Detection of clinically relevant copy number variants with whole-exome sequencing

Multi-gene risk score for prediction of clinical outcomes in treatment-naïve metastatic castrate-resistant prostate cancer

BACKGROUND

To determine the performance of a multi-gene copy number variation (MG-CNV) risk score in metastatic tissue and plasma biospecimens from treatment-naïve metastatic castration-resistant prostate cancer (mCRPC) patients for prediction of clinical outcomes.

METHODS

The mCRPC tissue and plasma cell-free DNA (cfDNA) biospecimen sequencing results obtained from publicly accessed cohorts in dbGaP, cBioPortal, and an institutional mCRPC cohort were used to develop a MG-CNV risk score derived from gains in AR, MYC, COL22A1, PIK3CA, PIK3CB, NOTCH1 and losses in TMPRSS2, NCOR1, ZBTB16, TP53, NKX3-1 in independent cohorts for determining overall survival (OS), progression-free survival (PFS) to first-line androgen receptor pathway inhibitors (ARPIs). The range of the risk scores for each cohort was dichotomized into "high-risk" and "low-risk" groups and association with OS/PFS determined. Univariate and multivariable Cox proportional hazards regressions were applied for survival analyses (P < .05 for statistical significance).

RESULTS

Of 1137 metastatic tissue-plasma biospecimens across all cohorts, 699/1137 were treatment-naive mCRPC (235/699 metastatic tissue; 464/699 plasma-cfDNA), and 311/1137 were matched tissue-cfDNA pairs. In multivariable analysis, the MG-CNV risk score derived from metastatic tissue or in cfDNA was statistically significantly associated with OS with high score associated with short survival (hazard ratio = 2.65, confidence interval = 1.99 to 3.51; P = 1.35-11) and shorter PFS to ARPIs (median PFS of 7.8 months) compared with 14 months in patients with low-risk score.

CONCLUSIONS

A molecular risk score in treatment-naïve mCRPC state obtained either in metastatic tissue or cfDNA predicts clinical survival outcomes and offers a tumor biology-based tool to design biomarker-based enrichment clinical trials.

Identification of Pathogenic Copy Number Variants in Mexican Patients With Inherited Retinal Dystrophies Applying an Exome Sequencing Data-Based Read-Depth Approach

BACKGROUND

Retinal dystrophies (RDs) are the most common cause of inherited blindness worldwide and are caused by genetic defects in about 300 different genes. While targeted next-generation sequencing (NGS) has been demonstrated to be a reliable and efficient method to identify RD disease-causing variants, it doesn't routinely identify pathogenic structural variant as copy number variations (CNVs). Targeted NGS-based CNV detection has become a crucial step for RDs molecular diagnosis, particularly in cases without identified causative single nucleotide or Indels variants. Herein, we report the exome sequencing (ES) data-based read-depth bioinformatic analysis in a group of 30 unrelated Mexican RD patients with a negative or inconclusive genetic result after ES.

METHODS

CNV detection was performed using ExomeDepth software, an R package designed to detect CNVs using exome data. Bioinformatic validation of identified CNVs was conducted through a commercially available CNV caller. All identified candidate pathogenic CNVs were orthogonally verified through quantitative PCR assays.

RESULTS

Pathogenic or likely pathogenic CNVs were identified in 6 out of 30 cases (20%), and of them, a definitive molecular diagnosis was reached in 5 cases, for a final diagnostic rate of ~17%. CNV-carrying genes included CLN3 (2 cases), ABCA4 (novel deletion), EYS, and RPGRIP1.

CONCLUSIONS

Our results indicate that bioinformatic analysis of ES data is a reliable method for pathogenic CNV detection and that it should be incorporated in cases with a negative or inconclusive molecular result after ES.

High positive predictive value of CNVs detected by clinical exome sequencing in suspected genetic diseases

BACKGROUND

Genetic disorders often manifest as abnormal fetal or childhood development. Copy number variations (CNVs) represent a significant genetic mechanism underlying such disorders. Despite their importance, the effectiveness of clinical exome sequencing (CES) in detecting CNVs, particularly small ones, remains incompletely understood. We aimed to evaluate the detection of both large and small CNVs using CES in a substantial clinical cohort, including parent-offspring trios and proband only analysis.

METHODS

We conducted a retrospective analysis of CES data from 2428 families, collected from 2018 to 2021. Detected CNV were categorized as large or small, and various validation techniques including chromosome microarray (CMA), Multiplex ligation-dependent probe amplification assay (MLPA), and/or PCR-based methods, were employed for cross-validation.

RESULTS

Our CNV discovery pipeline identified 171 CNV events in 154 cases, resulting in an overall detection rate of 6.3%. Validation was performed on 113 CNVs from 103 cases to assess CES reliability. The overall concordance rate between CES and other validation methods was 88.49% (100/113). Specifically, CES demonstrated complete consistency in detecting large CNV. However, for small CNVs, consistency rates were 81.08% (30/37) for deletions and 73.91% (17/23) for duplications.

CONCLUSION

CES demonstrated high sensitivity and reliability in CNV detection. It emerges as an economical and dependable option for the clinical CNV detection in cases of developmental abnormalities, especially fetal structural abnormalities.

The copy number variant architecture of psychopathology and cognitive development in the ABCD® study

Importance

Childhood is a crucial developmental phase for mental health and cognitive function, both of which are commonly affected in patients with psychiatric disorders. This neurodevelopmental trajectory is shaped by a complex interplay of genetic and environmental factors. While common genetic variants account for a large proportion of inherited genetic risk, rare genetic variations, particularly copy number variants (CNVs), play a significant role in the genetic architecture of neurodevelopmental disorders. Despite their importance, the relevance of CNVs to child psychopathology and cognitive function in the general population remains underexplored.

Objective

Investigating CNV associations with dimensions of child psychopathology and cognitive functions.

Design Setting and Participants

ABCD® study focuses on a cohort of over 11,875 youth aged 9 to 10, recruited from 21 sites in the US, aiming to investigate the role of various factors, including brain, environment, and genetic factors, in the etiology of mental and physical health from middle childhood through early adulthood. Data analysis occurred from April 2023 to April 2024.

Main Outcomes and Measures

In this study, we utilized PennCNV and QuantiSNP algorithms to identify duplications and deletions larger than 50Kb across a cohort of 11,088 individuals from the Adolescent Brain Cognitive Development® study. CNVs meeting quality control standards were subjected to a genome-wide association scan to identify regions associated with quantitative measures of broad psychiatric symptom domains and cognitive outcomes. Additionally, a CNV risk score, reflecting the aggregated burden of genetic intolerance to inactivation and dosage sensitivity, was calculated to assess its impact on variability in overall and dimensional child psychiatric and cognitive phenotypes.

Results

In a final sample of 8,564 individuals (mean age=9.9 years, 4,532 males) passing quality control, we identified 4,111 individuals carrying 5,760 autosomal CNVs. Our results revealed significant associations between specific CNVs and our phenotypes of interest, psychopathology and cognitive function. For instance, a duplication at 10q26.3 was associated with overall psychopathology, and somatic complaints in particular. Additionally, deletions at 1q12.1, along with duplications at 14q11.2 and 10q26.3, were linked to overall cognitive function, with particular contributions from fluid intelligence (14q11.2), working memory (10q26.3), and reading ability (14q11.2). Moreover, individuals carrying CNVs previously associated with neurodevelopmental disorders exhibited greater impairment in social functioning and cognitive performance across multiple domains, in particular working memory. Notably, a higher deletion CNV risk score was significantly correlated with increased overall psychopathology (especially in dimensions of social functioning, thought disorder, and attention) as well as cognitive impairment across various domains.

Conclusions and Relevance

In summary, our findings shed light on the contributions of CNVs to interindividual variability in complex traits related to neurocognitive development and child psychopathology.

Deep learning in cancer genomics and histopathology

Histopathology and genomic profiling are cornerstones of precision oncology and are routinely obtained for patients with cancer. Traditionally, histopathology slides are manually reviewed by highly trained pathologists. Genomic data, on the other hand, is evaluated by engineered computational pipelines. In both applications, the advent of modern artificial intelligence methods, specifically machine learning (ML) and deep learning (DL), have opened up a fundamentally new way of extracting actionable insights from raw data, which could augment and potentially replace some aspects of traditional evaluation workflows. In this review, we summarize current and emerging applications of DL in histopathology and genomics, including basic diagnostic as well as advanced prognostic tasks. Based on a growing body of evidence, we suggest that DL could be the groundwork for a new kind of workflow in oncology and cancer research. However, we also point out that DL models can have biases and other flaws that users in healthcare and research need to know about, and we propose ways to address them.

Comparison of first-tier whole-exome sequencing with a multi-step traditional approach for diagnosing paediatric outpatients: An Italian prospective study

BACKGROUND

The recent guidelines suggest the use of genome-wide analyses, such as whole exome sequencing (WES), at the beginning of the diagnostic approach for cases with suspected genetic conditions. However, in many realities it still provides for the execution of a multi-step pathway, thus requiring several genetic tests to end the so-called 'diagnostic odyssey'.

METHODS

We reported the results of GENE Project (Genomic analysis Evaluation NEtwork): a multicentre prospective cohort study on 125 paediatric outpatients with a suspected genetic disease in which we performed first-tier trio-WES, including exome-based copy number variation analysis, in parallel to a 'traditional approach' of two/three sequential genetic tests.

RESULTS

First-tier trio-WES detected a conclusive diagnosis in 41.6% of patients, way above what was found with routine genetic testing (25%), with a time-to-result of about 50 days. Notably, the study showed that 44% of WES-reached diagnoses would be missed with the traditional approach. The diagnostic rate (DR) of the two approaches varied in relation to the phenotypic class of referral and to the proportion of cases with a defined diagnostic suspect, proving the major difference for neurodevelopmental disorders. Moreover, trio-WES analysis detected variants in candidate genes of unknown significance (EPHA4, DTNA, SYNCRIP, NCOR1, TFDP1, SPRED3, EDA2R, PHF12, PPP1R12A, WDR91, CDC42BPG, CSNK1D, EIF3H, TMEM63B, RIPPLY3) in 19.4% of undiagnosed cases.

CONCLUSION

Our findings represent real-practice evidence of how first-tier genome-wide sequencing tests significantly improve the DR for paediatric outpatients with a suspected underlying genetic aetiology, thereby allowing a time-saving setting of the correct management, follow-up and family planning.

Germline CNV Detection through Whole-Exome Sequencing (WES) Data Analysis Enhances Resolution of Rare Genetic Diseases

Whole-Exome Sequencing (WES) has proven valuable in the characterization of underlying genetic defects in most rare diseases (RDs). Copy Number Variants (CNVs) were initially thought to escape detection. Recent technological advances enabled CNV calling from WES data with the use of accurate and highly sensitive bioinformatic tools. Amongst 920 patients referred for WES, 454 unresolved cases were further analysed using the ExomeDepth algorithm. CNVs were called, evaluated and categorized according to ACMG/ClinGen recommendations. Causative CNVs were identified in 40 patients, increasing the diagnostic yield of WES from 50.7% (466/920) to 55% (506/920). Twenty-two CNVs were available for validation and were all confirmed; of these, five were novel. Implementation of the ExomeDepth tool promoted effective identification of phenotype-relevant and/or novel CNVs. Among the advantages of calling CNVs from WES data, characterization of complex genotypes comprising both CNVs and SNVs minimizes cost and time to final diagnosis, while allowing differentiation between true or false homozygosity, as well as compound heterozygosity of variants in AR genes. The use of a specific algorithm for calling CNVs from WES data enables ancillary detection of different types of causative genetic variants, making WES a critical first-tier diagnostic test for patients with RDs.

The exploration of genetic aetiology and diagnostic strategy for 321 Chinese individuals with intellectual disability

BACKGROUND

Intellectual disability is a heterogeneous neurodevelopmental disorder with complex genetic architectures. Different sequential methodologies are usually applied to identify the genetic aetiologies of ID patients.

METHODS

We collected 321 consecutive ID patients. All patients underwent karyotyping, while 293 and 164 cases further received copy number variation sequencing (CNV-seq) and whole-exome sequencing (WES). The updated WES technology can detect CNVs simultaneously. The diagnostic data from 137 patients who received WES and CNV-seq were used to define the approach that could be recommended as the first-tier test.

RESULTS

WES obtains the highest diagnostic yield of 50% (82/164), compared with karyotyping (7.79%, 25/321) and CNV-seq (19.80%, 58/293). Among the variants detected by WES, 66.67% (44/66) de novo and 57.58% (38/66) novel pathogenic/likely pathogenic (P/LP) variants were identified in patients with ID. Besides, 24 out of 25P/LP CNVs discovered by CNV-seq can also be accurately identified using WES in 137 patients who received WES and CNV-seq. Thus, genetic abnormalities found through karyotyping, CNV-seq, and WES can be completely detected by combined karyotyping and WES.

CONCLUSIONS

This study illustrates the genetic aberrations of a Chinese ID cohort and expands the mutation spectrum of ID-related genes. Compared with the conventional diagnostic strategy, a combination of karyotype analysis and WES could be recommended as the first-tier diagnostic strategy for ID patients.

Genomic testing for copy number and single nucleotide variants in spermatogenic failure

PURPOSE

To identify clinically significant genomic copy number (CNV) and single nucleotide variants (SNV) in males with unexplained spermatogenic failure (SPGF).

MATERIALS AND METHODS

Peripheral blood DNA from 97/102 study participants diagnosed with oligozoospermia, severe oligozoospermia, or non-obstructive azoospermia (NOA) was analyzed for CNVs via array comparative genomic hybridization (aCGH) and SNVs using whole-exome sequencing (WES).

RESULTS

Of the 2544 CNVs identified in individuals with SPGF, > 90% were small, ranging from 0.6 to 75 kb. Thirty, clinically relevant genomic aberrations, were detected in 28 patients (~ 29%). These included likely diagnostic CNVs in 3/41 NOA patients (~ 7%): 1 hemizygous, intragenic TEX11 deletion, 1 hemizygous DDX53 full gene deletion, and 1 homozygous, intragenic STK11 deletion. High-level mosaicism for X chromosome disomy (~ 10% 46,XY and ~ 90% 47,XXY) was also identified in 3 of 41 NOA patients who previously tested normal with conventional karyotyping. The remaining 24 CNVs detected were heterozygous, autosomal recessive carrier variants. Follow-up WES analysis confirmed 8 of 27 (30%) CNVs (X chromosome disomy excluded). WES analysis additionally identified 13 significant SNVs and/or indels in 9 patients (~ 9%) including X-linked AR, KAL1, and NR0B1 variants.

CONCLUSION

Using a combined genome-wide aCGH/WES approach, we identified pathogenic and likely pathogenic SNVs and CNVs in 15 patients (15%) with unexplained SPGF. This value equals the detection rate of conventional testing for aneuploidies and is considerably higher than the prevalence of Y chromosome microdeletions. Our results underscore the importance of comprehensive genomic analysis in emerging diagnostic testing of complex conditions like male infertility.

Algorithmic improvements for discovery of germline copy number variants in next-generation sequencing data

Background

Copy number variants (CNVs) play a significant role in human heredity and disease. However, sensitive and specific characterization of germline CNVs from NGS data has remained challenging, particularly for hybridization-capture data in which read counts are the primary source of copy number information.

Results

We describe two algorithmic adaptations that improve CNV detection accuracy in a Hidden Markov Model (HMM) context. First, we present a method for computing target- and copy number-specific emission distributions. Second, we demonstrate that the Pointwise Maximum a posteriori (PMAP) HMM decoding procedure yields improved sensitivity for small CNV calls compared to the more common Viterbi HMM decoder. We develop a prototype implementation, called Cobalt, and compare it to other CNV detection tools using sets of simulated and previously detected CNVs with sizes spanning a single exon to a full chromosome.

Conclusions

In both the simulation and previously detected CNV studies Cobalt shows similar sensitivity but significantly fewer false positive detections compared to other callers. Overall sensitivity is 80–90% for deletion CNVs spanning 1–4 targets and 90–100% for larger deletion events, while sensitivity is somewhat lower for small duplication CNVs.

How to proceed after "negative" exome: A review on genetic diagnostics, limitations, challenges, and emerging new multiomics techniques

Exome sequencing (ES) in the clinical setting of inborn metabolic diseases (IMDs) has created tremendous improvement in achieving an accurate and timely molecular diagnosis for a greater number of patients, but it still leaves the majority of patients without a diagnosis. In parallel, (personalized) treatment strategies are increasingly available, but this requires the availability of a molecular diagnosis. IMDs comprise an expanding field with the ongoing identification of novel disease genes and the recognition of multiple inheritance patterns, mosaicism, variable penetrance, and expressivity for known disease genes. The analysis of trio ES is preferred over singleton ES as information on the allelic origin (paternal, maternal, "de novo") reduces the number of variants that require interpretation. All ES data and interpretation strategies should be exploited including CNV and mitochondrial DNA analysis. The constant advancements in available techniques and knowledge necessitate the close exchange of clinicians and molecular geneticists about genotypes and phenotypes, as well as knowledge of the challenges and pitfalls of ES to initiate proper further diagnostic steps. Functional analyses (transcriptomics, proteomics, and metabolomics) can be applied to characterize and validate the impact of identified variants, or to guide the genomic search for a diagnosis in unsolved cases. Future diagnostic techniques (genome sequencing [GS], optical genome mapping, long-read sequencing, and epigenetic profiling) will further enhance the diagnostic yield. We provide an overview of the challenges and limitations inherent to ES followed by an outline of solutions and a clinical checklist, focused on establishing a diagnosis to eventually achieve (personalized) treatment.

Mechanisms of structural chromosomal rearrangement formation

Structural chromosomal rearrangements result from different mechanisms of formation, usually related to certain genomic architectural features that may lead to genetic instability. Most of these rearrangements arise from recombination, repair, or replication mechanisms that occur after a double-strand break or the stalling/breakage of a replication fork. Here, we review the mechanisms of formation of structural rearrangements, highlighting their main features and differences. The most important mechanisms of constitutional chromosomal alterations are discussed, including Non-Allelic Homologous Recombination (NAHR), Non-Homologous End-Joining (NHEJ), Fork Stalling and Template Switching (FoSTeS), and Microhomology-Mediated Break-Induced Replication (MMBIR). Their involvement in chromoanagenesis and in the formation of complex chromosomal rearrangements, inverted duplications associated with terminal deletions, and ring chromosomes is also outlined. We reinforce the importance of high-resolution analysis to determine the DNA sequence at, and near, their breakpoints in order to infer the mechanisms of formation of structural rearrangements and to reveal how cells respond to DNA damage and repair broken ends.

DECoN: A Detection and Visualization Tool for Exonic Copy Number Variants

Detection of copy number variants from targeted sequencing, including whole-exome sequencing, can be particularly difficult since the break points of the CNV are not always captured. Here we describe DECoN, a software tool which uses changes in read depth to identify CNVs that affect whole exons. It is optimized for clinical use and allows for interactive visualization of CNVs identified.

Technological Improvements in the Genetic Diagnosis of Rett Syndrome Spectrum Disorders

Rett syndrome (RTT) is a severe neurodevelopmental disorder that constitutes the second most common cause of intellectual disability in females worldwide. In the past few years, the advancements in genetic diagnosis brought by next generation sequencing (NGS), have made it possible to identify more than 90 causative genes for RTT and significantly overlapping phenotypes (RTT spectrum disorders). Therefore, the clinical entity known as RTT is evolving towards a spectrum of overlapping phenotypes with great genetic heterogeneity. Hence, simultaneous multiple gene testing and thorough phenotypic characterization are mandatory to achieve a fast and accurate genetic diagnosis. In this review, we revise the evolution of the diagnostic process of RTT spectrum disorders in the past decades, and we discuss the effectiveness of state-of-the-art genetic testing options, such as clinical exome sequencing and whole exome sequencing. Moreover, we introduce recent technological advancements that will very soon contribute to the increase in diagnostic yield in patients with RTT spectrum disorders. Techniques such as whole genome sequencing, integration of data from several “omics”, and mosaicism assessment will provide the tools for the detection and interpretation of genomic variants that will not only increase the diagnostic yield but also widen knowledge about the pathophysiology of these disorders.

Incorporation of exome-based CNV analysis makes trio-WES a more powerful tool for clinical diagnosis in neurodevelopmental disorders: A retrospective study

Neurodevelopmental disorders (NDDs) are a genetically heterogeneous group of diseases, affecting 1%-3% of children. Whole-exome sequencing (WES) has been widely used as a first-tier tool for identifying genetic causes of rare diseases. Trio-WES was performed in a cohort of 74 pedigrees with NDDs. Exome-based copy number variant (CNV) calling was incorporated into the traditional single-nucleotide variant (SNV) and small insertion/deletion (Indel) analysis pipeline for WES data. An overall positive diagnostic yield of 54.05% (40/74) was obtained in the pipeline of combinational SNV/Indel and CNV analysis, including 35.13% (26/74) from SNV/Indel analysis and 18.92% (14/74) from exome-based CNV analysis, respectively. In total, SNV/Indel analysis identified 38 variants in 28 different genes, of which 24 variants were novel; exome-based CNV analysis identified 14 CNVs, including 2 duplications and 12 deletions, which ranged from 440 bp (single exon) to 16.86 Mb (large fragment) in size. In particular, a hemizygous deletion of exon 1 in the SLC16A2 gene was detected. Based on the diagnostic results, two families underwent prenatal diagnosis and had unaffected babies. The incorporation of exome-based CNV detection into conventional SNV/Indel analysis for a single trio-WES test significantly improved the diagnostic rate, making WES a more powerful, practical, and cost-effective tool in the clinical diagnosis of NDDs.

Voltage-Gated Sodium Channel β1 Gene: An Overview

BACKGROUND

Voltage-gated sodium channels are protein complexes composed of 2 subunits, namely, pore-forming α- and regulatory β-subunits. A β-subunit consists of 5 proteins encoded by 4 genes (i.e., SCN1B-SCN4B).

SUMMARY

β1-Subunits regulate sodium ion channel functions, including gating properties, subcellular localization, and kinetics. Key Message: Sodium channel β1- and its variant β1B-subunits are encoded by SCN1B. These variants are associated with many human diseases, such as epilepsy, Brugada syndrome, Dravet syndrome, and cancers. On the basis of previous research, we aimed to provide an overview of the structure, expression, and involvement of SCN1B in physiological processes and focused on its role in diseases.

Detection of homozygous and hemizygous complete or partial exon deletions by whole-exome sequencing

The detection of copy number variations (CNVs) in whole-exome sequencing (WES) data is important, as CNVs may underlie a number of human genetic disorders. The recently developed HMZDelFinder algorithm can detect rare homozygous and hemizygous (HMZ) deletions in WES data more effectively than other widely used tools. Here, we present HMZDelFinder_opt, an approach that outperforms HMZDelFinder for the detection of HMZ deletions, including partial exon deletions in particular, in WES data from laboratory patient collections that were generated over time in different experimental conditions. We show that using an optimized reference control set of WES data, based on a PCA-derived Euclidean distance for coverage, strongly improves the detection of HMZ complete exon deletions both in real patients carrying validated disease-causing deletions and in simulated data. Furthermore, we develop a sliding window approach enabling HMZDelFinder_opt to identify HMZ partial deletions of exons that are undiscovered by HMZDelFinder. HMZDelFinder_opt is a timely and powerful approach for detecting HMZ deletions, particularly partial exon deletions, in WES data from inherently heterogeneous laboratory patient collections.

Clinically relevant copy-number variants in exome sequencing data of patients with dystonia

INTRODUCTION

Next-generation sequencing is now used on a routine basis for molecular testing but studies on copy-number variant (CNV) detection from next-generation sequencing data are underrepresented. Utilizing an existing whole-exome sequencing (WES) dataset, we sought to investigate the contribution of rare CNVs to the genetic causality of dystonia.

METHODS

The CNV read-depth analysis tool ExomeDepth was applied to the exome sequences of 953 unrelated patients with dystonia (600 with isolated dystonia and 353 with combined dystonia; 33% with additional neurological involvement). We prioritized rare CNVs that affected known disease genes and/or were known to be associated with defined microdeletion/microduplication syndromes. Pathogenicity assessment of CNVs was based on recently published standards of the American College of Medical Genetics and Genomics and the Clinical Genome Resource.

RESULTS

We identified pathogenic or likely pathogenic CNVs in 14 of 953 patients (1.5%). Of the 14 different CNVs, 12 were deletions and 2 were duplications, ranging in predicted size from 124bp to 17 Mb. Within the deletion intervals, BRPF1, CHD8, DJ1, EFTUD2, FGF14, GCH1, PANK2, SGCE, UBE3A, VPS16, WARS2, and WDR45 were determined as the most clinically relevant genes. The duplications involved chromosomal regions 6q21-q22 and 15q11-q13. CNV analysis increased the diagnostic yield in the total cohort from 18.4% to 19.8%, as compared to the assessment of single-nucleotide variants and small insertions and deletions alone.

CONCLUSIONS

WES-based CNV analysis in dystonia is feasible, increases the diagnostic yield, and should be combined with the assessment of single-nucleotide variants and small insertions and deletions.

A map of copy number variations in the Tunisian population: a valuable tool for medical genomics in North Africa

Copy number variation (CNV) is considered as the most frequent type of structural variation in the human genome. Some CNVs can act on human phenotype diversity, encompassing rare Mendelian diseases and genomic disorders. The North African populations remain underrepresented in public genetic databases in terms of single-nucleotide variants as well as for larger genomic mutations. In this study, we present the first CNV map for a North African population using the Affymetrix Genome-Wide SNP (single-nucleotide polymorphism) array 6.0 array genotyping intensity data to call CNVs in 102 Tunisian healthy individuals. Two softwares, PennCNV and Birdsuite, were used to call CNVs in order to provide reliable data. Subsequent bioinformatic analyses were performed to explore their features and patterns. The CNV map of the Tunisian population includes 1083 CNVs spanning 61.443 Mb of the genome. The CNV length ranged from 1.017 kb to 2.074 Mb with an average of 56.734 kb. Deletions represent 57.43% of the identified CNVs, while duplications and the mixed loci are less represented. One hundred and three genes disrupted by CNVs are reported to cause 155 Mendelian diseases/phenotypes. Drug response genes were also reported to be affected by CNVs. Data on genes overlapped by deletions and duplications segments and the sequence properties in and around them also provided insights into the functional and health impacts of CNVs. These findings represent valuable clues to genetic diversity and personalized medicine in the Tunisian population as well as in the ethnically similar populations from North Africa.

Genetic diagnoses in pediatric patients with epilepsy and comorbid intellectual disability

PURPOSE

The aim of this retrospective study is to investigate the genetic etiology and propose a diagnostic strategy for pediatric patients with epilepsy and comorbid intellectual disability (ID).

METHODS

From September 2014 to May 2020, a total of 102 pediatric patients diagnosed with epilepsy with co-morbid ID with unknown causes were included in this study. All patients underwent tests of single nucleotide polymorphism (SNP) array for chromosomal abnormalities. Whole exome sequencing (WES) was consecutively performed in patients without diagnostic copy number variants (CNVs) (n = 85) for single nucleotide variants (SNVs). Subgroup analyses based on the age of seizure onset and ID severity were done.

RESULTS

The overall diagnostic yield of genetic aberrations was 33.3 % (34/102), which comprised 50.0 % with diagnostic CNVs and 50.0 % with diagnostic SNVs. The yield nominally increased with ID severity and decreased with age of seizure onset, though this result was not statistically significant. The diagnostic yield of SNVs in patients with seizure onset in the first year of life (25.0 % (11/44)) was significantly higher than those with childhood-onset epilepsy (10.3 % (6/58)) (p = 0.049), however, the diagnostic yield of CNVs in patients with childhood-onset epilepsy (17.2 % (10/58) was higher than the diagnostic yield of SNVs (10.3 % (6/58)). The most frequently syndromic epilepsy detected by SNP array was Angelman syndrome (n=4), including one confirmed with paternal uniparental disomy. Meanwhile, the most frequent SNVs were mutations of MECP2 (n=2) and IQSEC2 (n = 2) in sporadic cases.

CONCLUSION

Both CMA and WES are advantageous as unbiased approaches for a genetically heterogeneous condition. We proposed an effective diagnostic strategy for pediatric patients with epilepsy. For patients with seizure onset in the first year of life, WES is recommended as the first-tier test. However, for patients with childhood-onset epilepsy, SNP array should be considered for the first-tier test.

Genetic testing in patients with nonsyndromic autism spectrum disorder and EEG abnormalities with or without epilepsy: Is exome trio-based testing the best clinical approach?

OBJECTIVES

The association between autism spectrum disorder (ASD) and epilepsy is well-known. Abnormalities on electroencephalography (EEG) studies have been reported in patients with ASD without a history of seizures, and these patients have lower functional scores on adaptive measures than patients with ASD with normal EEG studies. The purpose of the study was to evaluate the genetic test approach in children with ASD and abnormal EEGs.

METHODS

Data were collected from medical records at Cincinnati Children's Hospital Medical Center (CCHMC) of a previously published cohort of patients with well-characterized ASD based on evaluation by Developmental Pediatrics. Patients were subdivided into two groups: ASD without epilepsy, but with abnormal EEG results, and ASD with epilepsy. EEG data were abstracted from reports. In this follow-up study, we analyzed genetic testing data, namely the proportion of this cohort that received genetic testing, and the specific type of genetic testing that was ordered to analyze if there were any differences between groups.

RESULTS

Analysis was performed on 173 patients with ASD. Ninety-five patients had a diagnosis of epilepsy. Seventy-eight patients did not have a diagnosis of epilepsy but did have abnormal EEGs. In both groups, approximately three quarters of all subjects received routine neurodevelopmental genetic testing (77% versus 72% p = 0.15) without significant differences between groups. The ASD + epilepsy group was more likely to receive additional second-tier genetic testing outside of a routine neurodevelopmental workup (35% versus 15% p = 0.007). The ASD + epilepsy group was more likely to receive phenotype specific panels, most often an epilepsy gene panel of less than 250 genes (15% versus 3% p = 0.008). However, the ASD + epilepsy group was less likely to receive a genetic diagnosis from testing than the ASD + abnormal EEG group (9% versus 33%, p = 0.047).

CONCLUSIONS

Patients with ASD along with a formal epilepsy diagnosis received more genetic testing; but had an overall lower diagnostic rate than patients with ASD with abnormal EEGs but without a formal epilepsy diagnosis. Patients in this cohort without a diagnosis of epilepsy were more likely to get broad trio-based exome testing instead of targeted epilepsy gene panel testing. A higher diagnostic rate was found in patients when a broad genetic test strategy was implemented.

Simultaneous Detection of CNVs and SNVs Improves the Diagnostic Yield of Fetuses with Ultrasound Anomalies and Normal Karyotypes

The routine assessment to determine the genetic etiology for fetal ultrasound anomalies follows a sequential approach, which usually takes about 6–8 weeks turnaround time (TAT). We evaluated the clinical utility of simultaneous detection of copy number variations (CNVs) and single nucleotide variants (SNVs)/small insertion-deletions (indels) in fetuses with a normal karyotype with ultrasound anomalies. We performed CNV detection by chromosomal microarray analysis (CMA) or low pass CNV-sequencing (CNV-seq), and in parallel SNVs/indels detection by trio-based clinical exome sequencing (CES) or whole exome sequencing (WES). Eight-three singleton pregnancies with a normal fetal karyotype were enrolled in this prospective observational study. Pathogenic or likely pathogenic variations were identified in 30 cases (CNVs in 3 cases, SNVs/indels in 27 cases), indicating an overall molecular diagnostic rate of 36.1% (30/83). Two cases had both a CNV of uncertain significance (VOUS) and likely pathogenic SNV, and one case carried both a VOUS CNV and an SNV. We demonstrated that simultaneous analysis of CNVs and SNVs/indels can improve the diagnostic yield of prenatal diagnosis with shortened reporting time, namely, 2–3 weeks. Due to the relatively long TAT for sequential procedure for prenatal genetic diagnosis, as well as recent sequencing technology advancements, it is clinically necessary to consider the simultaneous evaluation of CNVs and SNVs/indels to enhance the diagnostic yield and timely TAT, especially for cases in the late second trimester or third trimester.

Best practices for variant calling in clinical sequencing

Next-generation sequencing technologies have enabled a dramatic expansion of clinical genetic testing both for inherited conditions and diseases such as cancer. Accurate variant calling in NGS data is a critical step upon which virtually all downstream analysis and interpretation processes rely. Just as NGS technologies have evolved considerably over the past 10 years, so too have the software tools and approaches for detecting sequence variants in clinical samples. In this review, I discuss the current best practices for variant calling in clinical sequencing studies, with a particular emphasis on trio sequencing for inherited disorders and somatic mutation detection in cancer patients. I describe the relative strengths and weaknesses of panel, exome, and whole-genome sequencing for variant detection. Recommended tools and strategies for calling variants of different classes are also provided, along with guidance on variant review, validation, and benchmarking to ensure optimal performance. Although NGS technologies are continually evolving, and new capabilities (such as long-read single-molecule sequencing) are emerging, the “best practice” principles in this review should be relevant to clinical variant calling in the long term.

Integrated sequencing and array comparative genomic hybridization in familial Parkinson disease

OBJECTIVE

To determine how single nucleotide variants (SNVs) and copy number variants (CNVs) contribute to molecular diagnosis in familial Parkinson disease (PD), we integrated exome sequencing (ES) and genome-wide array-based comparative genomic hybridization (aCGH) and further probed CNV structure to reveal mutational mechanisms.

METHODS

We performed ES on 110 subjects with PD and a positive family history; 99 subjects were also evaluated using genome-wide aCGH. We interrogated ES and aCGH data for pathogenic SNVs and CNVs at Mendelian PD gene loci. We confirmed SNVs via Sanger sequencing and further characterized CNVs with custom-designed high-density aCGH, droplet digital PCR, and breakpoint sequencing.

RESULTS

Using ES, we discovered individuals with known pathogenic SNVs in GBA (p.Glu365Lys, p.Thr408Met, p.Asn409Ser, and p.Leu483Pro) and LRRK2 (p.Arg1441Gly and p.Gly2019Ser). Two subjects were each double heterozygotes for variants in GBA and LRRK2. Based on aCGH, we additionally discovered cases with an SNCA duplication and heterozygous intragenic GBA deletion. Five additional subjects harbored both SNVs (p.Asn52Metfs*29, p.Thr240Met, p.Pro437Leu, and p.Trp453*) and likely disrupting CNVs at the PRKN locus, consistent with compound heterozygosity. In nearly all cases, breakpoint sequencing revealed microhomology, a mutational signature consistent with CNV formation due to DNA replication errors.

CONCLUSIONS

Integrated ES and aCGH yielded a genetic diagnosis in 19.3% of our familial PD cohort. Our analyses highlight potential mechanisms for SNCA and PRKN CNV formation, uncover multilocus pathogenic variation, and identify novel SNVs and CNVs for further investigation as potential PD risk alleles.

The Impact of Next-Generation Sequencing on the Diagnosis, Treatment, and Prevention of Hereditary Neuromuscular Disorders

The impact of high-throughput sequencing in genetic neuromuscular disorders cannot be overstated. The ability to rapidly and affordably sequence multiple genes simultaneously has enabled a second golden age of Mendelian disease gene discovery, with flow-on impacts for rapid genetic diagnosis, evidence-based treatment, tailored therapy development, carrier-screening, and prevention of disease recurrence in families. However, there are likely many more neuromuscular disease genes and mechanisms to be discovered. Many patients and families remain without a molecular diagnosis following targeted panel sequencing, clinical exome sequencing, or even genome sequencing. Here we review how massively parallel, or next-generation, sequencing has changed the field of genetic neuromuscular disorders, and anticipate future benefits of recent technological innovations such as RNA-seq implementation and detection of tandem repeat expansions from short-read sequencing.

Intragenic Deletions of GNAS in Pseudohypoparathyroidism Type 1A Identify a New Region Affecting Methylation of Exon A/B

CONTEXT

Pseudohypoparathyroidism type 1A (PHP1A) and pseudopseudohypoparathyroidism (PPHP) are caused by inactivating mutations in the exons of GNAS that encode the alpha-subunit of the stimulatory G protein (Gsα). In some cases abnormal methylation of exon A/B of GNAS, a hallmark of PHP1B, has been reported.

OBJECTIVE

To identify the underlying genetic basis for PHP1A/PPHP in patients in whom molecular defects were not detected by GNAS sequencing and microarray-based analysis of copy number variations.

METHODS

Whole genome sequencing (WGS) and pyrosequencing of differentially methylated regions (DMRs) of GNAS using genomic deoxyribonucleic acid from affected patients.

RESULTS

We identified 2 novel heterozygous GNAS deletions: a 6.4 kb deletion that includes exon 2 of GNAS in the first proband that was associated with normal methylation (57%) of exon A/B DMR, and a 1438 bp deletion in a second PHP1A patient that encompasses the promoter region and 5' untranslated region of Gsα transcripts, which was inherited from his mother with PPHP. This deletion was associated with reduced methylation (32%) of exon A/B DMR.

CONCLUSIONS

WGS can detect exonic and intronic mutations, including deletions that are too small to be identified by microarray analysis, and therefore is more sensitive than other techniques for molecular analysis of PHP1A/PPHP. One of the deletions we identified led to reduced methylation of exon A/B DMR, further refining a region needed for normal imprinting of this DMR. We propose that deletion of this region can explain why some PHP1A patients have reduced of methylation of the exon A/B DMR.

Exon-focused targeted oligonucleotide microarray design increases detection of clinically relevant variants across multiple NHS genomic centres

In recent years, chromosomal microarrays have been widely adopted by clinical diagnostic laboratories for postnatal constitutional genome analysis and have been recommended as the first-line test for patients with intellectual disability, developmental delay, autism and/or congenital abnormalities. Traditionally, array platforms have been designed with probes evenly spaced throughout the genome and increased probe density in regions associated with specific disorders with a resolution at the level of whole genes or multiple exons. However, this level of resolution often cannot detect pathogenic intragenic deletions or duplications, which represent a significant disease-causing mechanism. Therefore, new high-resolution oligonucleotide comparative genomic hybridisation arrays (oligo-array CGH) have been developed with probes targeting single exons of disease relevant genes. Here we present a retrospective study on 27,756 patient samples from a consortium of state-funded diagnostic UK genomic centres assayed by either oligo-array CGH of a traditional design (Cytosure ISCA v2) or by an oligo-array CGH with enhanced exon-level coverage of genes associated with developmental disorders (CytoSure Constitutional v3). The new targeted design used in Cytosure v3 array has been designed to capture intragenic aberrations that would have been missed on the v2 array. To assess the relative performance of the two array designs, data on a subset of samples (n = 19,675), generated only by laboratories using both array designs, were compared. Our results demonstrate that the new high-density exon-focused targeted array design that uses updated information from large scale genomic studies is a powerful tool for detection of intragenic deletions and duplications that leads to a significant improvement in diagnostic yield.

Novel biallelic loss-of-function variants in CEP290 cause Joubert syndrome in two siblings

Background

Joubert syndrome (JS) is a rare genetic disorder, which can be defined by brain stem malformation, cerebellar vermis hypoplasia, and consequent “molar tooth sign” (MTS). JS always shares variety of phenotypes in development defects. With the development of next-generation sequencing, dozens of causative genes have been identified to JS so far. Here, we investigated two male siblings with JS and uncovered a novel pathogenesis through combined methods.

Results

The siblings shared similar features of nystagmus, disorders of intellectual development, typical MTS, and abnormal morphology in fourth ventricle. Whole-exome sequencing (WES) and chromosome comparative genomic hybridization (CGH) were then performed on the proband. Strikingly, a maternal inherited nonsense variant (NM_025114.3: c.5953G>T [p.E1985*]) in CEP290 gene and a paternal inherited deletion in 12q21.32 including exons 1 to 10 of CEP290 gene were identified in the two affected siblings. We further confirmed the two variants by in vitro experiments: quantitative PCR and PCR sequencing.

Conclusions

In this study, we first reported a novel causative mechanism of Joubert syndrome: a copy number variation (CNV) combined with a single-nucleotide variant in CEP290 gene, which can be helpful in the genetic diagnosis of this disease.

Evaluation of CNV detection tools for NGS panel data in genetic diagnostics

Although germline copy-number variants (CNVs) are the genetic cause of multiple hereditary diseases, detecting them from targeted next-generation sequencing data (NGS) remains a challenge. Existing tools perform well for large CNVs but struggle with single and multi-exon alterations. The aim of this work is to evaluate CNV calling tools working on gene panel NGS data and their suitability as a screening step before orthogonal confirmation in genetic diagnostics strategies. Five tools (DECoN, CoNVaDING, panelcn.MOPS, ExomeDepth, and CODEX2) were tested against four genetic diagnostics datasets (two in-house and two external) for a total of 495 samples with 231 single and multi-exon validated CNVs. The evaluation was performed using the default and sensitivity-optimized parameters. Results showed that most tools were highly sensitive and specific, but the performance was dataset dependant. When evaluating them in our diagnostics scenario, DECoN and panelcn.MOPS detected all CNVs with the exception of one mosaic CNV missed by DECoN. However, DECoN outperformed panelcn.MOPS specificity achieving values greater than 0.90 when using the optimized parameters. In our in-house datasets, DECoN and panelcn.MOPS showed the highest performance for CNV screening before orthogonal confirmation. Benchmarking and optimization code is freely available at https://github.com/TranslationalBioinformaticsIGTP/CNVbenchmarkeR .

Application of Whole-Exome Sequencing in Detecting Copy Number Variants in Patients with Developmental Delay and/or Multiple Congenital Malformations

Overcoming challenges for the unambiguous detection of copy number variations is essential to broaden our understanding of the role of genomic variants in the clinical phenotype. With the improvement of software and databases, whole-exome sequencing quickly can become an excellent strategy in the routine diagnosis of patients with a developmental delay and/or multiple congenital malformations. However, even after a detailed analysis of pathogenic single-nucleotide variants and indels in known disease genes, using whole-exome sequencing, some patients with suspected syndromic conditions are left without a conclusive diagnosis. These negative results could be the result of different factors including nongenetic etiologies, lack of knowledge about the genes that cause different disease phenotypes, or, in some cases, a deletion or duplication of genomic information not routinely detectable by whole-exome sequencing variant calling. Although copy number variant detection is possible using whole-exome sequencing data, such analysis presents significant challenges and cannot yet be used to replace chromosomal arrays for identification of deletions or duplications.

A machine-learning approach for accurate detection of copy number variants from exome sequencing

Copy number variants (CNVs) are a major cause of several genetic disorders, making their detection an essential component of genetic analysis pipelines. Current methods for detecting CNVs from exome-sequencing data are limited by high false-positive rates and low concordance because of inherent biases of individual algorithms. To overcome these issues, calls generated by two or more algorithms are often intersected using Venn diagram approaches to identify "high-confidence" CNVs. However, this approach is inadequate, because it misses potentially true calls that do not have consensus from multiple callers. Here, we present CN-Learn, a machine-learning framework that integrates calls from multiple CNV detection algorithms and learns to accurately identify true CNVs using caller-specific and genomic features from a small subset of validated CNVs. Using CNVs predicted by four exome-based CNV callers (CANOES, CODEX, XHMM, and CLAMMS) from 503 samples, we demonstrate that CN-Learn identifies true CNVs at higher precision (∼90%) and recall (∼85%) rates while maintaining robust performance even when trained with minimal data (∼30 samples). CN-Learn recovers twice as many CNVs compared to individual callers or Venn diagram-based approaches, with features such as exome capture probe count, caller concordance, and GC content providing the most discriminatory power. In fact, ∼58% of all true CNVs recovered by CN-Learn were either singletons or calls that lacked support from at least one caller. Our study underscores the limitations of current approaches for CNV identification and provides an effective method that yields high-quality CNVs for application in clinical diagnostics.

Genome sequencing and implications for rare disorders

The practice of genomic medicine stands to revolutionize our approach to medical care, and to realize this goal will require discovery of the relationship between rare variation at each of the ~ 20,000 protein-coding genes and their consequent impact on individual health and expression of Mendelian disease. The step-wise evolution of broad-based, genome-wide cytogenetic and molecular genomic testing approaches (karyotyping, chromosomal microarray [CMA], exome sequencing [ES]) has driven much of the rare disease discovery to this point, with genome sequencing representing the newest member of this team. Each step has brought increased sensitivity to interrogate individual genomic variation in an unbiased method that does not require clinical prediction of the locus or loci involved. Notably, each step has also brought unique limitations in variant detection, for example, the low sensitivity of ES for detection of triploidy, and of CMA for detection of copy neutral structural variants. The utility of genome sequencing (GS) as a clinical molecular diagnostic test, and the increased sensitivity afforded by addition of long-read sequencing or other -omics technologies such as RNAseq or metabolomics, are not yet fully explored, though recent work supports improved sensitivity of variant detection, at least in a subset of cases. The utility of GS will also rely upon further elucidation of the complexities of genetic and allelic heterogeneity, multilocus rare variation, and the impact of rare and common variation at a locus, as well as advances in functional annotation of identified variants. Much discovery remains to be done before the potential utility of GS is fully appreciated.

Phenotype-Driven Virtual Panel Is an Effective Method to Analyze WES Data of Neurological Disease

Objective: Whole Exome Sequencing (WES) is an effective diagnostic method for complicated and multi-system involved rare diseases. However, annotation and analysis of the WES result, especially for single case analysis still remain a challenge. Here, we introduce a method called phenotype-driven designing "virtual panel" to simplify the procedure and assess the diagnostic rate of this method. Methods: WES was performed in samples of 30 patients, core phenotypes of probands were then extracted and inputted into an in-house software, "Mingjian" to calculate and generate associated gene list of a virtual panel. Mingjian is a self-updating genetic disease computer supportive diagnostic system that based on the databases of HPO, OMIM, HGMD. The virtual panel that generated by Mingjian system was then used to filter and annotate candidate mutations. Sanger sequencing and co-segregation analysis among the family were then used to confirm the filtered mutants. Result: We first used phenotype-driven designing "virtual panel" to analyze the WES data of a patient whose core phenotypes are ataxia, seizures, esotropia, puberty and gonadal disorders, and global developmental delay. Two mutations, c.430T > C and c.640G > C in PMM2 were identified by this method. This result was also confirmed by Sanger sequencing among the family. The same analysing method was then used in the annotation of WES data of other 29 neurological rare disease patients. The diagnostic rate was 65.52%, which is significantly higher than the diagnostic rate before. Conclusion: Phenotype-driven designing virtual panel could achieve low-cost individualized analysis. This method may decrease the time-cost of annotation, increase the diagnostic efficiency and the diagnostic rate.

Fetal exome sequencing: yield and limitations in a tertiary referral center

OBJECTIVE

To explore the indications for and diagnostic outcomes of fetal exome sequencing in a tertiary referral center.

METHODS

Between 2012 and 2017, 77 unrelated fetal samples from pregnancies referred to our center underwent exome sequencing. The cohort included 37 fetuses, 36 products of conception (from cases of pregnancy termination or intrauterine fetal death), one case with DNA from both the fetus and a previous termination of pregnancy, and three cases with DNA of unknown origin. Exome sequencing was performed on DNA extracted from amniocytes or fetal tissue and, in some cases, from parental peripheral blood. Indications, turnaround time, diagnostic rates and pregnancy outcomes were investigated. Diagnostic yield was analyzed according to consanguinity (yes or no), sample type (proband only, or trio or other) and referral indication (malformation or isolated nuchal translucency (NT)).

RESULTS

The most common indication for fetal exome sequencing was multiple malformations (21/77, 27%), followed by isolated brain malformation (15/77, 19%). Twelve (16%) fetuses were referred for isolated increased NT. Exome analysis was diagnostic for 16 fetuses (21%); when subclassified into fetal malformations vs isolated increased NT it became clear that exome analysis did not reveal any known or probable pathogenic variants in cases referred for isolated increased NT, whereas, among the remaining fetuses, a molecular diagnosis was reached in 16/65 (25%). Proband-only cases received a diagnosis more often than did cases that had trio exome sequencing.

CONCLUSIONS

Exome sequencing has the potential to provide molecular diagnoses in cases in which conventional prenatal cytogenetic testing is negative. Referral bias of consanguineous cases could account for the high diagnostic rate of proband-only sequencing. Syndrome-specific prognostic information enables parents to make informed decisions, whereas challenges include time limitations and variant interpretation in the setting of non-specific fetal findings. As we report only established disease-gene associations, further segregation and functional studies in a research setting are expected to increase significantly the diagnostic yield. Copyright © 2018 ISUOG. Published by John Wiley & Sons Ltd.

A multiplex ligation‑dependent probe amplification‑based next‑generation sequencing approach for the detection of copy number variations in the human genome

The aim of the present study was to describe a multiplex ligation‑dependent probe amplification (MLPA)‑based next‑generation sequencing (NGS) assay that exhibited a significantly higher efficiency in detecting copy number variations (CNVs) and known single‑nucleotide variants, compared with traditional MLPA. MLPA polymerase chain reaction products were used to construct a library with indexed adapters, which was subsequently tested on an NGS platform, and the resulting data were analyzed by a series of analytical software. The reads from each probe reflected genetic variations in the target regions, and fragment differentiation was based on the specific base composition of the sequences, rather than fragment length, which was determined by capillary electrophoresis. The results of this approach were not only consistent with the MLPA results following capillary electrophoresis, but also coincided with the CNV results from the single‑nucleotide polymorphism array chip. This method allowed high‑throughput screening for the number of fragments and samples by integrating additional indices for detection. Furthermore, this technology precisely and accurately performed large‑scale detection and quantification of DNA variations, thereby serving as an effective and sensitive method for diagnosing genetic disorders caused by CNVs and known single‑nucleotide variations. Notably, MLPA‑NGS circumvents the problems associated with the inaccuracies of NGS in CNV detection due to the use of target sequence capture.

Evaluation of copy number variant detection from panel-based next-generation sequencing data

Background

Targeted gene capture and next‐generation sequencing (NGS) has been widely utilized as a robust and cost‐effective approach for detecting small variants among a group of disease genes. Copy number variations (CNV) can also be inferred from the read‐depth information but the accuracy of CNVs called from panel‐based NGS data has not been well evaluated.

Methods

Sequencing data were acquired from patients underwent routine clinical targeted panel sequencing testing. Pathogenic CNVs detected from targeted panel sequencing data were evaluated using CNVs generated by two clinical accepted platforms, namely chromosome microarray analysis (CMA) and multiple ligation‐dependent probe amplification (MLPA) as benchmarks. CNVkit was used in our study to call CNVs from sequencing data using read‐depth information. CMA and MLPA tests were used to confirm and further assess the size and breakpoints of CNVs.

Results

The size of CNVs detected using panel‐based NGS data are over 300 kb. The sizes of CNVs detected are slightly larger (102.3% on average) using the NGS platform than using the CMA platform, and the size accuracy improved as the size of variants increases. The breakpoints of CNVs detected using NGS data are quite close (within 2.3% of margin) to the breakpoints detected by CMA. CNVs on sex chromosomes, however, are less concordant between NGS and CMA platforms.

Conclusion

Copy number variations covering adequate exons on autosomes can be accurately detected using targeted panel sequencing data as using CMA. CNVs detected from sex chromosomes need further evaluation and validation. Except for exon‐level deletion/duplication and CNV on sex chromosome, our data support the use of panel‐based NGS data for routine clinical detection of pathogenic CNVs.

Ximmer: a system for improving accuracy and consistency of CNV calling from exome data

Background

While exome and targeted next-generation DNA sequencing are primarily used for detecting single nucleotide changes and small indels, detection of copy number variants (CNVs) can provide highly valuable additional information from the data. Although there are dozens of exome CNV detection methods available, these are often difficult to use, and accuracy varies unpredictably between and within datasets.

Findings

We present Ximmer, a tool that supports an end-to-end process for evaluating, tuning, and running analysis methods for detection of CNVs in germline samples. Ximmer includes a simulation framework, implementations of several commonly used CNV detection methods, and a visualization and curation tool that together enable interactive exploration and quality control of CNV results. Using Ximmer, we comprehensively evaluate CNV detection on four datasets using five different detection methods. We show that application of Ximmer can improve accuracy and aid in quality control of CNV detection results. In addition, Ximmer can be used to run analyses and explore CNV results in exome data.

Conclusions

Ximmer offers a comprehensive tool and method for applying and improving accuracy of CNV detection methods for exome data.

The clinical implementation of copy number detection in the age of next-generation sequencing

INTRODUCTION

The role of copy number variants (CNVs) in disease is now well established. In parallel NGS technologies, such as long-read technologies, there is continual development and data analysis methods continue to be refined. Clinical exome sequencing data is now a reality for many diagnostic laboratories in both congenital genetics and oncology. This provides the ability to detect and report both SNVs and structural variants, including CNVs, using a single assay for a wide range of patient cohorts. Areas covered: Currently, whole-genome sequencing is mainly restricted to research applications and clinical utility studies. Furthermore, detecting the full-size spectrum of CNVs as well as somatic events remains difficult for both exome and whole-genome sequencing. As a result, the full extent of genomic variants in an individual's genome is still largely unknown. Recently, new sequencing technologies have been introduced which maintain the long-range genomic context, aiding the detection of CNVs and structural variants. Expert commentary: The development of long-read sequencing promises to resolve many CNV and SV detection issues but is yet to become established. The current challenge for clinical CNV detection is how to fully exploit all the data which is generated by high throughput sequencing technologies.

Molecular testing in holoprosencephaly

Holoprosencephaly (HPE) is a structural brain anomaly characterized by failure of the forebrain to separate during early embryogenesis. Both genetic and environmental etiologies of HPE have been discovered over the last three decades. Traditionally, the genetic workup for HPE has been a karyotype, chromosomal microarray, and/or Sanger sequencing of select genes. The recent increased availability of next-generation sequencing has changed the molecular diagnostic landscape for HPE, associating new genes with this disorder such as FGFR1. We conducted a systematic review of the medical literature for the molecular testing of HPE for studies published in the last 20 years. We also queried known commercial diagnostic laboratories and used information on their websites to construct a list of available commercial testing. Our group released its first recommendations in 2010 and this update incorporates the technology shifts and gene discoveries over the last decade. These recommendations provide a guide for genetic diagnosis of HPE, which is paramount for patients and their families for prognosis, treatment, and genetic counseling.

Whole-genome sequencing in patients with ciliopathies uncovers a novel recurrent tandem duplication in IFT140

Ciliopathies represent a wide spectrum of rare diseases with overlapping phenotypes and a high genetic heterogeneity. Among those, IFT140 is implicated in a variety of phenotypes ranging from isolated retinis pigmentosa to more syndromic cases. Using whole-genome sequencing in patients with uncharacterized ciliopathies, we identified a novel recurrent tandem duplication of exon 27-30 (6.7 kb) in IFT140, c.3454-488_4182+2588dup p.(Tyr1152_Thr1394dup), missed by whole-exome sequencing. Pathogenicity of the mutation was assessed on the patients' skin fibroblasts. Several hundreds of patients with a ciliopathy phenotype were screened and biallelic mutations were identified in 11 families representing 12 pathogenic variants of which seven are novel. Among those unrelated families especially with a Mainzer-Saldino syndrome, eight carried the same tandem duplication (two at the homozygous state and six at the heterozygous state). In conclusion, we demonstrated the implication of structural variations in IFT140-related diseases expanding its mutation spectrum. We also provide evidences for a unique genomic event mediated by an Alu-Alu recombination occurring on a shared haplotype. We confirm that whole-genome sequencing can be instrumental in the ability to detect structural variants for genomic disorders.

Paediatric genomics: diagnosing rare disease in children

The majority of rare diseases affect children, most of whom have an underlying genetic cause for their condition. However, making a molecular diagnosis with current technologies and knowledge is often still a challenge. Paediatric genomics is an immature but rapidly evolving field that tackles this issue by incorporating next-generation sequencing technologies, especially whole-exome sequencing and whole-genome sequencing, into research and clinical workflows. This complex multidisciplinary approach, coupled with the increasing availability of population genetic variation data, has already resulted in an increased discovery rate of causative genes and in improved diagnosis of rare paediatric disease. Importantly, for affected families, a better understanding of the genetic basis of rare disease translates to more accurate prognosis, management, surveillance and genetic advice; stimulates research into new therapies; and enables provision of better support.

Diagnostic exome sequencing in early-onset Parkinson's disease confirms VPS13C as a rare cause of autosomal-recessive Parkinson's disease

Parkinson's disease (PD) is a genetically heterogeneous disorder and new putative disease genes are discovered constantly. Therefore, whole-exome sequencing could be an efficient approach to genetic testing in PD. To evaluate its performance in early-onset sporadic PD, we performed diagnostic exome sequencing in 80 individuals with manifestation of PD symptoms at age 40 or earlier and a negative family history of PD. Variants in validated and candidate disease genes and risk factors for PD and atypical Parkinson syndromes were annotated, followed by further analysis for selected variants. We detected pathogenic variants in Mendelian genes in 6.25% of cases and high-impact risk factor variants in GBA in 5% of cases, resulting in overall maximum diagnostic yield of 11.25%. One individual was compound heterozygous for variants affecting canonical splice sites in VPS13C, confirming the causal role of protein-truncating variants in this gene linked to autosomal-recessive early-onset PD. Despite the low diagnostic yield of exome sequencing in sporadic early-onset PD, the confirmation of the recently discovered VPS13C gene highlights its advantage over using predefined gene panels.

Family studies to find rare high risk variants in migraine

INTRODUCTION

Migraine has long been known as a common complex disease caused by genetic and environmental factors. The pathophysiology and the specific genetic susceptibility are poorly understood. Common variants only explain a small part of the heritability of migraine. It is thought that rare genetic variants with bigger effect size may be involved in the disease. Since migraine has a tendency to cluster in families, a family approach might be the way to find these variants. This is also indicated by identification of migraine-associated loci in classical linkage-analyses in migraine families. A single migraine study using a candidate-gene approach was performed in 2010 identifying a rare mutation in the TRESK potassium channel segregating in a large family with migraine with aura, but this finding has later become questioned. The technologies of next-generation sequencing (NGS) now provides an affordable tool to investigate the genetic variation in the entire exome or genome. The family-based study design using NGS is described in this paper. We also review family studies using NGS that have been successful in finding rare variants in other common complex diseases in order to argue the promising application of a family approach to migraine.

METHOD

PubMed was searched to find studies that looked for rare genetic variants in common complex diseases through a family-based design using NGS, excluding studies looking for de-novo mutations, or using a candidate-gene approach and studies on cancer. All issues from Nature Genetics and PLOS genetics 2014, 2015 and 2016 (UTAI June) were screened for relevant papers. Reference lists from included and other relevant papers were also searched. For the description of the family-based study design using NGS an in-house protocol was used.

RESULTS

Thirty-two successful studies, which covered 16 different common complex diseases, were included in this paper. We also found a single migraine study. Twenty-three studies found one or a few family specific variants (less than five), while other studies found several possible variants. Not all of them were genome wide significant. Four studies performed follow-up analyses in unrelated cases and controls and calculated odds ratios that supported an association between detected variants and risk of disease. Studies of 11 diseases identified rare variants that segregated fully or to a large degree with the disease in the pedigrees.

CONCLUSION

It is possible to find rare high risk variants for common complex diseases through a family-based approach. One study using a family approach and NGS to find rare variants in migraine has already been published but with strong limitations. More studies are under way.

Intersociety policy statement on the use of whole-exome sequencing in the critically ill newborn infant

The rapid advancement of next-generation sequencing (NGS) technology and the decrease in costs for whole-exome sequencing (WES) and whole-genome sequening (WGS), has prompted its clinical application in several fields of medicine. Currently, there are no specific guidelines for the use of NGS in the field of neonatal medicine and in the diagnosis of genetic diseases in critically ill newborn infants. As a consequence, NGS may be underused with reduced diagnostic success rate, or overused, with increased costs for the healthcare system. Most genetic diseases may be already expressed during the neonatal age, but their identification may be complicated by nonspecific presentation, especially in the setting of critical clinical conditions. The differential diagnosis process in the neonatal intensive care unit (NICU) may be time-consuming, uncomfortable for the patient due to repeated sampling, and ineffective in reaching a molecular diagnosis during NICU stay. Serial gene sequencing (Sanger sequencing) may be successful only for conditions for which the clinical phenotype strongly suggests a diagnostic hypothesis and for genetically homogeneous diseases. Newborn screenings with Guthrie cards, which vary from country to country, are designed to only test for a few dozen genetic diseases out of the more than 6000 diseases for which a genetic characterization is available. The use of WES in selected cases in the NICU may overcome these issues. We present an intersociety document that aims to define the best indications for the use of WES in different clinical scenarios in the NICU. We propose that WES is used in the NICU for critically ill newborn infants when an early diagnosis is desirable to guide the clinical management during NICU stay, when a strong hypothesis cannot be formulated based on the clinical phenotype or the disease is genetically heterogeneous, and when specific non-genetic laboratory tests are not available. The use of WES may reduce the time for diagnosis in infants during NICU stay and may eventually result in cost-effectiveness.

Whole-exome sequencing identifies an α-globin cluster triplication resulting in increased clinical severity of β-thalassemia

Whole-exome sequencing (WES) has been increasingly useful for the diagnosis of patients with rare causes of anemia, particularly when there is an atypical clinical presentation or targeted genotyping approaches are inconclusive. Here, we describe a 20-yr-old man with a lifelong moderate-to-severe anemia with accompanying splenomegaly who lacked a definitive diagnosis. After a thorough clinical workup and targeted genetic sequencing, we identified a paternally inherited β-globin mutation (HBB:c.93-21G>A, IVS-I-110:G>A), a known cause of β-thalassemia minor. As this mutation alone was inconsistent with the severity of the anemia, we performed WES. Although we could not identify any relevant pathogenic single-nucleotide variants (SNVs) or small indels, copy-number variant (CNV) analyses revealed a likely triplication of the entire α-globin cluster, which was subsequently confirmed by multiplex ligation-dependent probe amplification. Treatment and follow-up was redefined according to the diagnosis of β-thalassemia intermedia resulting from a single β-thalassemia mutation in combination with an α-globin cluster triplication. Thus, we describe a case where the typical WES-based analysis of SNVs and small indels was unrevealing, but WES-based CNV analysis resulted in a definitive diagnosis that informed clinical decision-making. More generally, this case illustrates the value of performing CNV analysis when WES is otherwise unable to elucidate a clear genetic diagnosis.

Novel copy-number variations in pharmacogenes contribute to interindividual differences in drug pharmacokinetics

PurposeVariability in pharmacokinetics and drug response is shaped by single-nucleotide variants (SNVs) as well as copy-number variants (CNVs) in genes with importance for drug absorption, distribution, metabolism, and excretion (ADME). While SNVs have been extensively studied, a systematic assessment of the CNV landscape in ADME genes is lacking.MethodsWe integrated data from 2,504 whole genomes from the 1000 Genomes Project and 59,898 exomes from the Exome Aggregation Consortium to identify CNVs in 208 relevant pharmacogenes.ResultsWe describe novel exonic deletions and duplications in 201 (97%) of the pharmacogenes analyzed. The deletions are population-specific and frequencies range from singletons up to 1%, accounting for >5% of all loss-of-function alleles in up to 42% of the genes studied. We experimentally confirmed novel deletions in CYP2C19, CYP4F2, and SLCO1B3 by Sanger sequencing and validated their allelic frequencies in selected populations.ConclusionCNVs are an additional source of pharmacogenetic variability with important implications for drug response and personalized therapy. This, together with the important contribution of rare alleles to the variability of pharmacogenes, emphasizes the necessity of comprehensive next-generation sequencing-based genotype identification for an accurate prediction of the genetic variability of drug pharmacokinetics.