New Insights into the Impact of Genome-Wide Copy Number Variations on Complex Congenital Heart Disease in Saudi Arabia

Dasouki, Majed; Wakil, Salma M.; Al‐Harazi, Olfat; Alkorashy, Maarab; Muiya, Nzioka P.; Andres, Editha; Hagos, Samya; Al-Dusery, Haya; Dzimiri, Nduna; Çolak, Dilek

doi:10.1089/omi.2019.0165

Cited by 6 publications

(3 citation statements)

References 40 publications

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“…These data reveal the diversity of CNVs in CHD, mainly involving 17q21.31, 16p11.2, 8p11.21 and 22q11.23 [33] Noonan syndrome and Leopard syndrome [34]. Mutations in genes expressed in cardiac vascular endothelial cells, including NTRK3, MCTP2, and MYH7, can also lead to a series of congenital heart diseases, such as heart valve stenosis, aortic arch dysplasia, atrial septal defect, and ventricular septal defect [35][36].…”

Section: The 2016 Guidelines Propose Prenatal Diagnosis Of Genetic Di...mentioning

confidence: 83%

Application of chromosomal microarray analysis in congenital heart disease

Xia

Guan

et al. 2022

Preprint

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Objective: To investigate the relationship between different types of fetal congenital heart disease (CHD) and genetic factors, and to evaluate the application value of chromosomal microarray analysis in prenatal diagnosi s of fetuses with CHD. Methods: 122 fetuses diagnosed with CHD by prenatal fetal ultrasound or echocardiography in Weihai Maternal and Child Health Hospital and that underwent prenatal diagnosis by amniocentesis from June 2016 to December 2020 were included as research subjects. Karyotype analysis, chromosomal microarray analysis technology, and sNP-array technology were used to detect karyotype and genome-wide copy number variation. Results: Of the 122 cases of fetal genetic results, 23 were abnormal results (18.85%, 23/122). 11 cases had abnormal karyotypes (9.02%, 11/122) ), 9 cases had aneuploidy (7.38%, 9/122), and 2 cases exhibited mosaicism (1.64%, 2/122). Chromosomal microarray analysis detected 12 cases (9.84%, 12/122) of CNVs. There were 6 cases of pCNV (4.92%, 6/122) and 6 cases of VOUS (4.92%, 6/122). CMA detected an additional 4.92% of pathogenic genetic abnormalities than karyotype analysis. The abnormal karyotype detection rate of the CHD group with extracardiac abnormalities was significantly higher than that of the independent CHD group (27.78% vs. 5.34%, P<0.01). The abnormal karyotype and pCNV detection rate of non-isolated ventricular septal defects were significantly higher than those of isolated ventricular septal defects, (23.53% vs. 0%, P<0.01; 14.71% vs. 0%). P < 0.05,). The detection rate of pCNV in the solitary ventricular septal defect with abnormal soft index group was significantly higher than that in the solitary ventricular septal defect group(36.4% vs. 0%, P<0.001). The detection rate of abnormal karyotype in the ventricular septal defect with extracardiac abnormality group was significantly higher than that in the isolated ventricular septal defect group (33.33% vs. 0%, P<0.05). Conclusion: Chromosomal microarray analysis technology can improve the detection rate of CHD in fetuses. CMA can detect 4.92% more pathogenic copy number variation than chromosomal karyotype analysis and the abnormal karyotype detection rate of CHD with extracardiac abnormalities was high. We observed a high detection rate of pathogenic CNV in non-isolated ventricular septal defect.

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Section: The 2016 Guidelines Propose Prenatal Diagnosis Of Genetic Di...mentioning

confidence: 83%

Application of chromosomal microarray analysis in congenital heart disease

Xia

Guan

et al. 2022

Preprint

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“…DNA was extracted from non-irradiated fibroblasts using the Puregene DNA Purification Kit (Gentra System, Qiagen, Minneapolis, MN, USA) according to the manufacturer’s instructions. DNA was genotyped using the Affymetrix CytoScan HD microarrays (Affymetrix, ThermoFisher Scientific, Waltham, MA, USA) according to the manufacturer’s instructions as described elsewhere ( 18 , 19 ). Preprocessing and quality control were performed with Chromosome Analysis Suite 3.1 tool (Thermo Fisher Scientific Inc., Waltham, Massachusetts, USA).…”

Section: Methodsmentioning

confidence: 99%

Multivariate piecewise linear regression model to predict radiosensitivity using the association with the genome-wide copy number variation

Tobiasz,

Al-Harbi,

Bin Judia

et al. 2023

Front. Oncol.

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IntroductionThe search for biomarkers to predict radiosensitivity is important not only to individualize radiotherapy of cancer patients but also to forecast radiation exposure risks. The aim of this study was to devise a machine-learning method to stratify radiosensitivity and to investigate its association with genome-wide copy number variations (CNVs) as markers of sensitivity to ionizing radiation.MethodsWe used the Affymetrix CytoScan HD microarrays to survey common CNVs in 129 fibroblast cell strains. Radiosensitivity was measured by the surviving fraction at 2 Gy (SF2). We applied a dynamic programming (DP) algorithm to create a piecewise (segmented) multivariate linear regression model predicting SF2 and to identify SF2 segment-related distinctive CNVs.ResultsSF2 ranged between 0.1384 and 0.4860 (mean=0.3273 The DP algorithm provided optimal segmentation by defining batches of radio-sensitive (RS), normally-sensitive (NS), and radio-resistant (RR) responders. The weighted mean relative errors (MRE) decreased with increasing the segments' number. The borders of the utmost segments have stabilized after partitioning SF2 into 5 subranges.DiscussionThe 5-segment model associated C-3SFBP marker with the most-RS and C-7IUVU marker with the most-RR cell strains. Both markers were mapped to gene regions (MCC and SLC1A6, respectively). In addition, C-3SFBP marker is also located in enhancer and multiple binding motifs. Moreover, for most CNVs significantly correlated with SF2, the radiosensitivity increased with the copy-number decrease.In conclusion, the DP-based piecewise multivariate linear regression method helps narrow the set of CNV markers from the whole radiosensitivity range to the smaller intervals of interest. Notably, SF2 partitioning not only improves the SF2 estimation but also provides distinctive markers. Ultimately, segment-related markers can be used, potentially with tissues’ specific factors or other clinical data, to identify radiotherapy patients who are most RS and require reduced doses to avoid complications and the most RR eligible for dose escalation to improve outcomes.

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“…Thirty recent publications (2015-2020) on large-scale sequencing or single-gene studies on CHD were selected for significant genotype–phenotype associations. Candidate gene enumerations of these publications were included in the search space of this study until a target number of 200 candidate genes was reached ( Bravo-Gil et al, 2019 ; Cohen et al, 2020 ; Dasouki et al, 2020 ; Demal et al, 2019 ; Dianatpour et al, 2020 ; Fotiou et al, 2019 ; Hawer et al, 2020 ; Hay et al, 2020 ; Haynes et al, 2020 ; Homsy et al, 2015 ; Ji et al, 2020 ; Jin et al, 2017 ; Lee et al, 2020 ; Liu et al, 2017 , 2020 ; Mastromoro et al, 2020 ; Morton et al, 2020 ; Muir et al, 2020 ; Page et al, 2019 ; Priest et al, 2016 ; Reuter et al, 2020 ; Richter et al, 2020a ; Samudrala et al, 2020 ; Sifrim et al, 2016 ; Szot et al, 2018 , 2019 ; Wang et al, 2020a , b ; Xu et al, 2018 ). The Ensembl and PubMed databases were searched for previous work detailing structural–developmental cardiac defects in vivo upon knockout or knockdown of the candidate gene.…”

Section: Methodsmentioning

confidence: 99%

CRISPR-based knockout and base editing confirm the role of MYRF in heart development and congenital heart disease

Doering

Cornean

Thumberger

et al. 2023

Disease Models &Amp; Mechanisms

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High-throughput DNA sequencing studies increasingly associate DNA variants with congenital heart disease (CHD). However, functional modeling is a crucial prerequisite for translating genomic data into clinical care. We used CRISPR-Cas9-mediated targeting of 12 candidate genes in the vertebrate model medaka (Oryzias latipes), five of which displayed a novel cardiovascular phenotype spectrum in F0 (crispants): mapre2, smg7, cdc42bpab, ankrd11 and myrf, encoding a transcription factor recently linked to cardiac-urogenital syndrome. Our myrf mutant line showed particularly prominent embryonic cardiac defects recapitulating phenotypes of pediatric patients, including hypoplastic ventricle. Mimicking human mutations, we edited three sites to generate specific myrf single-nucleotide variants via cytosine and adenine base editors. The Glu749Lys missense mutation in the conserved intramolecular chaperon autocleavage domain fully recapitulated the characteristic myrf mutant phenotype with high penetrance, underlining the crucial function of this protein domain. The efficiency and scalability of base editing to model specific point mutations accelerate gene validation studies and the generation of human-relevant disease models.

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New Insights into the Impact of Genome-Wide Copy Number Variations on Complex Congenital Heart Disease in Saudi Arabia

Cited by 6 publications

References 40 publications

Application of chromosomal microarray analysis in congenital heart disease

Application of chromosomal microarray analysis in congenital heart disease

Multivariate piecewise linear regression model to predict radiosensitivity using the association with the genome-wide copy number variation

CRISPR-based knockout and base editing confirm the role of MYRF in heart development and congenital heart disease

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