SNP-Array Genome Wide Association Study Meta-Analysis Identifies Innate Immune Susceptibility Loci Associated with Non-Del(5q) Myelodysplastic Syndromes Predisposition
Kathy L. McGrawChia‐Ho ChengY. Ann ChenHsin‐An HouGuilio GenoveseThomas CluzeauAndrea PellagattiBartlomiej PrzychodzenMar MalloArenillas LeonorAzim MohamedaliLionel AdèsDavid A. SallmanEric PadronLubomir SokolChimène MoreilhonSophie RaynaudBjörn NilssonHwei‐Fang TienJacqueline BoultwoodBenjamin L. EbertFrançesc SoléPierre FenauxGhulam MuftiJaroslaw P. MaciejewskiPeter A. KanetskyAlan F. List
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Keywords:
Genome-wide Association Study
Imputation (statistics)
SNP array
SNP
Genetic Association
Genome‐wide association studies (GWAS) are a popular approach for identifying common genetic variants and epistatic effects associated with a disease phenotype. The traditional statistical analysis of such GWAS attempts to assess the association between each individual single‐nucleotide polymorphism (SNP) and the observed phenotype. Recently, kernel machine‐based tests for association between a SNP set (e.g., SNPs in a gene) and the disease phenotype have been proposed as a useful alternative to the traditional individual‐SNP approach, and allow for flexible modeling of the potentially complicated joint SNP effects in a SNP set while adjusting for covariates. We extend the kernel machine framework to accommodate related subjects from multiple independent families, and provide a score‐based variance component test for assessing the association of a given SNP set with a continuous phenotype, while adjusting for additional covariates and accounting for within‐family correlation. We illustrate the proposed method using simulation studies and an application to genetic data from the Genetic Epidemiology Network of Arteriopathy (GENOA) study.
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Genome-wide association studies (GWAS) play a critical role in identifying many loci for common diseases and traits. There has been a rapid increase in the number of GWAS over the past decade. As additional GWAS are being conducted, it is unclear whether a novel signal associated with the trait of interest is independent of single nucleotide polymorphisms (SNPs) in the same region that has been previously associated with the trait of interest. The general approach to determining whether the novel association is independent of previous signals is to examine the association of the novel SNP with the trait of interest conditional on the previously identified SNP and/or calculate linkage disequilibrium (LD) between the two SNPs. However, the role of epistasis and SNP by SNP interactions are rarely considered. Through simulation studies, we examined the role of SNP by SNP interactions when determining the independence of two genetic association signals. We have created an R package on Github called gxgRC to generate these simulation studies based on user input. In genetic association studies of asthma, we considered the role of SNP by SNP interactions when determining independence of signals for SNPs in the ARG1 gene and bronchodilator response.
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Sézary syndrome (SS) is a rare variant of primary cutaneous T-cell lymphoma. Little is known about the underlying pathogenesis of S. To address this issue, we used Affymetrix 10K SNP microarray to analyse 13 DNA samples isolated from 8 SS patients and qPCR with ABI TaqMan SNP genotyping assays for the validation of the SNP microarray results. In addition, we tested the impact of SNP loss of heterozygosity (LOH) identified in SS cases on the gene expression profiles of SS cases detected with Affymetrix GeneChip U133A. The results showed: (1) frequent SNP copy number change and LOH involving 1, 2p, 3, 4q, 5q, 6, 7p, 8, 9, 10, 11, 12q, 13, 14, 16q, 17, and 20, (2) reduced SNP copy number at FAT gene (4q35) in 75% of SS cases, and (3) the separation of all SS cases from normal control samples by SNP LOH gene clusters at chromosome regions of 9q31q34, 10p11q26, and 13q11q12. These findings provide some intriguing information for our current understanding of the molecular pathogenesis of this tumour and suggest the possibility of presence of functional SNP LOH in SS tumour cells.
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To apply single nucleotide polymorphism array (SNP-array) for the diagnosis of Williams-Beuren syndrome (WBS) in a patient.Chromosome G-banding and SNP-array were used to analyze a girl featuring mental retardation.The karyotypes of the child and her parents were all normal, but SNP-array showed a 1.9 Mb deletion at 7q11.23 in the patient. The same deletion was not found in her parents.The mental retardation and special facies of the girl were probably due to the 7q11.23 microdeletion. SNP-array has an important value for the diagnosis of mental retardation.
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A genome-wide association study (GWAS) rapidly scans DNA markers in many individuals to find genetic links to diseases. New findings aid in disease detection, treatment and prevention. Imputation predicts untyped genotypes in genetic studies when data is missing due to quality, cost, or design issues. It’s a proven statistical technique for estimating unobserved genotypes by borrowing haplotype segments from a densely genotyped reference panel. This allows estimation and testing of associations at unassayed variants.Genotype imputation is vital in analyzing genome-wide association scans, helping geneticists evaluate evidence for association at untyped genetic markers. This summary outlines missing data issues and various imputation methods.
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Single Nucleotide Polymorphism (SNP) is a DNA sequence variation caused by the mutation at the level of genomic nucleotides. It has been reported as the third generation of genetic markers. The SNP-arrays, based on the principle of SNP, plays an important role in disease research mainly for genomic detection of predisposing genes. As a convenient, confident, sensitive and efficient technique, SNP arrays could be applicable for the multiple-point interaction analysis of candidate genes, making it a promising and powerful method for DNA analysis. Hematological malignancies consist of various categories and their incidence is rising significantly. A multiple-point gene interaction has been reported as the essential pathogenetic mechanism of these diseases. This review illustrates the process of SNP-arrays in genome-wide assay and the application of this technique to the pathogenesis, clinical manifestation, therapeutic response and the prognosis of the hematological malignancies, including leukemia, malignant lymphoma, juvenile myelo-monocytic leukemia, myelodysplastic syndrome, multiple myeloma and so on.
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Single-nucleotide polymorphism (SNP) arrays have been shown to identify cytogenetic abnormalities in myeloid neoplasms that may be missed by metaphase cytogenetics alone at initial diagnosis. This study examines the utility of serial SNP arrays in follow-up testing of myeloid neoplasms.We retrospectively reviewed results of SNP array testing in 44 patients with myeloid neoplasms and more than one SNP array study (n = 133 SNP arrays total; median, three per patient; range, two to eight per patient).Baseline abnormalities were identified by SNP array in 35 (79%) of 44 (79%) compared with 18 (50%) of 36 by metaphase karyotype. In follow-up studies, clonal evolution was found by both SNP array and karyotyping in seven (15.9%), by metaphase karyotyping alone in six (13.6%), and SNP arrays alone in two (4.5%). Overall survival was not significantly different between patients with or without clonal evolution detected by SNP array.This study, the first systematic examination of serial SNP arrays in myeloid neoplasms, confirms the clinical utility of SNP arrays at initial diagnosis but shows that clonal evolution of the karyotype can be detected by metaphase cytogenetics alone in most patients. Follow-up SNP array testing is not required in routine clinical use in most cases.
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To analyze a case with Angelman syndrome (AS) using single nucleotide polymorphism array (SNP array) and explore its genotype-phenotype correlation.G-banded karyotyping and SNP array were performed on a child featuring congenital malformations, intellectual disability and developmental delay. Mendelian error checking based on the SNP information was used to delineate the parental origin of detected abnormality. Result of the SNP array was validated with fluorescence in situ hybridization (FISH).The SNP array has detected a 6.053 Mb deletion at 15q11.2q13.1 (22,770,421- 28,823,722) which overlapped with the critical region of AS (type 1). The parents of the child showed no abnormal results for G-banded karyotyping, SNP array and FISH analysis, indicating a de novo origin of the deletion. Mendelian error checking based on the SNP information suggested that the 15q11.2q13.1 deletion was of maternal origin.SNP array can accurately define the size, location and parental origin of chromosomal microdeletions, which may facilitate the diagnosis of AS due to 15q11q13 deletion and better understanding of its genotype-phenotype correlation.
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Molecular Inversion Probe
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Background: Single nucleotide polymorphism array (SNP-array) has been introduced for prenatal diagnosis. We aimed to evaluate the clinical value of SNP-array in the diagnosis of fetal chromosomal anomalies. Methods: A retrospective study was conducted on 5000 cases tested by SNP-array, and the results of 4022 cases analyzed by both karyotyping and SNP-array were compared. Results: SNP-array analysis of 5000 samples revealed that the overall abnormality detection rate by SNP-array was 12.3%, and the overall detection rate of clinically significant copy number variations (CNVs) by SNP-array was 2.6%. SNP-array identified clinically significant submicroscopic CNVs in 4.5% fetuses with anomaly on ultrasonography, in 1.6% of fetuses with AMA, in 2.5% of fetuses with abnormal result on maternal serum screening, in 2.9% of fetuses with abnormal non-invasive prenatal testing (NIPT) results and in 3.0% of fetuses with other indications. Of the 4022 samples analyzed by both karyotyping and SNP-array, SNP-array could identify all the aneuploidy and triploidy detected by karyotyping but did not identify balanced structural chromosomal abnormalities and low-level mosaicism detected by karyotyping. Conclusions: SNP-array could additionally identify clinically significant submicroscopic CNVs, and we recommend the combination of SNP-array analysis and karyotyping in prenatal diagnosis.
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Products of conception
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