Biological Role and Disease Impact of Copy Number Variation in Complex Disease

In the human genome, DNA variants give rise to a variety of complex phenotypes. Ranging from single base mutations to copy number variations (CNVs), many of these variants are neutral in selection and disease etiology, making difficult the detection of true common or rare frequency disease-causing mutations. However, allele frequency comparisons in cases, controls, and families may reveal disease associations. Single nucleotide polymorphism (SNP) arrays and exome sequencing are popular assays for genome-wide variant identification. To limit bias between samples, uniform testing is crucial, including standardized platform versions and sample processing. Bases occupy single points while copy variants occupy segments. Bases are bi-allelic while copies are multi-allelic. One genome also encodes many different cell types. In this study, we investigate how CNV impacts different cell types, including heart, brain and blood cells, all of which serve as models of complex disease. Here, we describe ParseCNV, a systematic algorithm specifically developed as a part of this project to perform more accurate disease associations using SNP arrays or exome sequencing-generated CNV calls with quality tracking of variants, contributing to each significant overlap signal. Red flags of variant quality, genomic region, and overlap profile are assessed in a continuous score and shown to correlate over 90% with independent verification methods. We compared these data with our large internal cohort of 68,000 subjects, with carefully mapped CNVs, which gave a robust rare variant frequency in unaffected populations. In these investigations, we uncovered a number of loci in which CNVs are significantly enriched in non-coding RNA (ncRNA), Online Mendelian Inheritance in Man (OMIM), and genome-wide association study (GWAS) regions, impacting complex disease. By evaluating thoroughly the variant frequencies in pediatric individuals, we subsequently compared these frequencies in geriatric individuals to gain insight of these variants\u27 impact on lifespan. Longevity-associated CNVs enriched in pediatric patients were found to aggregate in alternative splicing genes. Congenital heart disease is the most common birth defect and cause of infant mortality. When comparing congenital heart disease families, with cases and controls genotyped both on SNP arrays and exome sequencing, we uncovered significant and confident loci that provide insight into the molecular basis of disease. Neurodevelopmental disease affects the quality of life and cognitive potential of many children. In the neurodevelopmental and psychiatric diseases, CACNA, GRM, CNTN, and SLIT gene families show multiple significant signals impacting a large number of developmental and psychiatric disease traits, with the potential of informing therapeutic decision-making. Through new tool development and analysis of large disease cohorts genotyped on a variety of assays, I have uncovered an important biological role and disease impact of CNV in complex disease

Common variants in polygenic schizophrenia

Schizophrenia is associated with both common single-nucleotide polymorphisms at the MHC locus and rare copy-number variants affecting many genes

Copy number variation analysis in the context of electronic medical records and large-scale genomics consortium efforts

The goal of this paper is to review recent research on copy number variations (CNVs) and their association with complex and rare diseases. In the latter part of this paper, we focus on how large biorepositories such as the electronic medical record and genomics (eMERGE) consortium may be best leveraged to systematically mine for potentially pathogenic CNVs, and we end with a discussion of how such variants might be reported back for inclusion in electronic medical records as part of medical history

A large-scale survey of the novel 15q24 microdeletion syndrome in autism spectrum disorders identifies an atypical deletion that narrows the critical region

<p>Abstract</p> <p>Background</p> <p>The 15q24 microdeletion syndrome has been recently described as a recurrent, submicroscopic genomic imbalance found in individuals with intellectual disability, typical facial appearance, hypotonia, and digital and genital abnormalities. Gene dosage abnormalities, including copy number variations (CNVs), have been identified in a significant fraction of individuals with autism spectrum disorders (ASDs). In this study we surveyed two ASD cohorts for 15q24 abnormalities to assess the frequency of genomic imbalances in this interval.</p> <p>Methods</p> <p>We screened 173 unrelated subjects with ASD from the Central Valley of Costa Rica and 1336 subjects with ASD from 785 independent families registered with the Autism Genetic Resource Exchange (AGRE) for CNVs across 15q24 using oligonucleotide arrays. Rearrangements were confirmed by array comparative genomic hybridization and quantitative PCR.</p> <p>Results</p> <p>Among the patients from Costa Rica, an atypical <it>de novo </it>deletion of 3.06 Mb in 15q23-q24.1 was detected in a boy with autism sharing many features with the other 13 subjects with the 15q24 microdeletion syndrome described to date. He exhibited intellectual disability, constant smiling, characteristic facial features (high anterior hairline, broad medial eyebrows, epicanthal folds, hypertelorism, full lower lip and protuberant, posteriorly rotated ears), single palmar crease, toe syndactyly and congenital nystagmus. The deletion breakpoints are atypical and lie outside previously characterized low copy repeats (69,838-72,897 Mb). Genotyping data revealed that the deletion had occurred in the paternal chromosome. Among the AGRE families, no large 15q24 deletions were observed.</p> <p>Conclusions</p> <p>From the current and previous studies, deletions in the 15q24 region represent rare causes of ASDs with an estimated frequency of 0.1 to 0.2% in individuals ascertained for ASDs, although the proportion might be higher in sporadic cases. These rates compare with a frequency of about 0.3% in patients ascertained for unexplained intellectual disability and congenital anomalies. This atypical deletion reduces the minimal interval for the syndrome from 1.75 Mb to 766 kb, implicating a reduced number of genes (15 versus 38). Sequencing of genes in the 15q24 interval in large ASD and intellectual disability samples may identify mutations of etiologic importance in the development of these disorders.</p

Modeling genetic inheritance of copy number variations

Copy number variations (CNVs) are being used as genetic markers or functional candidates in gene-mapping studies. However, unlike single nucleotide polymorphism or microsatellite genotyping techniques, most CNV detection methods are limited to detecting total copy numbers, rather than copy number in each of the two homologous chromosomes. To address this issue, we developed a statistical framework for intensity-based CNV detection platforms using family data. Our algorithm identifies CNVs for a family simultaneously, thus avoiding the generation of calls with Mendelian inconsistency while maintaining the ability to detect de novo CNVs. Applications to simulated data and real data indicate that our method significantly improves both call rates and accuracy of boundary inference, compared to existing approaches. We further illustrate the use of Mendelian inheritance to infer SNP allele compositions in each of the two homologous chromosomes in CNV regions using real data. Finally, we applied our method to a set of families genotyped using both the Illumina HumanHap550 and Affymetrix genome-wide 5.0 arrays to demonstrate its performance on both inherited and de novo CNVs. In conclusion, our method produces accurate CNV calls, gives probabilistic estimates of CNV transmission and builds a solid foundation for the development of linkage and association tests utilizing CNVs

Individual common variants exert weak effects on the risk for autism spectrum disorders.

While it is apparent that rare variation can play an important role in the genetic architecture of autism spectrum disorders (ASDs), the contribution of common variation to the risk of developing ASD is less clear. To produce a more comprehensive picture, we report Stage 2 of the Autism Genome Project genome-wide association study, adding 1301 ASD families and bringing the total to 2705 families analysed (Stages 1 and 2). In addition to evaluating the association of individual single nucleotide polymorphisms (SNPs), we also sought evidence that common variants, en masse, might affect the risk. Despite genotyping over a million SNPs covering the genome, no single SNP shows significant association with ASD or selected phenotypes at a genome-wide level. The SNP that achieves the smallest P-value from secondary analyses is rs1718101. It falls in CNTNAP2, a gene previously implicated in susceptibility for ASD. This SNP also shows modest association with age of word/phrase acquisition in ASD subjects, of interest because features of language development are also associated with other variation in CNTNAP2. In contrast, allele scores derived from the transmission of common alleles to Stage 1 cases significantly predict case status in the independent Stage 2 sample. Despite being significant, the variance explained by these allele scores was small (Vm&lt; 1%). Based on results from individual SNPs and their en masse effect on risk, as inferred from the allele score results, it is reasonable to conclude that common variants affect the risk for ASD but their individual effects are modest