Non-invasive prediction of preeclampsia using the maternal plasma cell-free DNA profile and clinical risk factors.

Background: Preeclampsia (PE) is a pregnancy complication defined by new onset hypertension and proteinuria or other maternal organ damage after 20 weeks of gestation. Although non-invasive prenatal testing (NIPT) has been widely used to detect fetal chromosomal abnormalities during pregnancy, its performance in combination with maternal risk factors to screen for PE has not been extensively validated. Our aim was to develop and validate classifiers that predict early- or late-onset PE using the maternal plasma cell-free DNA (cfDNA) profile and clinical risk factors. Methods: We retrospectively collected and analyzed NIPT data of 2,727 pregnant women aged 24-45 years from four hospitals in China, which had previously been used to screen for fetal aneuploidy at 12 + 0 ~ 22 + 6 weeks of gestation. According to the diagnostic criteria for PE and the time of diagnosis (34 weeks of gestation), a total of 143 early-, 580 late-onset PE samples and 2,004 healthy controls were included. The wilcoxon rank sum test was used to identify the cfDNA profile for PE prediction. The Fisher's exact test and Mann-Whitney U-test were used to compare categorical and continuous variables of clinical risk factors between PE samples and healthy controls, respectively. Machine learning methods were performed to develop and validate PE classifiers based on the cfDNA profile and clinical risk factors. Results: By using NIPT data to analyze cfDNA coverages in promoter regions, we found the cfDNA profile, which was differential cfDNA coverages in gene promoter regions between PE and healthy controls, could be used to predict early- and late-onset PE. Maternal age, body mass index, parity, past medical histories and method of conception were significantly differential between PE and healthy pregnant women. With a false positive rate of 10%, the classifiers based on the combination of the cfDNA profile and clinical risk factors predicted early- and late-onset PE in four datasets with an average accuracy of 89 and 80% and an average sensitivity of 63 and 48%, respectively. Conclusion: Incorporating cfDNA profiles in classifiers might reduce performance variations in PE models based only on clinical risk factors, potentially expanding the application of NIPT in PE screening in the future.

Identifying occult maternal malignancies from 1.93 million pregnant women undergoing noninvasive prenatal screening tests.

PURPOSE: Multiple chromosomal aneuploidies may be associated with maternal malignancies and can cause failure of noninvasive prenatal screening (NIPS) tests. However, multiple chromosomal aneuploidies show poor specificity and selectivity for diagnosing maternal malignancies. METHODS: This multicenter retrospective analysis evaluated 639 pregnant women who tested positive for multiple chromosomal aneuploidies on initial NIPS test between January 2016 and December 2017. Women were assessed using genome profiling of copy-number variations, which was translated to cancer risk using a novel bioinformatics algorithm called the cancer detection pipeline (CDP). Sensitivity, specificity, and positive predictive value (PPV) of diagnosing maternal malignancies were compared for multiple chromosomal aneuploidies, the CDP model, and the combination of CDP and plasma tumor markers. RESULTS: Of the 639 subjects, 41 maternal malignant cancer cases were diagnosed. Multiple chromosomal aneuploidies predicted maternal malignancies with a PPV of 7.6%. Application of the CDP algorithm to women with multiple chromosomal aneuploidies allowed 34 of the 41 (83%) cancer cases to be identified, while excluding 422 of 501 (84.2%) of the false positive cases. Combining the CDP with plasma tumor marker testing gave PPV of 75.0%. CONCLUSION: The CDP algorithm can diagnose occult maternal malignancies with a reasonable PPV in multiple chromosomal aneuploidies-positive pregnant women in NIPS tests. This performance can be further improved by incorporating findings for plasma tumor markers.

[Prenatal diagnosis of fetal urinary abnormalities and microdeletion on chromosome 1q21.1].

OBJECTIVE: To investigate genetic etiology of fetal urinary abnormalities with array-based comparative genomic hycridization(array-CGH). METHODS: Thirty-two fetuses with variable urinary abnormalities but normal karyotyping by conventional cytogenetic technique were selected. DNA from the fetuses and their parents samples were prepared and hybridization with Affymetrix cytogenetic 2.7M arrays by follwing the manufacture's standard protocol. The data were analyzed by special CHAS software packages. RESULTS: By using array-CGH detection, genomic imbalanced copy number variations (CNVs) were identified in night fetuses(28%), four out of night CNVs were inherited from parental samples; two were indicated to be benign variants(6%) in the database; and the other three CNVs (9%) were all de novo adjacent microdeletions and microduplication mapping on to common chromosome 1q21.1 region, within which was genitourinaty system function associated gene PDZK1. CONCLUSION: The incidence of genomic unbalanced variations in fetuses with congenital urinary malformations is approximately 28%, including about 9% pathogenic variations. Copy number variations (CNVs) of chromosome 1q21.1 region are associated with congenital urinary malformations which may be due to haploinsufficiency or overexpression of PDZK1 gene.

[Short tandem repeat polymerase chain reaction used in prenatal diagnoses of the zygosity and common chromosomal trisomies in multiple pregnancies].

OBJECTIVE: To evaluate the value of short tandem repeat polymerase chain reaction (STR-PCR) in identification of zygosity in multiple pregnancy and detection of the common chromosomal trisomies. METHODS: Amniotic fluid or fetal blood samples were collected from 38 fetuses in 17 multiple pregnant women who had indications for prenatal diagnosis or planed to be performed feticide. Of the 17 cases there were 13 sets of twins (26 fetuses) and 4 sets of triplets (12 fetuses). Parental blood samples were collected. STR-PCR technique was employed to determine the zygosity and detect trisomy 21, trisomy 18, trisomy 13, and trisomy sex chromosomes. Amniotic fluid or blood samples were collected from 18 singleton pregnant fetuses as controls for detecting chromosomal trisomies. RESULTS: All 7 cases with gestation by assisted reproductive techniques were multizygotic. In 7 cases associated with one fetal malformation, only one set of twin was dizygotic. There were no above mentioned trisomies found in the multiple pregnancies while 2 trisomy 21, one trisomy 18 and 13 respectively were detected in the singleton pregnant group. Feticide was performed on 4 multizygotic cases in which 3 were triplets and 1 was twin associated with an abnormal fetus. Following-up showed that there was no any bad effect after procedure. CONCLUSION: STR-PCR can be used in identifying the zygosity correctly and quickly while being used in detecting chromosomal trisomies. It facilitates monitoring multiple pregnancy as well as selecting appropriate methods of feticide.