Biomarkers in Scleroderma: Progressing from Association to Clinical Utility

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.

Cardiac magnetic resonance predicts ventricular arrhythmias in scleroderma: the Scleroderma Arrhythmia Clinical Utility Study (SAnCtUS)

OBJECTIVES

Cardiac rhythm disturbances constitute the most frequent cardiovascular cause of death in SSc. However, electrocardiographic findings are not a part of risk stratification in SSc. We aimed to translate 24 h Holter findings into a tangible risk prediction score using cardiovascular magnetic resonance.

METHODS

The Scleroderma Arrhythmia Clinical Utility Study (SAnCtUS) was a prospective multicentre study including 150 consecutive SSc patients from eight European centres, assessed with 24 h Holter and cardiovascular magnetic resonance, including ventricular function, oedema (T2 ratio) and late gadolinium enhancement (%LGE). Laboratory/clinical parameters were included in multivariable corrections. A combined endpoint of sustained ventricular tachycardia requiring hospitalization and sudden cardiac death at a median (interquartile range) follow-up of 1 (1.0-1.4) year was generated.

RESULTS

Only T2 ratio and %LGE were significant predictors of ventricular rhythm disturbances, but not of supraventricular rhythm disturbances, after multivariable correction and adjustment for multiple comparisons. Using decision-tree analysis, we created the SAnCtUS score, a four-category scoring system based on T2 ratio and %LGE, for identifying SSc patients at high risk of experiencing ventricular rhythm disturbance at baseline. Increasing SAnCtUS scores were associated with a greater disease and arrhythmic burden. All cases of non-sustained ventricular tachycardia (n = 7) occurred in patients with the highest SAnCtUS score (=4). Having a score of 4 conveyed a higher risk of reaching the combined endpoint in multivariable Cox regression compared with scores 1/2/3 [hazard ratio (95% CI): 3.86 (1.14, 13.04), P = 0.029] independently of left ventricular ejection fraction and baseline ventricular tachycardia occurrence.

CONCLUSION

T2 ratio and %LGE had the greatest utility as independent predictors of rhythm disturbances in SSc patients.

Emerging Roles of Matricellular Proteins in Systemic Sclerosis

Systemic sclerosis is a rare chronic heterogenous disease that involves inflammation and vasculopathy, and converges in end-stage development of multisystem tissue fibrosis. The loss of tight spatial distribution and temporal expression of proteins in the extracellular matrix (ECM) leads to progressive organ stiffening, which is a hallmark of fibrotic disease. A group of nonstructural matrix proteins, known as matricellular proteins (MCPs) are implicated in dysregulated processes that drive fibrosis such as ECM remodeling and various cellular behaviors. Accordingly, MCPs have been described in the context of fibrosis in sclerosis (SSc) as predictive disease biomarkers and regulators of ECM synthesis, with promising therapeutic potential. In this present review, an informative summary of major MCPs is presented highlighting their clear correlations to SSc- fibrosis.

Existing and novel biomarkers for precision medicine in systemic sclerosis

The discovery and validation of biomarkers resulting from technological advances in the analysis of genomic, transcriptomic, lipidomic and metabolomic pathways involved in the pathogenesis of complex human diseases have led to the development of personalized and rationally designed approaches for the clinical management of such disorders. Although some of these approaches have been applied to systemic sclerosis (SSc), an unmet need remains for validated, non-invasive biomarkers to aid in the diagnosis of SSc, as well as in the assessment of disease progression and response to therapeutic interventions. Advances in global transcriptomic technology over the past 15 years have enabled the assessment of microRNAs that circulate in the blood of patients and the analysis of the macromolecular content of a diverse group of lipid bilayer membrane-enclosed extracellular vesicles, such as exosomes and other microvesicles, which are released by all cells into the extracellular space and circulation. Such advances have provided new opportunities for the discovery of biomarkers in SSc that could potentially be used to improve the design and evaluation of clinical trials and that will undoubtedly enable the development of personalized and individualized medicine for patients with SSc.

A prospective, open-label, non-comparative study of ambrisentan with anti-fibrotic agent combination therapy in the treatment of diffuse systemic sclerosis

Background

Systemic Sclerosis is a multifactorial autoimmune rheumatic disease characterized by inflammation, fibrosis, immune dysregulation and vascular dysfunction.

Methods

An open label, prospective, non-comparative study evaluating ambrisentan with an antifibrotic agent in diffuse cutaneous systemic sclerosis (dcSSc). Recruited 15 consecutive patients with dcSSc who were already on a stable dose of an antifibrotic agent and if they met inclusion criteria they were initiated on ambrisentan 5 mg/day for 12 months. Primary outcome measure was the modified Rodnan skin score (mRSS) while secondary measures were the short form 36 (SF-36) questionnaire, the Medsger severity score and pulmonary function studies.

Results

Fifteen patients were recruited and ten patients completed all 12 months of the study. An intention to treat was used to analyze the data. There was statistical improvement of the mean mRSS and the perceived change in health component of the SF-36. The Medsger severity score and pulmonary function studies remained unchanged over the course of the study.

Conclusion

Patients who tolerated the combination of an antifibrotic with ambrisentan had an improvement of their mRSS over the course of the study as well as an improvement of their perceived health.

Trial registration

Clinicaltrials.gov, NCT01093885; March 2010.

Baseline Plasma Cell Gene Signature Predicts Improvement in Systemic Sclerosis Skin Scores Following Treatment With Inebilizumab (MEDI-551) and Correlates With Disease Activity in Systemic Lupus Erythematosus and Chronic Obstructive Pulmonary Disease

OBJECTIVE

B cells impact the progression of systemic sclerosis (SSc; scleroderma) through multiple pathogenic mechanisms. CD19 inhibition in mice reduced skin thickness, collagen production, and autoantibody levels, consistent with CD19 expression on plasma cells (PCs), the source of antibody production. PC depletion could effectively reduce collagen deposition and inflammation in SSc; therefore, we investigated the effects of PC depletion on SSc disease activity.

METHODS

A PC gene signature was evaluated in SSc skin biopsy samples in 2 phase I clinical trials. We assessed microarray data from tissue from public studies of chronic obstructive pulmonary disease (COPD), idiopathic pulmonary fibrosis (IPF), dermatomyositis (DM), systemic lupus erythematosus (SLE), and atopic dermatitis, as well as blood from a phase IIb clinical trial in SLE.

RESULTS

The PC signature was elevated in SSc skin specimens compared to healthy donor skin (P = 2.28 × 10^-6 ) and correlated with the baseline modified Rodnan skin thickness score (MRSS) (r = 0.64, P = 0.0004). Patients with a high PC signature at baseline showed greater improvement in the MRSS (mean ± SD change 35 ± 16%; P = 6.30 × 10^-4 ) following anti-CD19 treatment with inebilizumab (MEDI-551) than did patients with a low PC signature at baseline (mean ± SD change 8 ± 12%; P = 0.104). The PC signature was overexpressed in tissue from patients with SLE, DM, COPD, interstitial lung disease, and IPF relative to controls (all fold change >2; P < 0.001). The PC signature also differed significantly between SLE patients with mild-to-moderate disease and those with severe disease (SLE Disease Activity Index cutoff at 10) (fold change 1.44; P = 3.90 × 10^-3 ) and correlated significantly with the degree of emphysema in COPD (r = 0.53, P = 7.55 × 10^-8 ).

CONCLUSION

Our results support the notion that PCs have a role in the pathogenesis of SSc and other autoimmune or pulmonary indications. An elevated pretreatment PC signature was associated with increased benefit from MEDI-551 in SSc.

Interstitial lung disease in systemic sclerosis: challenges in early diagnosis and management

Interstitial lung disease (ILD) is a group of lung diseases characterized by thickening of the interstitium surrounding pulmonary alveolar walls. It is related to specific radiographic features in lung imaging and/or the presence of restrictive disorders in pulmonary function tests (PFTs). ILD is one of the leading causes of death in systemic sclerosis patients. Major risk factors of ILD associated with SSc (SSc-ILD) include male sex, diffuse type of cutaneous SSc and presence of anti-Scl-70 antibodies.

SSc-ILD is challenging to diagnose at an early stage as the symptoms are non-specific. The greatest risk of its development is during the 4–5 years after the initial diagnosis of systemic sclerosis. Clinical vigilance at the time, including regular pulmonary function tests and/or high-resolution com-puted tomography (HRCT), is needed. The aim of this paper is to summarize the current knowledge on early diagnostic methods and progression risk factors for SSc-ILD.

Subsets in systemic sclerosis: one size does not fit all

Purpose

Systemic sclerosis (SSc) is a heterogeneous disease that is often divided into subsets to stratify patients and predict prognosis. We hypothesized that individual methods of subsetting would not prognosticate equally well for different outcomes or in patients at different stages of disease.

Methods

We subsetted subjects with SSc using three approaches: limited versus diffuse cutaneous SSc (lcSSc, dcSSc); grouped by SSc-specific antibodies; and, grouped using unsupervised clustering. We studied patients with <2 years or between 2-4 years of disease duration, separately. Outcomes were time to death and time to development of (a) SF-36 Physical Component Score <40, (b) forced vital capacity <70% predicted, (c) echocardiographic pulmonary hypertension, and (d) interstitial lung disease. We used Cox proportional hazards models to determine the ability of the subsets to predict the outcomes of interest, and Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) to compare the performance of the models.

Results

In this international, multicentered cohort of over 500 SSc subjects with less than four years of disease duration, none of the three methods of subsetting studied was able to predict all of the outcomes of interest. Different subsetting methods predicted different outcomes within and between each disease duration group. In general, subsetting by skin performed somewhat better than the two other methods, but this was not consistent and there was considerable variability in the models.

Conclusions

Subsetting SSc to consistently predict morbidity and mortality in subjects at different stages of disease remains an important challenge.