as rheumatoid arthritis, psoriasis, and cancer. The human monoclonal antibody (HuMab) 10F8 and the hybridoma 35B11-B bind to an epitope on human IL-8, respectively. 10F8 inhibited interaction between IL-8 and neutrophils in eczema and pustulosis palmoplantaris patients while 35B11-B decreased size lesion in rat model. The binding interaction of monoclonal antibodies and IL-8, especially how complementarity-determining region (CDR) loops could bind the N-terminal of IL-8, has not been fully deliberated at molecular-level. Here, we used a combination of molecular docking, heated and long coarse-grained molecular dynamics simulations to identify key residues of established interaction. Based on heated MD simulation, docked pose of complexes generated by ClusPro showed good binding stability throughout of 70 ns simulation. Based on long molecular dynamic simulations, key residues for the binding were identified throughout of 1000 ns simulation. TYR-53, ASP-99, and ARG-100 of heavy chain CDR together with TYR-33 of light chain CDR are among the highest contributing energy residues within the binding interaction. Meanwhile, LYS11 and TYR13 of IL-8 are important for the determination of overall binding energy. Furthermore, the result of decomposition residues analysis is in good agreement with the interaction analysis data. Current study provides a list of important interacting residues and further scrutiny on these residues is essential for future development and design of a new and stable recombinant antibody against IL-8.Communicated by Ramaswamy H. Sarma.

The Metabolic Footprint of Systemic Effects in the Blood Caused by Radiotherapy and Inflammatory Conditions: A Systematic Review

Response to radiotherapy (RT) includes tissue toxicity, which may involve inflammatory reactions. We aimed to compare changes in metabolic patterns induced at the systemic level by radiation and inflammation itself. Patients treated with RT due to head and neck cancer and patients with inflammation-related diseases located in the corresponding anatomical regions were selected. PubMed and Web of Science databases were searched from 1 January 2000 to 10 August 2023. Twenty-five relevant studies where serum/plasma metabolic profiles were analyzed using different metabolomics approaches were identified. The studies showed different metabolic patterns of acute and chronic inflammatory diseases, yet changes in metabolites linked to the urea cycle and metabolism of arginine and proline were common features of both conditions. Although the reviewed reports showed only a few specific metabolites common for early RT response and inflammatory diseases, partly due to differences in metabolomics approaches, several common metabolic pathways linked to metabolites affected by radiation and inflammation were revealed. They included pathways involved in energy metabolism (e.g., metabolism of ketone bodies, mitochondrial electron transport chain, Warburg effect, citric acid cycle, urea cycle) and metabolism of certain amino acids (Arg, Pro, Gly, Ser, Met, Ala, Glu) and lipids (glycerolipids, branched-chain fatty acids). However, metabolites common for RT and inflammation-related diseases could show opposite patterns of changes. This could be exemplified by the lysophosphatidylcholine to phosphatidylcholine ratio (LPC/PC) that increased during chronic inflammation and decreased during the early phase of response to RT. One should be aware of dynamic metabolic changes during different phases of response to radiation, which involve increased levels of LPC in later phases. Hence, metabolomics studies that would address molecular features of both types of biological responses using comparable analytical and clinical approaches are needed to unravel the complexities of these phenomena, ultimately contributing to a deeper understanding of their impact on biological systems.

Research progress of metabolomics in psoriasis

ABSTRACT

Psoriasis is a chronic inflammatory skin disease with significant physical and psychological burdens. The interplay between the innate and adaptive immune systems is thought to contribute to the pathogenesis; however, the details of the pathogenesis remain unclear. In addition, reliable biomarkers for diagnosis, assessment of disease activity, and monitoring of therapeutic response are limited. Metabolomics is an emerging science that can be used to identify and analyze low molecular weight molecules in biological systems. During the past decade, metabolomics has been widely used in psoriasis research, and substantial progress has been made. This review summarizes and discusses studies that applied metabolomics to psoriatic disease. These studies have identified dysregulation of amino acids, carnitines, fatty acids, lipids, and carbohydrates in psoriasis. The results from these studies have advanced our understanding of: (1) the molecular mechanisms of psoriasis pathogenesis; (2) diagnosis of psoriasis and assessment of disease activity; (3) the mechanism of treatment and how to monitor treatment response; and (4) the link between psoriasis and comorbid diseases. We discuss common research strategies and progress in the application of metabolomics to psoriasis, as well as emerging trends and future directions.

Inhibition of LPS-Induced Inflammatory Response of Oral Mesenchymal Stem Cells in the Presence of Galectin-3

Galectin-3 (GAL-3) is a beta-galactoside binding lectin produced by mesenchymal stem cells (MSCs) and other cell sources under inflammatory conditions. Several studies have reported that GAL-3 exerts an anti-inflammatory action, regulated by its natural ligand GAL-3 BP. In the present study, we aimed to assess the GAL-3 mediated regulation of the MSC function in an LPS-induced inflammation setting. Human gingival mesenchymal stem cells (hGMSCs) were stimulated in vitro with LPSs; the expression of TLR4, NFκB p65, MyD88 and NALP3 were assessed in the hGMSCs via immunofluorescence imaging using confocal microscopy, Western blot assay, and RT-PCR before and after the addition of GAL-3, both alone and with the addition of its inhibitors. LPSs stimulated the expression of TLR4, NFκB p65, MyD88 and NALP3 in hGMSCs, which was inhibited by GAL-3. The addition of either GAL3-BP or the antibody to GAL-3 were able to revert the GAL-3-mediated effects, restoring the expression of TLR4, NFκB p65, MyD88 and NALP3. GAL-3 induces the downregulation of the LPS-induced inflammatory program in MSCs.

High-resolution magic angle spinning NMR for intact biological specimen analysis: Initial discovery, recent developments, and future directions

High-resolution magic angle spinning (HRMAS) NMR, an approach for intact biological material analysis discovered more than 25 years ago, has been advanced by many technical developments and applied to many biomedical uses. This article provides a history of its discovery, first by explaining the key scientific advances that paved the way for HRMAS NMR's invention, and then by turning to recent developments that have profited from applying and advancing the technique during the last 5 years. Developments aimed at directly impacting healthcare include HRMAS NMR metabolomics applications within studies of human disease states such as cancers, brain diseases, metabolic diseases, transplantation medicine, and adiposity. Here, the discussion describes recent HRMAS NMR metabolomics studies of breast cancer and prostate cancer, as well as of matching tissues with biofluids, multimodality studies, and mechanistic investigations, all conducted to better understand disease metabolic characteristics for diagnosis, opportune windows for treatment, and prognostication. In addition, HRMAS NMR metabolomics studies of plants, foods, and cell structures, along with longitudinal cell studies, are reviewed and discussed. Finally, inspired by the technique's history of discoveries and recent successes, future biomedical arenas that stand to benefit from HRMAS NMR-initiated scientific investigations are presented.

Current Knowledge in Skin Metabolomics: Updates from Literature Review

Metabolomic profiling is an emerging field consisting of the measurement of metabolites in a biological system. Since metabolites can vary in relation to different stimuli, specific metabolic patterns can be closely related to a pathological process. In the dermatological setting, skin metabolomics can provide useful biomarkers for the diagnosis, prognosis, and therapy of cutaneous disorders. The main goal of the present review is to present a comprehensive overview of the published studies in skin metabolomics. A search for journal articles focused on skin metabolomics was conducted on the MEDLINE, EMBASE, Cochrane, and Scopus electronic databases. Only research articles with electronically available English full text were taken into consideration. Studies specifically focused on cutaneous microbiomes were also excluded from the present search. A total of 97 papers matched all the research criteria and were therefore considered for the present work. Most of the publications were focused on inflammatory dermatoses and immune-mediated cutaneous disorders. Skin oncology also turned out to be a relevant field in metabolomic research. Only a few papers were focused on infectious diseases and rarer genetic disorders. All the major metabolomic alterations published so far in the dermatological setting are described extensively in this review.

Toward Personalized Interventions for Psoriasis Vulgaris: Molecular Subtyping of Patients by Using a Metabolomics Approach

Aim: Psoriasis vulgaris (PV) is a complicated autoimmune disease characterized by erythema of the skin and a lack of available cures. PV is associated with an increased risk of metabolic syndrome and cardiovascular disease, which are both mediated by the interaction between systemic inflammation and aberrant metabolism. However, whether there are differences in the lipid metabolism between different levels of severity of PV remains elusive. Hence, we explored the molecular evidence for the subtyping of PV according to alterations in lipid metabolism using serum metabolomics, with the idea that such subtyping may contribute to the development of personalized treatment.

Methods: Patients with PV were recruited at a dermatology clinic and classified based on the presence of metabolic comorbidities and their Psoriasis Area and Severity Index (PASI) from January 2019 to November 2019. Age- and sex-matched healthy controls were recruited from the preventive health department of the same institution for comparison. We performed targeted metabolomic analyses of serum samples and determined the correlation between metabolite composition and PASI scores.

Results: A total of 123 participants, 88 patients with PV and 35 healthy subjects, were enrolled in this study. The patients with PV were assigned to a “PVM group” (PV with metabolic comorbidities) or a “PV group” (PV without metabolic comorbidities) and further subdivided into a “mild PV” (MP, PASI <10) and a “severe PV” (SP, PASI ≥10) groups. Compared with the matched healthy controls, levels of 27 metabolites in the MP subgroup and 28 metabolites in the SP subgroup were found to be altered. Among these, SM (d16:0/17:1) and SM (d19:1/20:0) were positively correlated with the PASI in the MP subgroup, while Cer (d18:1/18:0), PC (18:0/22:4), and PC (20:0/22:4) were positively correlated with the PASI in the SP subgroup. In the PVM group, levels of 17 metabolites were increased, especially ceramides and phosphatidylcholine, compared with matched patients from the PV group. In addition, the correlation analysis indicated that Cer (d18:1/18:0) and SM (d16:1/16:1) were not only correlated with PASI but also has strongly positive correlations with biochemical indicators.

Conclusion: The results of this study indicate that patients with PV at different severity levels have distinct metabolic profiles, and that metabolic disorders complicate the disease development. These findings will help us understand the pathological progression and establish strategies for the precision treatment of PV.

Therapeutic Potential of Combining IL-6 and TNF Blockade in a Mouse Model of Allergic Asthma

Combined anti-cytokine therapy is a promising therapeutic approach for uncontrolled steroid-resistant asthma. In this regard, simultaneous blockade of IL-4 and IL-13 signaling by Dupilumab (anti-IL-4Ra monoclonal antibody) was recently approved for severe eosinophilic asthma. However, no therapeutic options for neutrophilic asthma are currently available. Recent advances in our understanding of asthma pathogenesis suggest that both IL-6 and TNF may represent potential targets for treatment of severe neutrophilic asthma. Nevertheless, the efficacy of simultaneous pharmacological inhibition of TNF and IL-6 in asthma was not yet studied. To evaluate the potency of combined cytokine inhibition, we simultaneously administrated IL-6 and TNF inhibitors to BALB/c mice with HDM-induced asthma. Combined IL-6/TNF inhibition, but not individual blockade of these two cytokines, led to complex anti-inflammatory effects including reduced Th2-induced eosinophilia and less prominent Th17/Th1-mediated neutrophilic infiltrate in the airways. Taken together, our results provide evidence for therapeutic potential of combined IL-6/TNF inhibition in severe steroid-resistant asthma.

A systematic review: metabolomics-based identification of altered metabolites and pathways in the skin caused by internal and external factors

The skin's ability to function optimally is affected by many diverse factors. Metabolomics has a great potential to improve our understanding of the underlying metabolic changes and the affected pathways. Therefore, the objective of this study was to review the current state of the literature and to perform further metabolic pathway analysis on the obtained data. The aim was to gain an overview of the metabolic changes under altered conditions and to identify common and different patterns as a function of the investigated factors. A cross-study comparison of the extracted studies from different databases identified 364 metabolites, whose concentrations were considerably altered by the following factor groups: irradiation, xenobiotics, aging, and skin diseases (mainly psoriasis). Using metabolic databases and pathway analysis tools the individual metabolites were assigned to the corresponding metabolic pathways and the most strongly affected signaling pathways were identified. All factors induced oxidative stress. Thus, antioxidant defense systems, especially coenzyme Q₁₀  (aging) and the glutathione system (irradiation, aging, xenobiotics) were impacted. Lipid metabolism was also impacted by all factors studied. The carnitine shuttle as part of β-oxidation was activated by all factor groups except aging. Glycolysis, Krebs (TCA) cycle and purine metabolism were mainly affected by irradiation and xenobiotics. The pentose phosphate pathway was activated and Krebs cycle was downregulated in response to oxidative stress. In summary, it can be ascertained that mainly energy metabolism, lipid metabolism, antioxidative defense and DNA repair systems were impacted by the factors studied.