Anticoagulation and antiplatelet therapy in hereditary hemorrhagic telangiectasia: A scoping review

Pharmacogenomic Considerations for Anticoagulant Prescription in Patients with Hereditary Haemorrhagic Telangiectasia

Hereditary haemorrhagic telangiectasia (HHT) is a vascular dysplasia that commonly results in bleeding but with frequent indications for therapeutic anticoagulation. Our aims were to advance the understanding of drug-specific intolerance and evaluate if there was an indication for pharmacogenomic testing. Genes encoding proteins involved in the absorption, distribution, metabolism, and excretion of warfarin, heparin, and direct oral anticoagulants (DOACs) apixaban, rivaroxaban, edoxaban, and dabigatran were identified and examined. Linkage disequilibrium with HHT genes was excluded, before variants within these genes were examined following whole genome sequencing of general and HHT populations. The 44 genes identified included 5/17 actionable pharmacogenes with guidelines. The 76,156 participants in the Genome Aggregation Database v3.1.2 had 28,446 variants, including 9668 missense substitutions and 1076 predicted loss-of-function (frameshift, nonsense, and consensus splice site) variants, i.e., approximately 1 in 7.9 individuals had a missense substitution, and 1 in 71 had a loss-of-function variant. Focusing on the 17 genes relevant to usually preferred DOACs, similar variant profiles were identified in HHT patients. With HHT patients at particular risk of haemorrhage when undergoing anticoagulant treatment, we explore how pre-emptive pharmacogenomic testing, alongside HHT gene testing, may prove beneficial in reducing the risk of bleeding and conclude that HHT patients are well placed to be at the vanguard of personalised prescribing.

Pulmonary hypertension in hereditary hemorrhagic telangiectasia: A clinical review

Hereditary hemorrhagic telangiectasia (HHT) is a rare autosomal dominant hereditary disorder characterized by recurrent spontaneous epistaxis, mucocutaneous telangiectasias, and solid organ arteriovenous malformations (AVMs). Pulmonary hypertension (PH) is an increasingly recognized complication in patients with HHT, most often precipitated by high-output heart failure in the presence of hepatic AVMs as well as pulmonary arterial hypertension in the form of a proliferative vasculopathy. The presence of PH in patients with HHT is associated with significant elevations in rates of morbidity and mortality. Additionally, there is growing recognition of a thromboembolic propensity in this population that increases the risk of chronic thromboembolic PH, posing unique clinical considerations regarding the use of anticoagulation. Patients with HHT are also at risk of PH due to disorders commonly seen in the general population, including left-sided heart and lung disease. The etiology of PH in HHT is multifaceted and complex; the diagnostic approach and treatment strategies must consider the underlying pathophysiology of HHT. This comprehensive review summarizes current knowledge of PH in HHT, detailing the pathogenesis of known etiologies, diagnostic evaluation, and suggested treatment modalities as well as emerging therapies that may be of future interest.

Unsupervised machine learning algorithms identify expected haemorrhage relationships but define unexplained coagulation profiles mapping to thrombotic phenotypes in hereditary haemorrhagic telangiectasia

Hereditary haemorrhagic telangiectasia (HHT) can result in challenging anaemia and thrombosis phenotypes. Clinical presentations of HHT vary for relatives with identical casual mutations, suggesting other factors may modify severity. To examine objectively, we developed unsupervised machine learning algorithms to test whether haematological data at presentation could be categorised into sub-groupings and fitted to known biological factors. With ethical approval, we examined 10 complete blood count (CBC) variables, four iron index variables, four coagulation variables and eight iron/coagulation indices combined from 336 genotyped HHT patients (40% male, 60% female, 86.5% not using iron supplementation) at a single centre. T-SNE unsupervised, dimension reduction, machine learning algorithms assigned each high-dimensional datapoint to a location in a two-dimensional plane. k-Means clustering algorithms grouped into profiles, enabling visualisation and inter-profile comparisons of patients' clinical and genetic features. The unsupervised machine learning algorithms using t-SNE and k-Means identified two distinct CBC profiles, two iron profiles, four clotting profiles and three combined profiles. Validating the methodology, profiles for CBC or iron indices fitted expected patterns for haemorrhage. Distinct coagulation profiles displayed no association with age, sex, C-reactive protein, pulmonary arteriovenous malformations (AVMs), ENG/ACVRL1 genotype or epistaxis severity. The most distinct profiles were from t-SNE/k-Means analyses of combined iron-coagulation indices and mapped to three risk states - for venous thromboembolism in HHT; for ischaemic stroke attributed to paradoxical emboli through pulmonary AVMs in HHT; and for cerebral abscess attributed to odontogenic bacteremias in immunocompetent HHT patients with right-to-left shunting through pulmonary AVMs. In conclusion, unsupervised machine learning algorithms categorise HHT haematological indices into distinct, clinically relevant profiles which are independent of age, sex or HHT genotype. Further evaluation may inform prophylaxis and management for HHT patients' haemorrhagic and thrombotic phenotypes.