Comprehensive and non-invasive prenatal screening of coding variation

全面、无创的编码变异产前筛查

• 批准号: 10678005
• 负责人: Michael H Duyzend
• 金额: $ 7.95万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10678005
• 关键词: Acceleration; Advisory Committees; Algorithms; Amniocentesis; Aneuploidy; Automobile Driving; Awareness; Blood; Blood specimen; Calibration; Chorionic Villi Sampling; Clinical; Clinical Management; Code; Counseling; DNA; Data; Detection; Development; Diagnosis; Discipline; Family; Fellowship; Genes; Genetic; Genetic Code; Genetic Diseases; Genetic Variation; Genomics; Genotype; Goals; Human; Incidental Findings; Infrastructure; Institution; International; Karyotype; Maternal-fetal medicine; Medicine; Mendelian disorder; Mentors; Methods; Modeling; Molecular Diagnosis; Morbidity - disease rate; Mothers; Ontology; Pathogenicity; Patients; Performance; Phenotype; Physicians; Plasma; Pregnancy; Pregnancy Outcome; Prenatal Diagnosis; Prenatal care; Preventive measure; Preventive treatment; Research; Research Support; Resolution; Sampling; Scientist; Sensitivity and Specificity; Signs and Symptoms; Site; Standardization; Statistical Models; Structure; Surveys; Techniques; Technology; Testing; Time; Training; Umbilical Cord Blood; Variant; Work; analytical method; biobank; career; carrier testing; cell free DNA; cell free fetal DNA; clinical application; clinical diagnosis; clinically relevant; cloud based; database structure; diagnostic screening; early pregnancy; exome; exome sequencing; fetal; gene discovery; genetic testing; hands on research; improved; innovation; insertion/deletion mutation; insight; laboratory experience; member; neonatal outcome; novel; phenotypic data; population based; prenatal; prenatal testing; screening; skills; standard of care; targeted sequencing; tool; training opportunity

Abstract Non-invasive prenatal screening (NIPS) involves assessment of circulating cell-free fetal DNA (cffDNA) extracted from maternal plasma and the widespread clinical application of this technique to detect chromosomal aneuploidies in pregnancy is now routine and the standard of care. While NIPS technology has advanced to detect some targeted genomic abnormalities, current approaches are low-resolution and able to capture only a small fraction of genetic conditions important to prenatal diagnosis. Our preliminary studies on 6 samples suggest the feasibility of a high resolution non-invasive prenatal screen (hrNIPS), that can capture the vast majority of pathogenic coding variation (SNV, indel, CNV). However, our results suggest that the ability to call all types of variation can be improved through calibration of statistical models and development of new techniques. Integration of phenotype data will allow interpretation and prioritization of identified pathogenic variants. Therefore, we will deploy hrNIPS on 100 samples with paired fetal exome sequencing data to develop and calibrate methods over this large number of samples (Aim 1). We will call variation on these samples using the improved methods and implement an infrastructure to capture systematic phenotypes in these samples using the phenopackets schema (Aim 2). Further, we will use phenopackets and associated HPO terms to leverage phenotype-aware algorithms to prioritize identified variants for further review. We will interpret all variation in a clinical context using ACMG criteria and explore which types of variants might impact prenatal care (Aim 3). Finally, we will investigate the potential added value of hrNIPS as a maternal carrier screen. In parallel with these research aims, an exceptional team of seven mentors and advisors across disciplines, career stages, and institutions will provide didactic training, hands-on research support, and regular opportunities for presentation. Collectively, the ability to comprehensively assess coding variation in pregnancy with hrNIPS would allow early and non-invasive pregnancy assessment for molecular diagnosis and has the potential to transform the standard of care.

摘要 非侵入性产前筛查（NIPS）涉及评估循环无细胞胎儿DNA（cffDNA） 从母体血浆中提取的染色体，以及该技术在检测染色体 非整倍体的怀孕现在是常规和标准的护理。虽然NIPS技术已经发展到 检测一些有针对性的基因组异常，目前的方法是低分辨率，只能捕捉到一个 一小部分对产前诊断很重要的遗传条件。我们对6个样品的初步研究 提出了一种高分辨率非侵入性产前筛查（hrNIPS）的可行性，这种筛查可以捕获大量的 大多数致病性编码变异（SNV、indel、CNV）。然而，我们的研究结果表明， 所有类型的变化都可以通过校准统计模型和开发新的 技术.表型数据的整合将允许对已鉴定的致病性 变体。 因此，我们将在100个具有配对胎儿外显子组测序数据的样本上部署hrNIPS，以开发和分析基因组。 在大量样本上校准方法（目标1）。我们将使用 改进的方法和实施基础设施，以捕获这些样品中的系统表型， phenopackets schema（Aim 2）.此外，我们将使用phenopackets和相关的HPO条款来利用 表型感知算法，以优先考虑所识别的变体，用于进一步审查。我们将解释所有的变化在一个 使用ACMG标准的临床背景，并探索哪些类型的变异可能影响产前护理（目的3）。 最后，我们将研究hrNIPS作为母体载体筛选的潜在附加值。与此同时， 研究目标，一个特殊的团队，七个导师和顾问跨学科，职业阶段， 各机构将提供教学培训、实践研究支持和定期发表演讲的机会。 总的来说，用hrNIPS全面评估妊娠期编码变异的能力将允许早期诊断。 和非侵入性妊娠评估的分子诊断，并有可能改变标准 照顾。