Variant detection and variant analysis process for diagnosis of CH and MODY

描述(由申请人提供)：项目摘要/摘要：Correlagen在内分泌学和免疫学领域开发和商业化针对单基因疾病的基于DNA的诊断测试，例如先天性高胰岛素血症(CH)和青年成熟期糖尿病(MODY)。目前，序列变异的检测是基于对基因编码区和内含子/外显子连接的PCR扩增和全序列测定。第一个具体目标是扩展这种变异检测方法，以便除了检测序列变异外，还可以检测基因组缺失。最近的研究表明，基因组缺失在很大程度上导致疾病表型(Eichler，2006；McCarroll，2006；Walsh，2006)。如果这种缺失跨越整个PCR扩增片段(扩增片段)，则通过基因组DNA的直接Sanger DNA序列分析是检测不到的，因为序列仍然是从常染色体基因的另一个染色体拷贝获得的。因此，仅通过DNA测序进行变异检测可能会导致假阴性结果。这一限制对于诊断通常与基因大缺失相关的疾病特别重要，例如MODY5(Bellanne-Chantelot，2005)。因此，将开发一种用于缺失检测的标准化定量PCR协议，该协议可以很容易地与Correlagen现有的全测序平台集成。第二个具体目标是改进Correlagen目前的不同评分方法，以创建一个新的、多因素评分方案。这一先进的评分方案将用于分析在诊断测试期间在CH和MODY基因中发现的变异。这些变异中有一些是新发现的，目前被归类为意义未知的变异，限制了它们的诊断价值。将分析各种现有的基于算法的解释变量重要性的方法，以了解它们准确预测变量的已知函数的能力，以及导致错误预测的模式。将对来自普通人群的DNA样本进行患病率研究，以确定CH和MODY基因的常见多态，并开发用于评估基因型/表型相关性强度的计算器。在这些研究的基础上，将开发新的算法和遗传参数来评估变异。同时，将开发一个信息技术平台，随着评分协议的演变跟踪分数的变化。根据特定目标1和2中提出的研究而产生的改进的变异检测和变异评分方案将被纳入Correlagen目前的服务流程，以增强其用于诊断遗传疾病的检测服务的临床实用性。项目叙述/相关性：我们的努力将导致一种系统和可靠的变异检测和分析方法，该方法可以应用于Correlagen和我们技术的其他参考实验室许可证获得者测试的其他基因中发现的变异。更广泛地说，这些方法也有可能成为学术界和工业界进行基因测试的标准方法。

DESCRIPTION (provided by applicant): Project Summary/Abstract: Correlagen develops and commercializes DNA-based diagnostic testing for monogenic diseases, such as congenital hyperinsulinism (CH) and maturity-onset diabetes of the young (MODY), in the areas of endocrinology and immunology. Currently, sequence variant detection is based on PCR amplification and full sequencing of gene coding regions and intron/exon junctions. The first specific aim is to expand on this variant detection methodology to allow detection of genomic deletions in addition to sequence variation. Recent studies have shown that genomic deletions cause disease phenotypes at a significant frequency {Eichler, 2006; McCarroll, 2006; Walsh, 2006). Such deletions are not detectable by direct Sanger DNA sequence analysis of genomic DNA if they span an entire PCR-amplification fragment (amplicon) since sequence is still obtained from the other chromosome copy for autosomal genes. Thus, variant detection by DNA sequencing alone can potentially lead to a false negative result. This limitation is of particular concern for the diagnosis of diseases commonly associated with large deletions in a gene, such as MODY5 (Bellanne-Chantelot, 2005). Therefore, a standardized quantitative PCR protocol for deletion detection will be developed that can be easily integrated with Correlagen's existing full-sequencing platform. The second specific aim focuses on refining Correlagen's current variant scoring method to create a new, multi-factorial scoring protocol. This advanced scoring protocol will be used to analyze variants discovered in CH and MODY genes during diagnostic testing. A number of these variants are newly discovered and are currently classified as variants of unknown significance, limiting their diagnostic value. Various existing algorithmic-based methods for interpreting variant significance will be analyzed for their capacity to predict the known function of variants accurately and for patterns leading to false predictions. A prevalence study on DNA samples derived from the general population will be performed to identify common polymorphisms in CH and MODY genes, and calculator for assessing the strength of genotype/phenotype correlations will developed. Based on these studies, new algorithms and genetic parameters for evaluating variants will be developed. Concurrently, an information technology platform will be developed to track changes in scores as the scoring protocol evolves. The improved variant detection and variant scoring protocols resulting from the studies proposed in specific aims 1 and 2 will be incorporated into Correlagen's current service processes to enhance the clinical utility of its testing services for the diagnosis of genetic diseases. Project Narrative/Relevance: Our efforts will lead to a systematic and reliable method of variant detection and analysis that can be applied to variants found in other genes tested by Correlagen and by other reference laboratory licensees of our technology. More broadly, these methods also have the potential to become standard methodology for genetic testing performed in both academia and industry.