Prenatal diagnosis of fetal genetic disease has evolved to reach a prominent position in obstetric clinical care. Established screening methods targeted towards serum proteins are used routinely alongside ultrasonography to identify potentially abnormal pregnancies. Definitive diagnosis is then undertaken using interventional procedures such as amniocentesis and chorionic villus sampling (CVS) that obtain fetal or placental cells, respectively, for karyotype analysis. However, these invasive procedures involve a risk of associated miscarriage. This is significant because, for trisomy 21, current non-invasive first trimester screening methods have detection rates of 82 to 87% and false positive rates of approximately 5%. Therefore, up to 18% of true positives are missed and one expectant mother in every twenty who are screened will undergo an unnecessary invasive diagnostic procedure that could result in the avoidable miscarriage of her baby. In addition to the risk of mortality and morbidity, invasive procedures invoke considerable parental anxiety. Our goal is to dramatically reduce these avoidable miscarriages and other associated risks by developing a diagnostic method that significantly improves the sensitivity and specificity of non-invasive prenatal detection of aneuploidy in the first trimester. To achieve this goal we will expand on our recently published work to test the hypothesis that shotgun next generation sequencing of first trimester maternal plasma DNA provides improved sensitivity and specificity over existing combinations of serum screening and ultrasound. Significantly, earlier economic and logistical barriers preventing the translation of this approach to clinical practice have very recently been overcome by the emergence of methods for high-throughput DNA sequencing that are cost-effective for clinical diagnosis. Specifically, in Aim 1, we will carry out shotgun next generation sequencing on samples of maternal plasma DNA obtained in the first trimester of pregnancy from large cohorts of confirmed aneuploidy and control pregnancies (combined n = 70). We will then undertake a formal statistical analysis to determine the sensitivity and specificity of next-generation DNA sequencing for the detection of aneuploidy on chromosomes 13, 18, 21 and X and compare these results to sensitivity and specificity data obtained using existing first trimester screening methods in the same cohort (Aim 2). Finally we will develop a software package with graphical user interface that can be utilized by non-specialist end users for the rapid analysis of next generation sequencing data and the detection of aneuploidy (Aim 3). We anticipate that this new first trimester test will increase the detection rate of fetal aneuploidy to 95% and reduce the false positive rate to 1%, resulting in an 80% reduction in unnecessary miscarriages associated with invasive prenatal diagnosis after first trimester screening.

Public Health Relevance

The primary goal of this study is to test the hypothesis that next-generation sequencing of maternal plasma DNA provides significantly improved sensitivity and specificity over existing combinations of serum screening and ultrasound. Specifically, in Aim 1, we will carry out shotgun next generation sequencing on samples of maternal plasma DNA obtained in the first trimester of pregnancy from large cohorts of confirmed aneuploidy and control pregnancies (combined n = 700). We will then undertake a formal statistical analysis to determine the sensitivity and specificity of next-generation DNA sequencing for the detection of aneuploidy on chromosomes 13, 18, 21 and X and compare these results to sensitivity and specificity data obtained using existing first trimester screening methods in the same cohort (Aim 2). Finally we will develop a software package with graphical user interface that can be utilized by non-specialist end users for the rapid analysis of next generation sequencing data and the detection of aneuploidy (Aim 3). We anticipate that this new first trimester test will increase the detection rate of fetal aneuploidy from 82% to 95% and reduce the false positive rate from 5% to 1%, resulting in an 80% reduction in the rate of avoidable fetal miscarriage associated with invasive prenatal diagnosis.

Agency
National Institute of Health (NIH)
Institute
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Type
Research Project (R01)
Project #
1R01HD068578-01
Application #
8084747
Study Section
Genetics of Health and Disease Study Section (GHD)
Program Officer
Urv, Tiina K
Project Start
2011-05-15
Project End
2016-01-31
Budget Start
2011-05-15
Budget End
2012-01-31
Support Year
1
Fiscal Year
2011
Total Cost
$481,483
Indirect Cost
Name
Magee-Women's Research Institute and Foundation
Department
Type
DUNS #
119132785
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213
Chu, Tianjiao; Shaw, Patricia A; Yeniterzi, Suveyda et al. (2017) Comparative evaluation of the Minimally-Invasive Karyotyping (MINK) algorithm for non-invasive prenatal testing. PLoS One 12:e0171882
Chu, Tianjiao; Yeniterzi, Suveyda; Yatsenko, Svetlana A et al. (2016) High Levels of Sample-to-Sample Variation Confound Data Analysis for Non-Invasive Prenatal Screening of Fetal Microdeletions. PLoS One 11:e0153182
Yatsenko, Svetlana A; Peters, David G; Saller, Devereux N et al. (2015) Maternal cell-free DNA-based screening for fetal microdeletion and the importance of careful diagnostic follow-up. Genet Med 17:836-8
Peters, David G; Yatsenko, Svetlana A; Surti, Urvashi et al. (2015) Recent advances of genomic testing in perinatal medicine. Semin Perinatol 39:44-54
Chu, Tianjiao; Yeniterzi, Suveyda; Yatsenko, Svetlana A et al. (2015) Cell-free nucleic acids as non-invasive biomarkers of gynecological disorders, fetal aneuploidy and constitutional maternal chromosomal mosaicism. Hum Reprod Update 21:690-2
Chu, Tianjiao; Bunce, Kimberly; Shaw, Patricia et al. (2014) Comprehensive analysis of preeclampsia-associated DNA methylation in the placenta. PLoS One 9:e107318
Chu, Tianjiao; Yeniterzi, Suveyda; Rajkovic, Aleksandar et al. (2014) High resolution non-invasive detection of a fetal microdeletion using the GCREM algorithm. Prenat Diagn 34:469-77
Bunce, Kimberly; Chu, Tianjiao; Surti, Urvashi et al. (2012) Discovery of epigenetic biomarkers for the noninvasive diagnosis of fetal disease. Prenat Diagn 32:542-9
Himes, Katherine P; Handley, Daniel; Chu, Tianjiao et al. (2012) Comprehensive analysis of the transcriptional response of human decidual cells to lipopolysaccharide stimulation. J Reprod Immunol 93:17-27
Peters, David; Chu, Tianjiao; Yatsenko, Svetlana A et al. (2011) Noninvasive prenatal diagnosis of a fetal microdeletion syndrome. N Engl J Med 365:1847-8