Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Ed2978ac-6bda-498f-8923-bc13181433e3 - samples

ABSTRACT: This dataset contains the clinical phenotypes/covariates information for all the individuals. This dataset was generated as part of the following study: Panousis et al (2019). Combined genetic and transcriptome analysis of patients with SLE: Distinct, targetable signatures for susceptibility and severity.

PROVIDER: EGAD00001005040 | EGA |

REPOSITORIES: EGA

ACCESS DATA

Json Xml

Similar Datasets

54a79a19-0fcd-4f59-9ed4-9651c92964fd - samples

Project description:This dataset contains the RPKM and raw read counts of expression for all the individuals. This dataset was generated as part of the following study: Panousis et al (2019). Combined genetic and transcriptome analysis of patients with SLE: Distinct, targetable signatures for susceptibility and severity.

| EGAD00001005039 | EGA

e8d36e8c-583c-42fb-a7c2-996300fc3b31 - samples

Project description:This dataset contains the sQTL summary statistics (nominal pass, significant sQTLs). sQTL mapping was performed with QTLtools. This dataset was generated as part of the following study: Panousis et al (2019). Combined genetic and transcriptome analysis of patients with SLE: Distinct, targetable signatures for susceptibility and severity.

| EGAD00001005042 | EGA

0773c7f5-e98a-457f-9a79-b8d0ab3866eb - samples

Project description:This dataset contains the eQTL summary statistics (nominal pass, significant eQTLs, best associated variant per gene). eQTL mapping was performed with fastQTL. This dataset was generated as part of the following study: Panousis et al (2019). Combined genetic and transcriptome analysis of patients with SLE: Distinct, targetable signatures for susceptibility and severity.

| EGAD00001005041 | EGA

896a742f-087b-48e7-8197-43a655aba2a9 - samples

Project description:This dataset contains 200 RNA-seq bam files (142 SLE, 58 healthy individuals). RNA libraries were prepared with the Illumina TruSeq sample preparation kit and were sequenced on Illumina HiSeq2000. 49 bp paired-end reads were mapped to the GRCh37 reference human genome using the GEM mapper.This dataset was generated as part of the following study: Panousis et al (2019). Combined genetic and transcriptome analysis of patients with SLE: Distinct, targetable signatures for susceptibility and severity

| EGAD00001005037 | EGA

dfa0b3b4-864a-48a7-9c51-0e84cd2c46bb - samples

Project description:This dataset contains the imputed genotypes for 197 individuals. All individuals were genotyped with the Illumina HumanCoreExome-24 array. The individuals were phased with SHAPEIT and imputed to the 1000 Genomes Project Phase III using IMPUTE2. This dataset was generated as part of the following study: Panousis et al (2019). Combined genetic and transcriptome analysis of patients with SLE: Distinct, targetable signatures for susceptibility and severity

| EGAD00001005038 | EGA

TWAS-based translational genomics approach identifies IL10RB as the top candidate gene for COVID-19 host susceptibility and severity

Project description:Recent efforts have identified genetic loci that are associated with coronavirus disease 2019 (COVID-19) infection rates and disease outcome severity. Translating these genetic findings into druggable genes that regulate COVID-19 host susceptibility is a critical next step. Using a translational genomics approach that integrates COVID-19 genetic susceptibility variants, multi-tissue genetically regulated gene expression (GReX) and perturbagen signatures, we identify IL10RB as the top key regulator of COVID-19 host susceptibility. In a series of validation steps we show that predicted GReX up-regulation of IL10RB and higher IL10RB expression in COVID-19 patient blood is associated with worse COVID-19 outcomes, and that in vitro IL10RB overexpression is associated with increased viral load and activation of disease-relevant molecular pathways.

2022-07-22 | GSE180622 | GEO

An AI-guided invariant signature places MIS-C with Kawasaki disease in a continuum of host immune responses

Project description:A significant surge in cases of multisystem inflammatory syndrome in children (MIS-C, also called Pediatric Inflammatory Multisystem Syndrome - PIMS) has been observed amidst the COVID-19 pandemic. MIS-C shares many clinical features with Kawasaki disease (KD), although clinical course and outcomes are divergent. We analyzed whole blood RNA sequences, serum cytokines, and formalin fixed heart tissues from these patients using a computational toolbox of two gene signatures, i.e., viral pandemic (ViP), and a subset of it called, severe (s)ViP signatures that were developed in the context of SARS-CoV-2 infection in COVID-19 and a 13-transcript signature previously demonstrated to be diagnostic for KD. Our analyses revealed that KD and MIS-C are on the same continuum of the host immune response as COVID-19 but diverge with two different cardiac phenotypes. The ViP signatures helped unravel the nature of the host immune response (IL15-centric) in MIS-C and KD, reveal unique targetable cytokine pathways in MIS-C, place MIS-C farther along in the spectrum in severity compared to KD and pinpoint key clinical (reduced cardiac function) and laboratory (thrombocytopenia and eosinopenia) parameters that can be useful to track severity.

2022-03-20 | GSE178491 | GEO

Multi-omic profiling reveals widespread dysregulation of innate immunity and hematopoiesis in COVID-19

Project description:Our understanding of protective vs. pathologic immune responses to SARS-CoV-2, the virus that causes Coronavirus disease 2019 (COVID-19), is limited by inadequate profiling of patients at the extremes of the disease severity spectrum. Here, we performed multi-omic single-cell immune profiling of 64 COVID-19 patients across the full range of disease severity, from outpatients with mild disease to fatal cases. Our transcriptomic, epigenomic, and proteomic analyses reveal widespread dysfunction of peripheral innate immunity in severe and fatal COVID-19, with the most profound disturbances including prominent hyperactivation signatures in neutrophils and monocytes with anti-inflammatory features. We also leverage epigenomic analysis to identify loss of accessibility at NF-kB binding sites within pro-inflammatory cytokine gene loci as a potential mechanism for the striking lack of cytokine production observed in monocytes in severe and fatal COVID-19. We further demonstrate that emergency myelopoiesis is a prominent feature of fatal COVID-19. Collectively, our results reveal disease severity-associated immune phenotypes in COVID-19 and identify pathogenesis-associated pathways that are potential targets for therapeutic intervention.

2021-05-08 | GSE174072 | GEO

Peripheral blood mononuclear cell gene expression in chronic obstructive pulmonary disease

Project description:Expression data were generated on 136 subjects from the COPDGene® study using Affymetrix microarrays. Multiple linear regression with adjustment for covariates (gender, age, body mass index, family history, smoking status, pack years) was used to identify candidate genes and Ingenuity Pathway Analysis was used to identify candidate pathways. Candidate genes identified included those that play a role in the immune system, inflammatory responses, and sphingolipid metabolism. Many of our final candidate genes also show an association with related disease phenotypes such as emphysema, gas trapping, and 6-minute walk distance. 42 control subjects and 94 subjects with varying severity of COPD had PBMC gene expression profiles generated. All subjects are non-hispanic white, current or former smokers.

2013-05-06 | E-GEOD-42057 | biostudies-arrayexpress

Blood coagulation and complement activation interact to increase disease activity in systemic lupus erythematosus and coagulation D-Dimer combined with complement C4 is a biomarker of lupus activity

Project description:This study was conducted to (1) find deregulation of certain pathways in SLE at multi-omics levels; (2) evaluate the associations among blood coagulation, complement activation, inflammatory responses and SLE disease severity; (3) develop biomarkers to facilitate better the assessment of the likelihood of lupus activity.

2018-10-27 | PXD004443 | Pride

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data