60 resultados para CNVs


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Copy number variants (CNVs) account for a major proportion of human genetic polymorphism and have been predicted to have an important role in genetic susceptibility to common disease. To address this we undertook a large, direct genome-wide study of association between CNVs and eight common human diseases. Using a purpose-designed array we typed 19,000 individuals into distinct copy-number classes at 3,432 polymorphic CNVs, including an estimated 50% of all common CNVs larger than 500 base pairs. We identified several biological artefacts that lead to false-positive associations, including systematic CNV differences between DNAs derived from blood and cell lines. Association testing and follow-up replication analyses confirmed three loci where CNVs were associated with diseaseIRGM for Crohns disease, HLA for Crohns disease, rheumatoid arthritis and type 1 diabetes, and TSPAN8 for type 2 diabetesalthough in each case the locus had previously been identified in single nucleotide polymorphism (SNP)-based studies, reflecting our observation that most common CNVs that are well-typed on our array are well tagged by SNPs and so have been indirectly explored through SNP studies. We conclude that common CNVs that can be typed on existing platforms are unlikely to contribute greatly to the genetic basis of common human diseases. © 2010 Macmillan Publishers Limited. All rights reserved.

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Introduction: Autism Spectrum Disorder (ASD) is a frequent and complex neurodevelopmental disorder, characterized by impairments in social communication and repetitive behaviors and with a high male to female ratio: ~4:1. Genetic factors, including rare Copy Number Variants (CNVs), have a substantial impact in ASD risk 1, and are associated with specific phenotypic manifestations 2. Recent studies reported that rare inherited CNVs are enriched in mothers of ASD children compared with mothers of controls and are preferentially transmitted from mothers to ASD children suggesting a sex bias in CNV transmission; further, the imbalanced transmission of small pathogenic CNVs from unaffected mothers to their sons with ASD has been described 3, 4. An increased prevalence of autism - like personality traits is found in unaffected relatives of ASD children, suggesting a genetic liability of a broader autism phenotype (BAP) 5. The BAP in parents of autistic children can be assessed by the Social Responsiveness Scale (SRS) 6 and Broad Autism Phenotype Questionnaire (BAPQ) 7 reports . The SRS is 65 - item questionnaire to identify sub - clinical social impairments and interpersonal behaviour in individuals . The BAPQ is a 36 - item questionnaire measures social aloofness, rigid personality, and pragmatic language deficits in both parents and children.

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Autism Spectrum Disorder (ASD) is a frequent and complex neurodevelopmental disorder, characterized by impairments in social communication and repetitive behaviors and with a high male to female ratio: ~4:1. Genetic factors, including rare Copy Number Variants (CNVs), have a substantial impact in ASD risk1, and are associated with specific phenotypic manifestations2. Recent studies reported that rare inherited CNVs are enriched in mothers of ASD children compared with mothers of controls and are preferentially transmitted from mothers to ASD children suggesting a sex bias in CNV transmission; further, the imbalanced transmission of small pathogenic CNVs from unaffected mothers to their sons with ASD has been described3,4. An increased prevalence of autism-like personality traits is found in unaffected relatives of ASD children, suggesting a genetic liability of a broader autism phenotype (BAP)5. The BAP in parents of autistic children can be assessed by the Social Responsiveness Scale (SRS)6 and Broad Autism Phenotype Questionnaire (BAPQ)7 reports. The SRS is 65-item questionnaire to identify sub-clinical social impairments and interpersonal behaviour in individuals. The BAPQ is a 36-item questionnaire measures social aloofness, rigid personality, and pragmatic language deficits in both parents and children.

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Brazil is one of the largest beef producers and exporters in the world with the Nelore breed representing the vast majority of Brazilian cattle (Bos taurus indicus). Despite the great adaptability of the Nelore breed to tropical climate, meat tenderness (MT) remains to be improved. Several factors including genetic composition can influence MT. In this article, we report a genome-wide analysis of copy number variation (CNV) inferred from Illumina1 High Density SNP-chip data for a Nelore population of 723 males. We detected >2,600 CNV regions (CNVRs) representing 6.5% of the genome. Comparing our results with previous studies revealed an overlap in 1400 CNVRs (>50%). A total of 1,155 CNVRs (43.6%) overlapped 2,750 genes. They were enriched for processes involving guanosine triphosphate (GTP), previously reported to influence skeletal muscle physiology and morphology. Nelore CNVRs also overlapped QTLs for MT reported in other breeds (8.9%, 236 CNVRs) and from a previous study with this population (4.1%, 109 CNVRs). Two CNVRs were also proximal to glutathione metabolism genes that were previously associated with MT. Genome-wide association study of CN state with estimated breeding values derived from meat shear force identified 6 regions, including a region on BTA3 that contains genes of the cAMP and cGMP pathway. Ten CNVRs that overlapped regions associated with MT were successfully validated by qPCR. Our results represent the first comprehensive CNV study in Bos taurus indicus cattle and identify regions in which copy number changes are potentially of importance for the MT phenotype.

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Background Schizophrenia is associated with lower pre-morbid intelligence (IQ) in addition to (pre-morbid) cognitive decline. Both schizophrenia and IQ are highly heritable traits. Therefore, we hypothesized that genetic variants associated with schizophrenia, including copy number variants (CNVs) and a polygenic schizophrenia (risk) score (PSS), may influence intelligence. Method IQ was estimated with the Wechsler Adult Intelligence Scale (WAIS). CNVs were determined from single nucleotide polymorphism (SNP) data using the QuantiSNP and PennCNV algorithms. For the PSS, odds ratios for genome-wide SNP data were calculated in a sample collected by the Psychiatric Genome-Wide Association Study (GWAS) Consortium (8690 schizophrenia patients and 11 831 controls). These were used to calculate individual PSSs in our independent sample of 350 schizophrenia patients and 322 healthy controls. Results Although significantly more genes were disrupted by deletions in schizophrenia patients compared to controls (p = 0.009), there was no effect of CNV measures on IQ. The PSS was associated with disease status (R 2 = 0.055, p = 2.1 × 10 -7) and with IQ in the entire sample (R 2 = 0.018, p = 0.0008) but the effect on IQ disappeared after correction for disease status. Conclusions Our data suggest that rare and common schizophrenia-associated variants do not explain the variation in IQ in healthy subjects or in schizophrenia patients. Thus, reductions in IQ in schizophrenia patients may be secondary to other processes related to schizophrenia risk. © Cambridge University Press 2013.

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Copy number variations (CNVs) as described in the healthy population are purported to contribute significantly to genetic heterogeneity. Recent studies have described CNVs using lymphoblastoid cell lines or by application of specifically developed algorithms to interrogate previously described data. However, the full extent of CNVs remains unclear. Using high-density SNP array, we have undertaken a comprehensive investigation of chromosome 18 for CNV discovery and characterisation of distribution and association with chromosome architecture. We identified 399 CNVs, of which loss represents 98%, 58% are less than 2.5 kb in size and 71% are intergenic. Intronic deletions account for the majority of copy number changes with gene involvement. Furthermore, one-third of CNVs do not have putative breakpoints within repetitive sequences. We conclude that replicative processes, mediated either by repetitive elements or microhomology, account for the majority of CNVs in the healthy population. Genomic instability involving the formation of a non-B structure is demonstrated in one region.

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Genome-wide association studies followed by replication provide a powerful approach to map genetic risk factors for asthma. We sought to search for new variants associated with asthma and attempt to replicate the association with four loci reported previously (ORMDL3, PDE4D, DENND1B and IL1RL1). Genome-wide association analyses of individual single nucleotide polymorphisms (SNPs), rare copy number variants (CNVs) and overall CNV burden were carried out in 986 asthma cases and 1846 asthma-free controls from Australia. The most-associated locus in the SNP analysis was ORMDL3 (rs6503525, P = 4.8 x 10(-)(7)). Five other loci were associated with P < 10(-)(5), most notably the chemokine CXC motif ligand 14 (CXCL14) gene (rs31263, P = 7.8 x 10(-)(6)). We found no evidence for association with the specific risk variants reported recently for PDE4D, DENND1B and ILR1L1. However, a variant in IL1RL1 that is in low linkage disequilibrium with that reported previously was associated with asthma risk after accounting for all variants tested (rs10197862, gene wide P = 0.01). This association replicated convincingly in an independent cohort (P = 2.4 x 10(-)(4)). A 300-kb deletion on chromosome 17q21 was associated with asthma risk, but this did not reach experiment-wide significance. Asthma cases and controls had comparable CNV rates, length and number of genes affected by deletions or duplications. In conclusion, we confirm the association between asthma risk and variants in ORMDL3 and identify a novel risk variant in IL1RL1. Follow-up of the 17q21 deletion in larger cohorts is warranted.

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Large-scale chromosome rearrangements such as copy number variants (CNVs) and inversions encompass a considerable proportion of the genetic variation between human individuals. In a number of cases, they have been closely linked with various inheritable diseases. Single-nucleotide polymorphisms (SNPs) are another large part of the genetic variance between individuals. They are also typically abundant and their measuring is straightforward and cheap. This thesis presents computational means of using SNPs to detect the presence of inversions and deletions, a particular variety of CNVs. Technically, the inversion-detection algorithm detects the suppressed recombination rate between inverted and non-inverted haplotype populations whereas the deletion-detection algorithm uses the EM-algorithm to estimate the haplotype frequencies of a window with and without a deletion haplotype. As a contribution to population biology, a coalescent simulator for simulating inversion polymorphisms has been developed. Coalescent simulation is a backward-in-time method of modelling population ancestry. Technically, the simulator also models multiple crossovers by using the Counting model as the chiasma interference model. Finally, this thesis includes an experimental section. The aforementioned methods were tested on synthetic data to evaluate their power and specificity. They were also applied to the HapMap Phase II and Phase III data sets, yielding a number of candidates for previously unknown inversions, deletions and also correctly detecting known such rearrangements.

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A Deficiência Intelectual (DI) é uma condição complexa, que acomete 2-3% da população mundial, constituindo um importante problema de saúde pública. No entanto, uma parcela significativa dos casos de DI permanece sem um diagnóstico definitivo, o que demonstra que muitos fatores etiológicos associados a esta condição ainda precisam ser elucidados. Há um consenso de que o número de homens com DI supera em 30% o número de mulheres, um achado atribuído à presença de mutações em genes localizados no cromossomo X. Dentre os genes presentes neste cromossomo que são expressos no cérebro, o Jumonji AT-rich interactive domain 1C (JARID1C) foi identificado como um potencial candidato a estar relacionado à DI ligada ao X (DILX). O gene JARID1C codifica uma desmetilase da lisina 4 da histona H3 (H3K4), imprescindível para a regulação epigenética. Tão importante quanto o estudo do gene JARID1C em pacientes com DI é a busca por variações no número de cópias gênicas (VNCs) em regiões cromossômicas subteloméricas. Genes relacionados ao desenvolvimento cerebral são enriquecidos em VNCs e as regiões subteloméricas são mais susceptíveis à formação destes rearranjos. Diante do exposto, neste estudo, investigamos mutações no gene JARID1C (exons 3, 4, 5, 8, 10, 14 e 23) em 148 homens portadores de DI pertencentes a famílias com padrão de segregação sugestivo de DILX. Paralelamente, analisamos VNCs subteloméricas em 174 homens com DI familiar de etiologia idiopática, independente do padrão de segregação. Para todos os indivíduos selecionados, amostras de DNA genômico foram extraídas a partir de sangue periférico e alterações genéticas frequentemente relacionadas à DI foram previamente excluídas (expansões trinucleotídicas nos loci FRAXA e FRAXE e mutações nos genes MECP2 e ARX). A análise do gene JARID1C foi realizada pela técnica de PCR, seguida da análise dos produtos amplificados por sequenciamento. Foram identificadas quatro variantes silenciosas (c.564G>A, c.633G>C, c.1884G>A, c.1902C>A). Através da análise in silico de sequências exônicas acentuadoras de splicing (ESEs) localizadas nas posições das variantes encontradas, foi possível classificar a variante c.1884G>A como neutra e as três variantes restantes como possíveis criadoras de ESEs. Já para a investigação das VNCs subteloméricas, foi utilizada a metodologia de Multiplex Ligation-dependent Probe Amplification (MLPA), capaz de identificar microdeleções e microduplicações nas 46 regiões subteloméricas. Para este fim, inicialmente, os indivíduos foram investigados pelo kit de MLPA P036, enquanto que para aqueles que exibiram alterações também foi utilizado o kit P070. A validação das VNCs encontradas foi realizada por PCR quantitativo em Tempo Real. A análise por MLPA revelou um indivíduo apresentando duas deleções (9p e 13q), um indivíduo apresentando duas amplificações (1p e 2p), dois indivíduos apresentando uma deleção e uma amplificação (18p e 18q; 4p e 8p), quatro indivíduos portadores de uma deleção cada (10p, 20p, 3q e 22q) e dois indivíduos com uma amplificação cada (7q e 20p). Algumas das alterações subteloméricas encontradas (2,87%) representam VNCs de relevância clínica para o estudo da DI, reforçando a importância do rastreamento de rotina de VNCs subteloméricas na DI familiar. Consideramos que a elucidação de novos genes ou mecanismos moleculares diretamente relacionados à DI é um caminho promissor e urgente para o estabelecimento de novas estratégias terapêuticas possíveis.

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Background Single nucleotide polymorphisms (SNPs) have been used extensively in genetics and epidemiology studies. Traditionally, SNPs that did not pass the Hardy-Weinberg equilibrium (HWE) test were excluded from these analyses. Many investigators have addressed possible causes for departure from HWE, including genotyping errors, population admixture and segmental duplication. Recent large-scale surveys have revealed abundant structural variations in the human genome, including copy number variations (CNVs). This suggests that a significant number of SNPs must be within these regions, which may cause deviation from HWE. Results We performed a Bayesian analysis on the potential effect of copy number variation, segmental duplication and genotyping errors on the behavior of SNPs. Our results suggest that copy number variation is a major factor of HWE violation for SNPs with a small minor allele frequency, when the sample size is large and the genotyping error rate is 0~1%. Conclusions Our study provides the posterior probability that a SNP falls in a CNV or a segmental duplication, given the observed allele frequency of the SNP, sample size and the significance level of HWE testing.

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Determination of copy number variants (CNVs) inferred in genome wide single nucleotide polymorphism arrays has shown increasing utility in genetic variant disease associations. Several CNV detection methods are available, but differences in CNV call thresholds and characteristics exist. We evaluated the relative performance of seven methods: circular binary segmentation, CNVFinder, cnvPartition, gain and loss of DNA, Nexus algorithms, PennCNV and QuantiSNP. Tested data included real and simulated Illumina HumHap 550 data from the Singapore cohort study of the risk factors for Myopia (SCORM) and simulated data from Affymetrix 6.0 and platform-independent distributions. The normalized singleton ratio (NSR) is proposed as a metric for parameter optimization before enacting full analysis. We used 10 SCORM samples for optimizing parameter settings for each method and then evaluated method performance at optimal parameters using 100 SCORM samples. The statistical power, false positive rates, and receiver operating characteristic (ROC) curve residuals were evaluated by simulation studies. Optimal parameters, as determined by NSR and ROC curve residuals, were consistent across datasets. QuantiSNP outperformed other methods based on ROC curve residuals over most datasets. Nexus Rank and SNPRank have low specificity and high power. Nexus Rank calls oversized CNVs. PennCNV detects one of the fewest numbers of CNVs.

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We conducted a genome-wide association study testing single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) for association with early-onset myocardial infarction in 2,967 cases and 3,075 controls. We carried out replication in an independent sample with an effective sample size of up to 19,492. SNPs at nine loci reached genome-wide significance: three are newly identified (21q22 near MRPS6-SLC5A3-KCNE2, 6p24 in PHACTR1 and 2q33 in WDR12) and six replicated prior observations1-4 (9p21, 1p13 near CELSR2-PSRC1-SORT1, 10q11 near CXCL12, 1q41 in MIA3, 19p13 near LDLR and 1p32 near PCSK9). We tested 554 common copy number polymorphisms (>1% allele frequency) and none met the pre-specified threshold for replication (P < 10-3). We identified 8,065 rare CNVs but did not detect a greater CNV burden in cases compared to controls, in genes compared to the genome as a whole, or at any individual locus. SNPs at nine loci were reproducibly associated with myocardial infarction, but tests of common and rare CNVs failed to identify additional associations with myocardial infarction risk.

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OBJECTIVE The authors used a genome-wide association study (GWAS) of multiply affected families to investigate the association of schizophrenia to common single-nucleotide polymorphisms (SNPs) and rare copy number variants (CNVs). METHOD The family sample included 2,461 individuals from 631 pedigrees (581 in the primary European-ancestry analyses). Association was tested for single SNPs and genetic pathways. Polygenic scores based on family study results were used to predict case-control status in the Schizophrenia Psychiatric GWAS Consortium (PGC) data set, and consistency of direction of effect with the family study was determined for top SNPs in the PGC GWAS analysis. Within-family segregation was examined for schizophrenia-associated rare CNVs. RESULTS No genome-wide significant associations were observed for single SNPs or for pathways. PGC case and control subjects had significantly different genome-wide polygenic scores (computed by weighting their genotypes by log-odds ratios from the family study) (best p=10-17, explaining 0.4% of the variance). Family study and PGC analyses had consistent directions for 37 of the 58 independent best PGC SNPs (p=0.024). The overall frequency of CNVs in regions with reported associations with schizophrenia (chromosomes 1q21.1, 15q13.3, 16p11.2, and 22q11.2 and the neurexin-1 gene [NRXN1]) was similar to previous case-control studies. NRXN1 deletions and 16p11.2 duplications (both of which were transmitted from parents) and 22q11.2 deletions (de novo in four cases) did not segregate with schizophrenia in families. CONCLUSIONS Many common SNPs are likely to contribute to schizophrenia risk, with substantial overlap in genetic risk factors between multiply affected families and cases in large case-control studies. Our findings are consistent with a role for specific CNVs in disease pathogenesis, but the partial segregation of some CNVs with schizophrenia suggests that researchers should exercise caution in using them for predictive genetic testing until their effects in diverse populations have been fully studied.