CSF pQTL study in the Japanese population [somascan]
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE83710 | GEO | 2016/12/30
SECONDARY ACCESSION(S): PRJNA326773
REPOSITORIES: GEO
Similar Datasets
Project description:Cerebrospinal fluid (CSF) is virtually the only one accessible source of proteins derived from the central nervous system (CNS) of living humans and possibly reflects the pathophysiology of a variety of neuropsychiatric diseases. However, little is known regarding the genetic basis of variation in protein levels of human CSF. We examined CSF levels of 1,126 proteins in 133 subjects and performed genome-wide association analysis of 514,227 single nucleotide polymorphisms (SNPs) to detect protein quantitative trait loci (pQTLs). Spearman’s correlation was used to identify association between genotypes of SNPs and protein levels. A total of 421 cis and 25 trans SNP-protein pairs were significantly correlated at a false discovery rate (FDR) of less than 0.01 (nominal P < 7.66 x 10 −9). Cis-only analysis revealed additional 580 significant cis SNP-protein pairs with FDR < 0.01 (nominal P < 2.13 x 10 −5). pQTL SNPs were more likely, compared to non-pQLT SNPs, to be disease/trait-associated variants identified by previous genome-wide association studies. The present findings suggest that genetic variations play a major role in the regulation of protein expression in the CNS. The obtained database will serve as a valuable resource for future neuropsychiatric research.
2016-12-30 | GSE83709 | GEO
Project description:Cerebrospinal fluid (CSF) is virtually the only one accessible source of proteins derived from the central nervous system (CNS) of living humans and possibly reflects the pathophysiology of a variety of neuropsychiatric diseases. However, little is known regarding the genetic basis of variation in protein levels of human CSF. We examined CSF levels of 1,126 proteins in 133 subjects and performed genome-wide association analysis of 514,227 single nucleotide polymorphisms (SNPs) to detect protein quantitative trait loci (pQTLs). Spearman’s correlation was used to identify association between genotypes of SNPs and protein levels. A total of 421 cis and 25 trans SNP-protein pairs were significantly correlated at a false discovery rate (FDR) of less than 0.01 (nominal P < 7.66 x 10 −9). Cis-only analysis revealed additional 580 significant cis SNP-protein pairs with FDR < 0.01 (nominal P < 2.13 x 10 −5). pQTL SNPs were more likely, compared to non-pQLT SNPs, to be disease/trait-associated variants identified by previous genome-wide association studies. The present findings suggest that genetic variations play a major role in the regulation of protein expression in the CNS. The obtained database will serve as a valuable resource for future neuropsychiatric research.
2016-12-30 | GSE83708 | GEO
Project description:The identification of multiple signals at individual loci could explain additional phenotypic variance ('missing heritability') of common traits, and help identify causal genes. We examined gene expression levels as a model trait because of the large number of strong genetic effects acting in cis. Using expression profiles from 613 individuals, we performed genome-wide single nucleotide polymorphism (SNP) analyses to identify cis-expression quantitative trait loci (eQTLs), and conditional analysis to identify second signals. We examined patterns of association when accounting for multiple SNPs at a locus and when including additional SNPs from the 1000 Genomes Project. We identified 1298 cis-eQTLs at an approximate false discovery rate 0.01, of which 118 (9%) showed evidence of a second independent signal. For this subset of 118 traits, accounting for two signals resulted in an average 31% increase in phenotypic variance explained (Wilcoxon P< 0.0001). The association of SNPs with cis gene expression could increase, stay similar or decrease in significance when accounting for linkage disequilibrium with second signals at the same locus. Pairs of SNPs increasing in significance tended to have gene expression increasing alleles on opposite haplotypes, whereas pairs of SNPs decreasing in significance tended to have gene expression increasing alleles on the same haplotypes. Adding data from the 1000 Genomes Project showed that apparently independent signals could be potentially explained by a single association signal. Our results show that accounting for multiple variants at a locus will increase the variance explained in a substantial fraction of loci, but that allelic heterogeneity will be difficult to define without resequencing loci and functional work. Gene expression data was determined of peripheral blood samples (n=705) from InChianti cohort.
2013-06-21 | E-GEOD-48152 | biostudies-arrayexpress
Project description:Genome-wide association study (GWAS) was performed in 120 patient-parents trio samples from Japanese schizophrenia pedigrees ABSTRACT: Schizophrenia is a devastating neuropsychiatric disorder with genetically complex traits. Genetic variants should explain a considerable portion of the risk for schizophrenia, and genome-wide association study (GWAS) is a potentially powerful tool for identifying the risk variants that underlie the disease. Here, we report the results of a three-stage analysis of three independent cohorts consisting of a total of 2,535 samples from Japanese and Chinese populations for searching schizophrenia susceptibility genes using a GWAS approach. Firstly, we examined 115,770 single nucleotide polymorphisms (SNPs) in 120 patient-parents trio samples from Japanese schizophrenia pedigrees. In stage II, we evaluated 1,632 SNPs (1,159 SNPs of p < 0.01 and 473 SNPs of p < 0.05 that located in previously reported linkage regions). The second sample consisted of 1,012 case-control samples of Japanese origin. The most significant p value was obtained for the SNP in the ELAVL2 [(embryonic lethal, abnormal vision, Drosophila)-like 2] gene located on 9p21.3 (p = 0.00087). In stage III, we scrutinized the ELAVL2 gene by genotyping gene-centric tagSNPs in the third sample set of 293 family samples (1,163 individuals) of Chinese descent and the SNP in the gene showed a nominal association with schizophrenia in Chinese population (p = 0.026). The current data in Asian population would be helpful for deciphering ethnic diversity of schizophrenia etiology.
2011-06-13 | GSE27923 | GEO
Project description:The identification of multiple signals at individual loci could explain additional phenotypic variance ('missing heritability') of common traits, and help identify causal genes. We examined gene expression levels as a model trait because of the large number of strong genetic effects acting in cis. Using expression profiles from 613 individuals, we performed genome-wide single nucleotide polymorphism (SNP) analyses to identify cis-expression quantitative trait loci (eQTLs), and conditional analysis to identify second signals. We examined patterns of association when accounting for multiple SNPs at a locus and when including additional SNPs from the 1000 Genomes Project. We identified 1298 cis-eQTLs at an approximate false discovery rate 0.01, of which 118 (9%) showed evidence of a second independent signal. For this subset of 118 traits, accounting for two signals resulted in an average 31% increase in phenotypic variance explained (Wilcoxon P< 0.0001). The association of SNPs with cis gene expression could increase, stay similar or decrease in significance when accounting for linkage disequilibrium with second signals at the same locus. Pairs of SNPs increasing in significance tended to have gene expression increasing alleles on opposite haplotypes, whereas pairs of SNPs decreasing in significance tended to have gene expression increasing alleles on the same haplotypes. Adding data from the 1000 Genomes Project showed that apparently independent signals could be potentially explained by a single association signal. Our results show that accounting for multiple variants at a locus will increase the variance explained in a substantial fraction of loci, but that allelic heterogeneity will be difficult to define without resequencing loci and functional work.
2013-06-21 | GSE48152 | GEO
Project description:Genome-wide association study (GWAS) was performed in 120 patient-parents trio samples from Japanese schizophrenia pedigrees ABSTRACT: Schizophrenia is a devastating neuropsychiatric disorder with genetically complex traits. Genetic variants should explain a considerable portion of the risk for schizophrenia, and genome-wide association study (GWAS) is a potentially powerful tool for identifying the risk variants that underlie the disease. Here, we report the results of a three-stage analysis of three independent cohorts consisting of a total of 2,535 samples from Japanese and Chinese populations for searching schizophrenia susceptibility genes using a GWAS approach. Firstly, we examined 115,770 single nucleotide polymorphisms (SNPs) in 120 patient-parents trio samples from Japanese schizophrenia pedigrees. In stage II, we evaluated 1,632 SNPs (1,159 SNPs of p < 0.01 and 473 SNPs of p < 0.05 that located in previously reported linkage regions). The second sample consisted of 1,012 case-control samples of Japanese origin. The most significant p value was obtained for the SNP in the ELAVL2 [(embryonic lethal, abnormal vision, Drosophila)-like 2] gene located on 9p21.3 (p = 0.00087). In stage III, we scrutinized the ELAVL2 gene by genotyping gene-centric tagSNPs in the third sample set of 293 family samples (1,163 individuals) of Chinese descent and the SNP in the gene showed a nominal association with schizophrenia in Chinese population (p = 0.026). The current data in Asian population would be helpful for deciphering ethnic diversity of schizophrenia etiology. Affymetrix SNP arrays were performed according to the manufacturer's directions on DNA extracted from peripheral blood samples. SUPPLEMENTARY FILES: CEL files were processed by manufacture's protocol. Genotype data were analyzed with the GeneSpring GT (Varia) 2.0 software package developed by Agilent Technologies (Santa Clara, CA). Matrix tables for the Genetic programs were produced (Linkage format: http://bioinformatics.med.utah.edu/~alun/software/docs/linkage.html) File 1: Matrix file_SNP_Map.txt File 2: Matrix file_Family_Information.txt File 3: Matrix file_Pedigree_Format.txt (Genotyping data of Linkage format) Transmission disequilibrium test was performed using the R program (http://www.r-project.org). File 4: Matrix file_results.txt
2011-06-13 | E-GEOD-27923 | biostudies-arrayexpress
Project description:Juvenile idiopathic arthritis (JIA) is the most common chronic childhood rheumatic disease in the Western world. To identify novel JIA predisposing loci, a genome-wide association study (GWAS) in 814 Caucasian JIA cases and 3058 Caucasian controls was completed. After adjusting for the most significant HLA associations, the strongest novel associations included rs6479891 (10q21, odds ratio (OR)=1.59, P=1.3x10-8) and rs10761747 (OR=1.34, P=4.0x10-5) within JMJD1C; rs12719740 (15q26, OR=1.47, P=3.3x10-7) near FAM169B; rs4688011 (3q13, OR=1.33, P=1.1x10-4) within C3orf1 and rs4254850 (4q31, OR=0.85, P=7.8x10-3) near IL15. Eleven SNPs were genotyped in Caucasian replication cohorts (1744 cases, 7010 controls) and meta-analysis continued to provide evidence for association with three of the SNPs (rs6479891, P=4.3x10-5; rs12719740, P=5.2x10-4; rs4688011, P=3.6x10-7). Analysis of expression data from 68 JIA cases and 23 controls overlapping in the GWAS cohort1 and published lymphoblastoid cell lines (LCL)2 showed cis eQTL associations for JMJD1C SNPs (P=0.01 and P=1.6x10-6, respectively), and the C3orf1 SNP (P=5.7x10-6).
2012-03-23 | GSE26554 | GEO
Project description:Genetic analysis of gene expression level is a promising approach for characterizing candidate genes that are involved in complex economic traits such as meat quality. In the present study, we conducted expression quantitative trait loci (eQTL) and allele-specific expression (ASE) analyses based on RNA-sequencing (RNAseq) data from the longissimus muscle of 189 Duroc × Luchuan crossed pigs in order to identify some candidate genes for meat quality traits. Using a genome-wide association study based on a fixed linear model, we identified 7,192 cis-eQTL corresponding to 2,098 cis-genes (p ≤ 1.33e-3, FDR ≤ 0.05) and 6,400 trans-eQTL corresponding to 863 trans-genes (p ≤ 1.13e-6, FDR ≤ 0.05). ASE analysis using RNAseq SNPs identified 9,815 significant ASE-SNPs in 2,253 unique genes. Integrative analysis between the cis-eQTL and ASE target genes identified 540 common genes, including 33 genes with expression levels that were correlated with at least one meat quality trait. Among these 540 common genes, 63 have been reported previously as candidate genes for meat quality traits, such as PHKG1 (q-value = 1.67e-6 for the leading SNP in the cis-eQTL analysis), NUDT7 (q-value = 5.67e-13), FADS2 (q-value = 8.44e-5), and DGAT2 (q-value = 1.24e-3).This study provides valuable information on the genetics of gene expression in porcine skeletal muscle. The characterized cis-genes and ASE genes, combined with the correlations between gene expression level and meat quality traits will be useful to prioritize candidate genes in further studies.
2019-06-24 | GSE124315 | GEO
Project description:Genome-wide association studies (GWAS) have identified 19 risk variants associated with colorectal cancer. As most of these risk variants reside outside the coding regions of genes, we conducted cis-expression quantitative trait loci (cis-eQTL) analyses to investigate possible regulatory functions on the expression of neighboring genes. Forty microsatellite stable and CpG island methylator phenotype-negative colorectal tumors and paired adjacent-normal colon tissues were used for genome-wide SNP and gene expression profiling in our cis-eQTL analyses. This submission represents transcriptome component of study.
2012-01-31 | E-GEOD-31737 | biostudies-arrayexpress
Project description:Juvenile idiopathic arthritis (JIA) is the most common chronic childhood rheumatic disease in the Western world. To identify novel JIA predisposing loci, a genome-wide association study (GWAS) in 814 Caucasian JIA cases and 3058 Caucasian controls was completed. After adjusting for the most significant HLA associations, the strongest novel associations included rs6479891 (10q21, odds ratio (OR)=1.59, P=1.3x10-8) and rs10761747 (OR=1.34, P=4.0x10-5) within JMJD1C; rs12719740 (15q26, OR=1.47, P=3.3x10-7) near FAM169B; rs4688011 (3q13, OR=1.33, P=1.1x10-4) within C3orf1 and rs4254850 (4q31, OR=0.85, P=7.8x10-3) near IL15. Eleven SNPs were genotyped in Caucasian replication cohorts (1744 cases, 7010 controls) and meta-analysis continued to provide evidence for association with three of the SNPs (rs6479891, P=4.3x10-5; rs12719740, P=5.2x10-4; rs4688011, P=3.6x10-7). Analysis of expression data from 68 JIA cases and 23 controls overlapping in the GWAS cohort1 and published lymphoblastoid cell lines (LCL)2 showed cis eQTL associations for JMJD1C SNPs (P=0.01 and P=1.6x10-6, respectively), and the C3orf1 SNP (P=5.7x10-6). Peripheral blood samples were obtained from 23 healthy children and 68 children with JIA. RNA was purified from Ficoll-isolated mononuclear cells, fluorescently labeled and then hybridized to Affymetrix U133 Plus 2.0 GeneChips. Data were imported using Robust Multi-Array Average pre-processing and Distance Weighted Discrimination normalization. eQTL analysis were performed using genomewide association data.
2012-03-23 | E-GEOD-26554 | biostudies-arrayexpress