Objectives: We conducted a systematic review and meta-analysis to determine the diagnostic yield of exome sequencing (ES) for prenatal diagnosis of fetal structural anomalies, where karyotype/chromosomal microarray (CMA) is normal.Methods: Following electronic searches of four databases, we included studies with ≥10 structurally abnormal fetuses undergoing ES or whole genome sequencing. The incremental diagnostic yield of ES over CMA/karyotype was calculated and pooled in a meta-analysis. Sub-group analyses investigated effects of case selection and fetal phenotype on diagnostic yield. Results:We identified 72 reports from 66 studies, representing 4350 fetuses. The pooled incremental yield of ES was 31% (95% confidence interval (CI) 26%-36%, p < 0.0001). Diagnostic yield was significantly higher for cases pre-selected for likelihood of monogenic aetiology compared to unselected cases (42% vs. 15%, p < 0.0001). Diagnostic yield differed significantly between phenotypic sub-groups, ranging from 53% (95% CI 42%-63%, p < 0.0001) for isolated skeletal abnormalities, to 2% (95% CI 0%-5%, p = 0.04) for isolated increased nuchal translucency. Conclusion:Prenatal ES provides a diagnosis in an additional 31% of structurally abnormal fetuses when CMA/karyotype is non-diagnostic. The expected diagnostic yield depends on the body system(s) affected and can be optimised by pre-selection of cases following multi-disciplinary review to determine that a monogenic cause is likely. Key pointsWhat's already known about this topic? � Prenatal exome sequencing (ES) increases genetic diagnoses in fetuses with structural abnormalities and a normal karyotype and chromosomal microarray.� Published diagnostic yields from ES are varied and may be influenced by study size, case selection and fetal phenotype.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Background: Repeat expansion (RE) disorders affect ~1 in 3000 individuals and are clinically heterogeneous diseases caused by expansions of short tandem DNA repeats. Genetic testing is often locus-specific, resulting in under diagnosis of atypical clinical presentations, especially in paediatric patients without a prior positive family history. Whole genome sequencing (WGS) is emerging as a first-line test for rare genetic disorders, but until recently REs were thought to be undetectable by this approach. Methods: WGS pipelines for RE disorder detection were deployed by the 100,000 Genomes Project and Illumina Clinical Services Laboratory. Performance was retrospectively assessed across the 13 most common neurological RE loci using 793 samples with prior orthogonal testing (182 with expanded alleles and 611 with alleles within normal size) and prospectively interrogated in 13,331 patients with suspected genetic neurological disorders. Findings: WGS RE detection showed minimum 97.3% sensitivity and 99.6% specificity across all 13 disease-associated loci. Applying the pipeline to patients from the 100,000 Genomes Project identified pathogenic repeat expansions which were confirmed in 69 patients, including seven paediatric patients with no reported family history of RE disorders, with a 0.09% false positive rate. Interpretation: We show here for the first time that WGS enables the detection of causative repeat expansions with high sensitivity and specificity, and that it can be used to resolve previously undiagnosed neurological disorders. This includes children with no prior suspicion of a RE disorder. These findings are leading to diagnostic implementation of this analytical pipeline in the NHS Genomic Medicine Centres in England.
Purpose: To identify, using genome sequencing (GS), likely pathogenic non-coding variants in inherited retinal dystrophy (IRD) genes Methods: Patients with IRD were recruited to the study and underwent comprehensive ophthalmological evaluation and GS. The results of GS were investigated through virtual gene panel analysis and plausible pathogenic variants and clinical phenotype evaluated by multi-disciplinary team (MDT) discussion. For unsolved patients in whom a specific gene was suspected to harbour a missed pathogenic variant, targeted re-analysis of non-coding regions was performed on GS data. Candidate variants were functionally tested including by mRNA analysis, minigene and luciferase reporter assays. Results: Previously unreported, likely pathogenic, non-coding variants, in 7 genes (PRPF31, NDP, IFT140, CRB1, USH2A, BBS10, and GUCY2D), were identified in 11 patients. These were shown to lead to mis-splicing (PRPF31, IFT140, CRB1, USH2A) or altered transcription levels (BBS10, GUCY2D). Conclusion: MDT-led, phenotype driven, non-coding variant re-analysis of GS is effective in identifying missing causative alleles.
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