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      Meta-analysis of the diagnostic and clinical utility of genome and exome sequencing and chromosomal microarray in children with suspected genetic diseases

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          Abstract

          Genetic diseases are leading causes of childhood mortality. Whole-genome sequencing (WGS) and whole-exome sequencing (WES) are relatively new methods for diagnosing genetic diseases, whereas chromosomal microarray (CMA) is well established. Here we compared the diagnostic utility (rate of causative, pathogenic, or likely pathogenic genotypes in known disease genes) and clinical utility (proportion in whom medical or surgical management was changed by diagnosis) of WGS, WES, and CMA in children with suspected genetic diseases by systematic review of the literature (January 2011–August 2017) and meta-analysis, following MOOSE/PRISMA guidelines. In 37 studies, comprising 20,068 children, diagnostic utility of WGS (0.41, 95% CI 0.34–0.48, I 2 = 44%) and WES (0.36, 95% CI 0.33–0.40, I 2 = 83%) were qualitatively greater than CMA (0.10, 95% CI 0.08–0.12, I 2 = 81%). Among studies published in 2017, the diagnostic utility of WGS was significantly greater than CMA ( P < 0.0001, I 2 = 13% and I 2 = 40%, respectively). Among studies featuring within-cohort comparisons, the diagnostic utility of WES was significantly greater than CMA ( P < 0.001, I 2 = 36%). The diagnostic utility of WGS and WES were not significantly different. In studies featuring within-cohort comparisons of WGS/WES, the likelihood of diagnosis was significantly greater for trios than singletons (odds ratio 2.04, 95% CI 1.62–2.56, I 2 = 12%; P < 0.0001). Diagnostic utility of WGS/WES with hospital-based interpretation (0.42, 95% CI 0.38–0.45, I 2 = 48%) was qualitatively higher than that of reference laboratories (0.29, 95% CI 0.27–0.31, I 2 = 49%); this difference was significant among studies published in 2017 ( P < .0001, I 2 = 22% and I 2 = 26%, respectively). The clinical utility of WGS (0.27, 95% CI 0.17–0.40, I 2 = 54%) and WES (0.17, 95% CI 0.12–0.24, I 2 = 76%) were higher than CMA (0.06, 95% CI 0.05–0.07, I 2 = 42%); this difference was significant for WGS vs CMA ( P < 0.0001). In conclusion, in children with suspected genetic diseases, the diagnostic and clinical utility of WGS/WES were greater than CMA. Subgroups with higher WGS/WES diagnostic utility were trios and those receiving hospital-based interpretation. WGS/WES should be considered a first-line genomic test for children with suspected genetic diseases.

          Genetic sequencing: Improving disease diagnosis in children

          Children with suspected genetic disease are more likely to receive a diagnosis when gene sequencing technologies are employed. At present, a microarray test for short pieces of missing or extra chromosomes (chromosomal microarray, CMA) is the recommended test for diagnosing genetic disease in children. The recent use of whole-genome sequencing (WGS) and whole-exome sequencing (WES) for diagnosing genetic disease prompted Stephen Kingsmore at Rady Children’s Institute for Genomic Medicine in San Diego, California, USA, and colleagues to examine the effectiveness of these methods compared with CMA. Analyses of studies comprising over 20,000 children showed that using WGS and WES increased the likelihood of diagnosis and led to a change in inpatient management to prevent or ameliorate adverse health outcomes. The authors advocate the use of WGS or WES as a first-line genomic test for genetic disease in children.

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          THE USE OF CONFIDENCE OR FIDUCIAL LIMITS ILLUSTRATED IN THE CASE OF THE BINOMIAL

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            Resolution of Disease Phenotypes Resulting from Multilocus Genomic Variation.

            Background Whole-exome sequencing can provide insight into the relationship between observed clinical phenotypes and underlying genotypes. Methods We conducted a retrospective analysis of data from a series of 7374 consecutive unrelated patients who had been referred to a clinical diagnostic laboratory for whole-exome sequencing; our goal was to determine the frequency and clinical characteristics of patients for whom more than one molecular diagnosis was reported. The phenotypic similarity between molecularly diagnosed pairs of diseases was calculated with the use of terms from the Human Phenotype Ontology. Results A molecular diagnosis was rendered for 2076 of 7374 patients (28.2%); among these patients, 101 (4.9%) had diagnoses that involved two or more disease loci. We also analyzed parental samples, when available, and found that de novo variants accounted for 67.8% (61 of 90) of pathogenic variants in autosomal dominant disease genes and 51.7% (15 of 29) of pathogenic variants in X-linked disease genes; both variants were de novo in 44.7% (17 of 38) of patients with two monoallelic variants. Causal copy-number variants were found in 12 patients (11.9%) with multiple diagnoses. Phenotypic similarity scores were significantly lower among patients in whom the phenotype resulted from two distinct mendelian disorders that affected different organ systems (50 patients) than among patients with disorders that had overlapping phenotypic features (30 patients) (median score, 0.21 vs. 0.36; P=1.77×10(-7)). Conclusions In our study, we found multiple molecular diagnoses in 4.9% of cases in which whole-exome sequencing was informative. Our results show that structured clinical ontologies can be used to determine the degree of overlap between two mendelian diseases in the same patient; the diseases can be distinct or overlapping. Distinct disease phenotypes affect different organ systems, whereas overlapping disease phenotypes are more likely to be caused by two genes encoding proteins that interact within the same pathway. (Funded by the National Institutes of Health and the Ting Tsung and Wei Fong Chao Foundation.).
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              Improved diagnostic yield compared with targeted gene sequencing panels suggests a role for whole-genome sequencing as a first-tier genetic test

              Purpose Genetic testing is an integral diagnostic component of pediatric medicine. Standard of care is often a time-consuming stepwise approach involving chromosomal microarray analysis and targeted gene sequencing panels, which can be costly and inconclusive. Whole-genome sequencing (WGS) provides a comprehensive testing platform that has the potential to streamline genetic assessments, but there are limited comparative data to guide its clinical use. Methods We prospectively recruited 103 patients from pediatric non-genetic subspecialty clinics, each with a clinical phenotype suggestive of an underlying genetic disorder, and compared the diagnostic yield and coverage of WGS with those of conventional genetic testing. Results WGS identified diagnostic variants in 41% of individuals, representing a significant increase over conventional testing results (24% P = 0.01). Genes clinically sequenced in the cohort (n = 1,226) were well covered by WGS, with a median exonic coverage of 40 × ±8 × (mean ±SD). All the molecular diagnoses made by conventional methods were captured by WGS. The 18 new diagnoses made with WGS included structural and non-exonic sequence variants not detectable with whole-exome sequencing, and confirmed recent disease associations with the genes PIGG, RNU4ATAC, TRIO, and UNC13A. Conclusion WGS as a primary clinical test provided a higher diagnostic yield than conventional genetic testing in a clinically heterogeneous cohort.
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                Author and article information

                Contributors
                skingsmore@rchsd.org
                Journal
                NPJ Genom Med
                NPJ Genom Med
                NPJ Genomic Medicine
                Nature Publishing Group UK (London )
                2056-7944
                9 July 2018
                9 July 2018
                2018
                : 3
                : 16
                Affiliations
                [1 ]Rady Children’s Institute for Genomic Medicine, San Diego, CA USA
                [2 ]ISNI 0000 0000 9442 535X, GRID grid.1058.c, Murdoch Children’s Research Institute, ; Melbourne, Australia
                [3 ]ISNI 0000 0001 2107 4242, GRID grid.266100.3, Department of Pediatrics, , University of California San Diego, ; San Diego, CA USA
                [4 ]ISNI 0000 0001 2179 088X, GRID grid.1008.9, Department of Paediatrics, , University of Melbourne, ; Melbourne, Australia
                Author information
                http://orcid.org/0000-0001-6690-2523
                Article
                53
                10.1038/s41525-018-0053-8
                6037748
                30002876
                b37f8644-1b7d-4fa5-a1be-54529765223e
                © The Author(s) 2018

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 17 February 2018
                : 30 April 2018
                : 10 May 2018
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