Accurate Distinction of Pathogenic from Benign CNVs in Mental Retardation

Copy number variants (CNVs) have recently been recognized as a common form of genomic variation in humans. Hundreds of CNVs can be detected in any individual genome using genomic microarrays or whole genome sequencing technology, but their phenotypic consequences are still poorly understood. Rare CNVs have been reported as a frequent cause of neurological disorders such as mental retardation (MR), schizophrenia and autism, prompting widespread implementation of CNV screening in diagnostics. In previous studies we have shown that, in contrast to benign CNVs, MR-associated CNVs are significantly enriched in genes whose mouse orthologues, when disrupted, result in a nervous system phenotype. In this study we developed and validated a novel computational method for differentiating between benign and MR-associated CNVs using structural and functional genomic features to annotate each CNV. In total 13 genomic features were included in the final version of a Naïve Bayesian Tree classifier, with LINE density and mouse knock-out phenotypes contributing most to the classifier's accuracy. After demonstrating that our method (called GECCO) perfectly classifies CNVs causing known MR-associated syndromes, we show that it achieves high accuracy (94%) and negative predictive value (99%) on a blinded test set of more than 1,200 CNVs from a large cohort of individuals with MR. These results indicate that this classification method will be of value for objectively prioritizing CNVs in clinical research and diagnostics

Single nucleotide polymorphism array analysis in copy number variant detection: assessment of its feasibility in the diagnostic setting

Intellectual disability/developmental delay (ID/DD) is a significant problem in child health affecting 2 to 3% of the population worldwide. While the underlying aetiology of ID/DD in a large proportion (about 50%) of these patients is unknown, 15 to 20% of the internationally reported cases detected using microarray technologies are due to copy number variants (CNVs), whereas only 3 to 5% of ID/DD can be identified with conventional cytogenetics. The Affymetrix® Cytoscan™ High Density (HD) Array (Affymetrix, Santa Clara, CA) containing over 2.4 million markers for copy number (CN) was used to detect genome-wide high resolution CN and single nucleotide polymorphisms (SNPs) in a cohort of 27 carefully selected patient samples. The patient selection was done based on relevant phenotypes, which included dysmorphism, ID/DD, suspected syndromes, and family history. Data analysis was performed using the Affymetrix Chromosome Analysis Suite (ChAS) (Affymetrix, Santa Clara, CA, USA software). Seven of the patients demonstrated pathogenic CNVs. Diagnoses included Kleefstra syndrome, Mowat-Wilson syndrome, Wolf-Hirschhorn syndrome, tetrasomy 9p, and a susceptibility locus for neurodevelopmental disorders due to a deletion of chromosome 1q21.1. This indicated a 26% detection rate in this cohort. In addition, three variants of unknown significance (VOUS) were detected. The aim of this study was to determine the potential relevance and applicability of microarray technologies for the detection of CNVs in the Western Cape ID/DD population of South Africa (SA) and in so doing, to introduce and develop molecular cytogenetics skills in the routine diagnostic cytogenetic environment. The results obtained in this study confirmed the significant improvement in the detection rate of CNVs in patients with ID/DD and thus the diagnostic utility of this technology for the detection of CNVs in ID/DD patients was confirmed

CNV-WebStore: Online CNV Analysis, Storage and Interpretation

<p>Abstract</p> <p>Background</p> <p>Microarray technology allows the analysis of genomic aberrations at an ever increasing resolution, making functional interpretation of these vast amounts of data the main bottleneck in routine implementation of high resolution array platforms, and emphasising the need for a centralised and easy to use CNV data management and interpretation system.</p> <p>Results</p> <p>We present CNV-WebStore, an online platform to streamline the processing and downstream interpretation of microarray data in a clinical context, tailored towards but not limited to the Illumina BeadArray platform. Provided analysis tools include CNV analsyis, parent of origin and uniparental disomy detection. Interpretation tools include data visualisation, gene prioritisation, automated PubMed searching, linking data to several genome browsers and annotation of CNVs based on several public databases. Finally a module is provided for uniform reporting of results.</p> <p>Conclusion</p> <p>CNV-WebStore is able to present copy number data in an intuitive way to both lab technicians and clinicians, making it a useful tool in daily clinical practice.</p

Évaluation du caryotype moléculaire en tant qu’outil diagnostique chez les enfants avec déficience intellectuelle et/ou malformations congénitales

Le caryotype moléculaire permet d’identifier un CNV chez 10-14% des individus atteints de déficience intellectuelle et/ou de malformations congénitales. C’est pourquoi il s’agit maintenant de l’analyse de première intention chez ces patients. Toutefois, le rendement diagnostique n’est pas aussi bien défini en contexte prénatal et l’identification de CNVs de signification clinique incertaine y est particulièrement problématique à cause du risque d’interruption de grossesse. Nous avons donc testé 49 fœtus avec malformations majeures et un caryotype conventionnel normal avec une micropuce CGH pangénomique, et obtenu un diagnostic dans 8,2% des cas. Par ailleurs, des micropuces à très haute résolution combinant le caryotype moléculaire et le génotypage de SNPs ont récemment été introduites sur le marché. En plus d’identifier les CNVs, ces plateformes détectent les LOHs, qui peuvent indiquer la présence d’une mutation homozygote ou de disomie uniparentale. Ces anomalies pouvant être associées à la déficience intellectuelle ou à des malformations, leur détection est particulièrement intéressante pour les patients dont le phénotype reste inexpliqué. Cependant, le rendement diagnostique de ces plateformes n’est pas confirmé, et l’utilité clinique réelle des LOHs n’est toujours pas établie. Nous avons donc testé 21 enfants atteints de déficience intellectuelle pour qui les méthodes standards d’analyse génétique n’avaient pas résulté en un diagnostic, et avons pu faire passer le rendement diagnostique de 14,3% à 28,6% grâce à l’information fournie par les LOHs. Cette étude démontre l’utilité clinique d’une micropuce CGH pangénomique chez des fœtus avec malformations, de même que celle d’une micropuce SNP chez des enfants avec déficience intellectuelle.Molecular karyotyping identifies a CNV in 10-14% of individuals affected with intellectual disability and/or congenital abnormalities. Therefore, it is now the first-tier analysis for these patients. However, the diagnostic yield is not as clear in the prenatal context, and the risk of pregnancy termination makes the detection of variants of uncertain clinical significance particularly problematic. We tested 49 fetuses with major malformations and a normal karyotype, using a pangenomic CGH array, and obtained a diagnosis in 8.2% of cases. Furthermore, high-resolution microarrays combining molecular karyotyping and SNP genotyping were recently introduced on the market. In addition to identifying CNVs, these platforms detect LOHs, which can indicate the presence of a homozygous mutation or of uniparental disomy. Since these abnormalities can be associated with intellectual disability or congenital abnormalities, their detection is of particular interest for patients whose phenotype remains unexplained. However, the diagnostic yield obtained with these platforms is not confirmed, and the real clinical value of LOH detection is not yet established. We tested 21 children affected with intellectual disability for whom standard genetic analyses failed to provide a diagnosis, and were able to increase the diagnostic yield from 14.3% to 28.6% as a result of the information provided by LOHs. This study shows the clinical usefulness of pangenomic CGH arrays in fetuses with malformation(s), as well as that of SNP arrays in children with intellectual disability

Targeted resequencing as diagnostic tool in patients with epilepsy

Epilepsy is one of the most common neurological disorder, affecting 5–8/1.000 individuals worldwide. Approximately 20–30 % of epilepsy cases are caused by acquired conditions such as stroke, tumor or head injury, but the remaining 70–80 % of cases are believed to be due to one or more genetic factors. In the last decade, advances in genomic technologies have led to a rapid increase in understanding of epilepsy genetics and to date, to the best of our knowledge, about 1000 genes have been associated with epilepsy. The aim of this study is to determine the contribution of some currently known disease-causing genes in a cohort of Italian patients affected by syndromic or non-syndromic forms of epilepsy. We designed a genes panel for Targeted Resequencing (TRS) containing 85 relevant epilepsy genes responsible for the most common epilepsy phenotypes known so far. A cohort of 49 patients (23 male and 26 female) with a clinical diagnosis of epilepsy, including both sporadic and familial cases, has been enrolled for the study and analyzed by TRS. This approach allowed us to identify variants in 25/49 (51%) patients analyzed. In detail, disease-causing mutations (classified as pathogenic or likely pathogenic following the American College of Medical genetics guidelines), has been identified in 10/25 (40%) affecting the genes ARX, GAMT, KCNQ2, MECP2, SCN1A, POLG, SPTAN1, STXBP1 and TCF4, while variants of uncertain clinical significance (VUS) has been identified in the remaining 15/25 patients (60%) affecting the genes ATP1A2, CACNB4, CLN3, CLN6, CNTN4, CACNA1H, CNTNAP2, GRIN2A, GRIN2B, KCNMA1, LIAS, POLG, PNKP, PRICKLE2, SCN1A, SCN2A, SPTAN1, SCN9A, TSC1. Next Generation Sequencing technologies have revolutionized our approach to genetic epilepsies both from research than clinical perspective. The identification of novel mutations in known epilepsy associated genes is useful to increase our knowledge about the molecular mechanisms of the disease. More importantly, our study highlight once again the utility of next generation sequencing in establishing an etiological basis in clinically and genetically heterogeneous conditions such as epilepsy. Knowing the genetic basis of the disease can be valuable not only for diagnosis but also for guiding treatment and, above all, estimating recurrence risk

The functional impact of copy number variation in the human genome

Copy number variation (CNV) is a class of genetic variation where large segments of the genome vary in copy number among different individuals. It has become clear in the past decade that CNV affects a significant proportion of the human genome and can play an important role in human disease. With array-based copy number detection and the current generation of sequencing technologies, our ability to discover genetic variants is running far ahead of our ability to interpret their functional impact. One approach to close this gap is to explore statistical association between genetic variants and phenotypes. In contrast to the successes of genome-wide association studies for common disease using common single nucleotide polymorphism (SNP) as markers, the majority of disease CNVs discovered so far have low population frequencies and are mainly involved in rare developmental disorders. Another strategy to improve interpretation of genomic variants is to establish a predictive understanding of their functional impact. Large heterozygous deletions are of particular interest, since (i) loss-of-function (LOF) of coding sequences encompassed by large deletions can be relatively unambiguously ascribed and (ii) haploinsufficiency (HI), wherein only one functional copy of a gene is not sufficient to maintain normal phenotype, is a major cause of dominant diseases. This thesis explored both approaches. Initially, I developed an informatics pipeline for robust discovery of CNVs from large numbers of samples genotyped using the Affymetrix whole-genome SNP array 6.0, to support both the association-based and prediction-based study. For the disease association strategy, I studied the role of both common and rare CNVs in severe early-onset obesity using a case-control design, from which a rare 220kb heterozygous deletion at 16p11.2 that encompasses SH2B1 was found causal for the phenotype and an 8kb common deletion upstream of NEGR1 was found to be significantly associated with the disease, particularly in females. Using the prediction-based approach, I characterized the properties of HI genes by comparing with genes observed to be deleted in apparently healthy individuals and I developed a prediction model to distinguish HI and haplosufficient (HS) genes using the most informative properties identified from these comparisons. An HI-based pathogenicity score was devised to distinguish pathogenic genic CNVs from benign genic CNVs. Finally, I proposed a probabilistic diagnostic framework to incorporate population variation, and integrate other sources of evidence, to enable an improved, and quantitative, identification of causal variants

High-resolution karyotyping by oligonucleotide microarrays : the next revolution in cytogenetics

Conventional karyotyping has been used as the standard cytogenetic technique since the 1970s. With conventional karyotyping one can detect aberrations larger than 5 __ 10 Mb and it can detect chromosomal aberrations in approximately 5% of patients with mental retardation (MR). To identify smaller copy number variants (CNVs) new molecular cytogenetic techniques have been developed. One of these techniques is the Single Nucleotide Polymorphism (SNP) array. This method allows the detection of SNP-genotype as well as the presence of small deletions and amplifications. In this thesis we have studied patients with MR and/or congenital malformations. The question we have tried to answer by studying the genome of the patient is whether we can find a cause for the signs and symptoms observed in the patient. The SNP array was successfully used for the detection of novel CNVs and has replaced the conventional karyotyping in the routine diagnostic flow in MR patients in our diagnostic setting. We are therefore able to make a diagnosis in a higher number of MR patients, thus improving medical care and genetic counselling. However, a major complexity is the finding of potentially pathogenic CNVs for which the clinical significance is not immediately clear.UBL - phd migration 201

An ethical analysis of divergent clinical approaches to the application of genetic testing for autism and schizophrenia

Genetic testing to identify genetic syndromes and copy number variants (CNVs) via whole genome platforms such as chromosome microarray (CMA) or exome sequencing (ES) is routinely performed clinically, and is considered by a variety of organizations and societies to be a “first-tier” test for individuals with developmental delay (DD), intellectual disability (ID), or autism spectrum disorder (ASD). However, in the context of schizophrenia, though CNVs can have a large effect on risk, genetic testing is not typically a part of routine clinical care, and no clinical practice guidelines recommend testing. This raises the question of whether CNV testing should be similarly performed for individuals with schizophrenia. Here we consider this proposition in light of the history of genetic testing for ID/DD and ASD, and through the application of an ethical analysis designed to enable robust, accountable and justifiable decision-making. Using a systematic framework and application of relevant bioethical principles (beneficence, non-maleficence, autonomy, and justice), our examination highlights that while CNV testing for the indication of ID has considerable benefits, there is currently insufficient evidence to suggest that overall, the potential harms are outweighed by the potential benefits of CNV testing for the sole indications of schizophrenia or ASD. However, although the application of CNV tests for children with ASD or schizophrenia without ID/DD is, strictly speaking, off-label use, there may be clinical utility and benefits substantive enough to outweigh the harms. Research is needed to clarify the harms and benefits of testing in pediatric and adult contexts. Given that genetic counseling has demonstrated benefits for schizophrenia, and has the potential to mitigate many of the potential harms from genetic testing, any decisions to implement genetic testing for schizophrenia should involve high-quality evidence-based genetic counselin