Four clinical and biological phenotypes in antiphospholipid syndrome: a cluster analysis of 174 patients with antinuclear antibody tests

抗核抗体 抗磷脂综合征 表型 医学 抗体 临床表型 星团(航天器) 免疫学 自身抗体 生物 遗传学 计算机科学 基因 程序设计语言
作者
Marie Ottavi,Pierre Toulon,Barbara Casolla,N. Martis
出处
期刊:Frontiers in Immunology [Frontiers Media]
卷期号:15 被引量:1
标识
DOI:10.3389/fimmu.2024.1361062
摘要

Introduction Antiphospholipid syndrome (APS) is an autoimmune thrombotic disease with various systemic presentations. This study aimed to identify homogeneous groups of patients based on a non-supervised hierarchical cluster analysis and assess the rate of relapse associated with antinuclear antibodies (ANA). Methods This retrospective observational study enrolled patients, over a 90-month period, who had APS as defined by the 2006 Sydney classification criteria, and for whom ANA workup was performed. Agglomerative unsupervised hierarchical clustering was conducted to classify patients into subgroups using 24 variables reflecting a range of clinical and biological baseline features associated with APS. Results Hundred and seventy-four patients were included and were categorized into four phenotypes. Cluster 1 (n=73) associated mostly middle-aged men with risk factors for cardiovascular disease. Obstetrical APS with low-risk thrombosis made up cluster 2 (n=25). Patients with venous thromboembolism (VTE), microvascular findings and double/triple positive APL antibodies (50%) were represented in cluster 3 (n=33). Whereas cluster 4 (n=43) characterized a predominantly female subpopulation with positive ANA and systemic lupus (n=23) that exhibited a high thrombotic risk and more frequent relapses (n=38) (p<0.001). Conclusions This study identified four homogenous groups of patients with APS listed as: i) cardiovascular and arterial risk, ii) obstetrical, iii) VTE and microvascular, and iv) ANA-positive APS. We found that ANA-positivity was associated with higher rates of relapse. Applying ANA status to classification criteria could constitute a novel approach to tailoring management for APS, based on phenotypic patterns and risk assessment.
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