Genome Wide Linkage analysis of large family with coronary artery disease
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE42137 | GEO | 2014/03/28
SECONDARY ACCESSION(S): PRJNA179197
REPOSITORIES: GEO
Similar Datasets
Project description:We used linkage data from CAD family to search for the responsible variant in disease. we used illumina array for linkage analysis of CAD affected family.
2014-03-28 | E-GEOD-42137 | biostudies-arrayexpress
Project description:We wanted to explore the genomic regions 1p13, 1q41, 9p21 and 10q11, which are among the labeled âtop 12 golden lociâ linked to coronary artery disease (CAD) risk, in order to see whether their geographic variation could be explained by demographic effects. To do this, we have genotyped these risk regions in a set of Mediterranean populations. Genomic DNA was extracted from blood cells using a Blood Midi kit (Omega Biotek, USA) according to manufacturer's procedures. DNA samples were genotyped for a combined set of 366 SNPs using an Illumina Custom GoldenGate Panel. SNPs were selected as a representative set of the common variation in the four genomic regions, according to the following criteria: i) average coverage of 1 SNP every 1.5 kb, ii) minor allele frequency (MAF) higher than 0.05 in CEU and TSI HapMap populations, iii) given priority to markers not in linkage disequilibrium (LD) (r2<0.8) in European populations, and iv) prioritizing markers previously associated with CAD. These criteria were applied giving preference to tag SNPs.
2016-11-24 | E-MTAB-5265 | biostudies-arrayexpress
Project description:Coronary artery disease (CAD) is a complex inflammatory disease involving genetic influences across several cell types. Genome-wide association studies (GWAS) have identified over 170 loci associated with CAD, where the majority of risk variants reside in noncoding DNA sequences impacting cis-regulatory elements (CREs). Here, we applied single-cell ATAC-seq to profile 28,316 cells across coronary artery segments from 41 patients with varying stages of CAD, which revealed 14 distinct cellular clusters. We mapped ~320,000 accessible sites across all cells, identified cell type-specific elements, transcription factors, and prioritized functional CAD risk variants via quantitative trait locus and sequence-based predictive modeling. We identified a number of candidate mechanisms for smooth muscle cell transition states and identified putative binding sites for risk variants. We further employed CRE to gene linkage to nominate disease-associated key driver transcription factors such as PRDM16 and TBX2. This single cell atlas provides a critical step towards interpreting cis-regulatory mechanisms in the vessel wall across the continuum of CAD risk.
2021-12-14 | GSE175621 | GEO
Project description:Coronary artery disease (CAD) is a complex disorder with genetic and environmental influences. Genome-wide association studies (GWAS) have identified over 300 genomic loci associated with disease risk. However, identifying the functional variants within these loci has been limited in large part due to linkage disequilibrium. This represents a critical step in understanding the molecular mechanisms underlying disease risk. To identify and prioritize candidate causal CAD-associated variants, we performed lentivirus-based massively parallel reporter assays (lentiMPRAs) in primary vascular smooth muscle cells (SMCs), which play significant roles in atherosclerosis, the underlying cause of CAD. We tested 25892 CAD-associated variants for their allele-specific enhancer activity in quiescent and proliferative SMCs, modeling healthy and disease conditions. We identified 122 candidate variants showing significant enhancer activity and differences in reporter gene expression between risk and non-risk alleles. We also identified 23 variants showing condition-biased allelic imbalance and 41 variants showing sex-biased allelic imbalance. We further functionally characterized 25892 variants by performing CUT&RUN assays to identify variants in enhancer and promoter regions of SMCs. By integrating the results of these experiments, we identified a credible set of 49 CAD-associated variants in functionally relevant regions. Furthermore, by comparing these identified variants with our previously obtained expression quantitative trait loci (eQTL) data, 27 of these 49 variants were associated with SMC gene expression levels. Finally, we performed CRISPRi experiments on 8 variants comprising 9 variant-gene pairs, rs35976034 (MAP1S), rs4888409 (CFDP1), rs73193808 (MAP3K7CL), rs67631072 (INPP5B/FHL3), rs1651285 (SNHG18), rs17293632 (SMAD3), rs2238792 (ARVCF), rs4627080 (NRIP3), to confirm their regulatory potential of nearby gene expression. Taken together, our results comprehensively fine-map the causal variants that confer increased risk of CAD through their effects on vascular smooth muscle cells.
2024-10-14 | GSE279300 | GEO
Project description:Coronary artery disease (CAD) is a complex disorder with genetic and environmental influences. Genome-wide association studies (GWAS) have identified over 300 genomic loci associated with disease risk. However, identifying the functional variants within these loci has been limited in large part due to linkage disequilibrium. This represents a critical step in understanding the molecular mechanisms underlying disease risk. To identify and prioritize candidate causal CAD-associated variants, we performed lentivirus-based massively parallel reporter assays (lentiMPRAs) in primary vascular smooth muscle cells (SMCs), which play significant roles in atherosclerosis, the underlying cause of CAD. We tested 25892 CAD-associated variants for their allele-specific enhancer activity in quiescent and proliferative SMCs, modeling healthy and disease conditions. We identified 122 candidate variants showing significant enhancer activity and differences in reporter gene expression between risk and non-risk alleles. We also identified 23 variants showing condition-biased allelic imbalance and 41 variants showing sex-biased allelic imbalance. We further functionally characterized 25892 variants by performing CUT&RUN assays to identify variants in enhancer and promoter regions of SMCs. By integrating the results of these experiments, we identified a credible set of 49 CAD-associated variants in functionally relevant regions. Furthermore, by comparing these identified variants with our previously obtained expression quantitative trait loci (eQTL) data, 27 of these 49 variants were associated with SMC gene expression levels. Finally, we performed CRISPRi experiments on 8 variants comprising 9 variant-gene pairs, rs35976034 (MAP1S), rs4888409 (CFDP1), rs73193808 (MAP3K7CL), rs67631072 (INPP5B/FHL3), rs1651285 (SNHG18), rs17293632 (SMAD3), rs2238792 (ARVCF), rs4627080 (NRIP3), to confirm their regulatory potential of nearby gene expression. Taken together, our results comprehensively fine-map the causal variants that confer increased risk of CAD through their effects on vascular smooth muscle cells.
2024-10-14 | GSE279298 | GEO
Project description:Genetics play major roles in the development of atherosclerotic coronary artery disease (CAD). Despite tremendous efforts worldwide invested to decipher the genetic components controlling the development of CAD, the genetic architecture of CAD remains largely unclear. As part of an on-going effort to identify molecules and pathways involved in the development of atherosclerotic CAD, we propose to use rigorous angiographic criteria to define CAD phenotype for genomics and metabolomics study. We identified two extreme groups, namely “young CAD” group, who are very young individuals (age <= 40 years) proven to have severe CAD required revascularization, and “CAD-free elderly”, who are at very advanced age (Age >= 80 years) but have no angiographically apparent CAD. Phenotypically, these two groups are in sharp contrary. Conventional risk factors account for small portion of different phenotypes. We hypothesize that there are genetically programmed pathways and molecules accelerating atherosclerotic pathogenesis, in the “young CAD” patients and preventing the development of CAD in the “CAD-free elderly” patients. We sought to combine genomics and metabolomics approaches to profile and identify these pathways and molecules. Both plasma and urine samples from patients in these two groups, and their age matched control groups, will undergo unbiased metabolomics profiling with high throughput quantitative nuclear magnetic resonance (NMR) and mass spectrometry (MS) technology in RTI metabolomics core facility. Comprehensive statistic and multi-variant analytic approaches will be used to identify pathways and molecules significance to the pathogenesis of atherosclerosis. These data will be integrated with genomics data from next generation sequencing of genetic materials from the same groups of patients to further explore the molecular mechanisms underlying atherosclerosis and CAD.
2015-12-31 | ST000306 | MetabolomicsWorkbench
Project description:Coronary artery disease (CAD) is the leading cause of mortality and morbidity driven by both genetic and environmental risk factors. Meta-analyses of genome-wide association studies (GWAS) have identified multiple single nucleotide polymorphisms (SNPs) associated with CAD and myocardial infarction (MI) susceptibility in multi-ethnic populations. The majority of these variants reside in non-coding regulatory regions and are co-inherited with hundreds of candidate regulatory SNPs. Herein, we use integrative genomic, epigenomic, and transcriptomic fine-mapping in human coronary artery smooth muscle cells (HCASMC) and tissues to identify causal regulatory variation and mechanisms responsible for CAD associations. Using these genome-wide maps we prioritize 65 candidate variants and perform allele-specific binding and expression analyses on 7 top candidates. We validate our findings in two independent cohorts of diseased human arterial expression quantitative trait loci (eQTL), which together demonstrate fundamental links between CAD associations and regulatory function in the appropriate disease context.
2016-07-06 | GSE72696 | GEO
Project description:Coronary artery disease (CAD) is the leading cause of human morbidity and mortality worldwide, underscoring the need to improve diagnostic strategies. Platelets play a major role, not only in the process of acute thrombosis during plaque rupture, but also in the formation of atherosclerosis itself. MicroRNAs are endogenous small non-coding RNAs that control gene expression and are expressed in a tissue and disease-specific manner. Therefore they have been proposed to be useful biomarkers. It remains unknown whether differences in miRNA expression levels in platelets can be found between patients with premature CAD and healthy controls. Methodology/Principal Findings In this case-control study we measured relative expression levels of platelet miRNAs using microarrays from 12 patients with premature CAD and 12 age- and sex-matched healthy controls. Six platelet microRNAs were significantly upregulated (miR340*, miR451, miR454*, miR545:9.1. miR615-5p and miR624*) and one miRNA (miR1280) was significantly downregulated in patients with CAD as compared to healthy controls. To validate these results, we measured the expression levels of these candidate miRNAs by qRT-PCR in platelets of individuals from two independent cohorts; validation cohort I consisted of 40 patients with premature CAD and 40 healthy controls and validation cohort II consisted of 27 patients with artery disease and 40 healthy relatives. MiR340* and miR624* were confirmed to be upregulated in patients with CAD as compared to healthy controls in both validation cohorts. Conclusion/Significance Two miRNAs in platelets are significantly upregulated in patients with CAD as compared to healthy controls. miRNA array analysis of isolated platelets from subjects with premature coronary artery disease compared to healthy control subjects.
2011-09-30 | E-GEOD-28858 | biostudies-arrayexpress
Project description:Recent meta-analyses of genome wide association studies (GWAS) have identified approximately 150 loci that are associated with coronary artery disease (CAD). To link the causal genes in these loci to functional transcriptional networks, we have used chromatin immunoprecipitation sequencing (ChIP-Seq) with human coronary artery smooth muscle cells (HCASMC) to investigate the cellular and molecular program downstream of one CAD associated transcription factor, TCF21. Analysis of the TCF21 downstream target genes for enrichment of molecular and cellular annotation terms identified processes relevant to CAD pathophysiology, including growth factor binding (PDGF, VEGF), matrix interactions (“integrin binding,” “cell adhesion”), and smooth muscle contraction (“actin filament-based processes,” “actin cytoskeleton”). Motif searches of peak sequences confirmed the canonical E-box CAGCTG as the likely binding sequence for TCF21, but also identified bZip motifs that coordinate binding of AP1 family transcription factors. Follow-up ChIP-Seq studies verified enriched binding of bZip factors JUN and JUND to TCF21 target loci. Importantly, analysis of the representation of CAD genes among TCF21 target loci showed highly significant enrichment. Further, expression quantitative trait variation mapped to target genes of TCF21 were significantly enriched among variants with low P-values in the GWAS analyses, and single nucleotide polymorphisms within TCF21 peaks were shown to be in linkage disequilibrium with CAD-associated SNPs, suggesting a functional interaction between TCF21 binding and causal variants in other CAD disease loci. Thus, data and analyses presented here provide evidence for a transcriptional regulatory network that links TCF21 function in smooth muscle cells with a number of other CAD-associated genes, and suggest that study of GWAS transcription factors may be a highly useful approach to identifying disease gene interactions and thus pathways that may be relevant to complex disease etiology.
2015-04-12 | GSE61369 | GEO
Project description:Coronary artery disease (CAD) and the frequently coexisting aortic valve stenosis (AS) are the heart diseases accounting for the highest proportion of cardiac surgeries. Routine biomarkers for an earl detection of either of these atherosclerotic-rooted conditions would be important to anticipate the diagnosis and to evaluate their severity with imaging techniques before they become advanced to the point where intervention or surgery have limited therapeutic benefit. Urine is an attractive biofluid for biomarker assessment, provided the noninvasive nature of its collection. Therefore, we conducted a shotgun proteomics analysis of urine collected from 12 CAD and/or AS patients and 11 cardiovascular disease-free controls, aiming at identification of putative molecular candidates that could differentiate these diseases from healthy subjects
2022-12-18 | PXD036800 | Pride