Autoantibody Clustering in Systemic Lupus Erythematosus-Associated Pulmonary Arterial Hypertension

World Congress on Heart Congress and Surgery

October 21, 2021 | Webinar

Ritasman Baisya

Clinical Immunology & Rheumatology, India

Scientific Tracks Abstracts: J Cardiovasc Dis Diagn

Abstract :

Introduction: Systemic lupus erythematous–associated pulmonary arterial hypertension (SLE-PAH) is one of the important causes of mortality in lupus patients. Different autoantibodies are associated with SLE-PAH which can predict its future development and management Objective: The objective of the study was to identify distinct autoantibody-based clusters in SLE-PAH patients and to compare demographic characters, clinical phenotypes, and therapeutic strategy across the clusters. Methods: Three distinct autoantibody clusters were identified using k-means cluster analysis in 71 SLE-PAH patients. After clustering, associations between final clusters and patient characteristics were assessed by one-way analysis of variance (ANOVA) with post hoc analysis for continuous variables and Fisher’s exact Hamilton test for categorical variables. Result: Cluster1 had predominant Sm-RNP, Smith, SS-A association; cluster 2 had no definite autoantibody association; and cluster 3 was associated with nucleosome, histone, dsDNA, and ribosomal P protein. Patients in cluster 3 had a highly active disease while those in cluster 1 had significant cytopenia. Mean age and mean right ventricular systolic pressure (RVSP) were both high in cluster 2, indicating later-onset PAH in this group. (Abstract Image) Conclusion: This was the first autoantibody-based cluster analysis study in SLE-PAH patients in India which confirmed that autoantibodies did exist as clusters and the presence of definite autoantibodies can predict future development of pulmonary hypertension in these patients.

Biography :

Dr Ritasman Baisya completed his MD Medicine course in 2018 and DM Rheumatology course in 2021 . As a young researcher ,he had special interest in advanced research on cardiovascular morbidity and mortality in autoimmune diseases including SLE .Cluster analysis , a new machine learning algorithm is used in the present study and ANA immunoblot was done for all patients .