Single-cell chromatin accessibility identifies pancreatic islet cell type– and state-specific regulatory programs of diabetes risk

Chiou, Joshua; Zeng, Chun; Zhang, Cheng; Han, Jee Yun; Schlichting, Michael; Miller, Michael; Mendez, Robert; Huang, Serina; Wang, Jinzhao; Sui, Yinghui; Deogaygay, Allison; Okino, Mei-Lin; Qiu, Yunjiang; Sun, Ying; Kudtarkar, Parul; Fang, Rongxin; Preißl, Sebastian; Sander, Maike; Gorkin, David U.; Gaulton, Kyle J.

doi:10.1038/s41588-021-00823-0

Cited by 126 publications

(152 citation statements)

References 103 publications

(161 reference statements)

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“…A recent report suggests that a subset of human a-cells, even from donors without diabetes, may exist in an immature state and may suffer a further loss of mature identity in T2D (Avrahami et al, 2020), perhaps related to their greater epigenetic plasticity (Bramswig et al, 2013) and distinct human a-cell states as defined by chromatin accessibility (Chiou et al, 2021). Here we provide evidence that ND acells that exhibit what would be considered inappropriately low exocytotic responses are enriched in transcripts and pathways associated with endocrine development (including FOXO1, PAX6, RFX6 and others) suggesting that a-cells with a lesser degree of maturity (Avrahami et al, 2020) show a concomitant alteration in functional properties.…”

Section: Discussionmentioning

confidence: 99%

“…Human a-cells likely exist in distinct states characterized by chromatin accessibility at the GCG promoter and sites enriched with transcription factor motifs characterizing endocrine lineage and development (Chiou et al, 2021)…”

Section: Impaired Functional Identity and Exocytosis In T2d A-cells Enriched In Lineage And Identity Markersmentioning

confidence: 99%

“…While little evidence so far exists to suggest that a-cells dedifferentiate, they have been shown to trans-differentiate in rodents following severe b-cell loss (Thorel et al, 2010) or genetic manipulation of transcription factor expression (Chakravarthy et al, 2017;Matsuoka et al, 2017). Interestingly, a-cells may show more plasticity than b-cells (Bramswig et al, 2013): they appear to exist in distinct states characterized by chromatin accessibility at promotors for GCG, functional genes such as ABCC8, and at sites enriched in motifs for binding of transcription factors for the RFX, GATA and NEUROD families, among others (Chiou et al, 2021). Human a-cells also appear to exhibit persistent immature transcript profiles which may contribute to impaired identity in T2D (Avrahami et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

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Heterogenous impairment of α-cell function in type 2 diabetes is linked to cell maturation state

Dai

Camunas-Soler

et al. 2021

Preprint

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In diabetes, glucagon secretion from pancreatic α-cells is dysregulated. We examined α-cells from human donors and mice using combined electrophysiological, transcriptomic, and computational approaches. Rising glucose suppresses α-cell exocytosis by reducing P/Q-type Ca2+ channel activity, and this is disrupted in type 2 diabetes (T2D). Upon high-fat-feeding of mice, α-cells shift towards a β-cell-like electrophysiologic profile in concert with an up-regulation of the β-cell Na+ channel isoform Scn9a and indications of impaired α-cell identity. In human α-cells we identify links between cell membrane properties and cell surface signalling receptors, mitochondrial respiratory complex assembly, and cell maturation. Cell type classification using machine learning of electrophysiology data demonstrates a heterogenous loss of electrophysiologic identity in α-cells from donors with T2D. Indeed, a sub-set of α-cells with impaired exocytosis is defined by an enrichment in progenitor markers suggesting important links between α-cell maturation state and dysfunction in T2D.

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Section: Discussionmentioning

confidence: 99%

Section: Impaired Functional Identity and Exocytosis In T2d A-cells Enriched In Lineage And Identity Markersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Heterogenous impairment of α-cell function in type 2 diabetes is linked to cell maturation state

Dai

Camunas-Soler

et al. 2021

Preprint

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“…This study had certain limitations. For example, islets are composed of β cells, α cells, PP cells, δ cells, endothelial cells, and other cell types ( Chiou, et al, 2021 ); therefore, it is necessary to clarify which cells express IL6 and IL11. In addition, the mechanisms of IL6 and IL11 should be further clarified with in vivo and in vitro experiments.…”

Section: Discussionmentioning

confidence: 99%

Glucotoxicity Activation of IL6 and IL11 and Subsequent Induction of Fibrosis May Be Involved in the Pathogenesis of Islet Dysfunction

Zhuang

Shen

et al. 2021

Front. Mol. Biosci.

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Background: Islet dysfunction is the main pathological process of type 2 diabetes mellitus (T2DM). Fibrosis causes islet dysfunction, but the current mechanism is still unclear. Here, bioinformatics analysis identified gene clusters closely related to T2DM and differentially expressed genes related to fibrosis, and animal models verified the roles of these genes.Methods: Human islet transcriptomic datasets were obtained from the Gene Expression Omnibus (GEO), and weighted gene coexpression network analysis (WGCNA) was applied to screen the key gene modules related to T2DM and analyze the correlations between the modules and clinical characteristics. Enrichment analysis was performed to identify the functions and pathways of the key module genes. WGCNA, protein-protein interaction (PPI) analysis and receiver operating characteristic (ROC) curve analysis were used to screen the hub genes. The hub genes were verified in another GEO dataset, the islets of high-fat diet (HFD)-fed Sprague-Dawley rats were observed by H&E and Masson’s trichrome staining, the fibrotic proteins were verified by immunofluorescence, and the hub genes were tested by immunohistochemistry.Results: The top 5,000 genes were selected according to the median absolute deviation, and 18 modules were analyzed. The yellow module was highly associated with T2DM, and its positive correlation with glycated hemoglobin (HbA1c) was significantly stronger than that with body mass index (BMI). Enrichment analysis revealed that extracellular matrix organization, the collagen-containing extracellular matrix and cytokine−cytokine receptor interaction might influence T2DM progression. The top three hub genes, interleukin 6 (IL6), IL11 and prostaglandin-endoperoxide synthase 2 (PTGS2), showed upregulated expression in T2DM. In the validation dataset, IL6, IL11, and PTGS2 levels were upregulated in T2DM, and IL6 and PTGS2 expression was positively correlated with HbA1c and BMI; however, IL11 was positively correlated only with HbA1c. In HFD-fed Sprague-Dawley rats, the positive of IL6 and IL11 in islets was stronger, but PTGS2 expression was not significantly altered. The extent of fibrosis, irregular cellular arrangement and positive actin alpha 2 (ACTA2) staining in islets was significantly greater in HFD-fed rats than in normal diet-fed rats.Conclusion: Glucotoxicity is a major factor leading to increased IL6 and IL11 expression, and IL6-and IL11-induced fibrosis might be involved in islet dysfunction.

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“…First, for type 2 diabetes, two SNPs, rs234866 and rs74046911 (r 2 = 0.02 (but D' = 1)), both located in an intron of KCNQ1 (initially reported as a candidate target gene 58,59 ), were fine-mapped (PIP = 0.97 and 0.92, respectively) and both linked by cS2G to CDKN1C (third closest TSS; cS2G linking scores = 1.00 and 0.96, respectively) (Figure 4a). CDKN1C is a gene expressed in pancreas for which a rare coding mutation was previously linked to type 2 diabetes 60 , and has been nominated as a candidate target gene at this locus using methylation data 61 and CRISPR-Cas9 genome editing 62 . CDKN1C was implicated by 3 of the functionally informed S2G strategies used by cS2G, including EpiMap enhancer-gene linking in endocrine pancreas (for both SNPs), identified by LDSC-SEG 50 as a critical tissue for type 2 diabetes (see Supplementary Table 15).…”

Section: Leveraging the Combined S2g Strategy To Pinpoint Disease Genesmentioning

confidence: 99%

Combining SNP-to-gene linking strategies to pinpoint disease genes and assess disease omnigenicity

Gazal

Weissbrod

Hormozdiari

et al. 2021

Preprint

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Although genome-wide association studies (GWAS) have identified thousands of disease-associated common SNPs, these SNPs generally do not implicate the underlying target genes, as most disease SNPs are regulatory. Many SNP-to-gene (S2G) linking strategies have been developed to link regulatory SNPs to the genes that they regulate in cis, but it is unclear how these strategies should be applied in the context of interpreting common disease risk variants. We developed a framework for evaluating and combining different S2G strategies to optimize their informativeness for common disease risk, leveraging polygenic analyses of disease heritability to define and estimate their precision and recall. We applied our framework to GWAS summary statistics for 63 diseases and complex traits (average N=314K), evaluating 50 S2G strategies. Our optimal combined S2G strategy (cS2G) included 7 constituent S2G strategies (Exon, Promoter, 2 fine-mapped cis-eQTL strategies, EpiMap enhancer-gene linking, Activity-By-Contact (ABC), and Cicero), and achieved a precision of 0.75 and a recall of 0.33, more than doubling the precision and/or recall of any individual strategy; this implies that 33% of SNP-heritability can be linked to causal genes with 75% confidence. We applied cS2G to fine-mapping results for 49 UK Biobank diseases/traits to predict 7,111 causal SNP-gene-disease triplets (with S2G-derived functional interpretation) with high confidence. Finally, we applied cS2G to genome-wide fine-mapping results for these traits (not restricted to GWAS loci) to rank genes by the heritability linked to each gene, providing an empirical assessment of disease omnigenicity; averaging across traits, we determined that the top 200 (1%) of ranked genes explained roughly half of the heritability linked to all genes. Our results highlight the benefits of our cS2G strategy in providing functional interpretation of GWAS findings; we anticipate that precision and recall will increase further under our framework as improved functional assays lead to improved S2G strategies.

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Single-cell chromatin accessibility identifies pancreatic islet cell type– and state-specific regulatory programs of diabetes risk

Cited by 126 publications

References 103 publications

Heterogenous impairment of α-cell function in type 2 diabetes is linked to cell maturation state

Heterogenous impairment of α-cell function in type 2 diabetes is linked to cell maturation state

Glucotoxicity Activation of IL6 and IL11 and Subsequent Induction of Fibrosis May Be Involved in the Pathogenesis of Islet Dysfunction

Combining SNP-to-gene linking strategies to pinpoint disease genes and assess disease omnigenicity

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