Biochemical and Molecular Newborn Screening for Familial Hypercholesterolemia

项目摘要 动脉粥样硬化性心血管疾病仍然是人类死亡的主要原因， 诊断和治疗的进展。家族性高胆固醇血症（FH）是一种遗传性疾病， 出生时血液中低密度脂蛋白胆固醇（LDL-C）水平显著升高 并使受影响的个体易患早期心血管疾病。FH影响200-250人中的1人， FH是人类最常见的潜在致命的遗传性疾病。所有未经治疗的FH男性中有一半死于 心血管疾病的发病率在55岁之前就已降低，15%未经治疗的FH女性在60岁之前死亡。在联合 在美国，大多数患有FH的个体仅根据其血液LDL-C水平进行诊断，尽管遗传因素 检测显示已知引起FH的基因之一的致病突变是另一种方法， 诊断.尽管广泛使用胆固醇测试，FH仍然严重诊断不足， 在包括美国在内的大多数国家，10%的FH患者被发现。 开发一种检测新生儿FH的工具代表了一个前所未有的机会， 治疗早期诊断和治疗FH可有效预防过早发病和死亡。 此外，幼儿FH的鉴定往往导致父母和其他一级诊断。 亲属处于危险之中，产生积极的级联效应。出于这些原因，多种不同的筛选策略 已经被设计用于识别患有FH的儿童和成人，但它们的成功有限。 筛查新生儿FH为人群范围内的检测提供了潜在的机会， 迄今为止，系统研究。 本研究的目的是设计一个测试算法，可以检测FH的新生儿群体。使用 生化和分子遗传学测试和现有的干血点从丢弃的威斯康星州新生儿 筛选标本，这项研究将评估一大群（10，000）新生儿的FH生化标志物， 导致FH的基因突变。生化标记遗传数据和新生儿人口统计信息 将用于创建多因素模型，以预测给定个体的FH。有效诊断FH， 新生儿期，使用现有的和高效的人口筛查工具，具有真实的潜力 这一疾病目前正在给我们的人口造成毁灭性的损失。

PROJECT SUMMARY Atherosclerotic cardiovascular disease remains the leading cause of death in humans despite significant advances in diagnosis and treatment. Familial hypercholesterolemia (FH) is a genetic disorder that leads to markedly increased levels of low-density lipoprotein cholesterol (LDL-C) in the blood that are present from birth and predispose affected individuals to early cardiovascular disease. FH affects 1 in 200-250 individuals, making FH the most common potentially fatal genetic disease in humans. Half of all untreated men with FH die of cardiovascular disease by age 55 and 15% of untreated women with FH die before 60 years of age. In the United States, most individuals with FH are diagnosed based on their blood levels of LDL-C alone, although genetic testing showing a disease-causing mutation in one of the genes known to cause FH is another way to make the diagnosis. Despite widespread use of cholesterol testing, FH remains profoundly underdiagnosed with less than 10% of individuals with FH identified in most countries, including the United States. The development of a tool to detect FH in the newborn represents an unprecedented opportunity to initiate early treatment. Early diagnosis and treatment of FH is effective at preventing premature morbidity and mortality. Additionally, identification of a young child with FH often leads to diagnosis of parents and other first-degree relatives at risk, creating a positive cascade effect. For these reasons, multiple different screening strategies have been designed to identify both children and adults with FH, but they have been of limited success. Screening newborns for FH presents a potential opportunity for population-wide detection but has not been systematically studied to date. The aim of this study is to design a testing algorithm that can detect FH in the newborn population. Using biochemical and molecular genetic tests and existing dried blood spots from discarded Wisconsin newborn screening specimens, this study will assess a large group (10,000) of newborns for FH biochemical markers and genetic mutations that cause FH. The biochemical markers, genetic data, and newborn demographic information will be used to create a multifactorial model to predict FH in a given individual. Effective diagnosis of FH in the newborn period, using an already existing and highly effective population screening tool, has the real potential to dramatically change the natural history of a disease that currently exerts a devastating toll on our population.