Detection Of Copy Number Variations Research Articles

Combined whole exome sequencing and chromosomal microarray analysis improve clinical interpretation of genomic variants in patients with intellectual disability

IntroductionaCGH determines pathogenic copy number variations (CNVs) in about 10% of patients with intellectual disability (ID). In another 20% of patients, probably pathogenic CNVs or variants with uncertain clinical significance are detected. It may be variants that do not fully explain the patient’s symptoms, aberrations with reduced penetrance or inherited from healthy parents. The use of a sequencing method for such cases is advisable.ObjectivesImprovement of diagnosis of intellectual disability.MethodsaCGH with 60K Agilent microarrays, qPCR, targeted sequencing, whole exome sequencing (WES).Results Six patients with ID and inherited deletions/duplications detected by aCGH and their parents if available were further examined by sequencing. Four patients had maternal CNVs: (1) del1q41 (SPATA17, LINC00210, RRP15), (2) del7q35 (TCAF2, exon 8), (3) dup8p22p21.3 (PSD3, exons 1-11), and (4) del12p11.1 (SYT10, exons 1-2). Two patients had paternal CNVs: (5) dup1q44 (SMYD3, exons 2-5) and (6) del15q11.2 (TUBGCP5, CYFIP1, NIPA1, NIPA2, LOC283683). The severe phenotype of patient (5) with dup1q44 could not be explained by the paternally inherited disruption of the single SMYD3 gene. WES determined probably pathogenic SNV in the MID1 gene associated with Opitz GBBB syndrome (OMIM 300000), which corresponds better to the patient’s phenotype and is likely to be the cause of the disease. Although del1q41 is included in the region of chromosome 1q41-q42 deletion syndrome (OMIM 612530) the phenotype of the patient (1) is much milder; WES in the patient detected two pathogenic (MPO, MAN2C1) and one probably pathogenic (ARID1B) SNVs. In patient (6) with del15q11.2 pat WES detected additional pathogenic SNV in exon 7 of the ARSE gene. In patient (3) with dup8p22p21.3 WES determined two SNVs with uncertain significance in the KIDINS220, FOXG1 genes. No SNVs were detected by WES in patient (2) with del7q35. For patient (4) with del12p11.1 targeted SYT10 sequencing revealed no pathogenic SNVs as well.ConclusionsSometimes aCGH-analysis is sufficient to identify the causes of ID, however, in the case of detection of CNVs with uncertain clinical significance and/or inherited from healthy parents, it may be necessary to further examine the patient using sequencing methods. So, the accurate diagnosis was made by WES for one patient of eight. For another two patients the combination of CNVs and SNPs should be considered. For the last three patients the described aberrations could not explain the phenotype and whole genome sequencing may be the solution.This study was supported by the Russian Science Foundation, grant 21-65-00017, https://rscf.ru/project/21-65-00017/Disclosure of InterestNone Declared

ConanVarvar: a versatile tool for the detection of large syndromic copy number variation from whole-genome sequencing data

BackgroundA wide range of tools are available for the detection of copy number variants (CNVs) from whole-genome sequencing (WGS) data. However, none of them focus on clinically-relevant CNVs, such as those that are associated with known genetic syndromes. Such variants are often large in size, typically 1–5 Mb, but currently available CNV callers have been developed and benchmarked for the discovery of smaller variants. Thus, the ability of these programs to detect tens of real syndromic CNVs remains largely unknown.ResultsHere we present ConanVarvar, a tool which implements a complete workflow for the targeted analysis of large germline CNVs from WGS data. ConanVarvar comes with an intuitive R Shiny graphical user interface and annotates identified variants with information about 56 associated syndromic conditions. We benchmarked ConanVarvar and four other programs on a dataset containing real and simulated syndromic CNVs larger than 1 Mb. In comparison to other tools, ConanVarvar reports 10–30 times less false-positive variants without compromising sensitivity and is quicker to run, especially on large batches of samples.ConclusionsConanVarvar is a useful instrument for primary analysis in disease sequencing studies, where large CNVs could be the cause of disease.

Expert consensus on the detection of genome-wide copy number variations in abortive tissues and family reproductive consultation

Chromosomal aberrations including numerical abnormalities and segment duplications/deletions, as genome-wide copy number variations (CNVs), are a leading cause for spontaneous abortion. Analysis of abortive tissues for such CNVs can detect potential genomic variations in the couple and provide guidance for the choice of appropriate method to avoid further miscarriage or birth of child with chromosomal disorders. With evidence-based clinical data, an expert group jointly formed by the Genetic Disease Prevention and Control Group, Committee for Birth Defects Prevention and Control, Chinese Association of Preventive Medicine; the Clinical Genetics Group, the Society of Medical Genetics, Chinese Medical Association; the Professional Committee for Prenatal Diagnosis of Genetic Diseases, the Society of Medical Geneticists, Chinese Medical Doctor Association has discussed and formulated this consensus, with an aim to provide guidance for the application of genomic CNVs detection for the abortive tissue and genetic counseling for family reproduction.

Molecular Diagnosis of Duchenne Muscular Dystrophy Using Single NGS-Based Assay.

Duchenne Muscular Dystrophy (DMD) is an X-linked inherited neuromuscular disorder caused by pathogenic variants in the dystrophin gene (DMD; locus Xp21.2). The variant spectrum of DMD is unique in that 65% of causative mutations are intragenic deletions, with intragenic duplications and point mutations (along with other sequence variants) accounting for 6% to 10% and 30% to 35%, respectively. The traditional strategy for molecular diagnostic testing for DMD involves initial screening for deletions/duplications using microarray-based comparative genomic hybridization followed by a full-sequence analysis of DMD for sequence variants. This traditional strategy is expensive and time-consuming due to the involvement of two separate tests to detect all types of variants in the DMD gene. Recent advancements in next-generation sequencing (NGS) technology and improvements in analysis algorithms related to copy number variant detection ultimately resulted in the development of a single NGS-based assay to detect all variant types, including deletions/duplications and sequence variants. This article initially discusses the strategic algorithm for establishing a molecular diagnosis of DMD and later provides detailed molecular diagnostic protocols for DMD, including an NGS-based sequencing assay with sequence and copy number variant analysis. © 2023 Wiley Periodicals LLC. Basic Protocol: Next-generation sequencing of the entire genomic sequence of the DMD gene using IDT xGen Lockdown Probes.

Population differentiated copy number variation between Eurasian wild boar and domesticated pig populations

Sus scrofa is a globally distributed livestock species that still maintains two different ways of life: wild and domesticated. Herein, we detected copy number variation (CNV) of 328 animals using short read alignment on Sscrofa11.1. We compared CNV among five groups of porcine populations: Asian domesticated (AD), European domesticated (ED), Asian wild (AW), European wild (EW), and Near Eastern wild (NEW). In total, 21,673 genes were identified on 154,872 copy number variation region (CNVR). Differences in gene copy numbers between populations were measured by considering the variance-based value {V}_{ST} and the one-way ANOVA test followed by Scheffe test. As a result, 111 genes were suggested as copy number variable genes. Abnormally gained copy number on EEA1 in all populations was suggested the presence of minor CNV in the reference genome assembly, Sscrofa11.1. Copy number variable genes were related to meat quality, immune response, and reproduction traits. Hierarchical clustering of all individuals and mean pairwise {V}_{ST} in breed level were visualized genetic relationship of 328 individuals and 56 populations separately. Our findings have shown how the complex history of pig evolution appears in genome-wide CNV of various populations with different regions and lifestyles.

Target-allele-specific probe single-base extension (TASP-SBE): a novel MALDI-TOF-MS strategy for multi-variants analysis and its application in simultaneous detection of α-/β-thalassemia mutations.

Single-nucleotide variants (SNVs) and copy number variations (CNVs) are the most common genomic variations that cause phenotypic diversity and genetic disorders. MALDI-TOF-MS is a rapid and cost-effective technique for multi-variant genotyping, but it is challenging to efficiently detect CNVs and clustered SNVs, especially to simultaneously detect CNVs and SNVs in one reaction. Herein, a novel strategy termed Target-Allele-Specific Probe Single-Base Extension (TASP-SBE) was devised to efficiently detect CNVs and clustered SNVs with MALDI-TOF-MS. By comprehensive use of traditional SBE and TASP-SBE strategies, a MALDI-TOF-MS assay was also developed to simultaneously detect 28 α-/β-thalassemia mutations in a single reaction system, including 4 α-thalassemia deletions, 3 HBA and 21 HBB SNVs. The results showed that all 28 mutations were sensitively identified, and the CNVs of HBA/HBB genes were also accurately analyzed based on the ratio of peak height (RPH) between the target allele and reference gene. The double-blind evaluation results of 989 thalassemia carrier samples showed a 100% concordance of this assay with other methods. In conclusion,a one-tube MALDI-TOF-MS assay was developed to simultaneously genotype 28 thalassemia mutations. This novel TASP-SBE was also verified a practicable strategy for the detection of CNVs and clustered SNVs, providing a feasible approach for multi-variants analysis with MALDI-TOF-MS technique.

A shortest path-based approach for copy number variation detection from next-generation sequencing data.

Copy number variation (CNV) is one of the main structural variations in the human genome and accounts for a considerable proportion of variations. As CNVs can directly or indirectly cause cancer, mental illness, and genetic disease in humans, their effective detection in humans is of great interest in the fields of oncogene discovery, clinical decision-making, bioinformatics, and drug discovery. The advent of next-generation sequencing data makes CNV detection possible, and a large number of CNV detection tools are based on next-generation sequencing data. Due to the complexity (e.g., bias, noise, alignment errors) of next-generation sequencing data and CNV structures, the accuracy of existing methods in detecting CNVs remains low. In this work, we design a new CNV detection approach, called shortest path-based Copy number variation (SPCNV), to improve the detection accuracy of CNVs. SPCNV calculates the k nearest neighbors of each read depth and defines the shortest path, shortest path relation, and shortest path cost sets based on which further calculates the mean shortest path cost of each read depth and its k nearest neighbors. We utilize the ratio between the mean shortest path cost for each read depth and the mean of the mean shortest path cost of its k nearest neighbors to construct a relative shortest path score formula that is able to determine a score for each read depth. Based on the score profile, a boxplot is then applied to predict CNVs. The performance of the proposed method is verified by simulation data experiments and compared against several popular methods of the same type. Experimental results show that the proposed method achieves the best balance between recall and precision in each set of simulated samples. To further verify the performance of the proposed method in real application scenarios, we then select real sample data from the 1,000 Genomes Project to conduct experiments. The proposed method achieves the best F1-scores in almost all samples. Therefore, the proposed method can be used as a more reliable tool for the routine detection of CNVs.

Copy number variations in SPAST and ATL1 are rare among Brazilians.

Copy number variations (CNV) may represent a significant proportion of SPG4 and SPG3A diagnosis, the most frequent autosomal dominant subtypes of hereditary spastic paraplegias (HSP). We aimed to assess the frequency of CNVs in SPAST and ATL1 and to update the molecular epidemiology of HSP families in southern Brazil. A cohort study that included 95 Brazilian index cases with clinical suspicion of HSP was conducted between April 2011 and September 2022. Multiplex Ligation Dependent Probe Amplification (MLPA) was performed in 41 cases without defined diagnosis by different massive parallel sequencing techniques (MPS). Diagnosis was obtained in 57/95 (60%) index cases, 15/57 (26.3%) being SPG4. Most frequent autosomal recessive HSP subtypes were SPG7 followed by SPG11, SPG76 and cerebrotendinous xanthomatosis. No CNVs in SPAST and ATL1 were found. Copy number variations are rare among SPG4 and SPG3A families in Brazil. Considering the possibility of CNVs detection by specific algorithms with MPS data, we consider that this is likely the most cost-effective approach to investigate CNVs in these genes in low-risk populations, with MLPA being reserved as an orthogonal confirmatory test.

Application value of CNV-seq for the prenatal diagnosis of women with high-risk pregnancies

To assess the application value of copy number variation sequencing (CNV-seq) for women with a high risk for fetal anomalies. Based on the results of non-invasive prenatal testing (NIPT), 271 high-risk pregnant women were divided into NIPT positive group (n = 83) and other anomaly group (advanced age, high risk by serological screening, repeated NIPT failure, adverse pregnancy history, abnormal ultrasound finding, and abnormal phenotype) (n = 188). CNV-seq was carried out to detect copy number variations (CNVs) in amniocytic DNA from the two groups of pregnant women, and karyotyping analysis of the amniotic cells was carried out for verification and comparison. The amniocytes from 271 pregnant women were detected. The detection rate was 20.66% (56/271) for pathogenic CNVs by CNV-seq and 19.19% (52/271) for pathogenic karyotypes by karyotyping analysis. The difference was statistically significant (P < 0.05). CNV-seq had shown that, compared with NIPT positive group, the detection rates for likely pathogenic CNVs and variants of unknown significance (VUS) in other abnormality group were significantly higher [2.41%(2/83) vs. 5.32%(10/188)](P < 0.05). CNV-seq can well suit the first-tier diagnosis for pregnant women suspected for fetal abnormality. In prenatal diagnosis settings, CNV-seq can identify additional and clinically significant cytogenetic abnormalities. In those with other abnormalities, the detection rates for likely pathogenic CNVs and VUS are higher than with the NIPT positive cases.

Combined exome analysis and exome depth assessment achieve a high diagnostic yield in an epilepsy case series, revealing significant genomic heterogeneity and novel mechanisms

ABSTRACT Objectives Genetics of epilepsy are highly heterogeneous and complex. Lesions detected involve genes encoding various types of channels, transcription factors, and other proteins implicated in numerous cellular processes, such as synaptogenesis. Consequently, a wide spectrum of clinical presentations and overlapping phenotypes hinders differential diagnosis and highlights the need for molecular investigations toward delineation of underlying mechanisms and final diagnosis. Characterization of defects may also contribute valuable data on genetic landscapes and networks implicated in epileptogenesis. Methods This study reports on genetic findings from exome sequencing (ES) data of 107 patients with variable types of seizures, with or without additional symptoms, in the context of neurodevelopmental disorders. Results Multidisciplinary evaluation of ES, including ancillary detection of copy number variants (CNVs) with the ExomeDepth tool, supported a definite diagnosis in 59.8% of the patients, reflecting one of the highest diagnostic yields in epilepsy. Conclusion Emerging advances of next-generation technologies and ‘in silico’ analysis tools offer the possibility to simultaneously detect several types of variations. Wide assessment of variable findings, specifically those found to be novel and least expected, reflects the ever-evolving genetic landscape of seizure development, potentially beneficial for increased opportunities for trial recruitment and enrollment, and optimized, even personalized, medical management.

A novel scatterplot-based method to detect copy number variation (CNV).

Objective: Most methods to detect copy number variation (CNV) have high false positive rates, especially for small CNVs and in real-life samples from clinical studies. In this study, we explored a novel scatterplot-based method to detect CNVs in microarray samples. Methods: Illumina SNP microarray data from 13,254 individuals were analyzed with scatterplots and by PennCNV. The data were analyzed without the prior exclusion of low-quality samples. For CNV scatterplot visualization, the median signal intensity of all SNPs located within a CNV region was plotted against the median signal intensity of the flanking genomic region. Since CNV causes loss or gain of signal intensities, carriers of different CNV alleles pop up in clusters. Moreover, SNPs within a deletion are not heterozygous, whereas heterozygous SNPs within a duplication show typical 1:2 signal distribution between the alleles. Scatterplot-based CNV calls were compared with standard results of PennCNV analysis. All discordant calls as well as a random selection of 100 concordant calls were individually analyzed by visual inspection after noise-reduction. Results: An algorithm for the automated scatterplot visualization of CNVs was developed and used to analyze six known CNV regions. Use of scatterplots and PennCNV yielded 1019 concordant and 108 discordant CNV calls. All concordant calls were evaluated as true CNV-findings. Among the 108 discordant calls, 7 were false positive findings by the scatterplot method, 80 were PennCNV false positives, and 21 were true CNVs detected by the scatterplot method, but missed by PennCNV (i.e., false negative findings). Conclusion: CNV visualization by scatterplots allows for a reliable and rapid detection of CNVs in large studies. This novel method may thus be used both to confirm the results of genome-wide CNV detection software and to identify known CNVs in hitherto untyped samples.

P562: Sequence and copy number variant detection in autosomal recessive conditions utilizing tiered-testing approach

P562: Sequence and copy number variant detection in autosomal recessive conditions utilizing tiered-testing approach

Copy Number Variations (CNVs) Account for 10.8% of Pathogenic Variants in Patients Referred for Hereditary Cancer Testing.

Germline copy number variation (CNV) is a type of genetic variant that predisposes significantly to inherited cancers. Today, next-generation sequencing (NGS) technologies have contributed to multi gene panel analysis in clinical practice. A total of 2,163 patients were screened for cancer susceptibility, using a solution-based capture method. A panel of 52 genes was used for targeted NGS. The capture-based approach enables computational analysis of CNVs from NGS data. We studied the performance of the CNV module of the commercial software suite SeqPilot (JSI Medical Systems) and of the non-commercial tool panelcn.MOPS. Additionally, we tested the performance of digital multiplex ligation-dependent probe amplification (digitalMLPA). Pathogenic/likely pathogenic variants (P/LP) were identified in 464 samples (21.5%). CNV accounts for 10.8% (50/464) of pathogenic variants, referring to deletion/duplication of one or more exons of a gene. In patients with breast and ovarian cancer, CNVs accounted for 10.2% and 6.8% of pathogenic variants, respectively. In colorectal cancer patients, CNV accounted for 28.6% of pathogenic/likely pathogenic variants. In silico CNV detection tools provide a viable and cost-effective method to identify CNVs from NGS experiments. CNVs constitute a substantial percentage of P/LP variants, since they represent up to one of every ten P/LP findings identified by NGS multigene analysis; therefore, their evaluation is highly recommended to improve the diagnostic yield of hereditary cancer analysis.

Varijacije u broju kopija na hromozomu 15 detektovane molekularnom kariotipizacijom kod pacijenata sa razvojnim kašnjenjem i urođenim anomalijama

Introduction: Global developmental delay (GDD) and congenital anomalies represent a heterogeneous group of medical conditions that may have a known genetic etiology. Molecular karyotyping is the gold standard for detecting copy number variations (CNV), and the first-line test in patients with GDD and congenital anomalies, with an average diagnostic yield of 15%. Chromosome 15 (C15) is one of the chromosomes on which CNV occurs most frequently. Aim: To analyze all detected (significant) CNVs on C15 in patients with GKR and/or congenital anomalies, estimate their share in the overall CNV detection rate of different pathogenicity classes, and present several illustrative cases. Material and methods: In the total sample of 350 patients analyzed by molecular karyotyping technique, 92 with detected significant CNV were singled out. All patients with variants on C15 were then analyzed and further classified according to type, size, and clinical significance. Results: In 11 patients, at least one significant CNV was detected on chromosome 15, which is 3.15% of the total sample and 11.96% of a sample of patients with significant CNV of any localization. In 72.7% cases, CNV was described as pathogenic or likely pathogenic and in 27.3% as a variant of unknown significance. In the total detection rate of csCNV from all chromosomes 15.4%, the percentage of variations from C15 was 17.2%. Conclusion: The detection rate of csCNVs on C15 in the diagnostic yield of the molecular karyotypisation of patients with GDD and congenital anomalies is 17.2%, which confirms that they make up a significant portion of the GDD etiology.

A Novel Tool for the Analysis and Detection of Copy Number Variants Associated with Haemoglobinopathies.

Several types of haemoglobinopathies are caused by copy number variants (CNVs). While diagnosis is often based on haematological and biochemical parameters, a definitive diagnosis requires molecular DNA analysis. In some cases, the molecular characterisation of large deletions/duplications is challenging and inconclusive and often requires the use of specific diagnostic procedures, such as multiplex ligation-dependent probe amplification (MLPA). Herein, we collected and comprehensively analysed all known CNVs associated with haemoglobinopathies. The dataset of 291 CNVs was retrieved from the IthaGenes database and was further manually annotated to specify genomic locations, breakpoints and MLPA probes relevant for each CNV. We developed IthaCNVs, a publicly available and easy-to-use online tool that can facilitate the diagnosis of rare and diagnostically challenging haemoglobinopathy cases attributed to CNVs. Importantly, it facilitates the filtering of available entries based on the type of breakpoint information, on specific chromosomal and locus positions, on MLPA probes, and on affected gene(s). IthaCNVs brings together manually curated information about CNV genomic locations, functional effects, and information that can facilitate CNV characterisation through MLPA. It can help laboratory staff and clinicians confirm suspected diagnosis of CNVs based on molecular DNA screening and analysis.

CONGA: Copy number variation genotyping in ancient genomes and low-coverage sequencing data.

To date, ancient genome analyses have been largely confined to the study of single nucleotide polymorphisms (SNPs). Copy number variants (CNVs) are a major contributor of disease and of evolutionary adaptation, but identifying CNVs in ancient shotgun-sequenced genomes is hampered by typical low genome coverage (<1×) and short fragments (<80 bps), precluding standard CNV detection software to be effectively applied to ancient genomes. Here we present CONGA, tailored for genotyping CNVs at low coverage. Simulations and down-sampling experiments suggest that CONGA can genotype deletions >1 kbps with F-scores >0.75 at ≥1×, and distinguish between heterozygous and homozygous states. We used CONGA to genotype 10,002 outgroup-ascertained deletions across a heterogenous set of 71 ancient human genomes spanning the last 50,000 years, produced using variable experimental protocols. A fraction of these (21/71) display divergent deletion profiles unrelated to their population origin, but attributable to technical factors such as coverage and read length. The majority of the sample (50/71), despite originating from nine different laboratories and having coverages ranging from 0.44×-26× (median 4×) and average read lengths 52-121 bps (median 69), exhibit coherent deletion frequencies. Across these 50 genomes, inter-individual genetic diversity measured using SNPs and CONGA-genotyped deletions are highly correlated. CONGA-genotyped deletions also display purifying selection signatures, as expected. CONGA thus paves the way for systematic CNV analyses in ancient genomes, despite the technical challenges posed by low and variable genome coverage.

Prenatal genetic diagnosis for fetuses with anomalies revealed by fetal echocardiography

To carry out amniocyte karyotyping analysis and chromosomal microarray analysis (CMA) for women with anomalies revealed by fetal echocardiography. From January 2019 to December 2021, genetic testing was carried out for 205 fetuses including 97 with soft marker anomalies and 108 with structural heart abnormalities. Among these, 138 only had abnormal fetal echocardiography, whilst 38 and 29 were complicated with extracardiac soft marker anomalies and extracardiac structural malformation, respectively. No significant difference was detected in the detection rate of genetic anomalies between fetuses with heart-related soft markers and those with abnormal heart structures (P > 0.05). Compared with those with abnormal fetal echocardiography alone, the detection rates of chromosomal aneuploidies in those with abnormal extracardiac soft markers or abnormal extracardiac structures were significantly higher (P < 0.05). Twenty-eight chromosomal aneuploidies (including a rare mosaicism), 2 balanced translocations and 1 supernumerary marker chromosome were detected by karyotyping analysis. Twenty-seven aneuploidies, 19 copy number variations (CNVs) and 1 uniparental disomy were detected by CMA. Prenatal diagnosis has attached great importance to the suggestive role of fetal heart-related soft markers, and chromosomal aneuploidies are more common among fetuses with abnormal extracardiac soft markers and extracardiac structural abnormalities. Chromosomal Karyotyping is useful for the detection of balanced translocations and mosaicisms. CMA is helpful for the detection of CNVs. Identification of the genetic causes can facilitate genetic counseling for the affected couples.

Cas9-Mediated Nanopore Sequencing Enables Precise Characterization of Structural Variants in CCM Genes.

Deletions in the CCM1, CCM2, and CCM3 genes are a common cause of familial cerebral cavernous malformations (CCMs). In current molecular genetic laboratories, targeted next-generation sequencing or multiplex ligation-dependent probe amplification are mostly used to identify copy number variants (CNVs). However, both techniques are limited in their ability to specify the breakpoints of CNVs and identify complex structural variants (SVs). To overcome these constraints, we established a targeted Cas9-mediated nanopore sequencing approach for CNV detection with single nucleotide resolution. Using a MinION device, we achieved complete coverage for the CCM genes and determined the exact size of CNVs in positive controls. Long-read sequencing for a CCM1 and CCM2 CNV revealed that the adjacent ANKIB1 and NACAD genes were also partially or completely deleted. In addition, an interchromosomal insertion and an inversion in CCM2 were reliably re-identified by long-read sequencing. The refinement of CNV breakpoints by long-read sequencing enabled fast and inexpensive PCR-based variant confirmation, which is highly desirable to reduce costs in subsequent family analyses. In conclusion, Cas9-mediated nanopore sequencing is a cost-effective and flexible tool for molecular genetic diagnostics which can be easily adapted to various target regions.

Genetic analysis of neurodevelopmental disorders in children

PurposeTo explore the genetic cause of children with unidentified etiology of neurodevelopmental disorders, thus providing references for the diagnosis, treatment and genetic counseling.Design and methodsChildren with neurodevelopmental disorders but unidentified etiology in the Child Healthcare Department, Children's Hospital of Nanjing Medical University from November 2018 to December 2021 were retrospectively analyzed. A total of 2 ml of peripheral venous blood was collected from the child and their parents for the whole exome sequencing (WES) and copy number variation (CNV) detection. Male children were subjected to fragile X syndrome testing to determine the genetic mutations. For those with positive results, Sanger sequencing was performed to explore the mutations in the gene sites and pedigrees.ResultsA total of 488 (33.5%) pathogenic variations were detected among 1,457 global developmental/intellectual disabilities (GDD/ID) children, including 362 (24.9%) cases of monogenic mutations, and 111 (7.6%) cases of chromosomal microdeletions or microduplications. There were 15/780 (1.92%) male children with fragile X syndrome. Single point mutations were detected in 277/362 (76.5%) and 85/362 (23.5%) male and female GDD/ID children, respectively, including 295 (81.5%) cases of missense mutations, 32 (8.8%) cases of frameshift mutations, 5 (2.2%) cases of non-sense mutations and 30 (8.3%) cases of splice site mutations. In addition, there were 166 (45.8%) cases of autosomal inheritance and 196 (54.2%) cases of X-linked inheritance. The X chromosome abnormalities were mostly observed in 362 GDD/ID children with monogenic mutations, including 15 cases of the AFF2 gene mutation, 13 cases of the MECP2 gene mutation and 12 cases of the HUWEI gene mutation. The CREBBP gene mutation was the most common autosome abnormality in GDD/ID children with monogenic mutations, which was detected in five cases. There were 74 cases of chromosomal microdeletions, 31 cases of chromosomal microduplications and six cases of both. A total of 114 novel pathogenic mutations responsible for GDD/ID were found, including four novel mutations in MECP2 and TRAPPC9 genes.ConclusionThe incidence of genetic abnormalities remains high in NDD children. Abundant novel mutations are responsible for GDD/ID in children, and can be used as references in the diagnosis of neurogenetic diseases.

Maternal Copy Number Imbalances in Non-Invasive Prenatal Testing: Do They Matter?

Non-invasive prenatal testing (NIPT) has become a routine practice in screening for common aneuploidies of chromosomes 21, 18, and 13 and gonosomes X and Y in fetuses worldwide since 2015 and has even expanded to include smaller subchromosomal events. In fact, the fetal fraction represents only a small proportion of cell-free DNA on a predominant background of maternal DNA. Unlike fetal findings that have to be confirmed using invasive testing, it has been well documented that NIPT provides information on maternal mosaicism, occult malignancies, and hidden health conditions due to copy number variations (CNVs) with diagnostic resolution. Although large duplications or deletions associated with certain medical conditions or syndromes are usually well recognized and easy to interpret, very little is known about small, relatively common copy number variations on the order of a few hundred kilobases and their potential impact on human health. We analyzed data from 6422 NIPT patient samples with a CNV detection resolution of 200 kb for the maternal genome and identified 942 distinct CNVs; 328 occurred repeatedly. We defined them as multiple occurring variants (MOVs). We scrutinized the most common ones, compared them with frequencies in the gnomAD SVs v2.1, dbVar, and DGV population databases, and analyzed them with an emphasis on genomic content and potential association with specific phenotypes.