Circulating Metabolomic Signature in Generalized Pustular Psoriasis Blunts Monocyte Hyperinflammation by Triggering Amino Acid Response

From rare to more common: The emerging role of omics in improving understanding and treatment of severe inflammatory and hyperinflammatory conditions

Inflammation is a pathogenic driver of many diseases, including atherosclerosis and rheumatoid arthritis. Hyperinflammation can be seen as any inflammatory response that is deleterious to the host, regardless of cause. In medicine, hyperinflammation is defined as severe, deleterious, and fluctuating systemic or local inflammation with presence of a cytokine storm. It has been associated with rare autoinflammatory disorders. However, advances in omics technologies, including genomics, proteomics, and metabolomics, have revealed it to be more common, occurring in sepsis and severe coronavirus disease 2019. With a focus on proteomics, this review highlights the key role of omics in this shift. Through an exploration of research, we present how omics technologies have contributed to improved diagnostics, prognostics, and targeted therapeutics in the field of hyperinflammation. We also discuss the integration of advanced technologies, multiomics approaches, and artificial intelligence in analyzing complex datasets to develop targeted therapies, and we address their potential for revolutionizing the clinical aspects of hyperinflammation. We emphasize personalized medicine approaches for effective treatments and outline challenges, including the need for standardized methodologies, robust bioinformatics tools, and ethical considerations regarding data privacy. This review aims to provide a comprehensive overview of the molecular mechanisms underpinning hyperinflammation and underscores the potential of omics technologies in enabling successful clinical management.

A Snapshot of Biomarkers in Psoriasis

A persistent long-standing, inflammatory skin condition that is brought on by a variety of factors is psoriasis. It is distinguished by itchy, scaly, reddish plaques, particularly on areas of the body that are frequently chafed, including the extensor sites of the limbs. Recent developments in molecular-targeted therapy that use biologics or small-molecule inhibitors can effectively cure even the worst psoriatic indications. The outstanding clinical outcomes of treatment help to clarify the disease's detrimental consequences on quality of life. Biomarkers that identify deep remission are essential for developing uniform treatment plans. Blood protein markers such as AMPs that are consistently quantifiable can be very helpful in routine clinical practice. The metabolic pathways involve biomarkers that can not only help diagnose psoriasis in a clinical setting but also indicate its severity based on the levels present in the body. Machine learning and AI have made a diagnosis of the expression of genes as biomarkers more accessible. In this article, biomarkers, as well as their key role in psoriasis, are discussed.

A multimodality score strategy for assessing the risk of immune checkpoint inhibitors related cardiotoxicity

This study aimed to find the association between four common clinical biomarkers and subsequent ICICT, developing a risk scoring strategy to assess the ICICT risk. Three terminals for ICICT were : Terminal 1, cancer therapy-related cardiomyopathies; Terminal 2, myocarditis or heart failure; and Terminal 3, myocarditis, heart failure, myocardial infarction, cerebral infarction, atrial fibrillation, or death. The thresholds were : N-terminal-pro-B-type-natriuretic-peptide ≥ 125 pg/mL, cardiac troponin T ≥ 6 ng/L, high-sensitivity C-reactive protein ≥ 3 mg/L, and coronary artery calcium score > 10 U. Each of the four abnormal biomarkers received 1 point. The links between biomarkers, score stage, and ICICT were analyzed. 375 patients with a mean follow-up of 1.91 years were included. All four biomarkers measured before immunotherapy were associated with a higher risk of developing ICICT. These scores were also associated with ICICT risk. The highest risk was the very high stage (score = 4) has 7.29, 8.83, and 7.02 folder higher risk compared to low risk group for Terminal 1-3, respectively. The cumulation of incidences also showed that the higher stages of score had an earlier onset and higher incidence of ICICT. 4 biomarkers and the scoring strategy enables clinicians to assess risk easily.

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.

Bcat2-Mediated Branched-Chain Amino Acid Catabolism Is Linked to the Aggravated Inflammation in Obese with Psoriasis Mice

SCOPE

The global prevalence of obesity has significantly increased, presenting a major health challenge. High-fat diet (HFD)-induced obesity is closely related to the disease severity of psoriasis, but the mechanism is not fully understood.

METHODS AND RESULTS

The study utilizes the HFD-induced obesity model along with an imiquimod (IMQ)-induced psoriasis-like mouse model (HFD-IMQ) to conduct transcriptomics and metabolomic analyses. HFD-induced obese mice exhibits more severe psoriasis-like lesions compared to normal diet (ND)-IMQ mice. The expression of genes of the IL-17 signaling pathway (IL-17A, IL-17F, S100A9, CCL20, CXCL1) is significantly upregulated, leading to an accumulation of T cells and neutrophils in the skin. Moreover, the study finds that there is an inhibition of the branched-chain amino acids (BCAAs) catabolism pathway, and the key gene branched-chain amino transferase 2 (Bcat2) is significantly downregulated, and the levels of leucine, isoleucine, and valine are elevated in the HFD-IMQ mice. Furthermore, the study finds that the peroxisome proliferator-activated receptor gamma (PPAR γ) is inhibited, while STAT3 activity is promoted in HFD-IMQ mice.

CONCLUSION

HFD-induced obesity significantly amplifies IL-17 signaling and exacerbates psoriasis, with a potential role played by Bcat2-mediated BCAAs metabolism. The study suggests that BCAA catabolism and PPAR γ-STAT3 exacerbate inflammation in psoriasis with obesity.

The role and application of three IFN-related reactions in psoriasis

The pathophysiology of psoriasis is a highly complicated one. Due to the disease's specificity, it not only affects the patient's skin negatively but also manifests systemic pathological changes. These clinical symptoms seriously harm the patient's physical and mental health. IFN, a common immunomodulatory factor, has been increasingly demonstrated to have a significant role in the development of psoriatic skin disease. Psoriasis is connected with a variety of immunological responses. New targets for the therapy of autoimmune skin diseases may emerge from further research on the mechanics of the associated IFN upstream and downstream pathways. Different forms of IFNs do not behave in the same manner in psoriasis, and understanding how different types of IFNs are involved in psoriasis may provide a better notion for future research. This review focuses on the involvement of three types of IFNs in psoriasis and related therapeutic investigations, briefly describing the three IFNs' production and signaling, as well as the dual effects of IFNs on the skin. It is intended that it would serve as a model for future research.

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.

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.

Interactions between the NLRP3-Dependent IL-1β and the Type I Interferon Pathways in Human Plasmacytoid Dendritic Cells

Generally, a reciprocal antagonistic interaction exists between the antiviral type I interferon (IFN) and the antibacterial nucleotide-binding oligomerization domain (NOD)-like receptor pyrin domain containing 3 (NLRP3)-dependent IL-1β pathways that can significantly shape immune responses. Plasmacytoid dendritic cells (pDCs), as professional type I IFN-producing cells, are the major coordinators of antiviral immunity; however, their NLRP3-dependent IL-1β secretory pathway is poorly studied. Our aim was to determine the functional activity of the IL-1β pathway and its possible interaction with the type I IFN pathway in pDCs. We found that potent nuclear factor-kappa B (NF-κB) inducers promote higher levels of pro-IL-1β during priming compared to those activation signals, which mainly trigger interferon regulatory factor (IRF)-mediated type I IFN production. The generation of cleaved IL-1β requires certain secondary signals in pDCs and IFN-α or type I IFN-inducing viruses inhibit IL-1β production of pDCs, presumably by promoting the expression of various NLRP3 pathway inhibitors. In line with that, we detected significantly lower IL-1β production in pDCs of psoriasis patients with elevated IFN-α levels. Collectively, our results show that the NLRP3-dependent IL-1β secretory pathway is inducible in pDCs; however, it may only prevail under inflammatory conditions, in which the type I IFN pathway is not dominant.

Classification and biomarker gene selection of pyroptosis-related gene expression in psoriasis using a random forest algorithm

Background: Psoriasis is a chronic and immune-mediated skin disorder that currently has no cure. Pyroptosis has been proved to be involved in the pathogenesis and progression of psoriasis. However, the role pyroptosis plays in psoriasis remains elusive.

Methods: RNA-sequencing data of psoriasis patients were obtained from the Gene Expression Omnibus (GEO) database, and differentially expressed pyroptosis-related genes (PRGs) between psoriasis patients and normal individuals were obtained. A principal component analysis (PCA) was conducted to determine whether PRGs could be used to distinguish the samples. PRG and immune cell correlation was also investigated. Subsequently, a novel diagnostic model comprising PRGs for psoriasis was constructed using a random forest algorithm (ntree = 400). A receiver operating characteristic (ROC) analysis was used to evaluate the classification performance through both internal and external validation. Consensus clustering analysis was used to investigate whether there was a difference in biological functions within PRG-based subtypes. Finally, the expression of the kernel PRGs were validated in vivo by qRT-PCR.

Results: We identified a total of 39 PRGs, which could distinguish psoriasis samples from normal samples. The process of T cell CD4 memory activated and mast cells resting were correlated with PRGs. Ten PRGs, IL-1β, AIM2, CASP5, DHX9, CASP4, CYCS, CASP1, GZMB, CHMP2B, and CASP8, were subsequently screened using a random forest diagnostic model. ROC analysis revealed that our model has good diagnostic performance in both internal validation (area under the curve [AUC] = 0.930 [95% CI 0.877–0.984]) and external validation (mean AUC = 0.852). PRG subtypes indicated differences in metabolic processes and the MAPK signaling pathway. Finally, the qRT-PCR results demonstrated the apparent dysregulation of PRGs in psoriasis, especially AIM2 and GZMB.

Conclusion: Pyroptosis may play a crucial role in psoriasis and could provide new insights into the diagnosis and underlying mechanisms of psoriasis.

Plasma metabolomic profiling reflects the malnourished and chronic inflammatory state in recessive dystrophic epidermolysis bullosa

BACKGROUND

Recessive dystrophic epidermolysis bullosa (RDEB) is a hereditary blistering disorder characterized by skin fragility, chronic inflammation, malnutrition, and fibrosis. Metabolomics is an emerging investigative field that helps elucidate disease pathophysiology and identify biomarkers. However, previous metabolomic studies in RDEB are limited.

OBJECTIVE

To investigate the plasma metabolomic profiles in RDEB patients.

METHODS

We recruited 10 RDEB patients and 10 age-/gender-matched healthy controls. Peripheral blood samples were collected and plasma metabolomic profiling was performed by LC-MS/MS analysis. MS data processing and compound identification were executed by MS-DIAL. Enrichment analysis was performed by MetaboAnalyst 5.0.

RESULTS

Metabolomic analyses demonstrated that most amino acid levels were downregulated in RDEB patients, and the extent of insufficiency correlated with clinical severity. Several metabolites were dysregulated in RDEB, including glutamine and glutamate metabolism, tryptophan-to-kynurenine ratio, phenylalanine-to-tyrosine ratio, and succinate accumulation.

LIMITATIONS

The study was limited by small case numbers and the unrepresentativeness of a single time-point blood sample.

CONCLUSION

Our study demonstrated the altered metabolomic profiles in RDEB, reflecting the disease severity, the chronic inflammatory and malnourished status, while the fibrotic signatures were not evident.