Expanding the utility of prenatal genetic testing

项目摘要 先天性畸形影响3-4%的怀孕，并造成20-30%的新生儿死亡。产前 诊断可以显著改善新生儿的健康和发育， 遗传疾病，特别是随着治疗选择，如基因治疗，继续增加。无创 产前检测（NIPT）现在广泛用于染色体异常，最近，用于识别 胎儿中的父系遗传/新生常染色体显性疾病。此外，越来越多的女性 在结构分析后，正在对胎盘穿刺或绒毛膜绒毛样本进行全外显子组测序（WES）。 胎儿的异常是通过超声波识别的艾德。然而，目前的WES范式缺乏检测能力， 不存在隐性单基因疾病的外显子水平CNV和NIPT选择。 隐性疾病占单基因疾病的一半以上，绝大多数已知的单基因疾病是隐性疾病。 这些病症是由单核苷酸多态性（SNP）引起的。虽然大规模测序工作 更好地定义SNP的流行，外显子水平拷贝数变异（CNV）的全基因组流行 仍然是未知的。对有限数量基因的研究表明，小的CNVs大致代表了 1%的变异，但超过9%的致病性变异。 我们正在收集两组临床样本：（1）当结构异常时， 在超声波上发现;（2）怀孕期间的母血和分娩时的脐带血。使用这些临床 样本，该提案的具体目的是：（1）证明多重外显子组捕获实用性和新颖性 外显子水平的CNV检测分析和（2）开发用于胎儿基因分型的分析框架和新型探针 来自母体的无细胞DNA目的1将采用CNV算法（mcCNV）在三个识别外显子水平的从头 变异，提高诊断率，并理想地识别新的候选基因，以了解人类 发展目的2通过引入隐性单基因，大大扩展了NIPT的可能用途 紊乱 通过这项研究计划和相关的培训计划，我将获得一个独特的和跨学科的技能， 以创新的方式将数据科学和生物统计学与人口遗传学相结合， 母胎医学这次培训将为我提供技术，统计和专业技能， 我需要成为一个学术中心的领导者，并追求我实践母胎医学的目标 作为一个物理学家和科学家进行研究。

PROJECT SUMMARY Congenital abnormalities affect 3-4% of pregnancies and cause 20-30% of neonatal deaths worldwide. Prenatal diagnosis can lead to significant improvements in newborn health and development for a growing number of genetic conditions, especially as treatment options, such as gene therapy, continue to increase. Non-invasive prenatal testing (NIPT) is now widely available for chromosomal abnormalities, and more recently, for identifying paternally-inherited/de novo autosomal dominant conditions in the fetus. Additionally, more and more women are being offered whole-exome sequencing (WES) on amniocentesis or chorionic villus samples after structural abnormalities in the fetus are identified on ultrasound. However, current WES paradigms lack the power to detect exon-level CNV and NIPT options for recessive single-gene disorders do not exist. Recessive conditions constitute over half of single-gene disorders, and the vast majority of known single-gene conditions are caused by single-nucleotide polymorphisms (SNPs). While large-scale sequencing efforts are better defining the prevalence of SNPs, the genome-wide prevalence of exon-level copy number variation (CNV) remains largely unknown. Research on a limited number of genes would suggest small CNVs represent roughly 1% of variants, but over 9% of pathogenic variants. We are collecting two cohorts of clinical samples: (1) mother-father-fetus trios when structural abnormalities are found on ultrasound; (2) maternal blood during pregnancy and cord blood at time of delivery. Using these clinical samples, the Specific Aims of this proposal are: (1) Demonstrate multiplexed exome capture utility and novel analysis for exon-level CNV detection and (2) Develop analysis framework and novel probes for fetal genotyping from maternal cell-free DNA. Aim 1 will employ the CNV algorithm (mcCNV) in trios to identify exon-level de novo variation, increasing the diagnostic yield and ideally identifying new candidate genes for understanding human development. Aim 2 greatly expands the possible utility of NIPT with the novel inclusion of recessive single-gene disorders. Through this research proposal and associated training plan, I will gain a unique and interdisciplinary skill-set that combines data science and biostatistics with population genetics in an innovative manner that is at the forefront of maternal-fetal medicine. This training will provide me with the technical, statistical, and professional skills I need to become a leader at an academic center and to pursue my goals of practicing maternal-fetal medicine and research as a physician-scientist.