InsPIRE islets
Ontology highlight
ABSTRACT:
PROVIDER: EGAS00001003997 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, many key tissues and cell-types required for appropriate functional inference are absent from large-scale resources such as ENCODE and GTEx. We explored the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using RNA-Seq and genotyping data from 420 islet donors. We find: (a) eQTLs have a variable replication rate across the 44 GTEx tissues (<73%), indicating that our study captured islet-specific cis-eQTL signals; (b) islet eQTL signals show marked overlap with islet epigenome annotation, though eQTL effect size is reduced in the stretch enhancers most strongly implicated in GWAS signal location; (c) selective enrichment of islet eQTL overlap with the subset of T2D variants implicated in islet dysfunction; and (d) colocalization between islet eQTLs and variants influencing T2D or related glycemic traits, delivering candidate effector transcripts at 23 loci, including DGKB and TCF7L2. Our findings illustrate the advantages of performing functional and regulatory studies in tissues of greatest disease-relevance while expanding our mechanistic insights into complex traits association loci activity with an expanded list of putative transcripts implicated in T2D development.
| EGAS00001004056 | EGA
Project description:Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, many key tissues and cell-types required for appropriate functional inference are absent from large-scale resources such as ENCODE and GTEx. We explored the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using RNA-Seq and genotyping data from 420 islet donors. We find: (a) eQTLs have a variable replication rate across the 44 GTEx tissues (<73%), indicating that our study captured islet-specific cis-eQTL signals; (b) islet eQTL signals show marked overlap with islet epigenome annotation, though eQTL effect size is reduced in the stretch enhancers most strongly implicated in GWAS signal location; (c) selective enrichment of islet eQTL overlap with the subset of T2D variants implicated in islet dysfunction; and (d) colocalization between islet eQTLs and variants influencing T2D or related glycemic traits, delivering candidate effector transcripts at 23 loci, including DGKB and TCF7L2. Our findings illustrate the advantages of performing functional and regulatory studies in tissues of greatest disease-relevance while expanding our mechanistic insights into complex traits association loci activity with an expanded list of putative transcripts implicated in T2D development.
| EGAS00001004044 | EGA
Project description:Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, many key tissues and cell-types required for appropriate functional inference are absent from large-scale resources such as ENCODE and GTEx. We explored the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using RNA-Seq and genotyping data from 420 islet donors. We find: (a) eQTLs have a variable replication rate across the 44 GTEx tissues (<73%), indicating that our study captured islet-specific cis-eQTL signals; (b) islet eQTL signals show marked overlap with islet epigenome annotation, though eQTL effect size is reduced in the stretch enhancers most strongly implicated in GWAS signal location; (c) selective enrichment of islet eQTL overlap with the subset of T2D variants implicated in islet dysfunction; and (d) colocalization between islet eQTLs and variants influencing T2D or related glycemic traits, delivering candidate effector transcripts at 23 loci, including DGKB and TCF7L2. Our findings illustrate the advantages of performing functional and regulatory studies in tissues of greatest disease-relevance while expanding our mechanistic insights into complex traits association loci activity with an expanded list of putative transcripts implicated in T2D development.
| EGAS00001004042 | EGA
Project description:In this study, we used single cell nucleus ATAC-seq (snATAC-seq) to profile 218,973 islet cells from 34 individuals, including islets from non-diabetic, pre-diabetic and type 2 diectic (T2D) donors. We characterize changes in regulatory programs of islet cell types in T2D progression, describe the relationship of these programs to genetic risk for T2D, and use allelic imbalance mapping to define cell type-specific functions for candidate T2D causal variants.
2023-02-07 | GSE169453 | GEO
Project description:Type-2 diabetes (T2D) mellitus results from a complex interplay of genetic and environmental factors leading to deficient insulin secretion from pancreatic islet beta cells. Here, we provide a the first comprehensive study of the human islet state of metabolically profiled pancreatectomized living human donors in relationship to glycemic control integrating clinical traits with multiple in situ islet and pre-operative blood omics datasets across the glycemia continuum from non diabetic healthy to overt T2D levels. Our transcriptomics and proteomics data suggest that progressive dysregulation of islet gene expression associated with increasing glucose intolerance is a disharmonic process resembling a non-linear trajectory of mature beta cell states towards trans-differentiation. Furthermore, we identify a unique islet gene set altered already in early-onset glucose intolerance and that, which correlates well across HbA1c levels - the gold-standard in clinical monitoring. Our findings reach beyond conventional clinical thresholds and can serve as direct or indirect prognostic markers for beta cell failure.
2021-10-12 | PXD022561 | Pride
Project description:We used single cell multiome (ATAC and RNA) sequencing to profile 85266 islet cells from 20 individuals, including islets from non-diabetic, pre-diabetic and type 2 diabetic (T2D) donors. We characterize changes in regulatory programs of islet cell types and subtypes in T2D progression, describe the relationship of these programs to genetic risk for T2D, and use allelic imbalance mapping to define cell type-specific functions for candidate T2D causal variants.
2023-02-07 | GSE200044 | GEO
Project description:The intersection of genome-wide association analyses with physiological and functional data indicates that variants regulating islet gene transcription influence type 2 diabetes predisposition and glucose homeostasis. However, the specific genes through which these regulatory variants act remain poorly characterized. In this study, we generated eQTL data from human islet samples to establish the extent to which this allowed us to identify candidate effector transcripts at GWAS loci for T2D and glycemic traits.
| EGAS00001001265 | EGA
Project description:Pancreatic islet beta cell heterogeneity has been identified, which plays a pivotal role in the pathological alterations of pancreatic islets in type 2 diabetes (T2D) mice. However, pathological alterations of beta cells in type 2 diabetes (T2D) mice remain to be investigated. We isolated pancreatic islets from the control and T2D mice and conducted scRNA-seq analysis using the 10x Genomics platform. Pathological alterations of beta cells in T2D were also explored.
2022-04-09 | GSE200531 | GEO
Project description:In this study, we achieved integrated transcriptomic and proteomic profiles of GK islets in a time-course fashion at different stages of T2D. Subsequent bioinformatics analysis revealed the chronological order of T2D-related molecular events during the deterioration of pancreatic islets. Our large quantitative dataset provide a valuable resource to obtain a comprehensive picture of the mechanisms responsible for islet dysfunction and to identify potential interventions to prevent beta-cell failure in human T2D.
2017-06-02 | PXD004709 | Pride
Project description:Recent advances in the understanding of the genetics of type 2 diabetes (T2D) susceptibility have focused attention on the regulation of transcriptional activity within the pancreatic beta-cell. MicroRNAs (miRNAs) represent an important component of regulatory control, and have proven roles in the development of human disease and control of glucose homeostasis. We set out to establish the miRNA profile of human pancreatic islets and of enriched beta-cell populations, and to explore their potential involvement in T2D susceptibility. We used Illumina small RNA sequencing to profile the miRNA fraction in three preparations each of primary human islets and of enriched beta-cells generated by fluorescence-activated cell sorting. In total, 366 miRNAs were found to be expressed (i.e. >100 cumulative reads) in islets and 346 in beta-cells; of the total of 384 unique miRNAs, 328 were shared. A comparison of the islet-cell miRNA profile with those of 15 other human tissues identified 40 miRNAs predominantly expressed (i.e. >50% of all reads seen across the tissues) in islets. Several highly-expressed islet miRNAs, such as miR-375, have established roles in the regulation of islet function, but others (e.g. miR-27b-3p, miR-192-5p) have not previously been described in the context of islet biology. As a first step towards exploring the role of islet-expressed miRNAs and their predicted mRNA targets in T2D pathogenesis, we looked at published T2D association signals across these sites. We found evidence that predicted mRNA targets of islet-expressed miRNAs were globally enriched for signals of T2D association (p-values <0.01, q-values <0.1). At six loci with genome-wide evidence for T2D association (AP3S2, KCNK16, NOTCH2, SCL30A8, VPS26A, and WFS1) predicted mRNA target sites for islet-expressed miRNAs overlapped potentially causal variants. In conclusion, we have described the miRNA profile of human islets and beta-cells and provide evidence linking islet miRNAs to T2D pathogenesis. Examination of the miRNA profiles in 3 preparations of isolated pancreatic islets and 3 preparations of FACS-enriched pancreatic beta-cells
2013-06-07 | E-GEOD-47720 | biostudies-arrayexpress