ArticleDiabetologia2024
Implicating type 2 diabetes effector genes in relevant metabolic cellular models using promoter-focused Capture-C.
Article in Diabetologia, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Integrative genomics and single-cell CRISPRi screening dissect Alzheimer GWAS non-coding variants regulating TSPAN14.American journal of human genetics · 2026Article
- Genome-Wide Discovery Reveals Adipose-Specific and Systemic Regulators of Insulin Resistance.medRxiv : the preprint server for health sciences · 2026Article
- Genomics link obesity and type 2 diabetes to Alzheimer's disease to unveil novel biological insights.medRxiv : the preprint server for health sciences · 2026Article
- Review
- Variant-to-function approaches for adipose tissue: Insights into cardiometabolic disorders.Cell genomics · 2025Review
- Genetic Variants of the Human Thiamine Transporter (International journal of molecular sciences · 2025Article
- Identifying patterns differing between high-dimensional datasets with generalized contrastive PCA.PLoS computational biology · 2025Article
- Analysis and validation of characteristic genes in RNA sequencing datasets from heart failure patients based on multiple algorithms.Frontiers in cardiovascular medicine · 2025Article
- CHARMER: detecting and harmonizing high-confidence chromatin interactions across tissues and Hi-C protocols.bioRxiv : the preprint server for biology · 2024Article
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Authors and funding
12 authors.
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Abstract
aims/hypothesisGenome-wide association studies (GWAS) have identified hundreds of type 2 diabetes loci, with the vast majority of signals located in non-coding regions; as a consequence, it remains largely unclear which 'effector' genes these variants influence. Determining these effector genes has been hampered by the relatively challenging cellular settings in which they are hypothesised to confer their effects.
methodsTo implicate such effector genes, we elected to generate and integrate high-resolution promoter-focused Capture-C, assay for transposase-accessible chromatin with sequencing (ATAC-seq) and RNA-seq datasets to characterise chromatin and expression profiles in multiple cell lines relevant to type 2 diabetes for subsequent functional follow-up analyses: EndoC-BH1 (pancreatic beta cell), HepG2 (hepatocyte) and Simpson-Golabi-Behmel syndrome (SGBS; adipocyte).
resultsThe subsequent variant-to-gene analysis implicated 810 candidate effector genes at 370 type 2 diabetes risk loci. Using partitioned linkage disequilibrium score regression, we observed enrichment for type 2 diabetes and fasting glucose GWAS loci in promoter-connected putative cis-regulatory elements in EndoC-BH1 cells as well as fasting insulin GWAS loci in SGBS cells. Moreover, as a proof of principle, when we knocked down expression of the SMCO4 gene in EndoC-BH1 cells, we observed a statistically significant increase in insulin secretion. CONCLUSIONS/
interpretationThese results provide a resource for comparing tissue-specific data in tractable cellular models as opposed to relatively challenging primary cell settings. DATA AVAILABILITY: Raw and processed next-generation sequencing data for EndoC-BH1, HepG2, SGBS_undiff and SGBS_diff cells are deposited in GEO under the Superseries accession GSE262484. Promoter-focused Capture-C data are deposited under accession GSE262496. Hi-C data are deposited under accession GSE262481. Bulk ATAC-seq data are deposited under accession GSE262479. Bulk RNA-seq data are deposited under accession GSE262480.
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