Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Functional genomics in primary T cells and monocytes identifies mechanisms by which genetic susceptibility loci influence systemic sclerosis risk

ABSTRACT: Systemic sclerosis (SSc) is a complex autoimmune disease with a strong genetic component. However, most of the causal genes associated to the disease are still unknown because associated variants affect mostly non-coding intergenic elements of the genome. The challenge in the post-GWAS era is to use functional genomics to translate the genetic findings into a better understanding of the disease, particularly by using disease-relevant cell types. We linked SSc-associated loci to 39 new potential target genes and confirm 7 previously known genes. We highlight novel causal genes, such as CXCR5 as the most probable candidate gene for the DDX6 locus. Some previously known SSc associated genes such as IRF8, STAT4, or CD247 interestingly showed cell type specific interactions. We also identified 15 potential drug targets already in use in other similar immune-mediated diseases that could be repurposed for SSc treatment. Furthermore, we observed that interactions are directly correlated with the expression of important genes implicated in cell type specific pathways and find evidence that chromatin conformation is linked to genotype.Our study reveals potential causal genes for SSc-associated loci, some of them acting in a cell type specific manner, suggesting novel biological mechanisms that might mediate SSc pathogenesis.

ORGANISM(S): Homo sapiens

PROVIDER: GSE212100 | GEO | 2022/08/29

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Protein interaction networks in the vasculature prioritize genes and pathways underlying coronary artery disease (Whitehead data)

Project description:Population-based association studies have identified many genetic risk loci for coronary artery disease (CAD), but it is often unclear how genes within these loci are linked to CAD. Here, we performed interaction proteomics for 11 CAD-risk genes to map their protein-protein interactions (PPIs) in human vascular cells and elucidate their biological relevance in CAD pathogenesis. The PPI networks contain many protein interactions that are outside of known biology in the vasculature and are enriched for genes involved in immunity-related and arterial-wall-specific mechanisms. Furthermore, several PPI networks derived from smooth muscle cells are significantly enriched for genetic variants associated with CAD and related vascular phenotypes. Finally, our networks identified 61 genes that are found in genetic loci associated with risk of CAD, prioritizing them as the causal candidates within these loci. Together, our results indicate that the PPI networks we have generated are a rich resource for guiding future research into the molecular pathogenesis of CAD.

2023-02-27 | MSV000091373 | MassIVE

IP-MS methods for Protein interaction networks in the vasculature prioritize genes and pathways underlying coronary artery disease

Project description:Zhu QM, Hsu YH, Lassen FH, MacDonald BT, Stead S, Malolepsza E, Kim A, Li T, Mizoguchi T, Schenone M, Guzman G,Tanenbaum B, Fornelos N, Carr SA, Gupta RM, Ellinor PT, Lage K. Population-based association studies have identified many genetic risk loci for coronary artery disease (CAD), but it is often unclear how genes within these loci are linked to CAD. Here, we performed interaction proteomics for 11 CAD-risk genes to map their protein-protein interactions (PPIs) in human vascular cells and elucidate their biological relevance in CAD pathogenesis. The PPI networks contain many protein interactions that are outside of known biology in the vasculature and are enriched for genes involved in immunity-related and arterial-wall-specific mechanisms. Furthermore, several PPI networks derived from smooth muscle cells are significantly enriched for genetic variants associated with CAD and related vascular phenotypes. Finally, our networks identified 61 genes that are found in genetic loci associated with risk of CAD, prioritizing them as the causal candidates within these loci. Together, our results indicate that the PPI networks we have generated are a rich resource for guiding future research into the molecular pathogenesis of CAD.

2023-04-12 | MSV000091699 | MassIVE

Integrative genomic analysis of blood pressure and related phenotypes in rats

Project description:Despite remarkable progress made in human genome-wide association studies, there remains a substantial gap between statistical evidence for genetic association and functional comprehension of the underlying mechanisms. To bridge the gap, we perform integrative genomic analysis of blood pressure and related phenotypes in the spontaneously hypertensive rat, an animal model of essential hypertension, searching causal genes and causal pathways. We identify 28 potential target genes, including rat homologs of human transcriptome-wide association study loci, for the tested traits and provide experimental evidence supporting the presence of key disease pathways and core disease-related gene loci in the genetic architecture of hypertension.

2021-05-04 | E-MTAB-9244 | biostudies-arrayexpress

Epigenomic and transcriptomic analysis of Systemic Sclerosis CD4+ T cells [Illumina]

Project description:Epigenomic and transcriptomic analysis of Systemic Sclerosis CD4+ T cells reveals long range dysregulation of key inflammatory pathways mediated by disease-associated susceptibility loci range dysregulation of key inflammatory pathways mediated by disease-associated System sclerosis (SSc) is a genetically complex autoimmune disease mediated by the interplay between genetic and epigenetic factors in a multitude of immune cells, with CD4+ T lymphocytes as one of the principle drivers of pathogenesis. In this study, we obtained DNA methylation and RNA expression profiles of CD4+ T cells from 48 SSc patients and 16 healthy controls. Consequently, we identified 9112 and 3929 differentially methylated CpGs positions (DMPs) and differentially expressed genes (DEGs) respectively. These DMPs and DEGs are enriched in functional categories related to inflammation and T cell biology. Furthermore, correlation analysis identified 17,500 possible DMP-DEG interaction pairs within a window of 5 Mb, and utilizing promoter capture Hi-C data, we confirmed 168 pairs of DMP-DEG physical interactions. Finally, utilizing SSc GWAS data, we identified three important SSc-associated susceptibility loci, CSK (rs1378942), IL12RB1 (rs2305743) and IKZF3-GSDMB (rs9303277), that physically interact with cg11062629-ULK3, cg10808810-JUND and cg19458020-CCR7 respectively. Overall, our study reveals a solid link between genetic, epigenetic and transcriptional deregulation in CD4+ T cells of SSc patients, providing further understanding to SSc pathogenesis.

2020-09-04 | GSE146092 | GEO

Epigenomic and transcriptomic analysis of Systemic Sclerosis CD4+ T cells [Affymetrix]

2020-09-04 | GSE146088 | GEO

Resolving molecular mechanisms of autoimmune disease in primary CD4 T cells

Project description:Numerous genomic loci have been implicated in autoimmune disorders, but attempts to identify causal variants, and thereby disease mechanisms, have been hampered by strong linkage disequilibrium – leaving most loci unresolved and the potential of GWAS unfulfilled. To overcome this, we developed a massively-parallel reporter assay for use in primary CD4 T-cells, a key effector of many autoimmune diseases, and sought to resolve potential causal variants via their functional effects. This provided testable hypotheses into disease mechanisms, which can provide previously unappreciated insights into molecular mechanisms of disease

2020-03-21 | GSE135925 | GEO

Systematic fine-mapping and functional studies of prostate cancer risk variants [4C]

Project description:To date, genome-wide association studies (GWAS) have revealed over 200 genetic risk loci associated with prostate cancer; yet, true disease-causing variants in gene regulatory regions remain elusive. Identification of causal variants and their targets from association signals relevant to prostate cancer is complicated by high linkage disequilibrium and limited availability of functional genomics data for specific tissue/cell types. Here, we integrated statistical fine-mapping and functional annotation from prostate-specific epigenomic profiles, high resolution 3D genome features, and quantitative trait loci data to distinguish causal variants from associations and identify target genes they regulate. Our fine-mapping analysis yielded 1,892 likely causal variants, and multiscale functional annotation linked them to 406 target genes. We prioritized rs10486567, located in an enhancer, as a genome-wide top-ranked SNP and predicted HOTTIP as its target. Deletion of the rs10486567-associated enhancer in prostate cancer cells decreased their capacity for invasive migration. HOTTIP overexpression in an enhancer-KO cell line rescued defective invasive migration. Furthermore, we found that rs10486567 regulates HOTTIP through allele-specific long- range chromatin interaction.

2023-02-25 | GSE197819 | GEO