Antiphospholipid syndrome: advances in diagnosis, pathogenesis, and management.
Christian LoodDavid Ware BranchThomas L OrtelPublished in: BMJ (Clinical research ed.) (2023)
Antiphospholipid syndrome (APS) is a thrombo-inflammatory disease propelled by circulating autoantibodies that recognize cell surface phospholipids and phospholipid binding proteins. The result is an increased risk of thrombotic events, pregnancy morbidity, and various other autoimmune and inflammatory complications. Although antiphospholipid syndrome was first recognized in patients with lupus, the stand alone presentation of antiphospholipid syndrome is at least equally common. Overall, the diagnosis appears to affect at least one in 2000 people. Studies of antiphospholipid syndrome pathogenesis have long focused on logical candidates such as coagulation factors, endothelial cells, and platelets. Recent work has shed light on additional potential therapeutic targets within the innate immune system, including the complement system and neutrophil extracellular traps. Vitamin K antagonists remain the mainstay of treatment for most patients with thrombotic antiphospholipid syndrome and, based on current data, appear superior to the more targeted direct oral anticoagulants. The potential role of immunomodulatory treatments in antiphospholipid syndrome management is receiving increased attention. As for many systemic autoimmune diseases, the most important future direction is to more precisely identify mechanistic drivers of disease heterogeneity in pursuit of unlocking personalized and proactive treatments for patients.
Keyphrases
- direct oral anticoagulants
- cell surface
- endothelial cells
- systemic lupus erythematosus
- venous thromboembolism
- immune response
- ejection fraction
- end stage renal disease
- oxidative stress
- newly diagnosed
- atrial fibrillation
- fatty acid
- human health
- multiple sclerosis
- prognostic factors
- pregnant women
- case report
- rheumatoid arthritis
- patient reported outcomes
- risk assessment
- machine learning
- drug induced
- current status
- deep learning
- artificial intelligence
- climate change
- smoking cessation
- data analysis
- high glucose