Copy number variation and neuropsychiatric illness.
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ABSTRACT:
SUBMITTER: Rees E
PROVIDER: S-EPMC8219524 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Neurodevelopmental problems (NPs) are more common in males, whereas anxiety and depression are more common in females. Rare copy number variants (CNVs) have been implicated in neurodevelopmental disorders. The aim of this study was to characterize the relationship between rare CNVs with NPs, anxiety, and depression in a childhood population sample, as well as to examine sex-specific effects. We analyzed a sample of N?=?12,982 children, of whom 5.3% had narrowly defined NPs (clinically diagnosed), 20.9% had broadly defined NPs (based on validated screening measures, but no diagnosis), and 3.0% had clinically diagnosed anxiety or depression. Rare (<1% frequency) CNVs were categorized by size (100-500?kb or?>?500?kb), type, and putative relevance to NPs. We tested for association of CNV categories with outcomes and examined sex-specific effects. Medium deletions (OR[CI]?=?1.18[1.05-1.33], p?=?.0053) and large duplications (OR[CI]?=?1.45[1.19-1.75], p?=?.00017) were associated with broadly defined NPs. Large deletions (OR[CI]?=?1.85[1.14-3.01], p?=?.013) were associated with narrowly defined NPs. There were no significant sex differences in CNV burden in individuals with NPs. Although CNVs were not associated with anxiety/depression in the whole sample, in individuals diagnosed with these disorders, females were more likely to have large CNVs (OR[CI]?=?3.75[1.45-9.68], p?=?.0064). Rare CNVs are associated with both narrowly and broadly defined NPs in a general population sample of children. Our results also suggest that large, rare CNVs may show sex-specific phenotypic effects.
| S-EPMC6767107 | biostudies-literature
Project description:Copy number variants (CNVs) are associated with psychiatric conditions in clinical populations. The relationship between rare CNV burden and neuropsychiatric traits in young, general populations is underexplored. A total of 6,807 children from the Avon Longitudinal Study of Parents and Children (ALSPAC) were studied. CNVs were inferred from single nucleotide polymorphism-array data using PennCNV. After excluding children with known candidate CNVs for schizophrenia (SCZ), rare (<1%) CNV burden (total number of genes affected by CNVs, total length of CNVs, and largest CNV carried) was analyzed in relation to: psychotic experiences (PEs) and anxiety/depression in adolescence; autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD), ASD and ADHD traits, and cognitive measures during childhood. Outcomes were also assessed in relation to known SCZ CNVs. The number of genes affected by rare CNVs was associated with a continuous measure of ASD: the standardized mean difference [SMD] per gene affected was increased by 0.018 [95%CI 0.011,0.025], p?=?3e-07 for duplications and by 0.021 [95%CI 0.010, 0.032], p?=?1e-04 for deletions. In line with our published results on educational attainment in ALSPAC, intelligence quotient (IQ) was associated with CNV burden: the SMD per gene affected was -0.017 [95%CI -0.025, -0.008] p?=?1e-04 for duplications and -0.023 [95%CI -0.037, -0.009], p?=?.002 for deletions. Associations were also observed for measures of coherence, attention, memory, and social cognition. SCZ-associated deletions were associated with IQ (SMD: -0.617 [95%CI -0.936, -0.298], p?=?2e-04), but not with PEs or other traits. We found that rare CNV burden and known SCZ candidate CNVs are associated with neuropsychiatric phenotypes in a nonclinically ascertained sample of young people.
| S-EPMC6099375 | biostudies-literature
Project description:Next-generation sequencing (NGS) technologies offer new opportunities for precise and accurate identification of genomic aberrations, including copy number variations (CNVs). For high-throughput NGS data, using depth of coverage has become a major approach to identify CNVs, especially for whole exome sequencing (WES) data. Due to the high level of noise and biases of read-count data and complexity of the WES data, existing CNV detection tools identify many false CNV segments. Besides, NGS generates a huge amount of data, requiring to use effective and efficient methods. In this work, we propose a novel segmentation algorithm based on the total variation approach to detect CNVs more precisely and efficiently using WES data. The proposed method also filters out outlier read-counts and identifies significant change points to reduce false positives. We used real and simulated data to evaluate the performance of the proposed method and compare its performance with those of other commonly used CNV detection methods. Using simulated and real data, we show that the proposed method outperforms the existing CNV detection methods in terms of accuracy and false discovery rate and has a faster runtime compared to the circular binary segmentation method.
| S-EPMC7278034 | biostudies-literature
Project description:In recent years there has been a growing interest in the role of copy number variations (CNV) in genetic diseases. Though there has been rapid development of technologies and statistical methods devoted to detection in CNVs from array data, the inherent challenges in data quality associated with most hybridization techniques remains a challenging problem in CNV association studies.To help address these data quality issues in the context of family-based association studies, we introduce a statistical framework for the intensity-based array data that takes into account the family information for copy-number assignment. The method is an adaptation of traditional methods for modeling SNP genotype data that assume Gaussian mixture model, whereby CNV calling is performed for all family members simultaneously and leveraging within family-data to reduce CNV calls that are incompatible with Mendelian inheritance while still allowing de-novo CNVs. Applying this method to simulation studies and a genome-wide association study in asthma, we find that our approach significantly improves CNV calls accuracy, and reduces the Mendelian inconsistency rates and false positive genotype calls. The results were validated using qPCR experiments.In conclusion, we have demonstrated that the use of family information can improve the quality of CNV calling and hopefully give more powerful association test of CNVs.
| S-EPMC3668900 | biostudies-other
Project description:Copy number variation is now recognized as one of the major sources of genetic variation among individuals in natural populations of any species. However, the relevance of these unexpected observations goes beyond diagnosing high diversity.Here, it is argued that the molecular rates of copy number variation, mainly the deletion rate upon variation, determine the evolutionary road of the genome regarding size. Genetic drift will govern this process only if the effective population size is lower than the inverse of the deletion rate. Otherwise, natural selection will do.
| S-EPMC5553737 | biostudies-other
Project description:Great Ape Copy Number Variation
| PRJNA144461 | ENA
Project description:Variably expressive copy-number variants (CNVs) are characterized by extensive phenotypic heterogeneity of neuropsychiatric phenotypes. Approaches to identify single causative genes for these phenotypes within each CNV have not been successful. Here, we posit using multiple lines of evidence, including pathogenicity metrics, functional assays of model organisms, and gene expression data, that multiple genes within each CNV region are likely responsible for the observed phenotypes. We propose that candidate genes within each region likely interact with each other through shared pathways to modulate the individual gene phenotypes, emphasizing the genetic complexity of CNV-associated neuropsychiatric features.
| S-EPMC6336245 | biostudies-literature
Project description:Many copy number variants (CNVs) confer risk for the same range of neurodevelopmental symptoms and psychiatric conditions including autism and schizophrenia. Yet, to date neuroimaging studies have typically been carried out one mutation at a time, showing that CNVs have large effects on brain anatomy. Here, we aimed to characterize and quantify the distinct brain morphometry effects and latent dimensions across 8 neuropsychiatric CNVs. We analyzed T1-weighted MRI data from clinically and non-clinically ascertained CNV carriers (deletion/duplication) at the 1q21.1 (n = 39/28), 16p11.2 (n = 87/78), 22q11.2 (n = 75/30), and 15q11.2 (n = 72/76) loci as well as 1296 non-carriers (controls). Case-control contrasts of all examined genomic loci demonstrated effects on brain anatomy, with deletions and duplications showing mirror effects at the global and regional levels. Although CNVs mainly showed distinct brain patterns, principal component analysis (PCA) loaded subsets of CNVs on two latent brain dimensions, which explained 32 and 29% of the variance of the 8 Cohen's d maps. The cingulate gyrus, insula, supplementary motor cortex, and cerebellum were identified by PCA and multi-view pattern learning as top regions contributing to latent dimension shared across subsets of CNVs. The large proportion of distinct CNV effects on brain morphology may explain the small neuroimaging effect sizes reported in polygenic psychiatric conditions. Nevertheless, latent gene brain morphology dimensions will help subgroup the rapidly expanding landscape of neuropsychiatric variants and dissect the heterogeneity of idiopathic conditions.
| S-EPMC8292542 | biostudies-literature
Project description:Detection of chromosomal aberrations from a single cell by array comparative genomic hybridization (single-cell array CGH), instead of from a population of cells, is an emerging technique. However, such detection is challenging because of the genome artifacts and the DNA amplification process inherent to the single cell approach. Current normalization algorithms result in inaccurate aberration detection for single-cell data. We propose a normalization method based on channel, genome composition and recurrent genome artifact corrections. We demonstrate that the proposed channel clone normalization significantly improves the copy number variation detection in both simulated and real single-cell array CGH data.
| S-EPMC3245619 | biostudies-literature
Project description: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.
| S-EPMC4131886 | biostudies-literature