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Gaulton, K. J.

Publications and source records attributed to Gaulton, K. J..

29 records · Page 2Linked to original sources

Large-scale genetic association and single cell accessible chromatin mapping defines cell type-specific mechanisms of type 1 diabetes risk

Translating genome-wide association studies (GWAS) of complex disease into mechanistic insight requires a comprehensive understanding of risk variant effects on disease-relevant cell types. To uncover cell type-specific mechanisms of type 1 diabetes (T1D) risk, we combined genetic association mapping and single cell epigenomics. We performed the largest to-date GWAS of T1D in 489,679 samples imputed into 59.2M variants, which identified 74 novel association signals including several large-effect rare variants. Fine-mapping of 141 total signals substantially improved resolution of causal variant credible sets, which primarily mapped to non-coding sequence. To annotate cell type-specific regulatory mechanisms of T1D risk variants, we mapped 448,142 candidate cis-regulatory elements (cCREs) in pancreas and peripheral blood mononuclear cell types using snATAC-seq of 131,554 nuclei. T1D risk variants were enriched in cCREs active in CD4+ T cells as well as several additional cell types including pancreatic exocrine acinar and ductal cells. High-probability T1D risk variants at multiple signals mapped to exocrine-specific cCREs including novel loci near CEL, GP2 and CFTR. At the CFTR locus, the likely causal variant rs7795896 mapped in a ductal-specific distal cCRE which regulated CFTR and the risk allele reduced transcription factor binding, enhancer activity and CFTR expression in ductal cells. These findings support a role for the exocrine pancreas in T1D pathogenesis and highlight the power of combining large-scale GWAS and single cell epigenomics to provide insight into the cellular origins of complex disease.

genetics↗

Mapping genetic effects on cell type-specific chromatin accessibility and annotating complex trait variants using single nucleus ATAC-seq

Gene regulation is highly cell type-specific and understanding the function of non-coding genetic variants associated with complex traits requires molecular phenotyping at cell type resolution. In this study we performed single nucleus ATAC-seq (snATAC-seq) and genotyping in peripheral blood mononuclear cells from 10 individuals. Clustering chromatin accessibility profiles of 66,843 total nuclei identified 14 immune cell types and sub-types. We mapped chromatin accessibility QTLs (caQTLs) in each immune cell type and sub-type which identified 6,248 total caQTLs, including those obscured from assays of bulk tissue such as with divergent effects on different cell types. For 3,379 caQTLs we further annotated putative target genes of variant activity using single cell co-accessibility, and caQTL variants were significantly correlated with the accessibility level of linked gene promoters. We fine-mapped loci associated with 16 complex immune traits and identified immune cell caQTLs at 517 candidate causal variants, including those with cell type-specific effects. At the 6q15 locus associated with type 1 diabetes, in line with previous reports, variant rs72928038 was a naive CD4+ T cell caQTL linked to BACH2 and we validated the allelic effects of this variant on regulatory activity in Jurkat T cells. These results highlight the utility of snATAC-seq for mapping genetic effects on accessible chromatin in specific cell types and provide a resource for annotating complex immune trait loci.

genomics↗

Cardiac Cell Type-Specific Gene Regulatory Programs and Disease Risk Association

BackgroundCis-regulatory elements such as enhancers and promoters are crucial for directing gene expression in the human heart. Dysregulation of these elements can result in many cardiovascular diseases that are major leading causes of morbidity and mortality worldwide. In addition, genetic variants associated with cardiovascular disease risk are enriched within cis-regulatory elements. However, the location and activity of these cis-regulatory elements in individual cardiac cell types remains to be fully defined. MethodsWe performed single nucleus ATAC-seq and single nucleus RNA-seq to define a comprehensive catalogue of candidate cis-regulatory elements (cCREs) and gene expression patterns for the distinct cell types comprising each chamber of four non-failing human hearts. We used this catalogue to computationally deconvolute dynamic enhancers in failing hearts and to assign cardiovascular disease risk variants to cCREs in individual cardiac cell types. Finally, we applied reporter assays, genome editing and electrophysiogical measurements in in vitro differentiated human cardiomyocytes to validate the molecular mechanisms of cardiovascular disease risk variants. ResultsWe defined >287,000 candidate cis-regulatory elements (cCREs) in human hearts at single-cell resolution, which notably revealed gene regulatory programs controlling specific cell types in a cardiac region/structure-dependent manner and during heart failure. We further report enrichment of cardiovascular disease risk variants in cCREs of distinct cardiac cell types, including a strong enrichment of atrial fibrillation variants in cardiomyocyte cCREs, and reveal 38 candidate causal atrial fibrillation variants localized to cardiomyocyte cCREs. Two such risk variants residing within a cardiomyocyte-specific cCRE at the KCNH2/HERG locus resulted in reduced enhancer activity compared to the non-risk allele. Finally, we found that deletion of the cCRE containing these variants decreased KCNH2 expression and prolonged action potential repolarization in an enhancer dosage-dependent manner. ConclusionsThis comprehensive atlas of human cardiac cCREs provides the foundation for not only illuminating cell type-specific gene regulatory programs controlling human hearts during health and disease, but also interpreting genetic risk loci for a wide spectrum of cardiovascular diseases.

genomics↗

A dual mechanism of enhancer activation by FOXA pioneer factors induces endodermal organ fates

FOXA pioneer transcription factors (TFs) displace nucleosomes and prime chromatin across enhancers of different endodermal organs in multipotent precursors before lineage induction. Here, we examined patterns and mechanisms of FOXA target site engagement using human pluripotent stem cell models of endodermal organ development. Unexpectedly, we find that only a subset of pancreatic, hepatic, and alveolar enhancers are FOXA-primed, whereas the majority are unprimed and engage FOXA only upon lineage induction. Analysis of sequence architecture revealed more abundant and stronger FOXA motifs at primed than unprimed enhancers and enrichment for lineage-specific TF motifs at unprimed enhancers. We show that FOXA recruitment to unprimed enhancers specifically depends on lineage-specific TFs, suggesting that regulatory DNA sequence logic governs temporal FOXA recruitment. Our findings suggest that FOXA-mediated enhancer priming broadly facilitates initiation of organ lineage programs, while secondary FOXA recruitment by lineage-specific TFs to the majority of enhancers confers organ specificity to gene expression.

genomics↗

Pancreatic progenitor epigenome maps prioritize type 2 diabetes risk genes with roles in development

Genetic variants associated with type 2 diabetes (T2D) risk affect gene regulation in metabolically relevant tissues, such as pancreatic islets. Here, we investigated contributions of regulatory programs active during pancreatic development to T2D risk. Generation of chromatin maps from developmental precursors throughout pancreatic differentiation of human embryonic stem cells (hESCs) identifies enrichment of T2D variants in pancreatic progenitor-specific stretch enhancers that are not active in islets. Genes associated with progenitor-specific stretch enhancers are predicted to regulate developmental processes, most notably tissue morphogenesis. Through gene editing in hESCs, we demonstrate that progenitor-specific enhancers harboring T2D-associated variants regulate cell polarity genes LAMA1 and CRB2. Knockdown of lama1 or crb2 in zebrafish embryos causes a defect in pancreas morphogenesis and impairs islet cell development. Together, our findings reveal that a subset of T2D risk variants specifically affects pancreatic developmental programs, suggesting that dysregulation of developmental processes can predispose to T2D.

genomics↗

Glucocorticoid signaling in pancreatic islets modulates gene regulatory programs and genetic risk of type 2 diabetes

Glucocorticoids are key regulators of glucose homeostasis and pancreatic islet function, but the gene regulatory programs driving responses to glucocorticoid signaling in islets and the contribution of these programs to diabetes risk are unknown. In this study we used ATAC-seq and RNA-seq to map chromatin accessibility and gene expression from eight primary human islet samples cultured in vitro with the glucocorticoid dexamethasone. We identified 2,838 accessible chromatin sites and 1,114 genes with significant changes in activity in response to glucocorticoids. Chromatin sites up-regulated in glucocorticoid signaling were prominently enriched for glucocorticoid receptor binding sites and up-regulated genes were enriched for ion transport and lipid metabolism, whereas down-regulated chromatin sites and genes were enriched for inflammatory, stress response and proliferative processes. Genetic variants associated with glucose levels and T2D risk were enriched in glucocorticoid-responsive chromatin sites, including fine-mapped risk variants at 54 known signals. Among fine-mapped variants in glucocorticoid-responsive chromatin, a likely casual variant at the 2p21 locus had glucocorticoid-dependent allelic effects on beta cell enhancer activity and affected SIX2 and SIX3 expression. Our results provide a comprehensive map of islet regulatory programs in response to glucocorticoids through which we uncover a role for islet glucocorticoid signaling in mediating risk of type 2 diabetes.

genomics↗

Single Nucleus Multiomic Profiling Reveals Age-Dynamic Regulation of Host Genes Associated with SARS-CoV-2 Infection

Respiratory failure is the leading cause of COVID-19 death and disproportionately impacts adults more than children. Here, we present a large-scale snATAC-seq dataset (90,980 nuclei) of the human lung, generated in parallel with snRNA-seq (46,500 nuclei), from healthy donors of ~30 weeks, ~3 years and ~30 years of age. Focusing on genes implicated in SARS-CoV-2 cell entry, we observed an increase in the proportion of alveolar epithelial cells expressing ACE2 and TMPRSS2 in adult compared to young lungs. Consistent with expression dynamics, 10 chromatin peaks linked to TMPRSS2 exhibited significantly increased activity with age and harbored IRF and STAT binding sites. Furthermore, we identified 14 common sequence variants in age-increasing peaks with predicted regulatory function, including several associated with respiratory traits and TMPRSS2 expression. Our findings reveal a plausible contributor to why children are more resistant to COVID-19 and provide an epigenomic basis for transferring this resistance to older populations.

genomics↗

Nutrient regulation of the islet epigenome controls adaptive insulin secretion

Adaptation of the islet {beta}-cell insulin secretory response to changing insulin demand is critical for blood glucose homeostasis, yet the mechanisms underlying this adaptation are unknown. Here, we show that nutrient-stimulated histone acetylation plays a key role in adapting insulin secretion through regulation of genes involved in {beta}-cell nutrient sensing and metabolism. Nutrient regulation of the epigenome occurs at sites occupied by the chromatin-modifying enzyme Lsd1 in islets. We demonstrate that {beta}-cell-specific deletion of Lsd1 leads to insulin hypersecretion, aberrant expression of nutrient response genes, and histone hyperacetylation. Islets from mice adapted to chronically increased insulin demand exhibited similar epigenetic and transcriptional changes. Moreover, genetic variants associated with fasting glucose and type 2 diabetes are enriched at LSD1-bound sites in human islets, suggesting that interpretation of nutrient signals is genetically determined. Our findings reveal that adaptive insulin secretion involves Lsd1-mediated coupling of nutrient state to regulation of the islet epigenome.

physiology↗

Trans-ethnic genome-wide association study provides insight into effector genes and molecular mechanisms for kidney function and highlights a causal effect on kidney-specific disease aetiologies

Chronic kidney disease (CKD) affects [~]10% of the global population, with considerable ethnic differences in prevalence and aetiology. We assembled genome-wide association studies (GWAS)1-3 of estimated glomerular filtration rate (eGFR), a measure of kidney function that defines CKD, in 312,468 individuals from four ancestry groups. We identified 93 loci (20 novel), which were delineated to 127 distinct association signals. These signals were homogenous across ancestries, and were enriched for protein-coding exons, kidney-specific histone modifications, and transcription factor binding sites for HDAC2 and EZH2. Fine-mapping revealed 40 high-confidence variants driving eGFR associations and highlighted potential causal genes with cell-type specific expression in glomerulus, and proximal and distal nephron. Mendelian randomisation (MR) supported causal effects of eGFR on overall and cause-specific CKD, kidney stone formation, diastolic blood pressure (DBP) and hypertension. These results define novel molecular mechanisms and effector genes for eGFR, offering insight into clinical outcomes and routes to CKD treatment development.

genetics↗

Developing a network view of type 2 diabetes risk pathways through integration of genetic, genomic and functional data

Genome wide association studies (GWAS) have identified several hundred susceptibility loci for Type 2 Diabetes (T2D). One critical, but unresolved, issue concerns the extent to which the mechanisms through which these diverse signals influencing T2D predisposition converge on a limited set of biological processes. However, the causal variants identified by GWAS mostly fall into non-coding sequence, complicating the task of defining the effector transcripts through which they operate. Here, we describe implementation of an analytical pipeline to address this question. First, we integrate multiple sources of genetic, genomic, and biological data to assign positional candidacy scores to the genes that map to T2D GWAS signals. Second, we introduce genes with high scores as seeds within a network optimization algorithm (the asymmetric prize-collecting Steiner Tree approach) which uses external, experimentally-confirmed protein-protein interaction (PPI) data to generate high confidence subnetworks. Third, we use GWAS data to test the T2D-association enrichment of the \"non-seed\" proteins introduced into the network, as a measure of the overall functional connectivity of the network. We find: (a) non-seed proteins in the T2D protein-interaction network so generated (comprising 705 nodes) are enriched for association to T2D (p=0.0014) but not control traits; (b) stronger T2D-enrichment for islets than other tissues when we use RNA expression data to generate tissue-specific PPI networks; and (c) enhanced enrichment (p=3.9xl0-5) when we combine analysis of the islet-specific PPI network with a focus on the subset of T2D GWAS loci which act through defective insulin secretion. These analyses reveal a pattern of non-random functional connectivity between causal candidate genes atT2D GWAS loci, and highlight the products of genes including YWHAG, SMAD4 or CDK2 as contributors to T2D-relevant islet dysfunction. The approach we describe can be applied to other complex genetic and genomic data sets, facilitating integration of diverse data types into disease-associated networks.\n\nAuthor summaryWe were interested in the following question: as we discover more and more genetic variants associated with a complex disease, such as type 2 diabetes, will the biological pathways implicated by those variants proliferate, or will the biology converge onto a more limited set of aetiological processes? To address this, we first took the 1895 genes that map to ~100 type 2 diabetes association signals, and pruned these to a set of 451 for which combined genetic, genomic and biological evidence assigned the strongest candidacy with respect to type 2 diabetes pathogenesis. We then sought to maximally connect these genes within a curated protein-protein interaction network. We found that proteins brought into the resulting diabetes interaction network were themselves enriched for diabetes association signals as compared to appropriate control proteins. Furthermore, when we used tissue-specific RNA abundance data to filter the generic protein-protein network, we found that the enrichment for type 2 diabetes association signals was enhanced within a network filtered for pancreatic islet expression, particularly when we selected the subset of diabetes association signals acting through reduced insulin secretion. Our data demonstrate convergence of the biological processes involved in type 2 diabetes pathogenesis and highlight novel contributors.

bioinformatics↗

Shared genetic contribution to type 1 and type 2 diabetes risk

The role of shared genetic risk in the etiology of type 1 diabetes (T1D) and type 2 diabetes (T2D) and the mechanisms of these effects is unknown. In this study, we generated T1D association data of 15k samples imputed into the HRC reference panel which we compared to T2D association data of 159k samples imputed into 1000 Genomes. The effects of genetic variants on T1D and T2D risk at known loci and genome-wide were positively correlated, which we replicated using data from the UK Biobank and clinically-defined diabetes in the WTCCC. Increased risk of T1D and T2D was correlated with higher fasting insulin and fasting glucose level and decreased birth weight, among T1D- and T2D-specifc correlations, and T1D and T2D associated variants were enriched in regulatory elements for pancreatic, insulin resistance (adipose, CD19+ B cell), and developmental (CD184+ endoderm) cell types. We fine-mapped causal variants at known T1D and T2D loci and found evidence for co-localization at five signals, four of which had same direction of effect, including CENPW and GLIS3. Shared risk variants at GLIS3 and other signals were associated with measures of islet function, while CENPW was associated with early growth, and we identified shared risk variants at GLIS3 in islet accessible chromatin with allelic effects on islet regulatory activity. Our findings support shared genetic risk involving variants affecting islet function as well as insulin resistance, growth and development in the etiology of T1D and T2D.

genetics↗