Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Ena-DATASET-GoT2D/T2D-GENES-09-07-2016-02:03:47:226-1135 - samples

ABSTRACT: The GoT2D study includes ~2800 samples, half T2D cases and half T2D controls, of Northern European ancestry sequenced over 3 three technologies: deep whole exome sequencing, low-pass (4x) whole genome sequencing, and OMNI 2.5M genotyping. Samples were ascertained to be phenotypically "extreme" (e.g. leaner, younger cases and older, more obese controls). Genotypes (SNVs, INDELs, and SVs) were called separately for each technology and then integrated via genotype refinement into a single phased reference panel; samples and variants were then excluded based on QC procedures described in Fuchsberger et al. Please note that 2 of the samples in the GoT2D vcf do not have phenotype data.

PROVIDER: EGAD00001002247 | EGA |

REPOSITORIES: EGA

ACCESS DATA

Json Xml

Publications

Reconsolidation of Traumatic Memories for PTSD: A randomized controlled trial of 74 male veterans.

Gray Richard R Budden-Potts Denise D Bourke Frank F

Psychotherapy research : journal of the Society for Psychotherapy Research 20171214 5

Design: A randomized waitlist-controlled design (n = 74) examined the efficacy of Reconsolidation of Traumatic Memories (RTM) among male veterans with current-month flashbacks and nightmares. Volunteers were randomly assigned to immediate treatment (three 120-minute sessions of RTM), or to a 3-week waiting condition before receiving the RTM treatment. Blinded psychometricians evaluated the symptoms at intake, 2 weeks, and 6 weeks post. Wait-listed participants were re-evaluated and ...[more]

PMID: 29241423

Similar Datasets

ena-DATASET-GoT2D/T2D-GENES-08-07-2016-21:22:44:693-1130 - samples

Project description:The T2D-GENES/GoT2D 13K exome sequencing study includes ~13,000 samples, half T2D cases and half T2D controls, from five ancestries (~5K Europeans, ~2K each of African-American, East-Asian, South-Asian, and Hispanic). Samples underwent deep exome sequencing, with SNVs and INDEls called according to GATK best practices; variant sites were then filtered according to the GATK best practices, and then samples and variants underwent further filtering based on aggregate genotype quality as described in Fuchsberger et al. (e.g. low call rate, excess heterozygosity for samples, low call rate or coverage for variants). Please note that one of the samples in the T2D-GENES vcf does not have phenotype data.

| EGAD00001002246 | EGA

ena-DATASET-GoT2D/T2D-GENES-23-08-2018-16:36:23:611-187 - samples

Project description:The GoDARTS T2D-GENES exome sequencing study includes 1924 samples, 965 T2D cases and 959 T2D controls, from European ancestry. This cohort is part of a larger exome sequencing effort from the T2D-GENES project and contains the exome sequencing vcf from the GoDARTS samples. The other data generated from the T2D-GENES project can be found in dbGAP. Samples underwent deep exome sequencing, with SNVs and INDEls called according to GATK best practices.

| EGAD00001004311 | EGA

T2D of Multi-omics

Project description:T2D of Multi-omics

| PRJEB28715 | ENA

GoT2D

Project description:The Genetics of Type 2 Diabetes Consortium (GoT2D) is a collaboration between the University of Michigan, the Broad Institute and the Wellcome Trust Centre for Human Genetics. The overall aim is to extend upon recent efforts, such as genome-wide association studies (GWAS) and large scale meta-analyses. While they have proved successful at mapping genomic loci that influence human diseases, like type 2 diabetes, much of the heritability remains unexplained. In this study, we use next generation sequencing and genotyping technologies to query for lower frequency variants in the human genome. Thereby, allowing a deeper characterization of the spectrum of alleles associated with type 2 diabetes risk, and a better assessment of the genes that play a role in the etiology of type 2 diabetes development. We studied 1,326 T2D cases and 1,331 normoglycemic controls from Northern and Central Europe (Sweden, Finland, UK, and Germany). To efficiently characterize the entire genome sequence of each individual, we performed low-coverage (~5x) whole-genome sequencing, augmented by deep coverage (~100x) sequencing of the exome (Fuchsberger et al, 2016), and dense (2.5M) single nucleotide polymorphism (SNP) genotyping using the HumanOmni2.5 array. The data deposited in dbGaP will include all the Swedish, Finnish, and UK samples, but the German data will be deposited in the European Genome-phenome Archive (<a href="https://www.ebi.ac.uk/ega/home">EGA</a>), by virtue of the project specific funding requirements.

| phs000840 | dbGaP

Perturb-Seq using T2D islets

Project description:Type 2 diabetes is associated with defective insulin secretion and reduced β-cell mass. Available treatments provide a temporary reprieve, but secondary failure rates are high, making insulin supplementation necessary. Reversibility of b-cell failure is a key translational question. Here, we reverse-engineered and interrogated pancreatic islet-specific regulatory networks to discover T2D-specific subpopulations characterized by metabolic-inflexibility and endocrine-progenitor/stem cell features. Single-cell gain- and loss-of-function and glucose-induced Ca++ flux analyses of top candidate MR in islet cells validated transcription factor BACH2 and associated epigenetic effectors as a key driver of T2D cell states. BACH2 knockout in T2D islets reversed cellular features of the disease, restoring a non-diabetic phenotype. BACH2-immunoreactive islet cells increased ~4-fold in diabetic patients, confirming the algorithmic prediction of clinically relevant subpopulations. Treatment with a BACH inhibitor lowered glycemia and increased plasma insulin levels in diabetic mice, and restored insulin secretion in diabetic mice and human islets. The findings suggest that T2D-specific populations of failing b-cells can be reversed and indicate pathways for pharmacological intervention, including via BACH2 inhibition.

2021-11-11 | GSE137766 | GEO

Korean T2D microbiome study

Project description:16S metagenome of Korean T2D cohort

| PRJEB45895 | ENA

T2D

Project description:WTCCC1 project Type 2 Diabetes (T2D) samples

| EGAD00000000009 | EGA

Perturb-Seq using T2D islets

Project description:Perturb-Seq using T2D islets

| PRJNA568200 | ENA

Comparison of Blood Transcriptomic Profiles of Healthy, T2D and Diabetic Nephropathy (DN) Reveals FTO as a potential target for DN

Project description:To identify the potential regulators in the progression of diabetic nephropathy (DN), we performed RNA sequencing of blood samples from healthy volunteers, patients with T2D, and patients with DN. Further analyses revealed that FTO was significantly downregulated in blood samples of T2D and DN patients, while the expression of other erasers, writers or readers remained unchanged between disease and healthy groups . Our study thus provides potential molecular mechanisms for DN progression and association of differential gene expression with the functional and structural changes observed in patients with DN.

2024-01-13 | GSE154881 | GEO

Subcutaneous adipose gene expression comparison between NW, OW, PT2, and T2D individuals

Project description:The prevalence of type 2 diabetes (T2D) has increased significantly over the past three decades, with an estimated 30-40% of cases remaining undiagnosed. Brown and beige adipose tissues are known for their remarkable catabolic capacity, and their ability to diminish blood glucose plasma concentration. Beige adipose tissue can be differentiated from adipose-derived stem cells or through transdifferentiation from white adipocytes. However, the impact of T2D progression on beige adipocytes' functional capacity remains unclear. Transcriptomic profiling of subcutaneous adipose tissue biopsies from healthy normal-weight, obese, prediabetic obese, and obese subjects diagnosed with T2D, reveals a progressive alteration in cellular processes associated with catabolic metabolism, circadian rhythms, thermogenesis-related signaling pathways, cellular stress, and inflammation. MAX is a potential transcription factor that links inflammation with the circadian clock and thermogenesis during the progression of T2D. This study unveils an unrecognized transcriptional circuit that increasingly disrupts subcutaneous adipose tissue oxidative capacity during the progression of T2D. These findings could open new research venues for developing chrono-pharmaceutical strategies to treat and prevent T2D.

2025-02-04 | GSE249298 | GEO

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