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家族性高胆固醇血症在立陶宛人群中的检测和筛查算法。

Algorithm for detection and screening of familial hypercholesterolemia in Lithuanian population.

机构信息

Faculty of Medicine, Vilnius University, Vilnius, Lithuania.

Clinic of Cardiac and Vascular Diseases, Vilnius University Hospital Santaros Klinikos, Vilnius, Lithuania.

出版信息

Lipids Health Dis. 2024 May 7;23(1):136. doi: 10.1186/s12944-024-02124-x.

DOI:10.1186/s12944-024-02124-x
PMID:38715054
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11077833/
Abstract

BACKGROUND

Familial 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.

METHODS

A 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.

RESULTS

A 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.

CONCLUSIONS

Most 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.

摘要

背景

家族性高胆固醇血症(FH)是最常见的常染色体显性遗传病之一。FH 导致低密度脂蛋白胆固醇(LDL-C)水平终生升高,进而导致动脉粥样硬化性心血管疾病。尽管有降脂治疗,FH 的发病率仍被广泛低估且治疗不足。FH 患者心血管风险增加;因此,早期诊断和治疗至关重要。为了应对 FH 的负担,一些国家已经实施了国家 FH 筛查计划。立陶宛目前用于 FH 检测的方法主要基于机会性检测,随后对指数病例一级亲属进行级联筛查。

方法

本研究共纳入 428 例患者。疑似 FH 的患者被转介至脂质科中心进行全面评估。根据荷兰脂质诊所网络(DLCN)评分系统符合可能或明确 FH 标准的患者,或 LDL-C≥6.5mmol/L 的患者进行基因检测。还记录了实验室和仪器检查、早期动脉粥样硬化的血管标志物数据以及放射科医生和眼科医生等其他专家的咨询。

结果

共有 127/428(30%)例患者进行了基因检测。在 38.6%(n=49/127)的患者中发现了 FH 相关突变。在纳入的 428 例患者中,诊断为冠心病(CAD)的患者为 13%(n=57/428),而早发性 CAD 的患者为 47/428(11%)。在 49 例 FH 相关突变患者中诊断出 CAD,其中 19%(n=9/49)为早发性,且均为早发性。

结论

本研究中的大多数患者被归类为可能或可能的 FH,无论年龄和性别均无差异。FH 的中位诊断年龄为 47 岁,女性明显大于男性,这表明该研究与 LitHir 计划有很强的联系。在可能和明确的 FH 患者以及有 FH 致病突变的患者中,CAD 和早发性 CAD 更为常见。本研究中描述的算法是立陶宛首次尝试实施特定工具,该工具可最大限度地提高 FH 检出率,准确诊断 FH,排除血脂异常的继发性原因,并更准确地选择患者进行级联筛查启动。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f19f/11077833/cb78c803dbeb/12944_2024_2124_Fig5_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f19f/11077833/cb78c803dbeb/12944_2024_2124_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f19f/11077833/1640b42bf1c8/12944_2024_2124_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f19f/11077833/8e0cd4312a3e/12944_2024_2124_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f19f/11077833/12893666b2be/12944_2024_2124_Fig3_HTML.jpg
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