Metabolomic profile of systemic sclerosis patients

NMR-based metabolomic signature: An important tool for the diagnosis and study of pathogenesis of autoimmune hepatitis

BACKGROUND AND AIMS

Metabolomics is used to predict, diagnose, and monitor metabolic disorders but altered metabolomic signatures have also been reported in diverse diseases, including autoimmune disorders. However, the metabolomic profile in autoimmune hepatitis (AIH) has not been investigated in depth. Therefore, we investigated the metabolomic signature of AIH and its significance as a diagnostic and pathogenetic tool.

APPROACH AND RESULTS

Metabolites in plasma samples from 50 patients with AIH at diagnosis, 43 healthy controls, 72 patients with primary biliary cholangitis (PBC), 26 patients with metabolic dysfunction-associated liver disease, and 101 patients with chronic viral hepatitis were determined by 1 H NMR (nuclear magnetic resonance) spectroscopy. Fifty-two metabolites were quantified, and metabolic pathway analysis was performed. Multivariate analysis revealed that AIH could be differentiated from healthy controls and each of the disease controls ( p <0.001). Fifteen metabolites differentiated AIH from disease controls (PBC+chronic viral hepatitis+metabolic dysfunction-associated liver disease) (95% sensitivity and 92% specificity). Ten distinct metabolic pathways were altered in AIH compared to disease controls. The metabolic pathway of branched-chain amino acids (lower valine, leucine, and isoleucine levels and their catabolic intermediates in PBC), methionine (lower methionine, 2-aminobutyrate, and 2-hydroxybutyrate levels in PBC), alanine-aspartate-glutamate (lower metabolites in PBC), and that of metabolites associated with gut microbiota (lower choline, betaine, and dimethylamine levels in PBC) were significantly different between AIH and PBC ( p <0.01).

CONCLUSIONS

1 H NMR spectroscopy could be a promising novel tool to diagnose and study AIH pathogenesis as there is no need for much sample handling, is highly reproducible with high sensitivity and specificity, and low cost.

Metabolic fingerprinting of systemic sclerosis: a systematic review

Introduction: Systemic sclerosis (SSc) is a chronic autoimmune disease, marked by an unpredictable course, high morbidity, and increased mortality risk that occurs especially in the diffuse and rapidly progressive forms of the disease, characterized by fibrosis of the skin and internal organs and endothelial dysfunction. Recent studies suggest that the identification of altered metabolic pathways may play a key role in understanding the pathophysiology of the disease. Therefore, metabolomics might be pivotal in a better understanding of these pathogenic mechanisms. Methods: Through a systematic review of the literature following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Guidelines (PRISMA), searches were done in the PubMed, EMBASE, Web of Science, and Scopus databases from 2000 to September 2022. Three researchers independently reviewed the literature and extracted the data based on predefined inclusion and exclusion criteria. Results: Of the screened studies, 26 fulfilled the inclusion criteria. A total of 151 metabolites were differentially distributed between SSc patients and healthy controls (HC). The main deregulated metabolites were those derived from amino acids, specifically homocysteine (Hcy), proline, alpha-N-phenylacetyl-L-glutamine, glutamine, asymmetric dimethylarginine (ADMA), citrulline and ornithine, kynurenine (Kyn), and tryptophan (Trp), as well as acylcarnitines associated with long-chain fatty acids and tricarboxylic acids such as citrate and succinate. Additionally, differences in metabolic profiling between SSc subtypes were identified. The diffuse cutaneous systemic sclerosis (dcSSc) subtype showed upregulated amino acid-related pathways involved in fibrosis, endothelial dysfunction, and gut dysbiosis. Lastly, potential biomarkers were evaluated for the diagnosis of SSc, the identification of the dcSSc subtype, pulmonary arterial hypertension, and interstitial lung disease. These potential biomarkers are within amino acids, nucleotides, carboxylic acids, and carbohydrate metabolism. Discussion: The altered metabolite mechanisms identified in this study mostly point to perturbations in amino acid-related pathways, fatty acid beta-oxidation, and in the tricarboxylic acid cycle, possibly associated with inflammation, vascular damage, fibrosis, and gut dysbiosis. Further studies in targeted metabolomics are required to evaluate potential biomarkers for diagnosis, prognosis, and treatment response.

Serum metabolomic profiling reveals potential biomarkers in systemic sclerosis

BACKGROUND

Systemic sclerosis (SSc) is a chronic and systemic autoimmune disease marked by the skin and visceral fibrosis. Metabolic alterations have been found in SSc patients; however, serum metabolomic profiling has not been thoroughly conducted. Our study aimed to identify alterations in the metabolic profile in both SSc patients before and during treatment, as well as in mouse models of fibrosis. Furthermore, the associations between metabolites and clinical parameters and disease progression were explored.

METHODS

High-performance liquid chromatography quadrupole time-of-flight mass spectrometry (HPLC-Q-TOF-MS)/MS was performed in the serum of 326 human samples and 33 mouse samples. Human samples were collected from 142 healthy controls (HC), 127 newly diagnosed SSc patients without treatment (SSc baseline), and 57 treated SSc patients (SSc treatment). Mouse serum samples were collected from 11 control mice (NaCl), 11 mice with bleomycin (BLM)-induced fibrosis and 11 mice with hypochlorous acid (HOCl)-induced fibrosis. Both univariate analysis and multivariate analysis (orthogonal partial least-squares discriminate analysis (OPLS-DA)) were conducted to unravel differently expressed metabolites. KEGG pathway enrichment analysis was performed to characterize the dysregulated metabolic pathways in SSc. Associations between metabolites and clinical parameters of SSc patients were identified by Pearson's or Spearman's correlation analysis. Machine learning (ML) algorithms were applied to identify the important metabolites that have the potential to predict the progression of skin fibrosis.

RESULTS

The newly diagnosed SSc patients without treatment showed a unique serum metabolic profile compared to HC. Treatment partially corrected the metabolic changes in SSc. Some metabolites (phloretin 2'-O-glucuronide, retinoyl b-glucuronide, all-trans-retinoic acid, and betaine) and metabolic pathways (starch and sucrose metabolism, proline metabolism, androgen and estrogen metabolism, and tryptophan metabolism) were dysregulated in new-onset SSc, but restored upon treatment. Some metabolic changes were associated with treatment response in SSc patients. Metabolic changes observed in SSc patients were mimicked in murine models of SSc, indicating that they may reflect general metabolic changes associated with fibrotic tissue remodeling. Several metabolic changes were associated with SSc clinical parameters. The levels of allysine and all-trans-retinoic acid were negatively correlated, while D-glucuronic acid and hexanoyl carnitine were positively correlated with modified Rodnan skin score (mRSS). In addition, a panel of metabolites including proline betaine, phloretin 2'-O-glucuronide, gamma-linolenic acid and L-cystathionine were associated with the presence of interstitial lung disease (ILD) in SSc. Specific metabolites identified by ML algorithms, such as medicagenic acid 3-O-b-D-glucuronide, 4'-O-methyl-(-)-epicatechin-3'-O-beta-glucuronide, valproic acid glucuronide, have the potential to predict the progression of skin fibrosis.

CONCLUSIONS

Serum of SSc patients demonstrates profound metabolic changes. Treatment partially restored the metabolic changes in SSc. Moreover, certain metabolic changes were associated with clinical manifestations such as skin fibrosis and ILD, and could predict the progression of skin fibrosis.

Systemic Sclerosis Patients Experiencing Mindfulness-Based Stress Reduction Program: The Beneficial Effect on Their Psychological Status and Quality of Life

Psychological concerns in Systemic Sclerosis (SSc) patients represent an important issue and should be addressed through non-pharmacological treatments. Thus, the aim of the present study was to assess the effects of the Mindfulness-Based Stress Reduction (MBSR) program on psychological variables and the perspectives and experiences of patients with an SSc diagnosis. Notably, 32 SSc patients were enrolled and assigned to either the intervention (MBSR) group or the waitlist group. Inclusion criteria were (i) age ≥ 18 years, SSc diagnosis according to EULAR/ACR diagnostic criteria and informed consent. Exclusion criteria were previous participation in any Mind-Body Therapy or psychiatric diagnosis. Quantitative and qualitative outcomes were investigated through clinometric questionnaires and individual interviews. MBSR did not significantly impact outcomes such as physical functionality, anxiety, hopelessness, depression, physical health status, perceived stress, mindfulness and mental health status. For the anger evaluation, statistically significant differences are found for both controlling and expressing anger, indicating that the MBSR program had a favorable impact. As for qualitative results, more awareness of daily activities, stress reduction in terms of recognizing the causes and implementing self-strategies to prevent them, adherence to therapy, and recognition of the effect of medication on their bodies were reported. In conclusion, it is important to highlight the absence of negative or side effects of the MBSR program and the positive impact on patients' experience and perspective; thus, we suggest this approach should be taken into account for SSc patients.

The Metabolomic Characterization of Different Types of Coronary Atherosclerotic Heart Disease in Male

Background

In clinical practice, many patients with coronary atherosclerotic heart disease (CAD) have atypical clinical symptoms. It is difficult to accurately identify stable CAD or unstable CAD early through clinical symptoms and coronary angiography. This study aimed to screen the potential metabolite biomarkers in male patients with stable CAD and unstable CAD.

Methods

In this work, the metabolomic characterization of the male patients with healthy control (n = 42), stable coronary artery disease (n = 60), non-ST-elevation acute coronary syndrome (n = 45), including prepercutaneous corona intervention (n = 14), and postpercutaneous coronary intervention (n = 31) were performed by using ultra-performance liquid chromatography-mass spectrometry (UPLC-MS). The serum samples of patients were analyzed by multivariate statistics.

Results

Results showed that 17 altered metabolites were identified to have a clear distinction between the stable CAD group and the healthy subjects. Compared with the stable coronary artery disease group, 15 specific metabolite markers were found in the acute coronary syndrome group. The percutaneous coronary intervention also affected the metabolic behavior of patients with CAD.

Conclusions

In summary, CAD is closely related to energy metabolism, lipid metabolism, and amino acid metabolism disorders. The different metabolic pattern characteristics of healthy, stable coronary artery disease and acute coronary syndrome are constructed, which brings a novel theoretical basis for the early diagnosis of patients with stable and unstable CAD.

Plasma Metabolomics Identifies the Dysregulated Metabolic Profile of Primary Immune Thrombocytopenia (ITP) Based on GC-MS

ITP is a common autoimmune bleeding disorder with elusive pathogenesis. Our study was implemented to profile the plasma metabolic alterations of patients diagnosed with ITP, aiming at exploring the potential novel biomarkers and partial mechanism of ITP. The metabolomic analysis of plasma samples was conducted using GC-MS on 98 ITP patients and 30 healthy controls (HCs). Age and gender matched samples were selected to enter the training set or test set respectively. OPLS-DA, t-test with FDR correction and ROC analyses were employed to screen out and evaluate the differential metabolites. Possible pathways were enriched based on metabolomics pathway analysis (MetPA). A total of 85 metabolites were investigated in our study and 17 differential metabolites with diagnostic potential were identified between ITP patients and HCs. MetPA showed that the metabolic disorders of ITP patients were mainly related to phenylalanine, tyrosine and tryptophan biosynthesis, phenylalanine metabolism and glyoxylate and dicarboxylate metabolism. Additionally, we discriminated 6 differential metabolites and 5 enriched pathways in predicting the resistance to glucocorticoids in chronic ITP patients. The distinct metabolites discovered in our study could become novel biomarkers for the auxiliary diagnosis and prognosis prediction of ITP. Besides, the dysregulated pathways might contribute to the development of ITP.

Plasma Metabolomic Profiling Reveals Four Possibly Disrupted Mechanisms in Systemic Sclerosis

Systemic sclerosis (SSc) is a rare systemic autoimmune disorder marked by high morbidity and increased risk of mortality. Our study aimed to analyze metabolomic profiles of plasma from SSc patients by using targeted and untargeted metabolomics approaches. Furthermore, we aimed to detect biochemical mechanisms relevant to the pathophysiology of SSc. Experiments were performed using high-performance liquid chromatography coupled to mass spectrometry technology. The investigation of plasma samples from SSc patients (n = 52) compared to a control group (n = 48) allowed us to identify four different dysfunctional metabolic mechanisms, which can be assigned to the kynurenine pathway, the urea cycle, lipid metabolism, and the gut microbiome. These significantly altered metabolic pathways are associated with inflammation, vascular damage, fibrosis, and gut dysbiosis and might be relevant for the pathophysiology of SSc. Further studies are needed to explore the role of these metabolomic networks as possible therapeutic targets of SSc.

Metabolic perturbations in fibrosis disease

Metabolic changes occur in all forms of disease but their impact on fibrosis is a relatively recent area of interest. This review provides an overview of the major metabolic pathways, glycolysis, amino acid metabolism and lipid metabolism, and highlights how they influence fibrosis at a cellular and tissue level, drawing on key discoveries in dermal, renal, pulmonary and hepatic fibrosis. The emerging influence of adipose tissue-derived cytokines is discussed and brings a link between fibrosis and systemic metabolism. To close, the concept of targeting metabolism for fibrotic therapy is reviewed, drawing on lessons from the more established field of cancer metabolism, with an emphasis on important considerations for clinical translation.

Association of metabolomic markers and response to nutritional support: A secondary analysis of the EFFORT trial using an untargeted metabolomics approach

BACKGROUND & AIMS

The EFFORT trial reported a substantial risk reduction for adverse events and mortality in medical in-patients receiving a nutritional support intervention. With the use of an untargeted metabolomics approach, we investigated the prognostic and therapeutic potential of metabolomic markers to understand, whether there are distinct metabolic patterns associated with malnutrition risk as assessed by the Nutritional Risk screening (NRS 2002) score, the risk of 30-day mortality and the response to nutritional support, respectively.

METHODS

Out of the 2088 samples we randomly selected 120 blood samples drawn on day 1 after hospital admission and before treatment initiation. Samples were stratified by NRS 2002, treatment allocation (intervention vs. control), and mortality at 30 days, but not on the type of medical illness. We performed untargeted analysis by liquid chromatography mass spectrometry (LC-MS/MS).

RESULTS

We measured 1389 metabolites in 120 patients of which 81 (67.5%) survived until day 30. After filtering, 371 metabolites remained, and 200 were matched to one or more Human Metabolome Data Base (HMDB) entries. Between group analysis showed a slight distinction between the treatment groups for patients with a NRS 3, but not for those with NRS 4 and ≥ 5. C-statistic between those who died and survived at day 30 ranged from 0.49 (95% confidence interval 0.35-0.68) for a combination of 5 metabolites/predictors to 0.66 (95% confidence interval 0.53-0.79) for a combination of 100 metabolites. Pathway analysis found significant enrichment in the pathways for nitrogen, vitamin B3 (nicotinate and nicotinamide), leukotriene, and arachidonic acid metabolisms in nutritional support responders compared to non-responders.

CONCLUSION

In our heterogenous population of medical inpatients with different illnesses and comorbidities, metabolomic markers showed little prognostic and therapeutic potential for better phenotyping malnutrition and response to nutritional therapy. Future studies should focus on more selected patient populations to understand whether a metabolomic approach can advance the nutritional care of patients.

[Autologous hematopoietic cells for severe autoimmune diseases: Guidelines of the Francophone Society of Bone Marrow Transplantation and Cellular Therapy (SFGM-TC) for immune monitoring and biobanking]

Autologous hematopoietic cell transplantation (AHCT) is a new treatment option for patients with severe autoimmune diseases (AD), based on the use of intensive or myeloablative chemotherapy to eradicate the pathogenic autoreactive immune cells and to allow the installation of a new and tolerant immune system during immune reconstitution process. Immune reconstitution analysis after AHCT is required for patients clinical follow-up and to further identify biological and immunological markers of the clinical response to develop individualized AHCT protocols. These MATHEC-SFGM-TC good clinical practice guidelines were developed by a multidisciplinary group of experts including members of the french reference center for stem Cell Therapy in Auto-immune Diseases (MATHEC), hematologists from the French speaking Society of Bone Marrow Transplantation and Cellular Therapy (SFGM-TC) and experts in immune monitoring and biobanking. The objectives are to provide practical recommandations for immune monitoring and biobanking of samples in patients with AD undergoing AHCT, for routine care purposes and investigational studies.

Novel classifications for systemic sclerosis: challenging historical subsets to unlock new doors

PURPOSE OF REVIEW

Systemic sclerosis (SSc) is a severe rheumatic disease characterized by a considerable heterogeneity in clinical presentations and pathophysiological mechanisms. This variability has a substantial impact on morbidity and mortality and limits the generalizability of clinical trial results. This review aims to highlight recent studies that have proposed new innovative approaches to decipher this heterogeneity, in particular, by attempting to optimize disease classification.

RECENT FINDINGS

The historical dichotomy limited/diffuse subsets based on cutaneous involvement has been challenged by studies highlighting an underestimated heterogeneity between these two subtypes and showing that presence of organ damage and autoantibody profiles markedly influenced survival beyond skin extension. Advanced computational methods using unsupervised machine learning analyses of clinical variables and/or high-throughput omics technologies, clinical variables trajectories modelling overtime or radiomics have provided significant insights on key pathogenic processes that could help defining new subgroups beyond the diffuse/limited subsets.

SUMMARY

We can anticipate that a future classification of SSc patients will integrate innovative approaches encompassing clinical phenotypes, variables trajectories, serological features and innovative omics molecular signatures. It nevertheless seems crucial to also pursue the implementation and standardization of readily available and easy to use tools that can be used in clinical practice.

Breathomics to diagnose systemic sclerosis using thermal desorption and comprehensive two-dimensional gas chromatography high-resolution time-of-flight mass spectrometry

Systemic sclerosis is a rare autoimmune disease associated with rapidly evolving interstitial lung disease, responsible for the disease severity and mortality. Specific biomarkers enabling the early diagnosis and prognosis associated with the disease progression are highly needed. Volatile organic compounds in exhaled breath are widely available and non-invasive and have the potential to reflect metabolic processes occurring within the body. Comprehensive two-dimensional gas chromatography coupled to high-resolution mass spectrometry was used to investigate the potential of exhaled breath to diagnose systemic sclerosis. The exhaled breath of 32 patients and 30 healthy subjects was analyzed. The high resolving power of this approach enabled the detection of 356 compounds in the breath of systemic sclerosis patients, which was characterized by an increase of mainly terpenoids and hydrocarbons. In addition, the use of 4 complementary statistical approaches (two-tailed equal variance t-test, fold change, partial least squares discriminant analysis, and random forest) resulted in the identification of 16 compounds that can be used to discriminate systemic sclerosis patients from healthy subjects. Receiver operating curves were generated that provided an accuracy of 90%, a sensitivity of 92%, and a specificity of 89%. The chemical identification of eight compounds predictive of systemic sclerosis was validated using commercially available standards. The analytical variations together with the volatile composition of room air were carefully monitored during the timeframe of the study to ensure the robustness of the technique. This study represents the first reported evaluation of exhaled breath analysis for systemic sclerosis diagnosis and provides surrogate markers for such disease.

Engineering Advanced In Vitro Models of Systemic Sclerosis for Drug Discovery and Development

Systemic sclerosis (SSc) is a complex multisystem disease with the highest case-specific mortality among all autoimmune rheumatic diseases, yet without any available curative therapy. Therefore, the development of novel therapeutic antifibrotic strategies that effectively decrease skin and organ fibrosis is needed. Existing animal models are cost-intensive, laborious and do not recapitulate the full spectrum of the disease and thus commonly fail to predict human efficacy. Advanced in vitro models, which closely mimic critical aspects of the pathology, have emerged as valuable platforms to investigate novel pharmaceutical therapies for the treatment of SSc. This review focuses on recent advancements in the development of SSc in vitro models, sheds light onto biological (e.g., growth factors, cytokines, coculture systems), biochemical (e.g., hypoxia, reactive oxygen species) and biophysical (e.g., stiffness, topography, dimensionality) cues that have been utilized for the in vitro recapitulation of the SSc microenvironment, and highlights future perspectives for effective drug discovery and validation.

Glycolysis-derived acidic microenvironment as a driver of endothelial dysfunction in systemic sclerosis

OBJECTIVES

Systemic sclerosis (SSc) is an autoimmune disease characterized by peripheral vasculopathy and skin and internal organ fibrosis. Accumulating evidence underlines a close association between a metabolic reprogramming of activated fibroblasts and fibrosis. This prompted us to determine the metabolism of SSc dermal fibroblasts and the effect on the vasculopathy characterizing the disease.

METHODS

Seahorse XF96 Extracellular Flux Analyzer was exploited to evaluate SSc fibroblast metabolism. In vitro invasion and capillary morphogenesis assays were used to determine the angiogenic ability of endothelial cells (EC). Immunofluorescence, flow cytometer and real time PCR techniques provided evidence of the molecular mechanism behind the impaired vascularization that characterizes SSc patients.

RESULTS

SSc fibroblasts, compared with control, showed a boosted glycolytic metabolism with increased lactic acid release and subsequent extracellular acidification, that in turn was found to impair EC invasion and organization in capillary-like networks without altering cell viability. A molecular link between extracellular acidosis and endothelial dysfunction was identified as acidic EC up-regulated MMP-12 which cleaves and inactivates uPAR, impairing angiogenesis in SSc. Moreover, the acidic environment was found to induce the loss of endothelial markers and the acquisition of mesenchymal-like features in EC, thus promoting the endothelial-to-mesenchymal transition (EndoMT) process that contributes to both capillary rarefaction and tissue fibrosis in SSc.

CONCLUSION

This study disclosed a liaison among the metabolic reprogramming of SSc dermal fibroblasts, extracellular acidosis and endothelial dysfunction that may contribute to the impairment and loss of peripheral capillary networks in SSc disease.

Serum metabolites as biomarkers in systemic sclerosis-associated interstitial lung disease

Systemic sclerosis (SSc) is a severe multi-organ disease with interstitial lung disease (ILD) being the major cause of death. While targeted therapies are emerging, biomarkers for sub-stratifying patients based on individual profiles are lacking. Herein, we investigated how levels of serum metabolites correlated with different stages of SSc and SSc-ILD. Serum samples of patients with SSc without ILD, stable and progressive SSc-ILD as well as of healthy controls (HC) were analysed using liquid targeted tandem mass spectrometry. The best discriminating profile consisted of 4 amino acids (AA) and 3 purine metabolites. L-tyrosine, L-tryptophan, and 1-methyl-adenosine distinguished HC from SSc patients. L-leucine, L-isoleucine, xanthosine, and adenosine monophosphate differentiated between progressing and stable SSc-ILD. In SSc-ILD, both, L-leucine and xanthosine negatively correlated with changes in FVC% predicted. Additionally, xanthosine was negatively correlated with changes in DLco% predicted and positively with the prognostic GAP index. Validation of L-leucine and L-isoleucine by an enzymatic assay confirmed both the sub-stratification of SSc-ILD patients and correlation with lung function and prognosis score. Serum metabolites may have potential as biomarkers for discriminating SSc patients based on the presence and severity of ILD. Confirmation in larger cohorts will be needed to appreciate their value for routine clinical care.

The multifaceted functional role of DNA methylation in immune-mediated rheumatic diseases

Genomic predisposition cannot explain the onset of complex diseases, as well illustrated by the largely incomplete concordance among monozygotic twins. Epigenetic mechanisms, including DNA methylation, chromatin remodelling and non-coding RNA, are considered to be the link between environmental stimuli and disease onset on a permissive genetic background in autoimmune and chronic inflammatory diseases. The paradigmatic cases of rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), systemic sclerosis (SSc), Sjogren's syndrome (SjS) and type-1 diabetes (T1D) share the loss of immunological tolerance to self-antigen influenced by several factors, with a largely incomplete role of individual genomic susceptibility. The most widely investigated epigenetic mechanism is DNA methylation which is associated with gene silencing and is due to the binding of methyl-CpG binding domain (MBD)-containing proteins, such as MECP2, to 5-methylcytosine (5mC). Indeed, a causal relationship occurs between DNA methylation and transcription factors occupancy and recruitment at specific genomic locus. In most cases, the results obtained in different studies are controversial in terms of DNA methylation comparison while fascinating evidence comes from the comparison of the epigenome in clinically discordant monozygotic twins. In this manuscript, we will review the mechanisms of epigenetics and DNA methylation changes in specific immune-mediated rheumatic diseases to highlight remaining unmet needs and to identify possible shared mechanisms beyond different tissue involvements with common therapeutic opportunities. Key Points • DNA methylation has a crucial role in regulating and tuning the immune system. • Evidences suggest that dysregulation of DNA methylation is pivotal in the context of immune-mediated rheumatic diseases. • DNA methylation dysregulation in FOXP3 and interferons-related genes is shared within several autoimmune diseases. • DNA methylation is an attractive marker for diagnosis and therapy.

Mitochondria, Aging, and Cellular Senescence: Implications for Scleroderma

PURPOSE OF REVIEW

The etiology of systemic sclerosis (SSc), which is a rare immune-mediated inflammatory disease characterized by vascular damage and fibrosis, is still unknown. However, different intrinsic (genetics) and extrinsic (environmental) factors play a part in the progression of the disease. This review focuses on the role of aging, mitochondrial dysfunction, and senescence in SSc.

RECENT FINDINGS

Mitochondrial dysfunction and senescence have been linked to the age-related susceptibility to other interstitial lung diseases (ILD) such as idiopathic pulmonary fibrosis (IPF). SSc is not regarded as an age-related disease but does show a higher incidence of cardiac events, fibrosis, and mortality at older age. We provide an overview of the current status of the role of aging, mitochondrial dysfunction, and senescence in SSc. Further work is needed to validate some of these pathways in SSc and may allow for new therapeutic interventions focused on restoring mitochondrial homeostasis and the targeted removal of chronic-senescent cells.

Fatty Acid and Carnitine Metabolism Are Dysregulated in Systemic Sclerosis Patients

Systemic sclerosis (SSc) is a rare chronic disease of unknown pathogenesis characterized by fibrosis of the skin and internal organs, vascular alteration, and dysregulation of the immune system. In order to better understand the immune system and its perturbations leading to diseases, the study of the mechanisms regulating cellular metabolism has gained a widespread interest. Here, we have assessed the metabolic status of plasma and dendritic cells (DCs) in patients with SSc. We identified a dysregulated metabolomic signature in carnitine in circulation (plasma) and intracellularly in DCs of SSc patients. In addition, we confirmed carnitine alteration in the circulation of SSc patients in three independent plasma measurements from two different cohorts and identified dysregulation of fatty acids. We hypothesized that fatty acid and carnitine alterations contribute to potentiation of inflammation in SSc. Incubation of healthy and SSc dendritic cells with etoposide, a carnitine transporter inhibitor, inhibited the production of pro-inflammatory cytokines such as IL-6 through inhibition of fatty acid oxidation. These findings shed light on the altered metabolic status of the immune system in SSc patients and opens up for potential novel avenues to reduce inflammation.

Multi-Platform Characterization of Cerebrospinal Fluid and Serum Metabolome of Patients Affected by Relapsing-Remitting and Primary Progressive Multiple Sclerosis

Background: Multiple sclerosis (MS) is a chronic immunemediated disease of the central nervous system with a highly variable clinical presentation and disease progression. In this study, we investigate the metabolomics profile of patients affected by relapsing–remitting MS (RRMS)and primary progressive MS (PPMS), in order to find potential biomarkers to distinguish between the two forms. Methods: Cerebrospinal Fluid CSF and blood samples of 34 patients (RRMS n = 22, PPMS n = 12) were collected. Nuclear magnetic resonance (¹H-NMR) and mass spectrometry (coupled with a gas chromatography and liquid chromatography) were used as analytical techniques. Subsequently, a multivariate statistical analysis was performed; the resulting significant variables underwent U-Mann–Whitney test and correction for multiple comparisons. Receiver Operating Characteristic ROC curves were built and the pathways analysis was conducted. Results: The analysis of the serum and the CSF of the two classes, allowed the identification of several altered metabolites (lipids, biogenic amines, and amino acids). The pathways analysis indicated the following pathways were affected: Glutathione metabolism, nitrogen metabolism, glutamine–glutamate metabolism, arginine–ornithine metabolism, phenylalanine, tyrosine and tryptophan biosynthesis etc. Conclusion: The analysis allowed the identification of a set of metabolites able to classify RRMS and PPMS patients, each of whom express different patterns of metabolites in the two biofluids.

Seminal Fluid Metabolomic Markers of Oligozoospermic Infertility in Humans

Infertility affects 12–15% of couples worldwide, and male factors are the cause of nearly half of all cases. Studying seminal fluid composition could lead to additional diagnostic accuracy and a better understanding of the pathophysiology of male factor infertility. Metabolomics offers a new opportunity to evaluate biomarkers and better understand pathological mechanisms. The aim of the study was to identify new markers or therapeutic targets to improve outcomes in male factor or idiopathic infertility patients. Semen samples were obtained from 29 men with a normal spermogram test, and from 18 oligozoospermic men. Samples were processed and analyzed by Nuclear Magnetic Resonance spectroscopy and, subsequently, multivariate and univariate statistical analyses. Receiving Operator Curves (ROC) and Spearman correlations were also performed. An Orthogonal Partial Least Square Discriminant Analysis supervised multivariate model was devised to compare the groups. The levels of fructose, myo-inositol, aspartate and choline were altered. Moreover, Spearman Correlation associated fructose, aspartate and myo-inositol with the total amount of spermatozoa, total motile spermatozoa, % of immotility and % of “in situ” spermatozoic motility respectively. NMR-based metabolomics allowed the identification of a specific metabolic fingerprint of the seminal fluids of patients affected by oligozoospermia.

Pediatric Acute-onset Neuropsychiatric Syndrome and Mycoplasma Pneumoniae Infection: A Case Report Analysis with a Metabolomics Approach

Pediatric Acute-onset Neuropsychiatric Syndrome (PANS) is a clinical condition characterized by a sudden and dramatic obsessive-compulsive disorder with a suggested post-infectious immune-mediated etiology. This condition is accompanied by an extensive series of relatively serious neuropsychiatric symptoms. The diagnosis of PANS is made by "exclusion", as the individual PANS symptoms overlap with a multiplicity of psychiatric disorders with the onset in childhood. A number of researchers accumulated evidence to support the hypothesis that PANS was closely associated with a number of infections. In the last decade, metabolomics played an essential role in improving the knowledge of complex biological systems and identifying potential new biomarkers as indicators of pathological progressions or pharmacologic responses to therapy. The metabolome is considered the most predictive phenotype, capable of recognizing epigenetic differences, reflecting more closely the clinical reality at any given moment and thus providing extremely dynamic data. In the present work, the most recent hypothesis and suggested mechanisms of this condition are reviewed and the case of a 10 - year-old girl with PANS is described, before and after clarithromycin treatment. The main results of this case report are discussed from a metabolomics point of view. The alteration of several metabolic pathways concerning the microbial activity highlights the possible role of the microbiome in the development of PANS. Furthermore, different metabolic perturbations at the level of protein biosynthesis, energy and amino acid metabolisms are observed and discussed. Based on our observations, it is believed that metabolomics is a promising technology to unravel the mysteries of PANS in the near future.

Analysis of gene expression profiles and protein-protein interaction networks in multiple tissues of systemic sclerosis

Background

Systemic sclerosis (SSc), a multi-organ disorder, is characterized by vascular abnormalities, dysregulation of the immune system, and fibrosis. The mechanisms underlying tissue pathology in SSc have not been entirely understood. This study intended to investigate the common and tissue-specific pathways involved in different tissues of SSc patients.

Methods

An integrative gene expression analysis of ten independent microarray datasets of three tissues was conducted to identify differentially expressed genes (DEGs). DEGs were mapped to the search tool for retrieval of interacting genes (STRING) to acquire protein–protein interaction (PPI) networks. Then, functional clusters in PPI networks were determined. Enrichr, a gene list enrichment analysis tool, was utilized for the functional enrichment of clusters.

Results

A total of 12, 2, and 4 functional clusters from 619, 52, and 119 DEGs were determined in the lung, peripheral blood mononuclear cell (PBMC), and skin tissues, respectively. Analysis revealed that the tumor necrosis factor (TNF) signaling pathway was enriched significantly in the three investigated tissues as a common pathway. In addition, clusters associated with inflammation and immunity were common in the three investigated tissues. However, clusters related to the fibrosis process were common in lung and skin tissues.

Conclusions

Analysis indicated that there were common pathological clusters that contributed to the pathogenesis of SSc in different tissues. Moreover, it seems that the common pathways in distinct tissues stem from a diverse set of genes.

Insights into myofibroblasts and their activation in scleroderma: opportunities for therapy?

PURPOSE OF REVIEW

The persistence of myofibroblasts is a key feature of fibrosis and in fibrotic diseases including scleroderma. This review evaluates the emerging concepts of the origins and cell populations that contribute to myofibroblasts and the molecular mechanisms that govern phenotypic conversion and that highlight opportunities for new interventional treatments in scleroderma.

RECENT FINDINGS

Studies have defined heterogeneity in fibroblast-like cells that can develop into myofibroblast in normal wound healing, scarring and fibrosis. Characterizing these distinct cell populations and their behaviour has been a key focus. In addition, the overarching impact of epigenetic regulation of genes associated with inflammatory responses, cell signalling and cell communication and the extracellular matrix (ECM) has provided important insights into the formation of myofibroblast and their function. Important new studies include investigations into the relationship between inflammation and myofibroblast production and further evidence has been gathered that reveal the importance of ECM microenvironment, biomechanical sensing and mechanotransduction.

SUMMARY

This review highlights our current understanding and outlines the increasing complexity of the biological processes that leads to the appearance of the myofibroblast in normal functions and in diseased tissues. We also focus on areas of special interest in particular, studies that have therapeutic potential in fibrosis and scleroderma.

Assessing the Metabolomic Profile of Multiple Sclerosis Patients Treated with Interferon Beta 1a by 1H-NMR Spectroscopy

Metabolomic research has emerged as a promising approach to identify potential biomarkers in multiple sclerosis (MS). The aim of the present study was to determine the effect of interferon beta (IFN ß) on the metabolome of MS patients to explore possible biomarkers of disease activity and therapeutic response. Twenty-one MS patients starting IFN ß therapy (Rebif® 44 μg; s.c. 3 times per week) were enrolled. Blood samples were obtained at baseline and after 6, 12, and 24 months of IFN ß treatment and were analyzed by high-resolution nuclear magnetic resonance spectroscopy. Changes in metabolites were analyzed. After IFN ß exposure, patients  were divided into responders and nonresponders according to the "no evidence of disease activity" (NEDA-3) definition (absence of relapses, disability progression, and magnetic resonance imaging activity), and samples obtained at baseline were analyzed to evaluate the presence of metabolic differences predictive of IFN ß response. The results of the investigation demonstrated differential distribution of baseline samples compared to those obtained during IFN ß exposure, particularly after 24 months of treatment (R2X = 0.812, R2Y = 0.797, Q2 = 0.613, p = 0.003). In addition, differences in the baseline metabolome between responder and nonresponder patients with respect to lactate, acetone, 3-OH-butyrate, tryptophan, citrate, lysine, and glucose levels were found (R2X = 0.442, R2Y = 0.768, Q2 = 0.532, p = 0.01). In conclusion, a metabolomic approach appears to be a promising, noninvasive tool that could potentially contribute to predicting the efficacy of MS therapies.