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. 2022 Oct 28;14(1):123.
doi: 10.1186/s13073-022-01130-x.

Application of exome sequencing for prenatal diagnosis of fetal structural anomalies: clinical experience and lessons learned from a cohort of 1618 fetuses

Affiliations

Application of exome sequencing for prenatal diagnosis of fetal structural anomalies: clinical experience and lessons learned from a cohort of 1618 fetuses

Fang Fu et al. Genome Med. .

Abstract

Background: Exome sequencing (ES) is becoming more widely available in prenatal diagnosis. However, data on its clinical utility and integration into clinical management remain limited in practice. Herein, we report our experience implementing prenatal ES (pES) in a large cohort of fetuses with anomalies detected by ultrasonography using a hospital-based in-house multidisciplinary team (MDT) facilitated by a three-step genotype-driven followed by phenotype-driven analysis framework.

Methods: We performed pES in 1618 fetal cases with positive ultrasound findings but negative for karyotyping and chromosome microarray analysis between January 2014 and October 2021, including both retrospective (n=565) and prospective (n=1053) cohorts. The diagnostic efficiency and its correlation to organ systems involved, phenotypic spectrum, and the clinical impacts of pES results on pregnancy outcomes were analyzed.

Results: A genotype-driven followed by phenotype-driven three-step approach was carried out in all trio pES. Step 1, a genotype-driven analysis resulted in a diagnostic rate of 11.6% (187/1618). Step 2, a phenotype-driven comprehensive analysis yielded additional diagnostic findings for another 28 cases (1.7%; 28/1618). In the final step 3, data reanalyses based on new phenotypes and/or clinical requests found molecular diagnosis in 14 additional cases (0.9%; 14/1618). Altogether, 229 fetal cases (14.2%) received a molecular diagnosis, with a higher positive rate in the retrospective than the prospective cohort (17.3% vs. 12.4%, p<0.01). The diagnostic rates were highest in fetuses with skeletal anomalies (30.4%) and multiple organ involvements (25.9%), and lowest in fetuses with chest anomalies (0%). In addition, incidental and secondary findings with childhood-onset disorders were detected in 11 (0.7%) cases. Furthermore, we described the prenatal phenotypes for the first time for 27 gene-associated conditions (20.0%, 27/135) upon a systematic analysis of the diagnosed cases and expanded the phenotype spectrum for 26 (19.3%) genes where limited fetal phenotypic information was available. In the prospective cohort, the combined prenatal ultrasound and pES results had significantly impacted the clinical decisions (61.5%, 648/1053).

Conclusions: The genotype-driven approach could identify about 81.7% positive cases (11.6% of the total cohort) with the initial limited fetal phenotype information considered. The following two steps of phenotype-driven analysis and data reanalyses helped us find the causative variants in an additional 2.6% of the entire cohort (18.3% of all positive findings). Our extensive phenotype analysis on a large number of molecularly confirmed prenatal cases had greatly enriched our current knowledge on fetal phenotype-genotype correlation, which may guide more focused prenatal ultrasound in the future. This is by far the largest pES cohort study that combines a robust trio sequence data analysis, systematic phenotype-genotype correlation, and well-established MDT in a single prenatal clinical setting. This work underlines the value of pES as an essential component in prenatal diagnosis in guiding medical management and parental decision making.

Keywords: Exome sequencing; Genotype-driven; Multidisciplinary model; Prenatal diagnosis; Structural anomaly; Ultrasound; pES.

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Conflict of interest statement

Lina Xiang, Jing Zhang, Sha Tang, and Ping Fang are employees of KingMed Diagnostics; they declare that they have no competing interests. The remaining authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
The pipeline of prenatal ES data analysis in our cohort study
Fig. 2
Fig. 2
Diagnostic rates based on malformation classification. The highest diagnostic rates were obtained in fetuses with multiple organ and skeletal anomalies and the lowest in fetuses with chest anomalies
Fig. 3
Fig. 3
Frequent positive and potential diagnostic genes. The number of cases by disease genes in different malformation categories is shown

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