Genome-wide study of copy number variation implicates multiple novel loci for schizophrenia risk in Han Chinese family trios.
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ABSTRACT:
SUBMITTER: Wu X
PROVIDER: S-EPMC8358640 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:To reveal the risk CNVs of SZ in Chinese population, we recrited and enrolled 100 Chinese family trios with a schizophrenia affected children and both of their father and mother. SZ was diagnosed according to DSM-IV criteria by two independent psychiatrists. There gDNA we screen the genome-wide CNV using Agilent SurePrint G3 Human CGH Microarray Kit (1x1M) and Agilent sex-matched human DNA was used as reference. The CNV were called by ADM-2 statistical algorithms with a threshold of 6.0. We compared the burden of large rare CNVs and found that SZ probands carried more duplications and less deletions. Furtherly, we performed familial inheritance analysis of transmission disequilibrium and de novo CNV detection, validated several associated CNV loci with SZ susceptibility and also identify eight novel loci conferring risk of SZ
2021-10-01 | E-MTAB-8075 | biostudies-arrayexpress
Project description:BackgroundAutism spectrum disorders (ASDs) are a group of neurodevelopmental conditions with a demonstrated genetic etiology. Rare (<1% frequency) copy number variations (CNVs) account for a proportion of the genetic events involved, but the contribution of these events in non-European ASD populations has not been well studied. Here, we report on rare CNVs detected in a cohort of individuals with ASD of Han Chinese background.MethodsDNA samples were obtained from 104 ASD probands and their parents who were recruited from Harbin, China. Samples were genotyped on the Affymetrix CytoScan HD platform. Rare CNVs were identified by comparing data with 873 technology-matched controls from Ontario and 1,235 additional population controls of Han Chinese ethnicity.ResultsOf the probands, 8.6% had at least 1 de novo CNV (overlapping the GIGYF2, SPRY1, 16p13.3, 16p11.2, 17p13.3-17p13.2, DMD, and NAP1L6 genes/loci). Rare inherited CNVs affected other plausible neurodevelopmental candidate genes including GRID2, LINGO2, and SLC39A12. A 24-kb duplication was also identified at YWHAE, a gene previously implicated in ASD and other developmental disorders. This duplication is observed at a similar frequency in cases and in population controls and is likely a benign Asian-specific copy number polymorphism.ConclusionsOur findings help define genomic features relevant to ASD in the Han Chinese and emphasize the importance of using ancestry-matched controls in medical genetic interpretations.
| S-EPMC4147384 | biostudies-literature
Project description:BackgroundResponse to antipsychotic drugs (APD) varies greatly among individuals and is affected by genetic factors. This study aims to demonstrate genome-wide associations between copy number variants (CNVs) and response to APD in patients with schizophrenia.MethodsA total of 3030 patients of Han Chinese ethnicity randomly received APD (aripiprazole, olanzapine, quetiapine, risperidone, ziprasidone, haloperidol and perphenazine) treatment for six weeks. This study is a secondary data analysis. Percentage change on the Positive and Negative Syndrome Scale (PANSS) reduction was used to assess APD efficacy, and more than 50% change was considered as APD response. Associations between CNV burden, gene set, CNV loci and CNV break-point and APD efficacy were analysed.FindingsHigher CNV losses burden decreased the odds of 6-week APD response (OR = 0.66 [0.44, 0.98]). CNV losses in synaptic pathway involved in neurotransmitters were associated with 2-week PANSS reduction rate. CNV involved in sialylation (1p31.1 losses) and cellular metabolism (19q13.32 gains) associated with 6-week PANSS reduction rate at genome-wide significant level. Additional 36 CNVs associated with PANSS factors improvement. The OR of protective CNVs for 6-week APD response was 3.10 (95% CI: 1.33-7.19) and risk CNVs was 8.47 (95% CI: 1.92-37.43). CNV interacted with genetic risk score on APD efficacy (Beta = -1.53, SE = 0.66, P = 0.021). The area under curve to differ 6-week APD response attained 80.45% (95% CI: 78.07%-82.82%).InterpretationCopy number variants contributed to poor APD efficacy and synaptic pathway involved in neurotransmitter was highlighted.FundingNational Natural Science Foundation of China, National Key R&D Program of China, China Postdoctoral Science Foundation.
| S-EPMC11225184 | biostudies-literature
Project description:Generally, copy number variation (CNV) is a large-scale structural variation between 50 bp and 1 kb of the genome. It can affect gene expression and is an important reason for genetic diversity and phenotypic trait diversity. Studies have shown that the eukaryotic translation initiation factor 4A2 (EIF4A2) gene plays an essential role in muscle development in both humans and pigs. However, the influence of bovine EIF4A2's copy number change on phenotypic traits has not been reported. To detect the tissue expression profile of the EIF4A2 gene in adult cattle and individuals' CNV type of variation. Then, we explored the correlation between EIF4A2-CNV and growth traits in Chinese cattle breeds. Real-time fluorescent quantitative reverse transcription PCR (qRT-qPCR) was used to determine the expression profile of the EIF4A2 gene. Real-time fluorescent quantitative PCR (qPCR) was used to detect the CNV type of bovine populations. Then, SPSS 26.0 was used for association analysis. In this study, a total of 513 individuals in four cattle breeds (Qinchuan cattle [QC], Yunling cattle [YL], Pinan cattle [PN] and Jiaxian cattle [JX]) were detected for EIF4A2 gene's CNV. The results showed that EIF4A2-CNV has an essential impact on hip width (HW) and rump length (RL) in QC, heart girth (HG), chest depth (CD) and RL in YL and HW in PN. However, it had no significant effect on JX. The above results suggest that EIF4A2 gene's CNV can be used as a molecular marker for cattle breeding, which is helpful to accelerate the breeding of superior beef cattle breeds.
| S-EPMC9514498 | biostudies-literature
Project description:Schizophrenia (SCZ) is a highly heritable neuropsychiatric disorder of complex genetic etiology. Previous genome-wide surveys have revealed a greater burden of large, rare copy number variations (CNVs) in SCZ cases and identified multiple rare recurrent CNVs that increase risk of SCZ although with incomplete penetrance and pleiotropic effects. Identification of additional recurrent CNVs and biological pathways enriched for SCZ CNVs requires greater sample sizes. We conducted a genome-wide survey for CNVs associated with SCZ using a Swedish national sample (4719 cases and 5917 controls). High-confidence CNV calls were generated using genotyping array intensity data, and their effect on risk of SCZ was measured. Our data confirm increased burden of large, rare CNVs in SCZ cases as well as significant associations for recurrent 16p11.2 duplications, 22q11.2 deletions and 3q29 deletions. We report a novel association for 17q12 duplications (odds ratio=4.16, P=0.018), previously associated with autism and mental retardation but not SCZ. Intriguingly, gene set association analyses implicate biological pathways previously associated with SCZ through common variation and exome sequencing (calcium channel signaling and binding partners of the fragile X mental retardation protein). We found significantly increased burden of the largest CNVs (>500 kb) in genes present in the postsynaptic density, in genomic regions implicated via SCZ genome-wide association studies and in gene products localized to mitochondria and cytoplasm. Our findings suggest that multiple lines of genomic inquiry--genome-wide screens for CNVs, common variation and exonic variation--are converging on similar sets of pathways and/or genes.
| S-EPMC4271733 | 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:The gene that codes for dopamine receptor D2 (DRD2 on chromosome 11q23) has long been a prime functional and positional candidate risk gene for schizophrenia. Collectively, prior case-control studies found a reliable effect of the Ser311Cys DRD2 polymorphism (rs1801028) on risk for schizophrenia, but few other polymorphisms in the gene had ever been evaluated and no adequately powered family-based association study has been performed to date. Our objective was to test 21 haplotype-tagging and all three known nonsynonymous single-nucleotide polymorphisms (SNPs) in DRD2 for association with schizophrenia in a family-based study of 2408 Han Chinese, including 1214 affected individuals from 616 families. We did not find a significant effect of rs1801028, but we did find significant evidence for association of schizophrenia with two multi-marker haplotypes spanning blocks of strong linkage disequilibrium (LD) and nine individual SNPs (Ps<0.05). Importantly, two SNPs (rs1079727 and rs2283265) and both multi-marker haplotypes spanning entire LD blocks (including one that contained rs1801028) remained significant after correcting for multiple testing. These results further add to the body of data implicating DRD2 as a schizophrenia risk gene; however, a causal variant(s) in DRD2 remains to be elucidated by further fine mapping of the gene, with particular attention given to the area surrounding the third through fifth exons.
| S-EPMC2755547 | biostudies-literature
Project description:Schizophrenia (SCZ) is a highly heritable psychiatric disorder that affects approximately 1% of population around the world. However, early relevant studies did not reach clear conclusions of the genetic mechanisms of SCZ, suggesting that additional susceptibility loci that exert significant influence on SCZ are yet to be revealed. So, in order to identify novel susceptibility genes that account for the genetic risk of SCZ, we performed a systematic family-based study using whole exome sequencing (WES) in 65 Han Chinese families. The analysis of 51 SCZ trios with both unaffected parents identified 22 exonic and 1 splice-site de novo mutations (DNMs) on a total of 23 genes, and showed that 12 genes carried rare protein-altering compound heterozygous mutations in more than one trio. In addition, we identified 26 exonic or splice-site single nucleotide polymorphisms (SNPs) on 18 genes with nominal significance (P < 5 × 10-4) using a transmission disequilibrium test (TDT) in all the families. Moreover, TDT result confirmed a SCZ susceptibility locus on 3p21.1, encompassing the multigenetic region NEK4-ITIH1-ITIH3-ITIH4. Through several different strategies to predict the potential pathogenic genes in silico, we revealed 4 previous discovered susceptibility genes (TSNARE1, PBRM1, STAB1 and OLIG2) and 4 novel susceptibility loci (PSEN1, TLR5, MGAT5B and SSPO) in Han Chinese SCZ patients. In summary, we identified a list of putative candidate genes for SCZ using a family-based WES approach, thus improving our understanding of the pathology of SCZ and providing critical clues to future functional validation.
| S-EPMC7026419 | biostudies-literature
Project description:BackgroundSchizophrenia is associated with rare copy-number (CN) mutations. Screening for such alleles genome-wide, though comprehensive, cannot study in-depth the causality of particular loci, therefore cannot provide the functional interpretation for the disease etiology. We hypothesized that CN mutations in the SELENBP1 locus could associate with the disorder and that these mutations could alter the gene product's activity in patients.MethodsWe analyzed SELENBP1 CN variation (CNV) in blood DNA from 49 schizophrenia patients and 49 controls (cohort A). Since CN of genes may vary among tissues, we investigated SELENBP1 CN in age- sex- and postmortem interval-matched cerebellar DNA samples from 14 patients and 14 controls (cohort B). Since CNV may either be de-novo or inherited we analyzed CNV of the SELENBP1 locus in blood DNA from 26 trios of schizophrenia probands and their healthy parents (cohort C). SELENBP1 mRNA levels were measured by real-time PCR.ResultsIn cohort A reduced CN of the SELENBP1 locus was found in four patients but in none of the controls. In cohort B we found reduced CN of the SELENBP1 locus in two patients but in none of the controls. In cohort C three patients exhibited drastic CN reduction, not present in their parents, indicating de-novo mutation. A reduction in SELENBP1 mRNA levels in the postmortem cerebellar samples of schizophrenia patients was found.ConclusionsWe report a focused study of CN mutations in the selenium binding-protein1 (SELENBP1) locus previously linked with schizophrenia. We provide evidence for recurrence of decreased CN of the SELENBP1 locus in three unrelated patients' cohorts but not in controls, raising the possibility of functional involvement of these mutations in the etiology of the disease.
| S-EPMC2915948 | biostudies-literature
Project description:The analysis of structural variants, in particular of copy-number variations (CNVs), has proven valuable in unraveling the genetic basis of human diseases. Hence, a large number of algorithms have been developed for the detection of CNVs in SNP array signal intensity data. Using the European and African HapMap trio data, we undertook a comparative evaluation of six commonly used CNV detection software tools, namely Affymetrix Power Tools (APT), QuantiSNP, PennCNV, GLAD, R-gada and VEGA, and assessed their level of pair-wise prediction concordance. The tool-specific CNV prediction accuracy was assessed in silico by way of intra-familial validation. Software tools differed greatly in terms of the number and length of the CNVs predicted as well as the number of markers included in a CNV. All software tools predicted substantially more deletions than duplications. Intra-familial validation revealed consistently low levels of prediction accuracy as measured by the proportion of validated CNVs (34-60%). Moreover, up to 20% of apparent family-based validations were found to be due to chance alone. Software using Hidden Markov models (HMM) showed a trend to predict fewer CNVs than segmentation-based algorithms albeit with greater validity. PennCNV yielded the highest prediction accuracy (60.9%). Finally, the pairwise concordance of CNV prediction was found to vary widely with the software tools involved. We recommend HMM-based software, in particular PennCNV, rather than segmentation-based algorithms when validity is the primary concern of CNV detection. QuantiSNP may be used as an additional tool to detect sets of CNVs not detectable by the other tools. Our study also reemphasizes the need for laboratory-based validation, such as qPCR, of CNVs predicted in silico.
| S-EPMC4510559 | biostudies-literature