New advances in genomics and epigenetics in antiphospholipid syndrome

Abstract

APS patients exhibit a wide clinical heterogeneity in terms of the disease's origin and progression. This diversity can be attributed to consistent aPL profiles and other genetic and acquired risk factors. Therefore, understanding the pathophysiology of APS requires the identification of specific molecular signatures that can explain the pro-atherosclerotic, pro-thrombotic and inflammatory states observed in this autoimmune disorder. In recent years, significant progress has been made in uncovering gene profiles and understanding the intricate epigenetic mechanisms and microRNA changes that regulate their expression. These advancements have highlighted the crucial role played by these regulators in influencing various clinical aspects of APS. This review delves into the recent advancements in genomic and epigenetic approaches used to uncover the mechanisms contributing to vascular and obstetric involvement in APS. Furthermore, we discuss the implementation of novel bioinformatics tools that facilitate the investigation of these mechanisms and pave the way for personalized medicine in APS.

Keywords: antiphospholipid syndrome; bioinformatics; epigenetics; microRNA; transcriptomics.

Figure 1.

Alteration of the IFN pathway in APS: consistent findings across independent studies. Recent independent studies have shed light on alteration of the IFN pathway in APS. Notably, three distinct investigations have consistently reported the upregulation of IFN-related genes in patients with APS, demonstrating their significant association with various clinical features such as autoantibody profile, thrombosis and pre-eclampsia. Despite the diversity in study cohorts, sample types (whole blood, PBMCs and neutrophils) and methodologies (RNAseq and RT-PCR), the consistent finding across all studies is upregulation of the IFN pathway. ML: machine learning; ROC AUC: area under the receiver operating characteristics curve

Figure 2.

Uncovering new opportunities and perspectives in APS research. Despite the advancements in new technologies, the field of APS still faces a shortage of large-scale studies. However, with the emergence of multi-omics technologies and innovative computational tools, particularly machine learning methodologies, there is an unprecedented opportunity to transform APS research. Integrating diverse clinical and molecular data from extensive cohorts of patients using these cutting-edge approaches holds the potential to unlock novel pathological mechanisms underlying APS. Additionally, these methods offer the promise of identifying previously unknown biomarkers and therapeutic targets. As a result, the development of precision medicine in APS can be significantly accelerated, offering more tailored and effective treatments to patients