Beyond Conventional Hemostasis Testing: The Diagnostic Impact of Genetic Analysis in inherited Mild Bleeding Disorders.

Abstract

Abstract: Mild bleeding disorders (MBDs) comprise a heterogeneous group of inherited conditions characterized by clinically relevant bleeding symptoms despite largely normal or inconclusive results in routine hemostatic testing. These disorders account for a substantial proportion of referrals to specialized hemostasis clinics and include von Willebrand disease (VWD), inherited platelet function disorders, and mild coagulation factor deficiencies. Despite systematic diagnostic algorithms, many patients with MBDs remain without a definitive diagnosis and are classified as having bleeding disorder of unknown cause (BDUC), complicating clinical management and counseling. Conventional diagnostic approaches rely on structured bleeding assessment tools, detailed family history, and stepwise laboratory testing. Biological variability, assay limitations, and phenotypic overlap often result in inconclusive findings.

Abstract: Recent advances in genetic analysis have begun to transform this diagnostic landscape. Targeted next-generation sequencing panels, whole-exome sequencing (WES), and whole-genome sequencing (WGS) enable identification of pathogenic variants across numerous hemostasis-related genes. In MBDs, genetic testing is valuable for refining diagnoses in qualitative VWD, confirming inherited platelet disorders, and identifying rare mild coagulopathies. In contrast, its diagnostic yield in type 1 and low von Willebrand factor (VWF) is modest, reflecting complex genetic architecture, modifier effects, and incomplete penetrance. In BDUC, genetic testing has revealed monogenic causes in some patients and multifactorial contributions in others.

Abstract: Genetic testing should therefore be regarded as a complementary tool rather than a replacing conventional diagnostics. Integrated with clinical and laboratory findings and supported by expert variant interpretation, it can reduce diagnostic uncertainty and improve disease classification in patients with MBDs.