Algorithm for detection and screening of familial hypercholesterolemia in Lithuanian population

Abstract

BackgroundFamilial hypercholesterolemia (FH) is one of the most common autosomal dominant diseases. FH causes a lifelong increase in low-density lipoprotein cholesterol (LDL-C) levels, which in turn leads to atherosclerotic cardiovascular disease. The incidence of FH is widely underestimated and undertreated, despite the availability and effectiveness of lipid-lowering therapy. Patients with FH have an increased cardiovascular risk; therefore, early diagnosis and treatment are vital. To address the burden of FH, several countries have implemented national FH screening programmes. The currently used method for FH detection in Lithuania is mainly based on opportunistic testing with subsequent cascade screening of index cases’ first-degree relatives.MethodsA total of 428 patients were included in this study. Patients with suspected FH are referred to a lipidology center for thorough evaluation. Patients who met the criteria for probable or definite FH according to the Dutch Lipid Clinic Network (DLCN) scoring system and/or had LDL-C > = 6.5 mmol/l were subjected to genetic testing. Laboratory and instrumental tests, vascular marker data of early atherosclerosis, and consultations by other specialists, such as radiologists and ophthalmologists, were also recorded.ResultsA total of 127/428 (30%) patients were genetically tested. FH-related mutations were found in 38.6% (n = 49/127) of the patients. Coronary artery disease (CAD) was diagnosed in 13% (n = 57/428) of the included patients, whereas premature CAD was found in 47/428 (11%) patients. CAD was diagnosed in 19% (n = 9/49) of patients with FH-related mutations, and this diagnosis was premature for all of them.ConclusionsMost patients in this study were classified as probable or possible FH without difference of age and sex. The median age of FH diagnosis was 47 years with significantly older females than males, which refers to the strong interface of this study with the LitHir programme. CAD and premature CAD were more common among patients with probable and definite FH, as well as those with an FH-causing mutation. The algorithm described in this study is the first attempt in Lithuania to implement a specific tool which allows to maximise FH detection rates, establish an accurate diagnosis of FH, excluding secondary causes of dyslipidaemia, and to select patients for cascade screening initiation more precisely.