High resolution array in the clinical approach to chromosomal phenotypes

Array genomic hybridization (AGH) has recently been implemented as a diagnostic tool for the detection of submicroscopic copy number variants (CNVs) in patients with developmental disorders. However, there is no consensus regarding the choice of the platform, the minimal resolution needed and systematic interpretation of CNVs. We report our experience in the clinical diagnostic use of high resolution AGH up to 100 kb on 131 patients with chromosomal phenotypes but previously normal karyotype. We evaluated the usefulness in our clinics and laboratories by the detection rate of causal CNVs and CNVs of unknown clinical significance and to what extent their interpretation would challenge the systematic use of high-resolution arrays in clinical application. Prioritizing phenotype-genotype correlation in our interpretation strategy to criteria previously described, we identified 33 (25.2%) potentially pathogenic aberrations. 16 aberrations were confirmed pathogenic (16.4% syndromic, 8.5% non-syndromic patients); 9 were new and individual aberrations, 3 of them were pathogenic although inherited and one is as small as approx 200 kb. 13 of 16 further CNVs of unknown significance were classified likely benign, for 3 the significance remained unclear. High resolution array allows the detection of up to 12.2% of pathogenic aberrations in a diagnostic clinical setting. Although the majority of aberrations are larger, the detection of small causal aberrations may be relevant for family counseling. The number of remaining unclear CNVs is limited. Careful phenotype-genotype correlations of the individual CNVs and clinical features are challenging but remain a hallmark for CNV interpretation.     

Clinical interpretation of copy number variants in the human genome

Molecular methods, by which copy number variants (CNVs) detection is available, have been gradually introduced into routine diagnostics over the last 15 years. Despite this, some CNVs continue to be a huge challenge when it comes to clinical interpretation. CNVs are an important source of normal and pathogenic variants, but, in many cases, their impact on human health depends on factors that are not yet known. Therefore, perception of their clinical consequences can change over time, as our knowledge grows. This review summarises guidelines that facilitate correct classification of identified changes and discusses difficulties with the interpretation of rare, small CNVs.     

Copy number variation (CNV) identification,interpretation, and database from Brazilian patients

Copy number variations (CNVs) constitute an important class of variation in the human genome and the interpretation of their pathogenicity considering different frequencies across populations is still a challenge for geneticists. Since the CNV databases are predominantly composed of European and non-admixed individuals, and Brazilian genetic constitution is admixed and ethnically diverse, diagnostic screenings on Brazilian variants are greatly difficulted by the lack of populational references. We analyzed a clinical sample of 268 Brazilian individuals, including patients with neurodevelopment disorders and/or congenital malformations. The pathogenicity of CNVs was classified according to their gene content and overlap with known benign and pathogenic variants. A total of 1,504 autosomal CNVs (1,207 gains and 297 losses) were classified as benign (92.9%), likely benign (1.6%), VUS (2.6%), likely pathogenic (0.2%) and pathogenic (2.7%). Some of the CNVs were recurrent and with frequency increased in our sample, when compared to populational open resources of structural variants: 14q32.33, 22q11.22, 1q21.1, and 1p36.32 gains. Thus, these highly recurrent CNVs classified as likely benign or VUS were considered non-pathogenic in our Brazilian sample. This study shows the relevance of introducing CNV data from diverse cohorts to improve on the interpretation of clinical impact of genomic variations.     

Copy Number Variation in Thai Population

Copy number variation (CNV) is a major genetic polymorphism contributing to genetic diversity and human evolution. Clinical application of CNVs for diagnostic purposes largely depends on sufficient population CNV data for accurate interpretation. CNVs from general population in currently available databases help classify CNVs of uncertain clinical significance, and benign CNVs. Earlier studies of CNV distribution in several populations worldwide showed that a significant fraction of CNVs are population specific. In this study, we characterized and analyzed CNVs in 3,017 unrelated Thai individuals genotyped with the Illumina Human610, Illumina HumanOmniexpress, or Illumina HapMap550v3 platform. We employed hidden Markov model and circular binary segmentation methods to identify CNVs, extracted 23,458 CNVs consistently identified by both algorithms, and cataloged these high confident CNVs into our publicly available Thai CNV database. Analysis of CNVs in the Thai population identified a median of eight autosomal CNVs per individual. Most CNVs (96.73%) did not overlap with any known chromosomal imbalance syndromes documented in the DECIPHER database. When compared with CNVs in the 11 HapMap3 populations, CNVs found in the Thai population shared several characteristics with CNVs characterized in HapMap3. Common CNVs in Thais had similar frequencies to those in the HapMap3 populations, and all high frequency CNVs (>20%) found in Thai individuals could also be identified in HapMap3. The majorities of CNVs discovered in the Thai population, however, were of low frequency, or uniquely identified in Thais. When performing hierarchical clustering using CNV frequencies, the CNV data were clustered into Africans, Europeans, and Asians, in line with the clustering performed with single nucleotide polymorphism (SNP) data. As CNV data are specific to origin of population, our population-specific reference database will serve as a valuable addition to the existing resources for the investigation of clinical significance of CNVs in Thais and related ethnicities.     

Chromosomal microarray analysis of consecutive individuals with autism spectrum disorders or learning disability presenting for genetic services

Chromosomal microarray analysis is now commonly used in clinical practice to identify copy number variants (CNVs) in the human genome. We report our experience with the use of the 105 K and 180 K oligonucleotide microarrays in 215 consecutive patients referred with either autism or autism spectrum disorders (ASD) or developmental delay/learning disability for genetic services at the University of Kansas Medical Center during the past 4 years (2009–2012). Of the 215 patients [140 males and 75 females (male/female ratio = 1.87); 65 with ASD and 150 with learning disability], abnormal microarray results were seen in 45 individuals (21%) with a total of 49 CNVs. Of these findings, 32 represented a known diagnostic CNV contributing to the clinical presentation and 17 represented non-diagnostic CNVs (variants of unknown significance). Thirteen patients with ASD had a total of 14 CNVs, 6 CNVs recognized as diagnostic and 8 as non-diagnostic. The most common chromosome involved in the ASD group was chromosome 15. For those with a learning disability, 32 patients had a total of 35 CNVs. Twenty-six of the 35 CNVs were classified as a known diagnostic CNV, usually a deletion (n = 20). Nine CNVs were classified as an unknown non-diagnostic CNV, usually a duplication (n = 8). For the learning disability subgroup, chromosomes 2 and 22 were most involved. Thirteen out of 65 patients (20%) with ASD had a CNV compared with 32 out of 150 patients (21%) with a learning disability. The frequency of chromosomal microarray abnormalities compared by subject group or gender was not statistically different. A higher percentage of individuals with a learning disability had clinical findings of seizures, dysmorphic features and microcephaly, but not statistically significant. While both groups contained more males than females, a significantly higher percentage of males were present in the ASD group.     

Application of high resolution SNP arrays in patients with congenital oral clefts in south China

Chromosome microarray analysis (CMA) has proven to be a powerful tool in postnatal patients with intellectual disabilities. However, the diagnostic capability of CMA in patients with congenital oral clefts remain mysterious. Here, we present our clinical experience in implementing whole-genome high-resolution SNP arrays to investigate 33 patients with syndromic and nonsyndromic oral clefts in whom standard karyotyping analyses showed normal karyotypes. We aim to identify the genomic aetiology and candidate genes in patients with congenital oral clefts. CMA revealed copy number variants (CNVs) in every patient, which ranged from 2 to 9 per sample. The size of detected CNVs varied from 100 to 3.2 Mb. In 33 patients, we identified six clinically significant CNVs. The incidence of clinically significant CNVs was 18.2% (6/33). Three of these six CNVs were detected in patients with nonsyndromic clefts, including one who presented with isolated cleft lip with cleft palate (CLP) and two with cleft palate only (CPO). The remaining three CNVs were detected in patients with syndromic clefts. However, no CNV was detected in patients with cleft lip only (CLO). The six clinically significant CNVs were as follows: 8p23.1 microduplication (198 kb); 10q22.2-q22.3 microdeletion (1766 kb); 18q12.3 microduplication (638 kb); 20p12.1 microdeletion (184 kb); 6q26 microdeletion (389 kb); and 22q11.21-q11.23 microdeletion (3163 kb). In addition, two novel candidate genes for oral clefts, KAT6B and MACROD2, were putatively identified. We also found a CNV of unknown clinical significance with a detection rate of 3.0% (1/33). Our results further support the notion that CNVs significantly contributed to the genetic aetiology of oral clefts and emphasize the efficacy of whole-genome high-resolution SNP arrays to detect novel candidate genes in patients with syndromic and nonsyndromic clefts.     

Challenges of interpreting copy number variation in syndromic and non-syndromic congenital heart defects

Array comparative genomic hybridization (aCGH) has led to an increased detection of causal chromosomal imbalances in individuals with congenital heart defects (CHD). The introduction of aCGH as a diagnostic tool in a clinical cardiogenetic setting entails numerous challenges. Based on our own experience as well as those of others described in the literature, we outline the state of the art and attempt to answer a number of outstanding questions such as the detection frequency of causal imbalances in different patient populations, the added value of higher-resolution arrays, and the existence of predictive factors in syndromic cases. We introduce a step-by-step approach for clinical interpretation of copy number variants (CNV) detected in CHD, which is primarily based on gene content and overlap with known chromosomal syndromes, rather than on CNV inheritance and size. Based on this algorithm, we have reclassified the detected aberrations in aCGH studies for their causality for syndromic and non-syndromic CHD. From this literature overview, supplemented with own investigations in a cohort of 46 sporadic patients with severe non-syndromic CHD, it seems clear that the frequency of causal CNVs in non-syndromic CHD populations is lower than that in syndromic CNV populations (3.6 vs. 19%). Moreover, causal CNVs in non-syndromic CHD mostly involve imbalances with a moderate effect size and reduced penetrance, whereas the majority of causal imbalances in syndromic CHD consistently affects human development and significantly reduces reproductive fitness.     

Copy number variants in pharmacogenetic genes

Variation in drug efficacy and toxicity remains an important clinical concern. Presently, single nucleotide polymorphisms (SNPs) only explain a portion of this problem, even in situations where the pharmacological trait is clearly heritable. The Human CNV Project identified copy number variations (CNVs) across approximately 12% of the human genome, and these CNVs were considered causes of diseases. Although the contribution of CNVs to the pathogenesis of many common diseases is questionable, CNVs play a clear role in drug-related genes by altering drug metabolizing and drug response. In this review, we provide a comprehensive evaluation of the clinical relevance of CNVs to drug efficacy, toxicity, and disease prevalence in world populations, and discuss the implication of using CNVs as a diagnostic tool in clinical intervention.     

Copy Number Variants in German Patients with Schizophrenia

Large rare copy number variants (CNVs) have been recognized as significant genetic risk factors for the development of schizophrenia (SCZ). However, due to their low frequency (1∶150 to 1∶1000) among patients, large sample sizes are needed to detect an association between specific CNVs and SCZ. So far, the majority of genome-wide CNV analyses have focused on reporting only CNVs that reached a significant P-value within the study cohort and merely confirmed the frequency of already-established risk-carrying CNVs. As a result, CNVs with a very low frequency that might be relevant for SCZ susceptibility are lost for secondary analyses. In this study, we provide a concise collection of high-quality CNVs in a large German sample consisting of 1,637 patients with SCZ or schizoaffective disorder and 1,627 controls. All individuals were genotyped on Illumina''s BeadChips and putative CNVs were identified using QuantiSNP and PennCNV. Only those CNVs that were detected by both programs and spanned ≥30 consecutive SNPs were included in the data collection and downstream analyses (2,366 CNVs, 0.73 CNVs per individual). The genome-wide analysis did not reveal a specific association between a previously unknown CNV and SCZ. However, the group of CNVs previously reported to be associated with SCZ was more frequent in our patients than in the controls. The publication of our dataset will serve as a unique, easily accessible, high-quality CNV data collection for other research groups. The dataset could be useful for the identification of new disease-relevant CNVs that are currently overlooked due to their very low frequency and lack of power for their detection in individual studies.     

Chromosome microarray testing for patients with congenital heart defects reveals novel disease causing loci and high diagnostic yield

Background

Congenital heart defects (CHD), as the most common congenital anomaly, have been reported to be frequently associated with pathogenic copy number variants (CNVs). Currently, patients with CHD are routinely offered chromosomal microarray (CMA) testing, but the diagnostic yield of CMA on CHD patients has not been extensively evaluated based on a large patient cohort. In this study, we retrospectively assessed the detected CNVs in a total of 514 CHD cases (a 422-case clinical cohort from Boston Children''s Hospital (BCH) and a 92-case research cohort from Shanghai Children’s Medical Center (SCMC)) and conducted a genotype-phenotype analysis. Furthermore, genes encompassed in pathogenic/likely pathogenic CNVs were prioritized by integrating several tools and public data sources for novel CHD candidate gene identification.

Results

Based on the BCH cohort, the overall diagnostic yield of CMA testing for CHD patients was 12.8(pathogenic CNVs)-18.5% (pathogenic and likely pathogenic CNVs). The diagnostic yield of CMA for syndromic CHD was 14.1-20.6% (excluding aneuploidy cases), whereas the diagnostic yield for isolated CHD was 4.3-9.3%. Four recurrent genomic loci (4q terminal region, 15q11.2, 16p12.2 and Yp11.2) were more significantly enriched in cases than in controls. These regions are considered as novel CHD loci. We further identified 20 genes as the most likely novel CHD candidate genes through gene prioritization analysis.

Conclusion

The high clinical diagnostic yield of CMA in this study provides supportive evidence for CMA as the first-line genetic diagnostic tool for CHD patients. The CNVs detected in our study suggest a number of CHD candidate genes that warrant further investigation.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1127) contains supplementary material, which is available to authorized users.     

Identification of Rare Recurrent Copy Number Variants in High-Risk Autism Families and Their Prevalence in a Large ASD Population

Structural variation is thought to play a major etiological role in the development of autism spectrum disorders (ASDs), and numerous studies documenting the relevance of copy number variants (CNVs) in ASD have been published since 2006. To determine if large ASD families harbor high-impact CNVs that may have broader impact in the general ASD population, we used the Affymetrix genome-wide human SNP array 6.0 to identify 153 putative autism-specific CNVs present in 55 individuals with ASD from 9 multiplex ASD pedigrees. To evaluate the actual prevalence of these CNVs as well as 185 CNVs reportedly associated with ASD from published studies many of which are insufficiently powered, we designed a custom Illumina array and used it to interrogate these CNVs in 3,000 ASD cases and 6,000 controls. Additional single nucleotide variants (SNVs) on the array identified 25 CNVs that we did not detect in our family studies at the standard SNP array resolution. After molecular validation, our results demonstrated that 15 CNVs identified in high-risk ASD families also were found in two or more ASD cases with odds ratios greater than 2.0, strengthening their support as ASD risk variants. In addition, of the 25 CNVs identified using SNV probes on our custom array, 9 also had odds ratios greater than 2.0, suggesting that these CNVs also are ASD risk variants. Eighteen of the validated CNVs have not been reported previously in individuals with ASD and three have only been observed once. Finally, we confirmed the association of 31 of 185 published ASD-associated CNVs in our dataset with odds ratios greater than 2.0, suggesting they may be of clinical relevance in the evaluation of children with ASDs. Taken together, these data provide strong support for the existence and application of high-impact CNVs in the clinical genetic evaluation of children with ASD.     

Common copy number variations in fifty radiosensitive cell lines

Hypersensitivity to radiation exposure is a major challenge to radiotherapy in the treatment of cancer patients. Copy number variations (CNVs) are believed to identify genomic regions of functional significance for radiosensitivity (RS) but have yet to be systematically investigated. We used Affymetrix 6.0 SNP arrays to survey common CNVs in a cohort of 50 radiosensitive lymphoblastoid cell lines (RS-LCLs) derived from patients with undiagnosed diseases. A total of 317 CNVs that were present in at least 10% of the studied cell lines were identified. Three hundred and eight CNVs overlapped with polymorphic CNVs, 13 of which were significantly enriched in the RS-LCLs compared to the reference. The remaining 9 CNVs were novel. The majority of these enriched and novel CNVs were chromosomal gains. The dominance of the chromosomal gains over losses is inconsistent with the traditional concept of molecular basis of RS and suggests more complex genetic mechanisms for RS.     

New copy number variations in schizophrenia

Genome-wide screenings for copy number variations (CNVs) in patients with schizophrenia have demonstrated the presence of several CNVs that increase the risk of developing the disease and a growing number of large rare CNVs; the contribution of these rare CNVs to schizophrenia remains unknown. Using Affymetrix 6.0 arrays, we undertook a systematic search for CNVs in 172 patients with schizophrenia and 160 healthy controls, all of Italian origin, with the aim of confirming previously identified loci and identifying novel schizophrenia susceptibility genes. We found five patients with a CNV occurring in one of the regions most convincingly implicated as risk factors for schizophrenia: NRXN1 and the 16p13.1 regions were found to be deleted in single patients and 15q11.2 in 2 patients, whereas the 15q13.3 region was duplicated in one patient. Furthermore, we found three distinct patients with CNVs in 2q12.2, 3q29 and 17p12 loci, respectively. These loci were previously reported to be deleted or duplicated in patients with schizophrenia but were never formally associated with the disease. We found 5 large CNVs (>900 kb) in 4q32, 5q14.3, 8q23.3, 11q25 and 17q12 in five different patients that could include some new candidate schizophrenia susceptibility genes. In conclusion, the identification of previously reported CNVs and of new, rare, large CNVs further supports a model of schizophrenia that includes the effect of multiple, rare, highly penetrant variants.     

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.     

Accurate in silico confirmation of rare copy number variant calls from exome sequencing data using transfer learning

Exome sequencing is widely used in genetic studies of human diseases and clinical genetic diagnosis. Accurate detection of copy number variants (CNVs) is important to fully utilize exome sequencing data. However, exome data are noisy. None of the existing methods alone can achieve both high precision and recall rate. A common practice is to perform heuristic filtration followed by manual inspection of read depth of putative CNVs. This approach does not scale in large studies. To address this issue, we developed a transfer learning method, CNV-espresso, for in silico confirming rare CNVs from exome sequencing data. CNV-espresso encodes candidate CNVs from exome data as images and uses pretrained convolutional neural network models to classify copy number states. We trained CNV-espresso using an offspring–parents trio exome sequencing dataset, with inherited CNVs as positives and CNVs with Mendelian errors as negatives. We evaluated the performance using additional samples that have both exome and whole-genome sequencing (WGS) data. Assuming the CNVs detected from WGS data as a proxy of ground truth, CNV-espresso significantly improves precision while keeping recall almost intact, especially for CNVs that span a small number of exons. CNV-espresso can effectively replace manual inspection of CNVs in large-scale exome sequencing studies.     

Prioritizing Clinically Relevant Copy Number Variation from Genetic Interactions and Gene Function Data

It is becoming increasingly necessary to develop computerized methods for identifying the few disease-causing variants from hundreds discovered in each individual patient. This problem is especially relevant for Copy Number Variants (CNVs), which can be cheaply interrogated via low-cost hybridization arrays commonly used in clinical practice. We present a method to predict the disease relevance of CNVs that combines functional context and clinical phenotype to discover clinically harmful CNVs (and likely causative genes) in patients with a variety of phenotypes. We compare several feature and gene weighing systems for classifying both genes and CNVs. We combined the best performing methodologies and parameters on over 2,500 Agilent CGH 180k Microarray CNVs derived from 140 patients. Our method achieved an F-score of 91.59%, with 87.08% precision and 97.00% recall. Our methods are freely available at https://github.com/compbio-UofT/cnv-prioritization. Our dataset is included with the supplementary information.     

Considering specific clinical features as evidence of pathogenic copy number variants

Since the introduction of high-resolution microarray technologies, it has become apparent that structural chromosomal rearrangements can lead to a wide variety of clinical manifestations, including developmental delay/intellectual disability (DD/ID). It has been shown previously that the diagnostic yield of genome-wide array-based identification of submicroscopic alterations in patients with ID varies widely and depends on the patient selection criteria. More attempts have recently been made to define the phenotypic clues of pathogenic copy number variants (CNVs). The aim of this study was to investigate a well-phenotyped cohort of patients with DD/ID and determine whether certain clinical features may serve as indicators for pathogenic CNVs. A retrospective analysis was conducted for patients with DD/ID (n?=?211) who were tested using genome-wide chromosomal microarray technologies and a review of the clinical data was performed. Pathogenic CNVs were detected in 29 patients. In comparison with individuals who had normal molecular karyotyping results (n?=?182), malformations of the musculoskeletal system; congenital malformations of the CNS (particularly hydrocephalus and congenital malformations of the corpus callosum); minor anomalies of the eye, face, and neck subgroup (particularly downward-slanting palpebral fissures, minor anomalies of the ear, and micrognathia); brachydactyly; and umbilical hernia were more common in patients with chromosomal alterations. A multivariate logistic regression analysis allowed the identification of three independent pathogenic CNV predictors: congenital malformations of the corpus callosum, minor anomalies of the ear, and brachydactyly. Insights into the chromosomal phenotype may help to increase the diagnostic yield of microarray technologies and sharpen the distinction between chromosomal alterations and other conditions.     

Identification of copy number variants on human chromosome 22 in patients with a variety of clinical findings

The aims of this study were to create a copy number variant (CNV) profile of human chromosome 22 and to establish a genotype-phenotype correlation for patients with genomic abnormalities on chromosome 22. Thus, 1,654 consecutive pediatric patients with a diversity of clinical findings were evaluated by high-resolution chromosomal microarray analysis (CMA). We identified 25 individuals with abnormal CNVs on chromosome 22, representing 1.5% of the cases analyzed in this cohort. Meanwhile, we detected 1,298 benign CNVs on this chromosome in these individuals. Twenty-one of the 25 abnormal CNVs and the majority of the benign CNVs occurred through involvement of the 8 unstable genomic regions enriched with low copy repeats (LCR22A-H). The highly dynamic status of LCR22s within the 22q11 region facilitates the formation of diverse genomic abnormalities. This CNV profile provides a general perspective of the spectrum of chromosome 22 genomic imbalances and subsequently improves the CNV-phenotype correlations.     

Recurrent CNVs disrupt three candidate genes in schizophrenia patients

Schizophrenia is a severe psychiatric disease with complex etiology, affecting approximately 1% of the general population. Most genetics studies so far have focused on disease association with common genetic variation, such as single-nucleotide polymorphisms (SNPs), but it has recently become apparent that large-scale genomic copy-number variants (CNVs) are involved in disease development as well. To assess the role of rare CNVs in schizophrenia, we screened 54 patients with deficit schizophrenia using Affymetrix's GeneChip 250K SNP arrays. We identified 90 CNVs in total, 77 of which have been reported previously in unaffected control cohorts. Among the genes disrupted by the remaining rare CNVs are MYT1L, CTNND2, NRXN1, and ASTN2, genes that play an important role in neuronal functioning but--except for NRXN1--have not been associated with schizophrenia before. We studied the occurrence of CNVs at these four loci in an additional cohort of 752 patients and 706 normal controls from The Netherlands. We identified eight additional CNVs, of which the four that affect coding sequences were found only in the patient cohort. Our study supports a role for rare CNVs in schizophrenia susceptibility and identifies at least three candidate genes for this complex disorder.