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Interpreting type 1 diabetes risk with genetics and single-cell epigenomics

Abstract

Genetic risk variants that have been identified in genome-wide association studies of complex diseases are primarily non-coding1. Translating these risk variants into mechanistic insights requires detailed maps of gene regulation in disease-relevant cell types2. Here we combined two approaches: a genome-wide association study of type 1 diabetes (T1D) using 520,580 samples, and the identification of candidate cis-regulatory elements (cCREs) in pancreas and peripheral blood mononuclear cells using single-nucleus assay for transposase-accessible chromatin with sequencing (snATAC–seq) of 131,554 nuclei. Risk variants for T1D were enriched in cCREs that were active in T cells and other cell types, including acinar and ductal cells of the exocrine pancreas. Risk variants at multiple T1D signals overlapped with exocrine-specific cCREs that were linked to genes with exocrine-specific expression. At the CFTR locus, the T1D risk variant rs7795896 mapped to a ductal-specific cCRE that regulated CFTR; 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 the pathogenesis of T1D and highlight the power of large-scale genome-wide association studies and single-cell epigenomics for understanding the cellular origins of complex disease.

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Fig. 1: Genome-wide association and fine mapping identify T1D risk signals.
Fig. 2: Reference map of single-cell chromatin accessibility from T1D-relevant tissues.
Fig. 3: Cell-type-specific enrichment and mechanisms of T1D risk variants.
Fig. 4: Fine-mapped T1D variant regulates CFTR in pancreatic ductal cells.

Data availability

Full summary statistics for the T1D GWAS have been deposited into the NHGRI-EBI GWAS catalogue with accession number GCST90014023 and can be downloaded from http://ftp.ebi.ac.uk/pub/databases/gwas/summary_statistics/GCST90014001-GCST90015000/GCST90014023/. Sequencing data for snATAC–seq have been deposited into the NCBI Gene Expression Omnibus (GEO) with accession number GSE163160. Data obtained from the TFClass database are available at http://tfclass.bioinf.med.uni-goettingen.de/ and from the PanglaoDB database at https://panglaodb.se/Source data are provided with this paper.

Code availability

Code used for processing snATAC–seq data sets and clustering cells is available at https://github.com/kjgaulton/pipelines/tree/master/T1D_snATAC_pipeline.

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Acknowledgements

This work was supported by NIH grants DK112155, DK120429 and DK122607 to K.J.G. and M.S., and T32 GM008666 to R.J.G. We thank S. Kuan for assistance with sequencing. Additional acknowledgements for each cohort are listed in the Supplementary Information.

Author information

Affiliations

Authors

Contributions

K.J.G. and J.C. designed the study and wrote the manuscript. J.C. performed genetic association and single-cell genomics analyses. R.J.G. performed molecular experiments on enhancer function. M.-L.O. and S. Huang performed molecular experiments on variant function. R.M. and E.B. contributed to analyses of single-cell gene expression. J.Y.H. and M.M. generated single-cell accessible chromatin data. P.B. and K.K. contributed to single-cell motif enrichment analysis. D.U.G. and S.P. supervised the generation of single-cell accessible chromatin data and contributed to data interpretation and analyses. M.S. supervised experiments related to enhancer function and contributed to data interpretation. S. Heller and A.K. contributed to the design and interpretation of enhancer experiments.

Corresponding authors

Correspondence to Joshua Chiou or Kyle J. Gaulton.

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Competing interests

K.J.G is a consultant for Genentech and holds stock in Vertex Pharmaceuticals; neither is related to the work in this study. The other authors declare no competing interests.

Additional information

Peer review information Nature thanks Jason Torres, Anna Hutchinson, Chris Wallace and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Independent association signals at T1D risk loci.

Bayes factors (natural log-transformed) for independent association signals at the known PTPN2 locus (left) and the novel BCL11A locus (right). Variants are coloured by linkage disequilibrium (r2) with the index variant for each signal.

Extended Data Fig. 2 Rare variants with large effects on T1D risk.

a, The relationship between minor allele frequency and T1D odds ratios (OR) for index variants at 136 T1D signals. Signals with common index variants and larger effect size estimates (PTPN22 1:114,377,568 A:G and INS 11:2,182,224 A:T) or rare index variants (MAF < 0.005) are labelled. Points and lines represent estimates for OR and 95% CI. b, Comparison of OR across cohorts for rare variants. Missing values indicate that the variant was not tested in the cohort. Points and lines represent estimates for OR and 95% CI.

Extended Data Fig. 3 Genetic correlations between T1D and other traits.

Genetic correlations between T1D and immune-related diseases (left), other diseases (middle), and non-disease traits (right); adj., adjusted; circ., circumference. Two-sided P values are adjusted for multiple comparisons with false discovery rate (FDR). Colours indicate significance: red, correlation is significant after FDR correction (FDR < 0.1); black, correlation is nominally significant (P < 0.05) but not significant after FDR correction; grey, correlation is not significant. Points and lines represent genetic correlation estimates and 95% CI.

Extended Data Fig. 4 Annotations derived from single-cell chromatin accessibility of T1D-relevant tissues.

a, Relative gene accessibility (column-normalized chromatin accessibility reads in gene bodies) showing examples of marker genes used to identify cluster labels. Aggregated chromatin accessibility profiles in a 50-kb window around selected marker genes (bottom). b, Single-cell motif enrichment z-scores (left) and expression of motif subfamily members (right) for examples of TFs with lineage-, cell-type-, or cell-state-specific motif enrichment and expression. TFs with matching motif enrichment and expression are highlighted. c, Co-accessibility between AQP1 and cCREs in ductal cells (left) and CEL and cCREs in acinar cells (right).

Extended Data Fig. 5 Single-cell RNA-seq reference map of PBMCs and pancreatic islets.

a, Clustering of 90,495 expression profiles from scRNA-seq experiments of peripheral blood mononuclear cells and pancreatic islets from published studies. Cells are plotted on the first two UMAP components and coloured according to cluster assignment. The number of cells in each cluster is shown next to its corresponding label. HSC, haematopoietic stem cell; γδ T, gamma delta T cell; pDC, plasmacytoid dendritic cell. b, Relative gene expression (average expression for all cells within a cluster and scaled from 0–100 across clusters) showing examples of marker genes used to assign cluster labels. c, Pearson correlation coefficient between gene expression and promoter accessibility specificity scores using a list containing the top 100 most specific genes for each scRNA-seq cluster found in snATAC–seq.

Extended Data Fig. 6 GWAS enrichment for T1D compared to other diseases and traits.

Stratified LD score regression coefficient z-scores for autoimmune and inflammatory diseases (top), other diseases (middle), and non-disease quantitative endophenotypes (bottom) for cCREs that are active in immune and pancreatic cell types. Two sided P values were calculated from z-scores and multiple test correction was performed using FDR. ***FDR < 0.001, **FDR < 0.01, *FDR < 0.1.

Source data

Extended Data Fig. 7 Fine-mapped variants linked to exocrine-specific genes.

a, The GP2 locus contains three variants in a distal cCRE that is co-accessible with the GP2 promoter in acinar cells, which account for the majority of the causal probability (cPPA = 0.98). Chromatin accessibility at both the distal cCRE and the GP2 promoter is highly specific to acinar cells. b, Variant rs72802342 at the CTRB1/2/BCAR1 locus overlaps a distal cCRE that is co-accessible with the CTRB2 and CTRB1 promoters in acinar cells. Chromatin accessibility at the CTRB1 and CTRB2 promoters is highly specific to acinar cells. Variants contained in the 99% credible set are circled in black.

Extended Data Fig. 8 rs7795896 has allelic effects on ductal enhancer activity.

a, Relative luciferase units (RLU) for reporter containing 594-bp sequence surrounding rs7795896 in Capan-1 cells (n = 6; 2 batches × 3 transfections). Centre line, median; box limits, 25th and 75th percentiles; whiskers extend to 1.5 × the interquartile range from the 25th and 75th percentiles. P value by two-sided, two-way ANOVA. b, Luciferase reporter assay in Capan-1 cells transfected with pGL4.23 minimal promoter plasmids containing rs7795896 in the forward orientation. Relative luciferase units (RLU) represent Firefly:Renilla ratios normalized to control cells transfected with the empty pGL4.23 vector. P value by two-sided Student’s t-test. c, Electrophoretic mobility shift assay with nuclear extract from Capan-1 cells using probes for rs7795896 alleles, with or without 200× unlabelled competitor probe (200× comp.). Quantification of the bound fraction (specific binding/free probe). Data are from n = 1 experiment. d, rs7795896 overlaps histone marks of active enhancers (H3K4me1, H3K27ac; region: chr7:117,050,000–117,125,000, hg19) but not promoters (H3K4me3) in pancreatic ductal adenocarcinoma (PDAC) cell lines (Capan-1, Capan-2, and CFPAC-1). rs7795896 overlaps a ChIP–seq peak for the transcription factor HNF1B in CFPAC-1 cells and a predicted HNF1B motif. e, Relative expression for genes in a 2-Mb window around rs7795896 with non-zero expression and the puromycin resistance and dCas9 genes. Ctrl, control, n = 3 biological replicates; Enh, enhancer, n = 9, 3 sgRNAs × 3 biological replicates; Prom, promoter, n = 3 biological replicates. Data are mean ± 95% CI. P values by two-sided Student’s t-test (Prom versus Ctrl) or two-sided ANOVA (Enh versus Ctrl); NS, not significant.

Source data

Extended Data Fig. 9 rs7795896 affects CFTR expression levels in ductal cells.

a, Bayesian colocalization of T1D signal and CFTR pancreas eQTL. Variants in the T1D credible set are circled. b, Expression of pancreatic cell type marker genes from scRNA-seq. c, Proportions of selected pancreatic cell types estimated by MuSiC for 220 bulk pancreas RNA-seq samples from the GTEx v7 release using single-cell expression profiles. d, −log10-transformed two-sided uncorrected P values from linear regression interaction between dosage and cell-type proportion for the CFTR pancreas eQTL.

Extended Data Fig. 10 Relationship between T1D and other pancreatic diseases.

a, rs7795896 GWAS association for T1D (from full meta-analysis), pancreatic disease, and autoimmune disease. Points and lines represent OR estimates and 95% CI. Two-sided P values from GWAS meta-analysis are unadjusted for multiple comparisons. b, Variants that regulate genes with specialized exocrine pancreas function influence T1D risk, and we hypothesize that these effects are mediated through inflammation and immune infiltration.

Supplementary information

Supplementary Information

This file contains Supplementary Figs. 1-9 and the Supplementary Note.

Reporting Summary

Supplementary Tables

This file contains Supplementary Tables 1-11.

Supplementary Data 1

This file contains the 99% credible sets for 136 independent T1D risk signals.

Supplementary Data 2

This file contains cell type-resolved TPM-normalized gene expression for pancreatic and immune cell types.

Supplementary Data 3

This file contains the catalog of 448,142 cCREs.

Supplementary Data 4

This file contains the subset of 25,436 cCREs elements with the most cell type-specific accessibility.

Supplementary Data 5

This file contains cell type-resolved chromVAR motif enrichment z-scores.

Supplementary Data 6

This file contains co-accessibility links between distal cCREs and gene promoters.

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Chiou, J., Geusz, R.J., Okino, ML. et al. Interpreting type 1 diabetes risk with genetics and single-cell epigenomics. Nature 594, 398–402 (2021). https://doi.org/10.1038/s41586-021-03552-w

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