Towards precision medicine in antiphospholipid syndrome

Abstract

Antiphospholipid syndrome is a rare systemic autoimmune disorder with complex pathophysiology and high heterogeneity in clinical presentation and treatment responses. The core idea of precision medicine is that the varying treatment responses among patients with the same clinical diagnosis are due to differences in their underlying pathogenetic mechanisms and genetic makeup. A better understanding of the pathophysiology and multiple clinical subtypes of antiphospholipid syndrome has led to better classification and subphenotyping of the syndrome. Advances in microarray analysis, cytometry, and omic technologies have helped to identify genes, epigenetic variations, and pathway-informed biomarkers and identified new factors in disease development. By stratifying patients with antiphospholipid syndrome based on clinical or laboratory phenotypes and cellular and molecular profiles in the blood and affected tissues, treatments can be more effectively tailored, improving efficacy and reducing toxicity. This Review explores the current evidence on clinical, genetic, and biomolecular stratification in antiphospholipid syndrome and how artificial intelligence algorithms from clinical and molecular profiles can guide precision medicine in antiphospholipid syndrome.