Detecting copy number variation in next generation sequencing data from diagnostic gene panels

Next-generation data filtering in the genomics era

Genomic data are ubiquitous across disciplines, from agriculture to biodiversity, ecology, evolution and human health. However, these datasets often contain noise or errors and are missing information that can affect the accuracy and reliability of subsequent computational analyses and conclusions. A key step in genomic data analysis is filtering - removing sequencing bases, reads, genetic variants and/or individuals from a dataset - to improve data quality for downstream analyses. Researchers are confronted with a multitude of choices when filtering genomic data; they must choose which filters to apply and select appropriate thresholds. To help usher in the next generation of genomic data filtering, we review and suggest best practices to improve the implementation, reproducibility and reporting standards for filter types and thresholds commonly applied to genomic datasets. We focus mainly on filters for minor allele frequency, missing data per individual or per locus, linkage disequilibrium and Hardy-Weinberg deviations. Using simulated and empirical datasets, we illustrate the large effects of different filtering thresholds on common population genetics statistics, such as Tajima's D value, population differentiation (FST), nucleotide diversity (π) and effective population size (Ne).

Genome-wide association testing beyond SNPs

Decades of genetic association testing in human cohorts have provided important insights into the genetic architecture and biological underpinnings of complex traits and diseases. However, for certain traits, genome-wide association studies (GWAS) for common SNPs are approaching signal saturation, which underscores the need to explore other types of genetic variation to understand the genetic basis of traits and diseases. Copy number variation (CNV) is an important source of heritability that is well known to functionally affect human traits. Recent technological and computational advances enable the large-scale, genome-wide evaluation of CNVs, with implications for downstream applications such as polygenic risk scoring and drug target identification. Here, we review the current state of CNV-GWAS, discuss current limitations in resource infrastructure that need to be overcome to enable the wider uptake of CNV-GWAS results, highlight emerging opportunities and suggest guidelines and standards for future GWAS for genetic variation beyond SNPs at scale.

Rett syndrome diagnostic odyssey: Limitations of NextGen sequencing

Typical (or classic) Rett syndrome (RTT) is an X-linked neurodevelopmental disorder characterized by a period of regression, partial or complete loss of purposeful hand movements, and acquired speech, impaired gait, and stereotyped hand movements. In over 95% of typical RTT, a pathogenic variant is found in the methyl-CPG binding protein 2 gene (MECP2). Here, we describe a young woman with clinically diagnosed typical RTT syndrome who lacked a genetic diagnosis despite 20 years of investigation and multiple rounds of sequencing the MECP2 gene. Recently, additional genetic testing using next-generation sequencing was completed, which revealed a partial insertion of the BCL11A gene within exon 4 of MECP2, resulting in a small deletion in MECP2, causing likely disruption of MeCP2 function due to a frameshift. This case demonstrates the ever-changing limitations of genetic testing, as well as the importance of continual pursuit of a diagnosis as technologies improve and are more widely utilized.

Comprehensive Approach for the Genetic Diagnosis of Patients with Waardenburg Syndrome

Waardenburg syndrome (WS) is a common genetic cause of syndromic hearing loss, accounting for 2-5% of congenital cases. It is characterized by hearing impairment and pigmentation abnormalities in the skin, hair, and eyes. Seven genes are associated with WS: PAX3, MITF, EDNRB, EDN3, SOX10, KITLG, and SNAI2. This study investigates the genetic causes of WS in three familial cases. Whole-exome sequencing (WES) was performed to identify single nucleotide variants (SNVs). Copy number variants (CNVs) were analyzed from the WES raw data and through multiplex ligation-dependent probe amplification (MLPA). The study identified one pathogenic SNV and two novel CNVs, corresponding to type I and type II WS patterns in the three families. The SNV, a nonsense variant (c.1198C>T p.Arg400*), was found in MITF and segregated in the affected father. The two CNVs were a deletion of exon 5 in PAX3 in a family with two affected members and a large novel deletion comprising seven genes, including SOX10, in a family with three affected members. These findings confirmed a WS diagnosis through genetic testing. The study emphasizes the importance of integrating multiple genetic testing approaches for accurate and reliable diagnosis, highlighting their role in improving patient management and providing tailored genetic counseling.

Comprehensive assessment of long-read sequencing platforms and calling algorithms for detection of copy number variation

Copy number variations (CNVs) play pivotal roles in disease susceptibility and have been intensively investigated in human disease studies. Long-read sequencing technologies offer opportunities for comprehensive structural variation (SV) detection, and numerous methodologies have been developed recently. Consequently, there is a pressing need to assess these methods and aid researchers in selecting appropriate techniques for CNV detection using long-read sequencing. Hence, we conducted an evaluation of eight CNV calling methods across 22 datasets from nine publicly available samples and 15 simulated datasets, covering multiple sequencing platforms. The overall performance of CNV callers varied substantially and was influenced by the input dataset type, sequencing depth, and CNV type, among others. Specifically, the PacBio CCS sequencing platform outperformed PacBio CLR and Nanopore platforms regarding CNV detection recall rates. A sequencing depth of 10x demonstrated the capability to identify 85% of the CNVs detected in a 50x dataset. Moreover, deletions were more generally detectable than duplications. Among the eight benchmarked methods, cuteSV, Delly, pbsv, and Sniffles2 demonstrated superior accuracy, while SVIM exhibited high recall rates.

Novel causative variants in Legius syndrome: SPRED1 Genotype spectrum expansion

Legius syndrome, commonly referred to as SPRED1-related neurofibromatosis type 1-like syndrome, is a rare autosomal dominant disorder characterized by café-au-lait macules, freckling, lipomas, macrocephaly, and heterogeneous neurodevelopmental manifestations, including a different degree of learning difficulties. Although a partial clinical overlap exists with neurofibromatosis type 1 (NF1), Legius syndrome is distinguished by its genetic etiology and the absence of neurofibromas, indicating an inherent lack of tumor risk. The SPRED1 gene encodes the Sprouty-related protein with an EVH1 domain 1 (SPRED1), a negative regulator of the RAS-MAPK signaling pathway with a crucial role in cellular growth and development. Despite various genetic variants and genomic deletions associated with Legius syndrome, the full genetic spectrum of this condition remains elusive. In this study, we investigated the underlying genetic etiology in a cohort of patients presenting with typical manifestations of Legius syndrome using a custom Next Generation Sequencing (NGS) panel and Multiplex Ligation-Dependent Probe Amplification (MLPA) for NF1 and SPRED1. We identified 12 novel SPRED1 damaging variants segregating with the phenotype in all families. These rare variants affect conserved residues of the protein and are predicted damaging according to in silico tools. No clear genotype-phenotype correlations could be observed in the current cohort and previously reported patients, underscoring the heterogeneous genotype spectrum of this condition. Our findings expand the understanding of SPRED1 variants causing Legius syndrome and underscore the importance of comprehensively characterizing the genetic landscape of this disorder. Despite the absence of clear genotype-phenotype correlations, elucidating the genetic etiology of Legius syndrome is pertinent for facilitating accurate diagnosis, genetic counseling, and therapeutic interventions.

Novel liquid biopsy CNV biomarkers in malignant melanoma

Malignant melanoma (MM) is known for its abundance of genetic alterations and a tendency for rapid metastasizing. Identification of novel plasma biomarkers may enhance non-invasive diagnostics and disease monitoring. Initially, we examined copy number variations (CNV) in CDK genes (CDKN2A, CDKN2B, CDK4) using MLPA (gDNA) and ddPCR (ctDNA) analysis. Subsequently, low-coverage whole genome sequencing (lcWGS) was used to identify the most common CNV in plasma samples, followed by ddPCR verification of chosen biomarkers. CNV alterations in CDK genes were identified in 33.3% of FFPE samples (Clark IV, V only). Detection of the same genes in MM plasma showed no significance, neither compared to healthy plasmas nor between pre- versus post-surgery plasma. Sequencing data showed the most common CNV occurring in 6q27, 4p16.1, 10p15.3, 10q22.3, 13q34, 18q23, 20q11.21-q13.12 and 22q13.33. CNV in four chosen genes (KIF25, E2F1, DIP2C and TFG) were verified by ddPCR using 2 models of interpretation. Model 1 was concordant with lcWGS results in 54% of samples, for model 2 it was 46%. Although CDK genes have not been proven to be suitable CNV liquid biopsy biomarkers, lcWGS defined the most frequently affected chromosomal regions by CNV. Among chosen genes, DIP2C demonstrated a potential for further analysis.

The Present and Future Landscapes of Molecular Diagnostics

Nucleic acid testing is the cornerstone of modern molecular diagnostics. This review describes the current status and future directions of molecular diagnostics, focusing on four major techniques: polymerase chain reaction (PCR), next-generation sequencing (NGS), isothermal amplification methods such as recombinase polymerase amplification (RPA) and loop-mediated isothermal amplification (LAMP), and clustered regularly interspaced short palindromic repeats (CRISPR)-based detection methods. We explore the advantages and limitations of each technique, describe how each overlaps with or complements other techniques, and examine current clinical offerings. This review provides a broad perspective into the landscape of molecular diagnostics and highlights potential future directions in this rapidly evolving field.

Copy number variant detection using next-generation sequencing in EYS-associated retinitis pigmentosa

Retinitis pigmentosa (RP) is the most common inherited retinal dystrophy and a major cause of blindness. RP is caused by several variants of multiple genes, and genetic diagnosis by identifying these variants is important for optimizing treatment and estimating patient prognosis. Next-generation sequencing (NGS), which is currently widely used for diagnosis, is considered useful but is known to have limitations in detecting copy number variations (CNVs). In this study, we re-evaluated CNVs in EYS, the main causative gene of RP, identified via NGS using multiplex ligation-dependent probe amplification (MLPA). CNVs were identified in NGS samples of eight patients. To identify potential CNVs, MLPA was also performed on samples from 42 patients who were undiagnosed by NGS but carried one of the five major pathogenic variants reported in Japanese EYS-RP cases. All suspected CNVs based on NGS data in the eight patients were confirmed via MLPA. CNVs were found in 2 of the 42 NGS-undiagnosed RP cases. Furthermore, results showed that 121 of the 661 patients with RP had EYS as the causative gene, and 8.3% (10/121 patients with EYS-RP) had CNVs. Although NGS using the CNV calling criteria utilized in this study failed to identify CNVs in two cases, no false-positive results were detected. Collectively, these findings suggest that NGS is useful for CNV detection during clinical diagnosis of RP.

Comparison of exon-level copy number variants in CytoScan XON assay and next-generation sequencing in clinical samples

BACKGROUND AND AIMS

Next-generation sequencing (NGS)-based copy number variants (CNVs) have high false-positive rates. The fewer the exons involved, the higher the false-positive rate. A CytoScan XON assay was developed to assess exon-level CNVs.

MATERIALS AND METHODS

Twenty-three clinically relevant exon-level CNVs in 20 patient blood samples found in previous NGS studies were compared with the results from the CytoScan XON and multiplex ligation-dependent probe amplification (MLPA).

RESULTS

Fifteen of the 23 exon-level CNVs were consistent with the NGS results. Among these, eight were confirmed using MLPA. In six out of eight discrepancies between the CytoScan Xon and NGS, MLPA was performed, and three were negative, indicating that the CNVs in NGS were false positives. The CytoScan XON exhibits a sensitivity of 72.7% for small exon-level CNVs, along with a specificity of 100%. The assay could not detect the three exon-level CNVs in PKD1 and TSC2 that were detected using both NGS and MLPA. This could be due to the distribution of the probes in some areas, and the CNV-calling regions containing multiple exons.

CONCLUSION

The CytoScan XON assay is a promising complementary tool for the detection of exon-level CNVs, provided that the users carefully examine the distribution of probes and calling regions.

Whole genome sequencing for copy number variant detection to improve diagnosis and management of rare diseases

First-line genetic investigations for rare neurological and developmental conditions have limitations in their ability to detect and characterize copy number variants (CNVs). Whole genome sequencing (WGS) offers potential advantages over other methods of CNV analysis. We aimed to demonstrate the utility of CNV detection using WGS through description of three clinical cases. WGS analysis was undertaken in three patients presenting to a national rare disease service, in whom a genetic aetiology remained uncertain after gene panel testing or microarray based comparative genomic hybridization (array CGH). In all three cases, WGS identified CNVs and confirmed zygosity and pathogenicity, resulting in genetic diagnoses of PRKN-related Parkinson disease, TAOK1-related neurodevelopmental disorder, and AP1G1-related Usmani-Riazuddin syndrome. This case series demonstrates the value of WGS analysis in identifying or better characterizing CNVs that were missed or deemed of uncertain significance using conventional methods of testing. Importantly, our approach facilitated accurate genetic diagnosis and counselling for the families involved.

The expanding diagnostic toolbox for rare genetic diseases

Genomic technologies, such as targeted, exome and short-read genome sequencing approaches, have revolutionized the care of patients with rare genetic diseases. However, more than half of patients remain without a diagnosis. Emerging approaches from research-based settings such as long-read genome sequencing and optical genome mapping hold promise for improving the identification of disease-causal genetic variants. In addition, new omic technologies that measure the transcriptome, epigenome, proteome or metabolome are showing great potential for variant interpretation. As genetic testing options rapidly expand, the clinical community needs to be mindful of their individual strengths and limitations, as well as remaining challenges, to select the appropriate diagnostic test, correctly interpret results and drive innovation to address insufficiencies. If used effectively - through truly integrative multi-omics approaches and data sharing - the resulting large quantities of data from these established and emerging technologies will greatly improve the interpretative power of genetic and genomic diagnostics for rare diseases.

Familial chylomicronemia syndrome: case reports of siblings with deletions of the GPIHBP1 gene

BACKGROUND

Familial chylomicronemia syndrome (FCS) is a rare monogenic form of severe hypertriglyceridemia, caused by mutations in genes involved in triglyceride metabolism. Herein, we report the case of a Korean family with familial chylomicronemia syndrome caused by compound heterozygous deletions of glycosylphosphatidylinositol-anchored high-density lipoprotein-binding protein 1 (GPIHBP1).

CASE PRESENTATION

A 4-year-old boy was referred for the evaluation of severe hypertriglyceridemia (3734 mg/dL) that was incidentally detected 4 months prior. His elder brother also demonstrated an elevated triglyceride level of 2133 mg/dL at the age of 9. Lipoprotein electrophoresis revealed the presence of chylomicrons, an increase in the proportion of pre-beta lipoproteins, and low serum lipoprotein lipase levels. The patient's parents and first elder brother had stable lipid profiles. For suspected FCS, genetic testing was performed using the next-generation sequencing-based analysis of 31 lipid metabolism-associated genes, which revealed no pathogenic variants. However, copy number variant screening using sequencing depth information suggested large heterozygous deletion encompassing all the coding exons of GPIHBP1. A real-time quantitative polymerase chain reaction was performed to validate the deletion site. The results showed that the siblings had two heterozygous copy number variants consisting of the whole gene and an exon 4 deletion, each inherited from their parents. During the follow-up period of 17 months, the patient did not develop pancreatitis, following dietary intervention.

CONCLUSION

These siblings' case of familial chylomicronemia syndrome caused by rare GPIHBP1 deletions highlight the implementation of copy number variants-beyond next-generation sequencing-as an important consideration in diagnosis. Accurate genetic diagnosis is necessary to establish the etiology of severe hypertriglyceridemia, which increases the risk of pancreatitis.

Advancements and progress in juvenile idiopathic arthritis: A Review of pathophysiology and treatment

Juvenile idiopathic arthritis (JIA) is a chronic clinical condition characterized by arthritic features in children under the age of 16, with at least 6 weeks of active symptoms. The etiology of JIA remains unknown, and it is associated with prolonged synovial inflammation and structural joint damage influenced by environmental and genetic factors. This review aims to enhance the understanding of JIA by comprehensively analyzing relevant literature. The focus lies on current diagnostic and therapeutic approaches and investigations into the pathoaetiologies using diverse research modalities, including in vivo animal models and large-scale genome-wide studies. We aim to elucidate the multifactorial nature of JIA with a strong focus towards genetic predilection, while proposing potential strategies to improve therapeutic outcomes and enhance diagnostic risk stratification in light of recent advancements. This review underscores the need for further research due to the idiopathic nature of JIA, its heterogeneous phenotype, and the challenges associated with biomarkers and diagnostic criteria. Ultimately, this contribution seeks to advance the knowledge and promote effective management strategies in JIA.

Developmental perspectives on the origins of psychotic disorders: The need for a transdiagnostic approach

Research on serious mental disorders, particularly psychosis, has revealed highly variable symptom profiles and developmental trajectories prior to illness-onset. As Dante Cicchetti pointed out decades before the term "transdiagnostic" was widely used, the pathways to psychopathology emerge in a system involving equifinality and multifinality. Like most other psychological disorders, psychosis is associated with multiple domains of risk factors, both genetic and environmental, and there are many transdiagnostic developmental pathways that can lead to psychotic syndromes. In this article, we discuss our current understanding of heterogeneity in the etiology of psychosis and its implications for approaches to conceptualizing etiology and research. We highlight the need for examining risk factors at multiple levels and to increase the emphasis on transdiagnostic developmental trajectories as a key variable associated with etiologic subtypes. This will be increasingly feasible now that large, longitudinal datasets are becoming available and researchers have access to more sophisticated analytic tools, such as machine learning, which can identify more homogenous subtypes with the ultimate goal of enhancing options for treatment and preventive intervention.

An overview of actionable and potentially actionable TSC1 and TSC2 germline variants in an online Database

Tuberous Sclerosis Complex (TSC) is caused by loss of function germline variants in the TSC1 or TSC2 tumor suppressor genes. Genetic testing for the detection of pathogenic variants in either TSC1 or TSC2 was implemented as a diagnostic criterion for TSC. However, TSC molecular diagnosis can be challenging due to the absence of variant hotspots and the high number of variants described. This review aimed to perform an overview of TSC1/2 variants submitted in the ClinVar database. Variants of uncertain significance (VUS), missense and single nucleotide variants were the most frequent in clinical significance (37-40%), molecular consequence (37%-39%) and variation type (82%-83%) categories in ClinVar in TSC1 and TSC2 variants, respectively. Frameshift and nonsense VUS have potential for pathogenic reclassification if further functional and segregation studies were performed. Indeed, there were few functional assays deposited in the database and literature. In addition, we did not observe hotspots for variation and many variants presented conflicting submissions regarding clinical significance. This study underscored the importance of disseminating molecular diagnostic results in a public database to render the information largely accessible and promote accurate diagnosis. We encourage the performance of functional studies evaluating the pathogenicity of TSC1/2 variants.

Genomic technologies for detecting structural variations in hematologic malignancies

Genomic structural variations in myeloid, lymphoid, and plasma cell neoplasms can provide key diagnostic, prognostic, and therapeutic information while elucidating the underlying disease biology. Several molecular diagnostic approaches play a central role in evaluating hematological malignancies. Traditional cytogenetic diagnostic assays, such as chromosome banding and fluorescence in situ hybridization, are essential components of the current diagnostic workup that guide clinical care for most hematologic malignancies. However, each assay has inherent limitations, including limited resolution for detecting small structural variations and low coverage, and can only detect alterations in the target regions. Recently, the rapid expansion and increasing availability of novel and comprehensive genomic technologies have led to their use in clinical laboratories for clinical management and translational research. This review aims to describe the clinical relevance of structural variations in hematologic malignancies and introduce genomic technologies that may facilitate personalized tumor characterization and treatment.

Detection of PTCH1 Copy-Number Variants in Mosaic Basal Cell Nevus Syndrome

Basal cell nevus syndrome (BCNS) is an inherited disorder characterized mainly by the development of basal cell carcinomas (BCCs) at an early age. BCNS is caused by heterozygous small-nucleotide variants (SNVs) and copy-number variants (CNVs) in the Patched1 (PTCH1) gene. Genetic diagnosis may be complicated in mosaic BCNS patients, as accurate SNV and CNV analysis requires high-sensitivity methods due to possible low variant allele frequencies. We compared test outcomes for PTCH1 CNV detection using multiplex ligation-probe amplification (MLPA) and digital droplet PCR (ddPCR) with samples from a BCNS patient heterozygous for a PTCH1 CNV duplication and the patient's father, suspected to have a mosaic form of BCNS. ddPCR detected a significantly increased PTCH1 copy-number ratio in the index patient's blood, and the father's blood and tissues, indicating that the father was postzygotic mosaic and the index patient inherited the CNV from him. MLPA only detected the PTCH1 duplication in the index patient's blood and in hair and saliva from the mosaic father. Our data indicate that ddPCR more accurately detects CNVs, even in low-grade mosaic BCNS patients, which may be missed by MLPA. In general, quantitative ddPCR can be of added value in the genetic diagnosis of mosaic BCNS patients and in estimating the recurrence risk for offspring.

On the core segmentation algorithms of copy number variation detection tools

Shotgun sequencing is a high-throughput method used to detect copy number variants (CNVs). Although there are numerous CNV detection tools based on shotgun sequencing, their quality varies significantly, leading to performance discrepancies. Therefore, we conducted a comprehensive analysis of next-generation sequencing-based CNV detection tools over the past decade. Our findings revealed that the majority of mainstream tools employ similar detection rationale: calculates the so-called read depth signal from aligned sequencing reads and then segments the signal by utilizing either circular binary segmentation (CBS) or hidden Markov model (HMM). Hence, we compared the performance of those two core segmentation algorithms in CNV detection, considering varying sequencing depths, segment lengths and complex types of CNVs. To ensure a fair comparison, we designed a parametrical model using mainstream statistical distributions, which allows for pre-excluding bias correction such as guanine-cytosine (GC) content during the preprocessing step. The results indicate the following key points: (1) Under ideal conditions, CBS demonstrates high precision, while HMM exhibits a high recall rate. (2) For practical conditions, HMM is advantageous at lower sequencing depths, while CBS is more competitive in detecting small variant segments compared to HMM. (3) In case involving complex CNVs resembling real sequencing, HMM demonstrates more robustness compared with CBS. (4) When facing large-scale sequencing data, HMM costs less time compared with the CBS, while their memory usage is approximately equal. This can provide an important guidance and reference for researchers to develop new tools for CNV detection.

Application of a Multiplex Ligation-Dependent Probe Amplification-Based Next-Generation Sequencing Approach for the Detection of Pathogenesis of Duchenne Muscular Dystrophy and Spinal Muscular Atrophy Caused by Copy Number Aberrations

Both Duchenne muscular dystrophy (DMD; OMIM no. 310200) and spinal muscular atrophy (SMA; OMIM no. 253300/253550/253400/271150) are genetic disorders characterized by progressive muscle degeneration and weakness. Genetic copy number aberrations in the pathogenetic genes DMD and SMN1 lead to alterations in functional proteins, resulting in DMD and SMA, respectively. Multiplex ligation-dependent probe amplification (MLPA) has become a standard method for the detection of common copy number aberrations (CNAs), including DMD and SMN1 deletions, both of which are associated with poor clinical outcomes. However, traditional MLPA assays only accommodate a maximum of 60 MLPA probes per test. To increase the number of targeted sequences in one assay, an MLPA-based next-generation sequencing (NGS) assay has been developed that is based on the standard MLPA procedure, allows high-throughput screening for a large number of fragments and samples by integrating additional indices for detection, and can be analyzed on all Illumina NGS platforms.

Copy Number Variations in Pancreatic Cancer: From Biological Significance to Clinical Utility

Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic cancer, characterized by high tumor heterogeneity and a poor prognosis. Inter- and intra-tumoral heterogeneity in PDAC is a major obstacle to effective PDAC treatment; therefore, it is highly desirable to explore the tumor heterogeneity and underlying mechanisms for the improvement of PDAC prognosis. Gene copy number variations (CNVs) are increasingly recognized as a common and heritable source of inter-individual variation in genomic sequence. In this review, we outline the origin, main characteristics, and pathological aspects of CNVs. We then describe the occurrence of CNVs in PDAC, including those that have been clearly shown to have a pathogenic role, and further highlight some key examples of their involvement in tumor development and progression. The ability to efficiently identify and analyze CNVs in tumor samples is important to support translational research and foster precision oncology, as copy number variants can be utilized to guide clinical decisions. We provide insights into understanding the CNV landscapes and the role of both somatic and germline CNVs in PDAC, which could lead to significant advances in diagnosis, prognosis, and treatment. Although there has been significant progress in this field, understanding the full contribution of CNVs to the genetic basis of PDAC will require further research, with more accurate CNV assays such as single-cell techniques and larger cohorts than have been performed to date.

BRACNAC: A BRCA1 and BRCA2 Copy Number Alteration Caller from Next-Generation Sequencing Data

Detecting copy number variations (CNVs) and alterations (CNAs) in the BRCA1 and BRCA2 genes is essential for testing patients for targeted therapy applicability. However, the available bioinformatics tools were initially designed for identifying CNVs/CNAs in whole-genome or -exome (WES) NGS data or targeted NGS data without adaptation to the BRCA1/2 genes. Most of these tools were tested on sample cohorts of limited size, with their use restricted to specific library preparation kits or sequencing platforms. We developed BRACNAC, a new tool for detecting CNVs and CNAs in the BRCA1 and BRCA2 genes in NGS data of different origin. The underlying mechanism of this tool involves various coverage normalization steps complemented by CNV probability evaluation. We estimated the sensitivity and specificity of our tool to be 100% and 94%, respectively, with an area under the curve (AUC) of 94%. The estimation was performed using the NGS data obtained from 213 ovarian and prostate cancer samples tested with in-house and commercially available library preparation kits and additionally using multiplex ligation-dependent probe amplification (MLPA) (12 CNV-positive samples). Using freely available WES and targeted NGS data from other research groups, we demonstrated that BRACNAC could also be used for these two types of data, with an AUC of up to 99.9%. In addition, we determined the limitations of the tool in terms of the minimum number of samples per NGS run (≥20 samples) and the minimum expected percentage of CNV-negative samples (≥80%). We expect that our findings will improve the efficacy of BRCA1/2 diagnostics. BRACNAC is freely available at the GitHub server.

Co-Occurrence of Germline Genomic Variants and Copy Number Variations in Hereditary Breast and Colorectal Cancer Patients

Hereditary Breast and Ovarian Cancer (HBOC) syndrome is an autosomal dominant disease associated with a high risk of developing breast, ovarian, and other malignancies. Lynch syndrome is caused by mutations in mismatch repair genes predisposing to colorectal and endometrial cancers, among others. A rare phenotype overlapping hereditary colorectal and breast cancer syndromes is poorly characterized. Three breast and colorectal cancer unrelated patients fulfilling clinical criteria for HBOC were tested by whole exome sequencing. A family history of colorectal cancer was reported in two patients (cases 2 and 3). Several variants and copy number variations were identified, which potentially contribute to the cancer risk or prognosis. All patients presented copy number imbalances encompassing PMS2 (two deletions and one duplication), a known gene involved in the DNA mismatch repair pathway. Two patients showed gains covering the POLE2 (cases 1 and 3), which is associated with DNA replication. Germline potentially damaging variants were found in PTCH1 (patient 3), MAT1A, and WRN (patient 2). Overall, concurrent genomic alterations were described that may increase the risk of cancer appearance in HBOC patients with breast and colorectal cancers.

De Novo Large Deletions in the PHEX Gene Caused X-Linked Hypophosphataemic Rickets in Two Italian Female Infants Successfully Treated with Burosumab

Pathogenic variants in the PHEX gene cause rare and severe X-linked dominant hypophosphataemia (XLH), a form of heritable hypophosphatemic rickets (HR) characterized by renal phosphate wasting and elevated fibroblast growth factor 23 (FGF23) levels. Burosumab, the approved human monoclonal anti-FGF23 antibody, is the treatment of choice for XLH. The genetic and phenotypic heterogeneity of HR often delays XLH diagnoses, with critical effects on disease course and therapy. We herein report the clinical and genetic features of two Italian female infants with sporadic HR who successfully responded to burosumab. Their diagnoses were based on clinical and laboratory findings and physical examinations. Next-generation sequencing (NGS) of the genes associated with inherited HR and multiple ligation probe amplification (MLPA) analysis of the PHEX and FGF23 genes were performed. While a conventional analysis of the NGS data did not reveal pathogenic or likely pathogenic small nucleotide variants (SNVs) in the known HR-related genes, a quantitative analysis identified two different heterozygous de novo large intragenic deletions in PHEX, and this was confirmed by MLPA. Our molecular data indicated that deletions in the PHEX gene can be the cause of a significant fraction of XLH; hence, their presence should be evaluated in SNV-negative female patients. Our patients successfully responded to burosumab, demonstrating the efficacy of this drug in the treatment of XLH. In conclusion, the execution of a phenotype-oriented genetic test, guided by known types of variants, including the rarest ones, was crucial to reach the definitive diagnoses and ensure our patients of long-term therapy administration.

Detection of germline variants with pathogenic potential in 48 patients with familial colorectal cancer by using whole exome sequencing

BACKGROUND

Hereditary genetic mutations causing predisposition to colorectal cancer are accountable for approximately 30% of all colorectal cancer cases. However, only a small fraction of these are high penetrant mutations occurring in DNA mismatch repair genes, causing one of several types of familial colorectal cancer (CRC) syndromes. Most of the mutations are low-penetrant variants, contributing to an increased risk of familial colorectal cancer, and they are often found in additional genes and pathways not previously associated with CRC. The aim of this study was to identify such variants, both high-penetrant and low-penetrant ones.

METHODS

We performed whole exome sequencing on constitutional DNA extracted from blood of 48 patients suspected of familial colorectal cancer and used multiple in silico prediction tools and available literature-based evidence to detect and investigate genetic variants.

RESULTS

We identified several causative and some potentially causative germline variants in genes known for their association with colorectal cancer. In addition, we identified several variants in genes not typically included in relevant gene panels for colorectal cancer, including CFTR, PABPC1 and TYRO3, which may be associated with an increased risk for cancer.

CONCLUSIONS

Identification of variants in additional genes that potentially can be associated with familial colorectal cancer indicates a larger genetic spectrum of this disease, not limited only to mismatch repair genes. Usage of multiple in silico tools based on different methods and combined through a consensus approach increases the sensitivity of predictions and narrows down a large list of variants to the ones that are most likely to be significant.

Systematic assessment of the contribution of structural variants to inherited retinal diseases

Despite increasing success in determining genetic diagnosis for patients with inherited retinal diseases (IRDs), mutations in about 30% of the IRD cases remain unclear or unsettled after targeted gene panel or whole exome sequencing. In this study, we aimed to investigate the contributions of structural variants (SVs) to settling the molecular diagnosis of IRD with whole-genome sequencing (WGS). A cohort of 755 IRD patients whose pathogenic mutations remain undefined were subjected to WGS. Four SV calling algorithms including include MANTA, DELLY, LUMPY and CNVnator were used to detect SVs throughout the genome. All SVs identified by any one of these four algorithms were included for further analysis. AnnotSV was used to annotate these SVs. SVs that overlap with known IRD-associated genes were examined with sequencing coverage, junction reads and discordant read pairs. Polymerase Chain Reaction (PCR) followed by Sanger sequencing was used to further confirm the SVs and identify the breakpoints. Segregation of the candidate pathogenic alleles with the disease was performed when possible. A total of 16 candidate pathogenic SVs were identified in 16 families, including deletions and inversions, representing 2.1% of patients with previously unsolved IRDs. Autosomal dominant, autosomal recessive and X-linked inheritance of disease-causing SVs were observed in 12 different genes. Among these, SVs in CLN3, EYS and PRPF31 were found in multiple families. Our study suggests that the contribution of SVs detected by short-read WGS is about 0.25% of our IRD patient cohort and is significantly lower than that of single nucleotide changes and small insertions and deletions.

[An analysis of the relationship between genetic factors and the risk of schizophrenia]

The etiology and pathogenesis of schizophrenia remain poorly understood, but it has been established that the contribution of heredity to the development of the disease is about 80-85%. Over the past decade, significant progress has been made in the search for specific genetic variants associated with the development of schizophrenia. The review discusses the results of modern large-scale studies aimed at searching for genetic associations with schizophrenia: genome-wide association studies (GWAS) and the search for rare variants (mutations or copy number variations, CNV), including the use of whole exome sequencing. We synthesize data on currently known genes that are significantly associated with schizophrenia and discuss their biological functions in order to identify the main molecular pathways involved in the pathophysiology of schizophrenia.

Copy Number Variant Analysis of Spinocerebellar Ataxia Genes in a Cohort of Dutch Patients With Cerebellar Ataxia

Background and Objectives

The spinocerebellar ataxias (SCAs) are a genetically heterogeneous group of neurodegenerative disorders generally caused by single nucleotide variants (SNVs) or indels in coding regions or by repeat expansions in coding and noncoding regions of SCA genes. Copy number variants (CNVs) have now also been reported for 3 genes-ITPR1, FGF14, and SPTBN2-but not all SCA genes have been screened for CNVs as the underlying cause of the disease in patients. In this study, we aim to assess the prevalence of CNVs encompassing 36 known SCA genes.

Methods

A cohort of patients with cerebellar ataxia who were referred to the University Medical Center Groningen for SCA genetic diagnostics was selected for this study. Genome-wide single nucleotide polymorphism (SNP) genotyping was performed using the Infinium Global Screening Array. Following data processing, genotyping data were uploaded into NxClinical software to perform CNV analysis per patient and to visualize identified CNVs in 36 genes with allocated SCA symbols. The clinical relevance of detected CNVs was determined using evidence from studies based on PubMed literature searches for similar CNVs and phenotypic features.

Results

Of the 338 patients with cerebellar ataxia, we identified putative clinically relevant CNV deletions in 3 patients: an identical deletion encompassing ITPR1 in 2 patients, who turned out to be related, and a deletion involving PPP2R2B in another patient. Although the CNV deletion in ITPR1 was clearly the underlying cause of SCA15 in the 2 related patients, the clinical significance of the deletion in PPP2R2B remained unknown.

Discussion

We showed that CNVs detectable with the limited resolution of SNP array are a very rare cause of SCA. Nevertheless, we suggest adding CNV analysis alongside SNV analysis to SCA gene diagnostics using next-generation sequencing approaches, at least for ITPR1, to improve the genetic diagnostics for patients.

Systematic assessment of the contribution of structural variants to inherited retinal diseases

Despite increasing success in determining genetic diagnosis for patients with inherited retinal diseases (IRDs), mutations in about 30% of the IRD cases remain unclear or unsettled after targeted gene panel or whole exome sequencing. In this study, we aimed to investigate the contributions of structural variants (SVs) to settling the molecular diagnosis of IRD with whole-genome sequencing (WGS). A cohort of 755 IRD patients whose pathogenic mutations remain undefined was subjected to WGS. Four SV calling algorithms including include MANTA, DELLY, LUMPY, and CNVnator were used to detect SVs throughout the genome. All SVs identified by any one of these four algorithms were included for further analysis. AnnotSV was used to annotate these SVs. SVs that overlap with known IRD-associated genes were examined with sequencing coverage, junction reads, and discordant read pairs. PCR followed by Sanger sequencing was used to further confirm the SVs and identify the breakpoints. Segregation of the candidate pathogenic alleles with the disease was performed when possible. In total, sixteen candidate pathogenic SVs were identified in sixteen families, including deletions and inversions, representing 2.1% of patients with previously unsolved IRDs. Autosomal dominant, autosomal recessive, and X-linked inheritance of disease-causing SVs were observed in 12 different genes. Among these, SVs in CLN3, EYS, PRPF31 were found in multiple families. Our study suggests that the contribution of SVs detected by short-read WGS is about 0.25% of our IRD patient cohort and is significantly lower than that of single nucleotide changes and small insertions and deletions.

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.

Identification of New Copy Number Variation and the Evaluation of a CNV Detection Tool for NGS Panel Data in Polish Familial Hypercholesterolemia Patients

Familial hypercholesterolemia (FH) is an inherited, autosomal dominant metabolic disorder mostly associated with disease-causing variant in LDLR, APOB or PCSK9. Although the dominant changes are small-scale missense, frameshift and splicing variants, approximately 10% of molecularly defined FH cases are due to copy number variations (CNVs). The first-line strategy is to identify possible pathogenic SNVs (single nucleotide variants) using multiple PCR, Sanger sequencing, or with more comprehensive approaches, such as NGS (next-generation sequencing), WES (whole-exome sequencing) or WGS (whole-genome sequencing). The gold standard for CNV detection in genetic diagnostics are MLPA (multiplex ligation-dependent amplification) or aCGH (array-based comparative genome hybridization). However, faster and simpler analyses are needed. Therefore, it has been proposed that NGS data can be searched to analyze CNV variants. The aim of the study was to identify novel CNV changes in FH patients without detected pathogenic SNVs using targeted sequencing and evaluation of CNV calling tool (DECoN) working on gene panel NGS data; the study also assesses its suitability as a screening step in genetic diagnostics. A group of 136 adult and child patients were recruited for the present study. The inclusion criteria comprised at least “possible FH” according to the Simon Broome diagnostic criteria in children and the DLCN (Dutch Lipid Clinical Network) criteria in adults. NGS analysis revealed potentially pathogenic SNVs in 57 patients. Thirty selected patients without a positive finding from NGS were subjected to MLPA analysis; ten of these revealed possibly pathogenic CNVs. Nine patients were found to harbor exons 4−8 duplication, two harbored exons 6−8 deletion and one demonstrated exon 9−10 deletion in LDLR. To test the DECoN program, the whole study group was referred for bioinformatic analysis. The DECoN program detected duplication of exons 4−8 in the LDLR gene in two patients, whose genetic analysis was stopped after the NGS step. The integration of the two methods proved to be particularly valuable in a five-year-old girl presenting with extreme hypercholesterolemia, with both a pathogenic missense variant (c.1747C>T) and exons 9−10 deletion in LDLR. This is the first report of a heterozygous deletion of exons 9 and 10 co-occurring with SNV. Our results suggest that the NGS-based approach has the potential to identify large-scale variation in the LDLR gene and could be further applied to extend CNV screening in other FH-related genes. Nevertheless, the outcomes from the bioinformatic approach still need to be confirmed by MLPA; hence, the latter remains the reference method for assessing CNV in FH patients.

Determining the Accuracy of Next Generation Sequencing Based Copy Number Variation Analysis in Hereditary Breast and Ovarian Cancer

BACKGROUND

Copy number variations (CNVs) are commonly associated with malignancies, including hereditary breast and ovarian cancers. Next generation sequencing (NGS) provides solutions for CNV detection in a single run. This study aimed to compare the accuracy of CNV detection by NGS analysing tool against Multiplex Ligation Dependent Probe Amplification (MLPA).

RESEARCH DESIGN AND METHODS

In total, 1276 cases were studied by targeted NGS panels and 691 cases (61 calls in 58 NGS-CNV positive and 633 NGS-CNV negative cases) were validated by MLPA.

RESULTS

Twenty-eight (46%) NGS-CNV positive calls were consistent, whereas 33 (54%) calls showed discordance with MLPA. Two cases were detected as SNV by the NGS and CNV by the MLPA analysis. In total, 2% of the cases showed an MLPA confirmed CNV region in BRCA1/2. The results of this study showed that despite the high false positive call rate of the NGS-CNV algorithm, there were no false negative calls. The cases that were determined to be negative by the NGS and positive by the MLPA were actually carrying SNVs that were located on the MLPA probe binding sites.

CONCLUSION

The diagnostic performance of NGS-CNV analysis is promising; however, the need for confirmation by different methods remains.

An Easy-to-Use Approach to Detect CNV From Targeted NGS Data: Identification of a Novel Pathogenic Variant in MO Disease

BACKGROUND

Despite the new next-generation sequencing (NGS) molecular approaches implemented the genetic testing in clinical diagnosis, copy number variation (CNV) detection from NGS data remains difficult mainly in the absence of bioinformatics personnel (not always available among laboratory resources) and when using very small gene panels that do not meet commercial software criteria. Furthermore, not all large deletions/duplications can be detected with the Multiplex Ligation-dependent Probe Amplification (MLPA) technique due to both the limitations of the methodology and no kits available for the most of genes.

AIM

We propose our experience regarding the identification of a novel large deletion in the context of a rare skeletal disease, multiple osteochondromas (MO), using and validating a user-friendly approach based on NGS coverage data, which does not require any dedicated software or specialized personnel.

METHODS

The pipeline uses a simple algorithm comparing the normalized coverage of each amplicon with the mean normalized coverage of the same amplicon in a group of "wild-type" samples representing the baseline. It has been validated on 11 samples, previously analyzed by MLPA, and then applied on 20 patients with MO but negative for the presence of pathogenic variants in EXT1 or EXT2 genes. Sensitivity, specificity, and accuracy were evaluated.

RESULTS

All the 11 known CNVs (exon and multi-exon deletions) have been detected with a sensitivity of 97.5%. A novel EXT2 partial exonic deletion c. (744-122)-?_804+?del -out of the MLPA target regions- has been identified. The variant was confirmed by real-time quantitative Polymerase Chain Reaction (qPCR).

CONCLUSION

In addition to enhancing the variant detection rate in MO molecular diagnosis, this easy-to-use approach for CNV detection can be easily extended to many other diagnostic fields-especially in resource-limited settings or very small gene panels. Notably, it also allows partial-exon deletion detection.