Copy number variation analysis in Japanese children with Autsim Spectrum Disorder by Affymetrix Genome-Wide Human SNP Array 6.0.
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA605341 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Autism spectrum disorder (ASD) is an innate neurodevelopmental disorder characterized by impairments in social communication/interaction, repetitive and restrictive behavior. Copy number variation (CNV) is a one of the structural variation of the genomic sequence, including large multiplications and deletions ranging from kb to Mb of DNA. These multiplication-deletion provide genomic diversity, while CNV affects the amount of gene products or transcriptional regulation, and result in strong association with biological process, metabolism and disease. In facts, many studies reported that the mapping of CNVs which strongly associated with ASD. The subjects of this study were the community-based 5 years old children because they might be able to except acquired effects after birth as much as possible and focus on the genetic background, and there are possibilities that the results will be specific to the Japanese patients with ASD.
2020-08-01 | GSE144918 | GEO
Project description:ObjectiveAlthough autism spectrum disorder (ASD) occurs worldwide, most genomic studies on ASD were performed on those of Western ancestry. We hypothesized ASD-related copy number variations (CNVs) of Japanese individuals might be different from those of Western individuals.MethodsSubjects were recruited from the Hirosaki 5-year-old children's developmental health check-up (HFC) between 2013 and 2016 (ASD group; n = 68, control group; n = 124). This study conducted CNV analysis using genomic DNA from peripheral blood of 5-year-old Japanese children. Fisher's exact test was applied for profiling subjects and CNV loci.ResultsFour ASD-related CNVs: deletion at 12p11.1, duplications at 4q13.2, 8p23.1 and 18q12.3 were detected (P = 0.015, 0.024, 0.009, 0.004, respectively). Specifically, the odds ratio of duplication at 18q12.3 was highest among the 4 CNVs (odds ratio, 8.13).ConclusionsFour CNVs: microdeletion at 12p11.1, microduplications at 4q13.2, 8p23.1 and 18q12.3 were detected as ASD-related CNVs in Japanese children in this study. Although these CNVs were consistent with several reports by Western countries at cytoband levels, these did not consistent at detailed genomic positions and sizes. Our data indicate the possibility that these CNVs are characteristic of Japanese children with ASD. We conclude that Japanese individuals with ASD may harbor CNVs different from those of Western individuals with ASD.
| S-EPMC8115735 | biostudies-literature
Project description:Human pluripotent stem cell (hPSC) lines exhibit repeated patterns of genetic variation, which can alter in vitro properties as well as suitability for clinical use. We examined associations between copy number variations (CNVs) on chromosome 17 and hPSC mesodiencephalic dopaminergic (mDA) differentiation. Affymetrix SNP arrays were performed according to the manufacturer's directions on DNA extracted from cryopreserved stem cell samples. Copy number analysis of Affymetrix Genome-Wide Human SNP Array 6.0 was performed for 17 stem cell samples.
2014-12-17 | E-GEOD-64241 | biostudies-arrayexpress
Project description:Autism spectrum disorder (ASD) is a complex heterogeneous developmental disease with a significant genetic background that is frequently caused by rare copy number variants (CNV). The aim of the study was to identify new candidate genes for ASD in the studied cohort of ASD-diagnosed patients. We used chromosomal microarray analysis (CMA) - a Cytoscan HD (Affymetrix, Santa Clara, CA, USA) to detect CNV in 87 ASD patients and their relatives and evaluated their clinical significance. Pathogenic and likely pathogenic mutations were identified by CMA in 8 and 9 ASD patients, respectively. CMA revealed 89 rare CNV: 8 pathogenic, 12 designated VOUS - likely pathogenic, 12 VOUS - uncertain, and 57 VOUS - likely benign or benign. CNV (pathogenic/VOUS-likely pathogenic/VOUS - uncertain) overlapping the same gene in more than one patient were observed in DOCK8 gene and PARK2 gene. This work presents new evidence about the possible roles of PARK2 and DOCK8 in the etiology of ASD, and suggests CTNNA2 as a candidate gene for ASD risk.
2018-05-25 | GSE114870 | GEO
Project description:Affymetrix CytoScan HD for autism spectrum disorder in children
| PRJNA472953 | ENA
Project description:BackgroundCopy number data are routinely being extracted from genome-wide association study chips using a variety of software. We empirically evaluated and compared four freely-available software packages designed for Affymetrix SNP chips to estimate copy number: Affymetrix Power Tools (APT), Aroma.Affymetrix, PennCNV and CRLMM. Our evaluation used 1,418 GENOA samples that were genotyped on the Affymetrix Genome-Wide Human SNP Array 6.0. We compared bias and variance in the locus-level copy number data, the concordance amongst regions of copy number gains/deletions and the false-positive rate amongst deleted segments.ResultsAPT had median locus-level copy numbers closest to a value of two, whereas PennCNV and Aroma.Affymetrix had the smallest variability associated with the median copy number. Of those evaluated, only PennCNV provides copy number specific quality-control metrics and identified 136 poor CNV samples. Regions of copy number variation (CNV) were detected using the hidden Markov models provided within PennCNV and CRLMM/VanillaIce. PennCNV detected more CNVs than CRLMM/VanillaIce; the median number of CNVs detected per sample was 39 and 30, respectively. PennCNV detected most of the regions that CRLMM/VanillaIce did as well as additional CNV regions. The median concordance between PennCNV and CRLMM/VanillaIce was 47.9% for duplications and 51.5% for deletions. The estimated false-positive rate associated with deletions was similar for PennCNV and CRLMM/VanillaIce.ConclusionsIf the objective is to perform statistical tests on the locus-level copy number data, our empirical results suggest that PennCNV or Aroma.Affymetrix is optimal. If the objective is to perform statistical tests on the summarized segmented data then PennCNV would be preferred over CRLMM/VanillaIce. Specifically, PennCNV allows the analyst to estimate locus-level copy number, perform segmentation and evaluate CNV-specific quality-control metrics within a single software package. PennCNV has relatively small bias, small variability and detects more regions while maintaining a similar estimated false-positive rate as CRLMM/VanillaIce. More generally, we advocate that software developers need to provide guidance with respect to evaluating and choosing optimal settings in order to obtain optimal results for an individual dataset. Until such guidance exists, we recommend trying multiple algorithms, evaluating concordance/discordance and subsequently consider the union of regions for downstream association tests.
| S-EPMC3146450 | biostudies-literature
Project description:DNA from four 29 cases, 38 tumor samples (23 PB, 12 LN, 1 Tonsil, 1 colonic biopsy, 1 spleen) and 29 normal DNA from the same patients were analyzed with Affymetrix SNP 6.0 platform for copy number alterations study. Affymetrix SNP arrays were performed according to the manufacturer's directions on DNA extracted from blood samples, lymph nodes and other tissues like spleen, tonsil and colonic biopsy
2013-11-04 | GSE46969 | GEO
Project description:Fresh frozen Melanoma patient samples were profiled on Affymetrix GeneChip Mapping 100K Set Arrays
2013-10-15 | GSE41592 | GEO
Project description:Reports on common mutations in neuroendocrine tumors (NET) are rare and clonality of NET metastases has not been investigated in this tumor entity yet. We selected a NET and a the corresponding lymph node and liver metastases as well as the derivative cell lines to screen for somatic mutations in the primary NET and to track the fate of genetic changes (by Affymetrix SNP 6.0 micorarray and targeted resequencing by 454 GS FLX) and during metastasis and in vitro progression. using Affymetrix SNP 6.0 Arrays.
2012-07-17 | GSE39371 | GEO