RESUMEN
Familial dysbetalipoproteinemia (FD) is a highly atherogenic genetically based lipid disorder with an underestimated actual prevalence. In recent years, several biochemical algorithms have been developed to diagnose FD using available laboratory tests. The practical applicability of FD diagnostic criteria and the prevalence of FD in Russia have not been previously assessed. We demonstrated that the diagnostic algorithms of FD, including the diagnostic apoB levels, require correction, taking into account the distribution of apoB levels in the population. At the same time, a triglycerides cutoff ≥ 1.5 mmol/L may be a useful tool in identifying subjects with FD. In this study, a high prevalence of FD was detected: 0.67% (one in 150) based on the ε2ε2 haplotype and triglycerides levels ≥ 1.5 mmol/L. We also analyzed the presence and pathogenicity of APOE variants associated with autosomal dominant FD in a large research sample.
Asunto(s)
Hiperlipoproteinemia Tipo III , Humanos , Proyectos Piloto , Prevalencia , Apolipoproteínas B , Federación de Rusia/epidemiología , TriglicéridosRESUMEN
One of the most common autosomal dominant disorders is familial hypercholesterolemia (FH), causing premature atherosclerotic cardiovascular diseases and a high risk of death due to lifelong exposure to elevated low-density lipoprotein cholesterol (LDL-C) levels. FH has a proven arsenal of treatments and the opportunity for genetic diagnosis. Despite this, FH remains largely underdiagnosed worldwide. Cascade screening is a cost-effective method for the identification of new patients with FH and the prevention of cardiovascular diseases. It is usually based only on clinical data. We describe a 48-year-old index patient with a very high LDL-C level without controlled guidelines-based medication, premature atherosclerosis, and a rare variant in the low-density lipoprotein receptor (LDLR) gene. Phenotypic cascade screening identified three additional FH relatives, namely the proband's daughter, and two young grandsons. The genetic screening made it possible to rule out FH in the proband's younger grandson. This clinical case demonstrates that genetic cascade screening is the most effective way of identifying new FH cases. We also first described in detail the phenotype of patients with a likely pathogenic variant LDLR-p.K223_D227dup.
RESUMEN
INTRODUCTION: One of the key stages of evaluating an edentulous ridge prior to dental implant placement is the analysis of neighboring anatomical structures such as canalis sinuosus (CS) with cone-beam computed tomography (CBCT). CBCT visualization has its own features, such as the change of slice thickness. The aim of the study was to analyze CS prevalence in relation to the slice thickness and CS diameter according to CBCT scans. MATERIALS AND METHODS: In total, 100 CBCT scans of 39 males and 61 females in the age span of 46 to 81 years were retrospectively studied. Terminal alveolar part of CS was analyzed in Ez3D2009 (Vatech) software on panoramic and cross-sectional views with 0.5 mm, 1 mm, 3 mm, and 10 mm slice thicknesses. The prevalence was documented with regard to the diameter and slice thickness and was statistically compared in age and gender groups. RESULTS: This CBCT study demonstrated 55.5% CS prevalence. There was no statistically significant difference in presence between age and gender groups regarding diameter as well as within different slice thickness. The study also showed the importance of the slice thickness choice for CS visualization: the best visualization was reached with 0.5 mm and 1 mm slice thicknesses. Visualization with 0.5 mm and 1 mm slice thicknesses was absolutely the same (55.5%). General CS prevalence with a 10 mm slice thickness (16.5%) was significantly lower (P < 0.05) than the prevalence with a 3 mm slice thickness (20.5%). The correlation between the slice thickness and a diameter more than 1.5 mm in size was not found. CONCLUSION: CBCT analysis showed that the highest CS prevalence was detected with the use of 0.5/1 mm slice thickness. As well, the higher CS diameter, the better is its visualization.