JAUNDICE NEXT: A diagnostic tool for cholestatic liver disease.

描述(申请人提供)：胆汁淤积(或病理性黄疸)是儿童肝病最常见的症状，通常是由于在胆汁形成和运输中起关键作用的基因突变所致。在成人中，相同基因的突变也会导致慢性胆汁淤积，可能表现为非特异性门脉纤维化、妊娠期肝内胆汁淤积和低磷脂相关性胆石症。利用这些疾病的遗传基础的最新知识，我们开发了一种高通量基因芯片，它可以识别导致最常见形式的慢性胆汁淤积症遗传综合征的基因突变。该芯片现在是一种临床测试，越来越多的医生将其作为有症状患者诊断算法的一部分。尽管该芯片极大地方便了特定的诊断，但其准确性受到无法可靠检测插入或缺失的限制，这些插入或缺失占致病突变的10%-20%，从而降低了芯片的灵敏度。在本应用程序中，我们建议通过开发下一个版本的突变筛选工具来解决这一技术差距，我们将其命名为“JAundICENEXT”。该工具定制了NextGen测序，以准确地调查目标基因的核苷酸组成，以诊断致病突变。我们的具体目标是“确定JAundICENEXT对目标基因进行排序的准确性。”为了检验假设-1“JAundICENEXT以99%的准确率对目标基因进行测序”，我们将JaundiceNext产生的核苷酸序列与标准测序方法产生的序列进行比较。为了检验假设-2“JAundICENEXT识别胆汁淤积症患者的插入和缺失突变”，我们将检查JAundICENEXT产生的序列输出是否检测到已知携带这些突变的DNA中的插入、缺失或缺失。总的来说，这些实验将验证JAundICENEXT的技术优势，并为未来的实验做好准备，以进一步对该分析进行台架测试，并开发一种自动检测算法，以在未来的第二阶段应用。 公共卫生相关性：黄疸是儿童和成人中常见的几种慢性肝病的临床症状。在之前的STTR中，我们开发了一种基因芯片来识别导致最常见形式的持续性黄疸(也称为胆汁淤积症)遗传综合征的基因突变。该芯片现在是一种临床测试，越来越多的医生将其作为有症状患者诊断算法的一部分。尽管该芯片极大地方便了特定的诊断，但其准确性受到无法可靠地检测插入或缺失的限制，这些插入或缺失占致病突变的10%-20%，从而降低了芯片的灵敏度。我们建议通过开发下一个版本的突变筛查工具来解决这一技术差距，我们将其命名为“JAundICENEXT”。这一新工具定制了强大的测序技术NextGen，以准确地同时检测四个基因中更广泛的突变。这些研究将提高一种非侵入性诊断工具的灵敏度和准确性，从而显著改进肝病患者的诊断算法。

DESCRIPTION (provided by applicant): Cholestasis (or pathologic jaundice) is the most common sign of liver disease in children and often results from mutations in genes that play a critical role in bile formation and transport. In adults, mutations in the same genes also cause chronic cholestasis that may manifest as non-specific portal fibrosis, intrahepatic cholestasis of pregnancy, and low-phospholipid-associated cholelithiasis. Using recent knowledge of the genetic basis of these disorders, we developed a high-throughput gene chip that identifies mutations in the genes that cause the most common forms of inherited syndromes of chronic cholestasis. The chip is now a clinical test that is increasingly used by physicians as part of diagnostic algorithms in symptomatic patients. Although the chip remarkably facilitates specific diagnoses, its accuracy is limited by the inability to reliably detect insertions or deletions, whih account for 10-20% of the disease-causing mutations, thus decreasing the sensitivity of the chip. In this application, we propose to solve this technological gap by developing the next version of a mutation-screening tool that we are naming "JAUNDICENEXT". This tool customizes NextGen sequencing to accurately survey the nucleotide composition of target genes to diagnose disease-causing mutations. Our Specific Aim is "to determine the accuracy of JAUNDICENEXT to sequence the target genes." To test Hypothesis-1 that "JAUNDICENEXT sequences the target genes at >99% accuracy," we will compare the nucleotide sequence produced by the JaundiceNext with the sequence produced by standard sequencing methodology. To test Hypothesis-2 that "JAUNDICENEXT identifies insertion and deletion mutations in patients with cholestasis," we will examine whether the sequence output produced by JAUNDICENEXT detects insertions, deletions, or indels in DNA known to carry these mutations. Collectively, these experiments will validate the technical merits of JAUNDICENEXT and position us for future experiments to further bench-test the assay and develop an automated detection algorithm to in a future Phase-II application. PUBLIC HEALTH RELEVANCE: Jaundice is a clinical sign that is common to several types of chronic liver diseases in children and adults. In a previous STTR, we developed a gene chip to identify mutations in the genes that cause the most common forms of inherited syndromes of persistent jaundice (also known as cholestasis). The chip is now a clinical test that is increasingly used by physicians as part of diagnostic algorithms in symptomatic patients. Although the chip remarkably facilitates specific diagnoses, its accuracy is limited by the inabiliy to reliably detect insertions or deletions, which account for 10-20% of the disease-causing mutations, thus decreasing the sensitivity of the chip. We propose to solve this technological gap by developing the next version of a mutation-screening tool that we are naming "JAUNDICENEXT". This new tool customizes NextGen, a powerful sequencing technology, to accurately detect the wider spectrum of mutations in four genes simultaneously. These studies will improve the sensitivity and accuracy of a non-invasive diagnostic tool that significantly improves the diagnostic algorithm in patients with liver disease.