: Prenatal Exome (pES) or Genome (pGS) Sequencing analysis showed a significant incremental diagnostic yield over karyotype and chromosomal microarray analysis (CMA) in fetal structural anomalies. Optimized indications and detection rates in different fetal anomalies are still under investigation. The aim of this study was to assess the incremental diagnostic yield in prenatally diagnosed Central Nervous System (CNS) anomalies. A systematic review on antenatal CNS anomalies was performed according to PRISMA guidelines, including n = 12 paper, accounting for 428 fetuses. Results were pooled in a meta-analysis fitting a logistic random mixed-effect model. The effect of interest was the incremental diagnostic rate of pES over karyotype/CMA in detecting likely pathogenic/pathogenic Single Nucleotide Variants (SNVs). A further meta-analysis adding the available pGS studies (including diagnostic coding SNVs only) and submeta-analysis on three CNS subcategories were also performed. The pooled incremental diagnostic yield estimate of pES studies was 38% (95% C.I.: [29%;47%]) and 36% (95% C.I.: [28%;45%]) when including diagnostic SNVs of pGS studies. The point estimate of the effect resulted 22% (95% C.I.: [15%;31%]) in apparently isolated anomalies, 33% (95% C.I.: [22%;46%]) in CNS-only related anomalies (≥1) and 46% (95% C.I.: [38%;55%]) in non-isolated anomalies (either ≥ 2 anomalies in CNS, or CNS and extra-CNS). Meta-analysis showed a substantial diagnostic improvement in performing Prenatal Genome-Wide Sequencing analysis (Exome or Genome) over karyotype and CMA in CNS anomalies.

Prenatal Genome-Wide Sequencing analysis (Exome or Genome) in detecting pathogenic Single Nucleotide Variants in fetal Central Nervous System Anomalies: systematic review and meta-analysis / Marchionni, Enrica; Guadagnolo, Daniele; Mastromoro, Gioia; Pizzuti, Antonio. - In: EUROPEAN JOURNAL OF HUMAN GENETICS. - ISSN 1018-4813. - (2024). [10.1038/s41431-024-01590-2]

Prenatal Genome-Wide Sequencing analysis (Exome or Genome) in detecting pathogenic Single Nucleotide Variants in fetal Central Nervous System Anomalies: systematic review and meta-analysis

Marchionni, Enrica;Guadagnolo, Daniele;Mastromoro, Gioia;Pizzuti, Antonio
2024

Abstract

: Prenatal Exome (pES) or Genome (pGS) Sequencing analysis showed a significant incremental diagnostic yield over karyotype and chromosomal microarray analysis (CMA) in fetal structural anomalies. Optimized indications and detection rates in different fetal anomalies are still under investigation. The aim of this study was to assess the incremental diagnostic yield in prenatally diagnosed Central Nervous System (CNS) anomalies. A systematic review on antenatal CNS anomalies was performed according to PRISMA guidelines, including n = 12 paper, accounting for 428 fetuses. Results were pooled in a meta-analysis fitting a logistic random mixed-effect model. The effect of interest was the incremental diagnostic rate of pES over karyotype/CMA in detecting likely pathogenic/pathogenic Single Nucleotide Variants (SNVs). A further meta-analysis adding the available pGS studies (including diagnostic coding SNVs only) and submeta-analysis on three CNS subcategories were also performed. The pooled incremental diagnostic yield estimate of pES studies was 38% (95% C.I.: [29%;47%]) and 36% (95% C.I.: [28%;45%]) when including diagnostic SNVs of pGS studies. The point estimate of the effect resulted 22% (95% C.I.: [15%;31%]) in apparently isolated anomalies, 33% (95% C.I.: [22%;46%]) in CNS-only related anomalies (≥1) and 46% (95% C.I.: [38%;55%]) in non-isolated anomalies (either ≥ 2 anomalies in CNS, or CNS and extra-CNS). Meta-analysis showed a substantial diagnostic improvement in performing Prenatal Genome-Wide Sequencing analysis (Exome or Genome) over karyotype and CMA in CNS anomalies.
2024
genome pGS
01 Pubblicazione su rivista::01a Articolo in rivista
Prenatal Genome-Wide Sequencing analysis (Exome or Genome) in detecting pathogenic Single Nucleotide Variants in fetal Central Nervous System Anomalies: systematic review and meta-analysis / Marchionni, Enrica; Guadagnolo, Daniele; Mastromoro, Gioia; Pizzuti, Antonio. - In: EUROPEAN JOURNAL OF HUMAN GENETICS. - ISSN 1018-4813. - (2024). [10.1038/s41431-024-01590-2]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1706342
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