Technology development for rapid detection and diagnosis of metabolic disorders

快速检测和诊断代谢紊乱的技术开发

• 批准号: 9066438
• 负责人: Curt Scharfe
• 金额: $ 25.25万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-07-10 至 2017-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9066438
• 关键词: Technology; development; rapid; detection; diagnosis

DESCRIPTION: Inborn errors of metabolism are detected at birth through public newborn screening (NBS) programs using tandem mass spectrometry (MS/MS), with early and definitive diagnosis critical to patient outcomes. However, a number of obstacles contribute to the delayed diagnosis of many diseases, including high rates of false positive screening results, the inability to differentiate disease subtypes, and biochemical heterogeneity leading to discrepancies in test results. Additionally, some disorders are not included in current NBS panels. Here we propose to investigate whether the combination of genetic and metabolite technologies established in our laboratories - based on targeted next-generation sequencing (NGS) and liquid chromatography tandem mass spectrometry (LC-MS/MS) - can shorten the time to diagnosis following an abnormal NBS result, as well as facilitate detection of additional disorders. We will focus on five disorders, three that exemplify the diagnostic challenges described above (VLCADD - very long-chain acyl-CoA dehydrogenase deficiency, GA1 - glutaric acidemia type I, and MMA - methylmalonic acidemia), and two that are not currently screened (OTCD - ornithine transcarbamoylase deficiency, and CPSD - carbamoylphosphate synthetase I deficiency). These disorders are all caused by mitochondrial enzyme defects that impact the homeostasis of a variety of pathways (e.g. amino acid and organic acid metabolism). Our genetic approach of the responsible disease genes utilizes complementary long padlock probes (cLPPs) for multiplex target capture and NGS, which will identify mutations and copy-number variations (CNVs) at clinical-grade accuracy and completeness and at very low cost. The metabolite approach involves a LC-MS/MS multiplex-marker panel combining both the standard NBS panel and additional markers (e.g. small molecule intermediates of energy metabolism). This strategy is based on the finding that metabolic changes detectable on the mitochondria-systems level, which are secondary to the primary enzyme defect identified in NBS, may play a role in the expression of the disease phenotype. Accordingly, our NGS panel of 524 genes not only contains the primary disease-causing genes but also functionally related candidate genes, which we have prioritized using a gene-network analysis of mitochondrial protein-protein interaction data. We will evaluate the performance of the two technologies using whole blood samples from children with confirmed disease and their parents, as well as archived dried blood spot (DBS) specimens from the patients collected at birth and obtained from the California Newborn Screening Program. Data analysis will utilize a new family-based, statistical sequence analysis to eliminate false-negative DNA variants, individual and combined metabolic marker analysis, and a systematic patient disease-phenotype analysis. In collaboration with the California NBS program, our results will contribute to the description and implementation of novel metabolic and genetic markers for screening of inherited metabolic conditions.

产品说明：先天性代谢缺陷在出生时通过公共新生儿筛查（NBS）计划使用串联质谱（MS/MS）检测，早期和明确的诊断对患者的预后至关重要。然而，一些障碍导致许多疾病的延迟诊断，包括高假阳性率的筛查结果，无法进行诊断，以及无法进行诊断。 以区分疾病亚型和生化异质性导致测试结果的差异。此外，一些疾病不包括在目前的NBS面板。在这里，我们建议研究我们实验室建立的遗传和代谢物技术的组合-基于靶向下一代测序（NGS）和液相色谱串联质谱（LC-MS/MS）-是否可以缩短NBS结果异常后的诊断时间，以及促进其他疾病的检测。我们将着力把握好五个 这些疾病中的三种是上述诊断挑战的疾病（VLCADD -极长链酰基-CoA脱氢酶缺乏症、GA 1-I型谷氨酸血症和MMA -甲基丙二酸血症），两种是目前未筛选的疾病（OTCD -鸟氨酸转氨甲酰酶缺乏症和CPSD -氨甲酰磷酸合成酶I缺乏症）。这些疾病都是由线粒体酶缺陷引起的，线粒体酶缺陷影响各种途径（例如氨基酸和有机酸代谢）的稳态。我们的遗传学方法的责任疾病基因利用互补长锁探针（cLPP）的多重目标捕获和NGS，这将确定突变和拷贝数变异（CNV）在临床级的准确性和完整性，并在非常低的成本。代谢物方法涉及LC-MS/MS多重标记物组，其结合了标准NBS组和其他标记物（例如能量代谢的小分子中间体）。这种策略是基于这样的发现，即在NBS中鉴定的主要酶缺陷的继发性代谢系统水平上可检测到的代谢变化可能在疾病表型的表达中起作用。因此，我们的524个基因的NGS面板不仅包含主要致病基因，而且还包含功能相关的候选基因，我们使用线粒体蛋白质-蛋白质相互作用数据的基因网络分析对其进行了优先排序。我们将使用确诊疾病儿童及其父母的全血样本以及出生时采集的患者存档干血斑（DBS）标本和从加州新生儿筛查项目中获得的标本来评估这两种技术的性能。数据分析将利用新的基于家族的统计序列分析来消除假阴性DNA变异、个体和组合代谢标志物分析以及系统的患者疾病表型分析。在与加州国家统计局计划合作，我们的研究结果将有助于描述和实施新的代谢和遗传标记筛选遗传代谢条件。