Scleroderma autoantibodies in guiding monitoring and treatment decisions

Shah, Shivani; Denton, Christopher P.

doi:10.1097/bor.0000000000000904

Cited by 12 publications

(8 citation statements)

References 66 publications

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“…Autoantibodies are one of the strongest predictors of disease course, outcome and therapeutic response in patients with SSc ( 4 , 15 ). Nevertheless, uncertainties remain in the clinical association for some autoantibodies.…”

Section: Discussionmentioning

confidence: 99%

“…Newer data suggest that antibodies could be pathogenic or at least contribute to the perennation of the disease ( 8 , 11 , 12 ). In addition, they have been established as strong predictors of disease outcome, of certain organ complications and therapeutic response ( 13 – 15 ). For example, Topo-1 and RP3 are more specific for dcSSc than ACA.…”

Section: Introductionmentioning

confidence: 99%

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Comprehensive autoantibody profiles in systemic sclerosis: Clinical cluster analysis

Höppner

Tabeling²,

Casteleyn³

et al. 2023

Front. Immunol.

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BackgroundSystemic sclerosis (SSc) belongs to the group of connective tissue diseases and is associated with the occurrence of disease-specific autoantibodies. Although it is still controversial whether these antibodies contribute to pathogenesis, there are new insights into the development of these specific antibodies and their possible pathophysiological properties. Interestingly, they are associated with specific clinical manifestations, but for some rarer antibodies this association is not fully clarified. The aim of this study is a comprehensive analysis of the serum autoantibody status in patients with SSc followed by correlation analyses of autoantibodies with the clinical course of the disease.MethodsSerum from SSc patients was analyzed using a line blot (EUROLINE, EUROIMMUN AG) for SSc-related autoantibodies. Autoantibodies to centromere, Topo-1, antimitochondrial antibodies (AMA) M2 subunit, angiotensin II type 1 receptors (AT1R) and endothelin-1 type-A-receptors (ETAR) were also determined by ELISA. We formed immunological clusters and used principal components analysis (PCA) to assign specific clinical characteristics to these clusters.ResultsA total of 372 SSc patients were included. 95.3% of the patients were antinuclear antibody positive and in 333 patients at least one SSc specific antibody could be detected. Four immunological clusters could be found by PCA. Centromere, Topo-1 and RP3 all formed own clusters, which are associated with distinct clinical phenotypes. We found that patients with an inverted phenotype, such as limited cutaneous SSc patients within the Topo-1 cluster show an increased risk for interstital lung disease compared to ACA positive patients. Anti-AT1R and anti-ETAR autoantibodies were measured in 176 SSc patients; no association with SSc disease manifestation was found. SSc patients with AMA-M2 antibodies showed an increased risk of cardiovascular events.ConclusionIn our in large cluster analysis, which included an extended autoantibody profile, we were able to show that serologic status of SSc patients provides important clues to disease manifestation, co-morbidities and complications. Line blot was a reliable technique to detect autoantibodies in SSc and detected rarer autoantibodies in 42% of our patients.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comprehensive autoantibody profiles in systemic sclerosis: Clinical cluster analysis

Höppner

Tabeling²,

Casteleyn³

et al. 2023

Front. Immunol.

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“…Autoantibodies are one of the strongest predictors of disease course, outcome and therapeutic response in patients with SSc. 4,15 Nevertheless, uncertainties remain in the clinical association for some autoantibodies. In the present study, we were able to demonstrate that the classical SSc antibodies (ACA, Topo-1 and RP3) show strong negative correlations and form their own clusters to which certain clinical manifestations of SSc can be assigned.…”

Section: Discussionmentioning

confidence: 99%

“…Tocilizumab showed significant decrease in rates of lung function decline in Topo-1 positive patients but not in Topo-1 negative patients in phase 2 and 3 studies. 15,79–81…”

Section: Discussionmentioning

confidence: 99%

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Comprehensive Autoantibody Profiles in Systemic Sclerosis: Clinical Cluster Analysis

Höppner

Tabeling

Casteleyn

et al. 2022

Preprint

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Background: Systemic sclerosis (SSc) belongs to the group of connective tissue diseases and is associated with the occurrence of disease-specific autoantibodies. Although it is still controversial whether these antibodies contribute to pathogenesis, there are new insights into the development of these specific antibodies and their possible pathophysiological properties. Interestingly, they are associated with specific clinical manifestations, but for some rarer antibodies this association is not fully clarified. The aim of this study is a comprehensive analysis of the serum autoantibody status in patients with SSc followed by correlation analyses of autoantibodies with the clinical course of the disease. Methods: Serum from SSc patients was analyzed using a line blot (EUROLINE, EUROIMMUN AG) for SSc-related autoantibodies. Autoantibodies to centromere, Topo-1, antimitochondrial antibodies (AMA) M2 subunit, angiotensin II type 1 receptors (AT1R) and endothelin-1 type-A-receptors (ETAR) were also determined by ELISA. We formed immunological clusters and used principal components analysis (PCA) to assign specific clinical characteristics to these clusters. Results: A total of 372 SSc patients were included. 95.3% of the patients were antinuclear antibody positive and in 333 patients at least one SSc specific antibody could be detected. Four immunological clusters could be found by PCA. Centromere, Topo-1 and RP3 all formed own clusters, which are associated with distinct clinical phenotypes. We found that patients with an inverted phenotype, such as limited cutaneous SSc patients within the Topo-1 cluster show an increased risk for ILD compared to ACA positive patients. Anti-AT1R and anti-ETAR autoantibodies were measured in 176 SSc patients; no association with SSc disease manifestation was found. SSc patients with AMA-M2 antibodies showed an increased risk of cardiovascular events. Conclusion: In our in large cluster analysis, which included an extended autoantibody profile, we were able to show that serologic status of SSc patients provides important clues to disease manifestation, co-morbidities and complications. Line blot was a reliable technique to detect autoantibodies in SSc and detected rarer autoantibodies in 42% of our patients.

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Use of artificial intelligence algorithms to analyse systemic sclerosis-interstitial lung disease imaging features

Zhao,

Long,

et al. 2024

Rheumatol Int

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Scleroderma autoantibodies in guiding monitoring and treatment decisions

Cited by 12 publications

References 66 publications

Comprehensive autoantibody profiles in systemic sclerosis: Clinical cluster analysis

Comprehensive autoantibody profiles in systemic sclerosis: Clinical cluster analysis

Comprehensive Autoantibody Profiles in Systemic Sclerosis: Clinical Cluster Analysis

Use of artificial intelligence algorithms to analyse systemic sclerosis-interstitial lung disease imaging features

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