Comprehensive Genotyping for Susceptibility to Metabolic Muscle Disease

描述（由申请人提供）：该项目的目标是开发一种大规模的代谢性肌肉疾病基因分型工具，可应用于某些高危人群，以防止危及生命的症状迅速成为公共卫生问题。在一般人群中，由环境因素如药物、病毒感染、过度劳累、麻醉、睡眠剥夺、暴露于极端温度和其他环境压力因素引发的危及生命的代谢性肌肉疾病正在增加。在潜在的风险人群中，有近2000万美国人正在服用降胆固醇药物，即他汀类药物；那些受到多种环境触发的人，包括军队、警察和消防新兵，以及运动员；每年有超过1500万美国人在全身麻醉下进行手术。最近扩大的新生儿筛查也有助于发现更多有发生严重代谢紊乱风险的新生儿，而目前还没有全面的突变筛查。有必要建立一个全面的基因分型平台，以便在症状出现之前为所有这些高风险群体提供致病突变和与风险相关的遗传变异检测。考虑到数以百万计的潜在风险美国人，这种筛查工具的疾病预防程度将对降低死亡率和发病率产生重大影响。对于这项I期研究，我们建议开发一种大规模的基因分型分析，用于与10种肌肉疾病相关的384种突变和遗传变异，从长远来看，可以应用于筛查所有7个风险组。使用的平台将是GoldenGate基因分型分析（Illumina），它采用尖端技术生产业内最强大的基因分型系统之一。GoldenGate检测允许在扩展和扩增步骤中进行高度复用，从而最大限度地减少了该过程所需的时间、试剂量和材料。该检测将用于筛选960份DNA样本，这些样本来自严重他汀类肌病患者和4个对照组。在初步研究中，评估了严重他汀类肌病患者中引起3种常见代谢性肌肉疾病的7个突变。10%的患者有疾病突变；在这些疾病中，携带者的数量增加了20倍之多。这项拟议的研究将使评估的突变和变异数量增加55倍，将研究的疾病数量增加2.75倍，预测具有致病风险因素的个体数量将至少增加到25%。该项目的结果预计将为在II期开发一种商业可用的测定方法奠定基础，该方法将扩大到包括各种遗传变异和疾病，并将应用于其他高风险群体。目前，还没有在本研究提出的水平上对代谢性肌肉疾病进行全面的基于遗传学的检测。这些疾病的共同之处在于，它们可由在普通人群中日益普遍的环境暴露引发。每年有成千上万的人因意外触发的潜在疾病而遭受危及生命的丧失能力的肌肉损伤，从不良药物反应（例如，他汀类药物暴露）到暴露在异常温度下的极端劳累（例如，部署到伊拉克的士兵）。对遗传性肌肉疾病进行综合基因分型的建议发展将导致长期具有成本效益的筛查，降低发病率，并降低与不良后果相关的医疗保健费用，至少有7个高风险群体代表3500万人。

DESCRIPTION (provided by applicant): The goal of this project is to develop a large-scale genotyping tool for metabolic muscle disease that can be applied to certain high risk groups in order to prevent life-threatening symptoms that are fast becoming a public health problem. The triggering of life-threatening metabolic muscle diseases by environmental factors such as drugs, viral infections, extreme exertion, anesthesia, sleep deprivation, exposure to temperature extremes, and other environmental stressors is increasing in the general population. Among those potentially at risk are nearly 20 million Americans taking cholesterol-lowering drugs, known as statins; those submitted to multiple environmental triggers including military, police and fire-fighting recruits, as well as athletes; and more than 15 million Americans who have surgery performed annually under general anesthesia. The recent expansion of newborn screening is also responsible for detecting larger numbers of newborns at risk for developing serious metabolic disorders for which no comprehensive mutation screen is available. There is a need for a comprehensive genotyping platform that will provide detection of disease-causing mutations and risk-associated genetic variants for all of these high risk groups preferably before symptoms arise. The extent of disease prevention from this screening tool will have a large impact on reducing both mortality and morbidity considering the millions of Americans potentially at risk. For this Phase I study, we propose to develop a large-scale genotyping assay for 384 mutations and genetic variants associated with 10 muscle diseases that, in the long-term, can be applied to screening all 7 risk groups. The platform used will be the GoldenGate Genotyping Assay (Illumina) which employs cutting edge technology for producing one of the most robust systems for genotyping in the industry. The GoldenGate assay allows for a high degree of multiplexing during extension and amplification steps, thus minimizing time, reagent volumes, and materials required for the process. The assay will be used to screen 960 DNA samples from individuals with severe statin myopathy and 4 control groups. In preliminary studies, 7 mutations causing 3 common metabolic muscle diseases were evaluated in patients with severe statin myopathy. Ten percent of patients had disease mutations; carrier status alone was increased for certain of these disorders as much as 20-fold. The proposed study will increase the number of mutations and variants evaluated by 55-fold and increase the number of disorders studied by 2.75-fold, predicting that the number of individuals with disease- causing risk factors will rise to at least 25%. The results of this project are expected to set the stage for the development of a commercially available assay in Phase II that will be expanded to include a wide variety of genetic variants and disorders and will be applied to additional high risk groups. At the present time, there is no comprehensive genetic-based testing for metabolic muscle diseases at the level proposed in this study. The disorders have in common the fact that they can be triggered by environmental exposures that are increasingly prevalent in the general population. Thousands of individuals suffer life-threatening episodes of incapacitating muscle damage every year from unexpected triggering of underlying disease ranging from adverse drug reactions (e.g., statin exposure) to extreme exertion during exposure to extraordinary temperatures (e.g., soldiers deployed to Iraq). The proposed development of comprehensive genotyping for hereditary muscle diseases will lead in the long-term to cost-effective screening, reduced morbidity, and lower healthcare costs relevant to adverse outcomes for at least 7 high risk groups representing >35 million individuals.