Biomarkers In Systemic Sclerosis Research Articles

551P BiP (GRP78) as potential blood and tissue biomarker in systemic sclerosis

551P BiP (GRP78) as potential blood and tissue biomarker in systemic sclerosis

Autoantibodies as putative biomarkers and triggers of cell dysfunctions in systemic sclerosis.

Antinuclear autoantibodies represent a serological hallmark of systemic sclerosis (SSc), with anticentromere, antitopoisomerase-I, and anti-RNA polymerase III antibodies routinely assessed for diagnosis, clinical subset classification, and prognosis. In addition, an increasing number of autoantibodies have been demonstrated to play a pathogenic role by mediating different SSc manifestations. This review aims to give an overview on autoantibodies as putative biomarkers in SSc and discuss their possible pathogenic role as triggers of cell dysfunctions. Over the years, different autoantibodies have been proposed as biomarkers aiding in diagnosis, disease subtype classification, disease progression prediction, organ involvement, as well as in understanding treatment response. Increasing literature also indicates functional autoantibodies as direct contributors to SSc pathogenesis by exerting agonistic or antagonistic activities on their specific cognate targets. In SSc, search and validation of novel autoantibodies with higher diagnostic specificity and more accurate predictive values are increasingly needed for early diagnosis and specific follow-up, and to define the best therapeutic option according to different disease subsets. Moreover, since autoantibodies are also emerging as functional pathogenic players, a better unraveling of their possible pathomechanisms becomes essential to identify new targets and develop promising therapeutic agents able to neutralize their effects.

Relationships between systemic sclerosis and atherosclerosis: screening for mitochondria-related biomarkers.

Patients with systemic sclerosis (SSc) are known to have higher incidence of atherosclerosis (AS). Mitochondrial injuries in SSc can cause endothelial dysfunction, leading to AS; thus, mitochondria appear to be hubs linking SSc to AS. This study aimed to identify the mitochondria-related biomarkers of SSc and AS. We identified common differentially expressed genes (DEGs) in the SSc (GSE58095) and AS (GSE100927) datasets of the Gene Expression Omnibus (GEO) database. Considering the intersection between genes with identical expression trends and mitochondrial genes, we used the least absolute shrinkage and selection operator (LASSO) as well as random forest (RF) algorithms to identify four mitochondria-related hub genes. Diagnostic nomograms were then constructed to predict the likelihood of SSc and AS. Next, we used the CIBERSORT algorithm to evaluate immune infiltration in both disorders, predicted the transcription factors for the hub genes, and validated these genes for the two datasets. A total of 112 genes and 13 mitochondria-related genes were identified; these genes were then significantly enriched for macrophage differentiation, collagen-containing extracellular matrix, collagen binding, antigen processing and presentation, leukocyte transendothelial migration, and apoptosis. Four mitochondria-related hub DEGs (IFI6, FSCN1, GAL, and SGCA) were also identified. The nomograms showed good diagnostic values for GSE58095 (area under the curve (AUC) = 0.903) and GSE100927 (AUC = 0.904). Further, memory B cells, γδT cells, M0 macrophages, and activated mast cells were significantly higher in AS, while the resting memory CD4+ T cells were lower and M1 macrophages were higher in SSc; all of these were closely linked to multiple immune cells. Gene set enrichment analysis (GSEA) showed that IFI6 and FSCN1 were involved in immune-related pathways in both AS and SSc; GAL and SGCA are related to mitochondrial metabolism pathways in both SSc and AS. Twenty transcription factors (TFs) were predicted, where two TFs, namely BRCA1 and PPARγ, were highly expressed in both SSc and AS. Four mitochondria-related biomarkers were identified in both SSc and AS, which have high diagnostic value and are associated with immune cell infiltration in both disorders. Hence, this study provides new insights into the pathological mechanisms underlying SSc and AS. The specific roles and action mechanisms of these genes require further clinical validation in SSc patients with AS.

Sirtuin3 and Sirtuin7 are promising biomarkers in systemic sclerosis

BackgroundSystemic sclerosis (SSc) is an autoimmune disease that results in micro-vasculopathy, leading to organ dysfunction. Sirtuins are known for their role in cellular processes such as the cell cycle, aging, and inflammation, Sirtuins also play an important role in regulating fibrotic responses, inhibiting collagen production and myofibroblast differentiation, implying that its dysregulation is involved in the pathogenesis of systemic sclerosis. The aim of this study was to determine the circulating Sirtuin3 and Sirtuin7 levels in patients suffering from systemic sclerosis with a focus on how they might be associated with the different clinical features and subsets of the disease.MethodsThis prospective cross-sectional case–control study included 56 participants 41 SSc patients and 15 healthy controls. Demographics, clinical, and laboratory data were analyzed. Quantitative determination of human Sirtuin3 and Sirtuin7 concentrations was done.ResultsAmong systemic sclerosis patients, the age of SSc patients was 42.27 ± 10.46 years. The mean serum levels of Sirtuin3 and Sirtuin7 were significantly lower in SSc patients than in healthy controls (p < 0.001). SIRT3 and SIRT7 levels among SSc patients showed a statistically significant positive correlation (p < 0.001). SIRT7 level was insignificantly decreased in dcSSc (14.16 ± 5.93) than in lcSSc (20.01 ± 8.34). Regarding the SIRT3 level, there was an insignificant difference between dcSSc and lcSSc. Modified Rodnan’s skin score correlated negatively with Sirtuin3 and Sirtuin7 levels. In systemic sclerosis patients with interstitial lung disease (56.1%), there was an insignificant difference in SIRT3 and SIRT7 levels (0.12 ± 0.01and 21.23 ± 8.23) compared with systemic sclerosis patients without interstitial lung disease (0.10 ± 0.01 and 17.47 ± 8.57), with p = 0.408 and 0.258, respectively. The receiver operating characteristic curve for SSc prediction with Sirtuin3 has an accuracy of 83.0%, sensitivity of 85.4%, and specificity of 80.0% and p < 0.001. Regarding Sirtuin7, it has an accuracy of 89.5%, sensitivity of 85.4%, and specificity of 93.3% and p < 0.001.ConclusionSirtuin3 and Sirtuin7 levels were found to have a significant positive correlation in SSc patients. Sirtuin3 and Sirtuin7 levels are both good diagnostic biomarkers for detecting and diagnosing SSc, with Sirtuin7 being more accurate, specific, and predictive of the disease than Sirtuin3. Sirtuin7 is thought to be a new biomarker for SSc disease.

P151 Nailfold capillaroscopy for prediction of novel severe organ involvement and mortality in systemic sclerosis

Abstract Background/Aims Nailfold capillaroscopy (NFC) has been suggested as a potential biomarker of disease severity in systemic sclerosis (SSc). Several studies report the association between capillary loss and disease severity however, the association of NFC abnormalities with novel severe organ involvement/progression and mortality in SSc has not been evaluated. We aim to evaluate the association of nailfold capillaroscopy (NFC) abnormalities with novel major organ involvement/progression and mortality in SSc. Methods Follow-up data from patients with SSc registered between 2000 and 2022 were analyzed. Patients underwent NFC at baseline. Baseline demographic data, antibody status, baseline pulmonary function, novel severe organ involvement/progression and mortality were registered. Novel organ involvement/progression was defined as new or progressive involvement of peripheral vasculature, lungs, heart, skin, gastrointestinal, kidney, musculoskeletal at 12 and 24 months of follow-up. The following NFC parameters were evaluated: capillary density, hemorrhages, enlarged and giant capillaries, avascular areas, organization of capillary architecture and scleroderma pattern (early/active/late). Logistic regression modelling was run to assess associations between NFC and clinical parameters, the occurrence of novel severe organ involvement and/or progression and mortality. Results 113 patients were included: 28 (25%) were male, 86 (76%) lcSSc and 27 (23%) dcSSc. 70 patients (61%) developed novel overall severe organ involvement/progression and 40 patients died (36%) during follow-up. Table 1 and table 2 summarizes the associations between NFC and novel severe organ involvement/progression and mortality during follow-up. Loss of capillary density was associated with overall severe organ involvement (p = 0.002), peripheral vascular involvement (p = 0.03), new ILD (p = 0.04) and skin progression (p = 0.01); avascular areas were associated with overall severe organ involvement (p = 0.03), new ILD (p = 0.03) and progression of ILD (p = 0.02) and scleroderma pattern was associated with overall severe organinvolvement (p = 0.03), peripheral vascular involvement (OR p = 0.04), new ILD (p = 0.004), progression of ILD (p = 0.03) and skin progression (p = 0.04). Mortality was associated with ILD (OR 2.56 CI 95% 1.5-7.2, p 0.04), DLCO &amp;lt;70% (2.34 CI 93% 1.42-6.23, p 0.03), a late pattern in NFC (3.42 95% CI 1.42-7.25, p 0.002), presence of hemorrhages (OR 1.77 95% CI 1.24-8.23, p0.034) and avascular zones (OR 6.22 95% CI 2.54-10.3, p 0.021). Survival rates from diagnosis at 10 years were lower in patients with NFC with active a late pattern (40% and 20%) compared with those with normal, unspecific and early pattern (100%, 90% and 70%) (p = 0.008 by log rank test) (figure 1). Conclusion NFC may be a potential biomarker in SSc for predicting novel severe organ involvement and/or progression and mortality. Abnormal capillary density, avascular areas and scleroderma pattern are predictors of overall severe organ involvement, peripheral vascular involvement, novel and progression of ILD and skin progression. Disclosure C. Sieiro Santos: None. P. Pérez García: None. J. Ordas Martínez: None. C. Álvarez Castro: None. E. Díez Álvarez: None.

Multiple serum biomarkers associate with mortality and interstitial lung disease progression in systemic sclerosis.

To investigate the prognostic utility of 28 serum biomarkers in systemic sclerosis (SSc), SSc-associated interstitial lung disease (SSc-ILD) and clinically relevant disease subgroups. Participants with sera, high-resolution computed tomography, and lung function within 12 months of baseline were identified from the Australian Scleroderma Cohort Study. Baseline was the time of serum collection. 27 of the prespecified 28 serum biomarkers were analysed and biomarker associations with mortality and ILD progression were investigated in univariable and multivariable analyses, including within disease subgroups and combined with established risk factors for poorer prognosis in SSc. 407 participants were identified, 252 (61.9%) with SSc-ILD. The median follow up after biomarker measurement was 6.31 (3.11-9.22) years. 16 biomarkers were associated with increased mortality. High levels of VCAM-1 were most strongly associated with mortality (HR 3.55; 95%CI 2.37-5.33; p< 0.001). Five additional biomarkers had a HR > 2: SP-D (2.28, 1.57-3.31; p< 0.001), E-selectin (2.19; 1.53-3.14; p< 0.001), IL-6 (2.15 1.50-3.09; p< 0.001), MMP3 (1.42-2.95; p< 0.001) and ET-1 (2.03, 1.40-2.92; p< 0.001). 11 biomarkers were independently associated with mortality following adjustment for sex, age and baseline forced vital capacity (FVC%predicted). Three biomarkers were associated with ILD progression at one year follow up: CXCL4 (OR 2.67, 1.46-4.88; p= 0.001), MMP-1 (2.56, 1.43-4.59; p= 0.002) and ET-1 (2.18, 1.24-3.83; p= 0.007). Multiple biomarkers, especially VCAM-1, E-Selectin, SP-D and CXCL4, provide prognostic utility beyond that of established risk factors for patients with SSc.

Biomarkers in the Pathogenesis, Diagnosis, and Treatment of Systemic Sclerosis.

Systemic sclerosis (SSc) is a complex autoimmune disease characterized by vascular damage, vasoinstability, and decreased perfusion with ischemia, inflammation, and exuberant fibrosis of the skin and internal organs. Biomarkers are analytic indicators of the biological and disease processes within an individual that can be accurately and reproducibly measured. The field of biomarkers in SSc is complex as recent studies have implicated at least 240 pathways and dysregulated proteins in SSc pathogenesis. Anti-nuclear antibodies (ANA) are classical biomarkers with well-described clinical classifications and are present in more than 90% of SSc patients and include anti-centromere, anti-Th/To, anti-RNA polymerase III, and anti-topoisomerase I antibodies. Transforming growth factor-β (TGF-β) is central to the fibrotic process of SSc and is intimately intertwined with other biomarkers. Tyrosine kinases, interferon-1 signaling, IL-6 signaling, endogenous thrombin, peroxisome proliferator-activated receptors (PPARs), lysophosphatidic acid receptors, and amino acid metabolites are new biomarkers with the potential for developing new therapeutic agents. Other biomarkers implicated in SSc-ILD include signal transducer and activator of transcription 4 (STAT4), CD226 (DNAX accessory molecule 1), interferon regulatory factor 5 (IRF5), interleukin-1 receptor-associated kinase-1 (IRAK1), connective tissue growth factor (CTGF), pyrin domain containing 1 (NLRP1), T-cell surface glycoprotein zeta chain (CD3ζ) or CD247, the NLR family, SP-D (surfactant protein), KL-6, leucine-rich α2-glycoprotein-1 (LRG1), CCL19, genetic factors including DRB1 alleles, the interleukins (IL-1, IL-4, IL-6, IL-8, IL-10 IL-13, IL-16, IL-17, IL-18, IL-22, IL-32, and IL-35), the chemokines CCL (2,3,5,13,20,21,23), CXC (8,9,10,11,16), CX3CL1 (fractalkine), and GDF15. Adiponectin (an indicator of PPAR activation) and maresin 1 are reduced in SSc patients. A new trend has been the use of biomarker panels with combined complex multifactor analysis, machine learning, and artificial intelligence to determine disease activity and response to therapy. The present review is an update of the various biomarker molecules, pathways, and receptors involved in the pathology of SSc.

Biomarkers in Systemic Sclerosis: An Overview.

Systemic sclerosis (SSc) is a complex autoimmune disease characterized by significant fibrosis of the skin and internal organs, with the main involvement of the lungs, kidneys, heart, esophagus, and intestines. SSc is also characterized by macro- and microvascular damage with reduced peripheral blood perfusion. Several studies have reported more than 240 pathways and numerous dysregulation proteins, giving insight into how the field of biomarkers in SSc is still extremely complex and evolving. Antinuclear antibodies (ANA) are present in more than 90% of SSc patients, and anti-centromere and anti-topoisomerase I antibodies are considered classic biomarkers with precise clinical features. Recent studies have reported that trans-forming growth factor β (TGF-β) plays a central role in the fibrotic process. In addition, interferon regulatory factor 5 (IRF5), interleukin receptor-associated kinase-1 (IRAK-1), connective tissue growth factor (CTGF), transducer and activator of transcription signal 4 (STAT4), pyrin-containing domain 1 (NLRP1), as well as genetic factors, including DRB1 alleles, are implicated in SSc damage. Several interleukins (e.g., IL-1, IL-6, IL-10, IL-17, IL-22, and IL-35) and chemokines (e.g., CCL 2, 5, 23, and CXC 9, 10, 16) are elevated in SSc. While adiponectin and maresin 1 are reduced in patients with SSc, biomarkers are important in research but will be increasingly so in the diagnosis and therapeutic approach to SSc. This review aims to present and highlight the various biomarker molecules, pathways, and receptors involved in the pathology of SSc.

Non-classical circulating monocytes expressing high levels of microsomal prostaglandin E2 synthase-1 tag an aberrant IFN-response in systemic sclerosis

Systemic sclerosis (SSc) is a complex disease that affects the connective tissue, causing fibrosis. SSc patients show altered immune cell composition and activation in the peripheral blood (PB). PB monocytes (Mos) are recruited into tissues where they differentiate into macrophages, which are directly involved in fibrosis. To understand the role of CD14+ PB Mos in SSc, a single-cell transcriptome analysis (scRNA-seq) was conducted on 8 SSc patients and 8 controls. Using unsupervised clustering methods, CD14+ cells were assigned to 11 clusters, which added granularity to the known monocyte subsets: classical (cMos), intermediate (iMos) and non-classical Mos (ncMos) or type 2 dendritic cells. NcMos were significantly overrepresented in SSc patients and showed an active IFN-signature and increased expression levels of PTGES, in addition to monocyte motility and adhesion markers. We identified a SSc-related cluster of IRF7+ STAT1+ iMos with an aberrant IFN-response. Finally, a depletion of M2 polarised cMos in SSc was observed. Our results highlighted the potential of PB Mos as biomarkers for SSc and provided new possibilities for putative drug targets for modulating the innate immune response in SSc.

Serum metabolomic profiling reveals potential biomarkers in systemic sclerosis

BackgroundSystemic 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. MethodsHigh-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. ResultsThe 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. ConclusionsSerum 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.

Bioinformatics-integrated screening of systemic sclerosis-specific expressed markers to identify therapeutic targets.

Systemic sclerosis (SSc) is a rare autoimmune disease characterized by extensive skin fibrosis. There are no effective treatments due to the severity, multiorgan presentation, and variable outcomes of the disease. Here, integrated bioinformatics was employed to discover tissue-specific expressed hub genes associated with SSc, determine potential competing endogenous RNAs (ceRNA) regulatory networks, and identify potential targeted drugs. In this study, four datasets of SSc were acquired. To identify the genes specific to tissues or organs, the BioGPS web database was used. For differentially expressed genes (DEGs), functional and enrichment analyses were carried out, and hub genes were screened and shown in a network of protein-protein interactions (PPI). The potential lncRNA-miRNA-mRNA ceRNA network was constructed using the online databases. The specifically expressed hub genes and ceRNA network were validated in the SSc mouse and in normal mice. We also used the receiver operating characteristic (ROC) curve to determine the diagnostic values of effective biomarkers in SSc. Finally, the Drug-Gene Interaction Database (DGIdb) identified specific medicines linked to hub genes. The pooled datasets identified a total of 254 DEGs. The tissue/organ-specifically expressed genes involved in this analysis are commonly found in the hematologic/immune system and bone/muscle tissue. The enrichment analysis of DEGs revealed the significant terms such as regulation of actin cytoskeleton, immune-related processes, the VEGF signaling pathway, and metabolism. Cytoscape identified six gene cluster modules and 23 hub genes. And 4 hub genes were identified, including Serpine1, CCL2, IL6, and ISG15. Consistently, the expression of Serpine1, CCL2, IL6, and ISG15 was significantly higher in the SSc mouse model than in normal mice. Eventually, we found that MALAT1-miR-206-CCL2, let-7a-5p-IL6, and miR-196a-5p-SERPINE1 may be promising RNA regulatory pathways in SSc. Besides, ten potential therapeutic drugs associated with the hub gene were identified. This study revealed tissue-specific expressed genes, SERPINE1, CCL2, IL6, and ISG15, as effective biomarkers and provided new insight into the mechanisms of SSc. Potential RNA regulatory pathways, including MALAT1-miR-206-CCL2, let-7a-5p-IL6, and miR-196a-5p-SERPINE1, contribute to our knowledge of SSc. Furthermore, the analysis of drug-hub gene interactions predicted TIPLASININ, CARLUMAB and BINDARIT as candidate drugs for SSc.

Coinfection of Dermal Fibroblasts by Human Cytomegalovirus and Human Herpesvirus 6 Can Boost the Expression of Fibrosis-Associated MicroRNAs.

Tissue fibrosis can affect every type of tissue or organ, often leading to organ malfunction; however, the mechanisms involved in this process are not yet clarified. A role has been hypothesized for Human Cytomegalovirus (HCMV) and Human Herpesvirus 6 (HHV-6) infections as triggers of systemic sclerosis (SSc), a severe autoimmune disease causing progressive tissue fibrosis, since both viruses and antiviral immune responses toward them have been detected in patients. Moreover, HCMV or HHV-6A infection was reported to increase the expression of fibrosis-associated transcriptional factors and miRNAs in human dermal fibroblasts. However, it is unlikely that they have separate effects in the infected host, as both viruses are highly prevalent in the human population. Thus, our study aimed to investigate, by quantitative real-time PCR microarray, the impact of HCMV/HHV-6A coinfection on the expression of pro-fibrotic miRNAs in coinfected cells, compared to the effect of single viruses. The results showed a possible synergistic effect of the two viruses on pro-fibrotic miRNA expression, thus suggesting that HCMV and HHV-6 may enhance each other and cooperate at inducing enhanced miRNA-driven fibrosis. These data may also suggest a possible use of virus-induced miRNAs as novel diagnostic or prognostic biomarkers for SSc and its clinical treatment.

Enrichr in silico analysis of MS-based extracted candidate proteomic biomarkers highlights pathogenic pathways in systemic sclerosis

Systemic sclerosis (SSc) is a rheumatic disease characterised by vasculopathy, inflammation and fibrosis. Its aetiopathogenesis is still unknown, and the pathways/mechanisms of the disease are not clarified. This study aimed to perform in silico analysis of the already Mass Spectrometry (MS)-based discovered biomarkers of SSc to extract possible pathways/mechanisms implicated in the disease. We recorded all published candidate MS-based found biomarkers related to SSc. We then selected a number of the candidate biomarkers using specific criteria and performed pathway and cellular component analyses using Enrichr. We used PANTHER and STRING to assess the biological processes and the interactions of the recorded proteins, respectively. Pathway analysis extracted several pathways that are associated with the three different stages of SSc pathogenesis. Some of these pathways are also related to other diseases, including autoimmune diseases. We observe that these biomarkers are located in several cellular components and implicated in many biological processes. STRING analysis showed that some proteins interact, creating significant clusters, while others do not display any evidence of an interaction. All these data highlight the complexity of SSc, and further investigation of the extracted pathways/biological processes and interactions may help study the disease from a different angle.

Correlation between Microvascular Damage and Internal Organ Involvement in Scleroderma: Focus on Lung Damage and Endothelial Dysfunction.

Systemic sclerosis (SSc) is an incurable connective tissue disease characterized by decreased peripheral blood perfusion due to microvascular damage and skin thickening/hardening. The microcirculation deficit is typically secondary to structural vessel damage, which can be assessed morphologically and functionally in a variety of ways, exploiting different technologies. This paper focuses on reviewing new studies regarding the correlation between microvascular damage, endothelial dysfunction, and internal organ involvement, particularly pulmonary changes in SSc. We critically reviewed the most recent literature on the correlation between blood perfusion and organ involvement. Many papers have demonstrated the link between structural microcirculatory damage and pulmonary involvement; however, studies that have investigated correlations between microvascular functional impairment and internal organ damage are scarce. Overall, the literature supports the correlation between organ involvement and functional microcirculatory impairment in SSc patients. Morphological and functional techniques appear to be emerging biomarkers in SSc, but obviously need further investigation.

Identification and validation of key immune-related genes with promising diagnostic and predictive value in systemic sclerosis

AimsTo screen and confirm key immune-related genes (IRGs) with diagnostic and predictive value in systemic sclerosis (SSc) and provide potential therapeutic targets for patients with SSc. Materials and methodsIn Gene Expression Omnibus database (GEO), four datasets of gene expression profiling related to SSc were downloaded and used for the analysis in this study. After differential analysis of SSc cases and controls in GSE130955, the differentially expressed genes (DEGs) were overlapped with IRGs to obtain the immune-related differentially expressed genes (IR-DEGs) in SSc. In addition, functional annotation and pathway enrichment of IR-DEGs were conducted. The protein-protein interaction network (PPI) was constructed to identify key IR-DEGs. Using GSE58095, GSE181549 and GSE130953, the diagnostic and predictive abilities for the key IR-DEGs in SSc were validated. Finally, the screened key genes were confirmed in skin derived bleomycin (BLM)-induced SSc mice by Real-time PCR. Key findingsNGFR, TNFSF13B, FCER1G, GIMAP5, TYROBP and CSF1R may have important or very high diagnostic value for SSc. TYROBP and TNFSF13B had moderate and mild predictive value respectively in SSc patients after treatment. Real-time PCR assay further confirmed that the expressions of Ngfr, Tyrobp, Csf1r, Fcer1g and Gimap5 were significantly higher in skin of BLM-induced SSc mice than that in controls. SignificanceThe key IR-DEGs, including NGFR, TNFSF13B, TYROBP, CSF1R, FCER1G and GIMAP5, may become auxiliary diagnostic indicators and potential biomarkers for SSc. Moreover, TNFSF13B and TYROBP could have good prospects as predictive indicators in SSc patients that accepted cyclophosphamide or transplantation therapy.

Utility of cytokines CXCL4, CXCL8 and GDF15 as biomarkers in systemic sclerosis

Background and objectivesSystemic sclerosis (SSc) is an autoinmune disease that can affect several organs and its mortality is fundamentally related to its pulmonary involvement. There are some cytokines with high serum levels of patients with SSc. Our goal is to determine the role of CXCL4, CXCL8 and GDF15 in the physiopathology of SSc and whether they can be considered organic damage biomarkers. Patients and methodsObservational case–control study of SSc patients (ACR/EULAR 2013 criteria). Demographic, clinical, analytical, activity, severity, health perception, and disability variables were collected. Moreover, Videocapillaroscopy, Echocardiography and Respiratory Function Test were made. Serum levels of CXCL4, CXCL8 and GDF15 were measured both in SSc patients and in healthy controls. ResultsA total of 42 patients were included (95.4% women), with an average age of 59.2 years and a median of 4 years from diagnosis. We also included 42 healthy controls. We found significantly higher levels of GDF15 in SSc patients than in controls (p<0.001), but no higher CXCL4 or CXCL8 levels. GDF15 was associated with Diffuse SSc, pulmonary arterial hypertension, interstitial lung disease, less forced vital capacity, high titles of antiScl70, disease activity, and dilated loops in capillaroscopy. CXCL4 levels were associated to a higher Rodnan punctuation, while CXCL8 was associated to C4 fraction consumption and tortuosities in capillaroscopy. ConclusionsGDF15 high levels were associated with diffuse SSc, lung impairment, disease activity and changes in capillaroscopy. Moreover, CXCL4 was only associated with skin impairment, while CXCL8 was not related to organic damage.

Insights into molecular and clinical characteristics of very early systemic sclerosis.

The early heterogenous presentation of systemic sclerosis (SSc), in particular without skin involvement, has been a confounding factor delaying early diagnosis. In fact, early signs of SSc as Raynaud's phenomenon and puffy fingers, are also typical of other connective tissue diseases (CTDs) such as mixed CTD and undifferentiated CTD. In the last decade, a significant effort has been dedicated in defining molecular characteristics that could be used as early SSc biomarkers. In this narrative review, we address the present situation where several clinical scenarios are in search of a correct positioning into the prescleroderma (pre-SSc) phase as well as in the very early phase of SSc. Literature data showed that a part of patients classified as sine scleroderma SSc (ssSSc), mixed CTD and undifferentiated CTD may already belong to the very early phase of SSc, thus having a different pattern of progression to SSc. Recently, the very early diagnosis of systemic sclerosis (VEDOSS) criteria has been validated. while the area of pre-SSc still remains fuzzy, the VEDOSS study has shown that a 'window of opportunity' does exist also for SSc. In the very next future, this may allow to start the treatment to prevent the disease progression to a more advanced fibrotic stage.

Novel biomarkers in systemic sclerosis

Introduction. Due to the heterogeneous nature of systemic sclerosis, it is difficult to predict disease progression and complications. Despite the discovery of novel autoantibodies associated with systemic sclerosis (SSc), there is an unmet need for biomarkers for diagnosis, disease progression, and response to treatment. Materials and methods. An analytical, qualitative study was performed with a narrative review of literature in the form of a synthesis article. Relevant primary sources published in 2020-2022 were identified and selected, using data extraction and analysis. Results. Anti-citrullinated protein/peptide antibody could be useful in identifying patients with a more prominent joint disease. Of most interest, the anti-carbamylated protein antibodies (anti-CarP) could be a relevant biomarker related to fibrotic skin and lung disease. Positive anti-RNA (Ribonucleic acid) polymerase III antibody and antinuclear antibodies (ANA) negativity were significantly associated with GAVE (gastral antral vascular ectasia). Autoantibodies against telomeres may help identify systemic sclerosis with lung disease. Osteopontin links myeloid activation and disease progression in systemic sclerosis. CTRP (C1q tumor necrosis factor-related proteins) 9 protein levels may be biomarker of lung disease severity. CD (cluster differentiation) 21-low B cells are linked to vascular damage. L-tyrosine, L-tryptophan, and 1-methyl-adenosine distinguished healthy controls from SSc patients. L-leucine, L-isoleucine, xanthosine, and adenosine monophosphate differentiated between progressing and stable SSc-ILD. CECs (circulating endothelial cells) are a direct indicator of systemic vascular damage. Levels of the protein, galectin-3, are associated with heart involvement in people with systemic sclerosis. Low levels of the galectin-10 protein (Gal-10) in scleroderma patients associate with inflammation and vascular changes in the lungs, leading to pulmonary arterial hypertension (PAH). High levels of the CD146 protein may be a potential biomarker in identifying people with systemic sclerosis. Blood levels of the protein endocan increased in scleroderma patients who are at risk for pulmonary arterial hypertension. FLCs (free light chain) could be employed as useful potential biomarker of early diagnosis and to follow disease activity. Conclusions. Novel discovered biomarkers could predict disease development, activity, and severity of diverse organ involvement, predict risk of complications of systemic sclerosis.

Polarisation-sensitive optical coherence tomography measurement of retardance in fibrosis, a non-invasive biomarker in patients with systemic sclerosis

Polarisation-sensitive optical coherence tomography (PS-OCT) offers a novel, non-invasive method of assessing skin fibrosis in the multisystem disease systemic sclerosis (SSc) by measuring collagen retardance. This study aimed to assess retardance as a biomarker in SSc. Thirty-one patients with SSc and 27 healthy controls (HC) underwent PS-OCT imaging. ‘Skin score’ was assessed by clinical palpation (0–3 scale). A subset of ten patients and ten age/sex-matched HC had a biopsy and longitudinal imaging. Histological assessment included quantification of epidermal thickness, collagen content (to assess fibrosis) and matrix metalloproteinase (MMP) activity (in situ zymography). PS-OCT images were assessed for epidermal thickness (structure) and fibrosis (retardance). Positive correlation was observed between epidermal thickness as measured by histology and structural PS-OCT (r = 0.79; p < 0.001). Retardance was: HC mean 0.21 (SD 0.21) radian/pixel; SSc skin score 0, 0.30 (0.19); skin score 1, 0.11 (0.16); skin score 2, 0.06 (0.12); skin score 3, 0.36 (0.35). Longitudinal retardance decreased at one-week across groups, increasing at one-month for HC/skin score 0–1; HC biopsy site retardance suggests scarring is akin to fibrosis. Relationships identified between retardance with both biopsy and skin score data indicate that retardance warrants further investigation as a suitable biomarker for SSc-related fibrosis.

Utility of cytokines CXCL4, CXCL8 and GDF15 as biomarkers in systemic sclerosis

Background and objectivesSystemic sclerosis (SSc) is an autoinmune disease that can affect several organs and its mortality is fundamentally related to its pulmonary involvement. There are some cytokines with high serum levels of patients with SSc. Our goal is to determine the role of CXCL4, CXCL8 and GDF15 in the physiopathology of SSc and whether they can be considered organic damage biomarkers. Patients and methodsObservational case–control study of SSc patients (ACR/EULAR 2013 criteria). Demographic, clinical, analytical, activity, severity, health perception, and disability variables were collected. Moreover, Videocapillaroscopy, Echocardiography and Respiratory Function Test were made. Serum levels of CXCL4, CXCL8 and GDF15 were measured both in SSc patients and in healthy controls. ResultsA total of 42 patients were included (95.4% women), with an average age of 59.2 years and a median of 4 years from diagnosis. We also included 42 healthy controls. We found significantly higher levels of GDF15 in SSc patients than in controls (p<0.001), but no higher CXCL4 or CXCL8 levels. GDF15 was associated with Diffuse SSc, pulmonary arterial hypertension, interstitial lung disease, less forced vital capacity, high titles of antiScl70, disease activity, and dilated loops in capillaroscopy. CXCL4 levels were associated to a higher Rodnan punctuation, while CXCL8 was associated to C4 fraction consumption and tortuosities in capillaroscopy. ConclusionsGDF15 high levels were associated with diffuse SSc, lung impairment, disease activity and changes in capillaroscopy. Moreover, CXCL4 was only associated with skin impairment, while CXCL8 was not related to organic damage.