New Computational Methods and Emerging Technologies in Prenatal Genetic Diagnosis

Massachusetts General Hospital, Boston MA

Investigators

Linked publications, trials & patents

Abstract

? DESCRIPTION (provided by applicant): Congenital anomalies are structural or functional abnormalities of varying degree of severity and affect approximately 2-3% of all births in the U.S. The currently recommended first-tier prenatal genetic screen (PGS) from the American College of Obstetricians and Gynecologists involves genome-wide screening of structural variations (SV), which represent the leading genetic cause of congenital anomalies, ranging from numerical abnormalities in the chromosomes to submicroscopic copy number variants (CNVs). There are two validated cytogenetic procedures for genome-wide detection of SV; karyotyping and chromosomal microarray (CMA). Karyotyping detects gross changes in the chromosomes, including balanced chromosomal rearrangements (BCRs), while CMA can identify large genomic imbalances. Neither method is capable of detecting both BCRs and CMA-resolution CNVs. Moreover, detection of submicroscopic BCRs and sub-array resolution CNVs is intractable to both methods, yet my preliminary studies suggest these `cryptic' SVs are an important and currently uncharacterized genetic cause of congenital anomalies. This fellowship will focus on the application of an innovative whole genome sequencing (WGS) approach to detect all mutational classes of SV in prenatal diagnostic testing, at a timeline and cost comparable to conventional cytogenetic methods. The project will leverage 4,400 already collected samples from the Prenatal Diagnostic Consortium in which both karyotyping and CMA have been performed at a centralized laboratory. The study hypothesizes that SV sequencing will have superior resolution to conventional methods, and that delineation of cryptic SVs will increase diagnostic yields by at least 50% compared to any currently available method. Aim 1 will test the sensitivity of WGS compared to karyotyping and CMA by analyzing over 200 prenatal samples with a cytogenetically detected and clinically significant SV. Aim 2 will establish the incidence, frequency, and diagnostic yield of cryptic SVs on 400 trios in which the proband harbors a structural defect / dysmorphism detected on ultrasound but no known pathogenic SV. Putative pathogenic SVs will be annotated and interpreted by large-scale quantitative analysis using convergent genomic data from CNV burden in >135,000 individuals and loss of function mutations in exome sequencing of >75,000 samples. Aim 3 will test the feasibility of SV detection from deeply sequenced prenatal libraries, and will perform an exploratory analysis comparing SV detection from amniocentesis vs cell free fetal DNA (cffDNA), which if successful could have a significant impact on PGS for cffDNA. Overall, this project represents a unique training opportunity to develop skills in each of my targeted areas of career development by gaining access and expertise in a diverse set of genomics technology, bioinformatics, statistical genetics, clinical genetics, and exposure to molecular diagnostic techniques. Moreover, while the training potential of the project is high, the studies proposed have the potential to transform PGS.