Type 2 diabetes mellitus (T2DM) is an increasingly prevalent multifactorial disease that has both genetic and environmental risk factors, resulting in impaired glucose homeostasis. Genome-wide association studies (GWAS) have identified over 400 genetic signals that are associated with altered risk of T2DM. Human physiology and epigenomic data support a central role for the pancreatic islet in the pathogenesis of T2DM. This Review focuses on the promises and challenges of moving from genetic associations to molecular mechanisms and highlights efforts to identify the causal variant and effector transcripts at T2DM GWAS susceptibility loci. In addition, we examine current human models that are used to study both β-cell development and function, including EndoC-β cell lines and human induced pluripotent stem cell-derived β-like cells. We use examples of four T2DM susceptibility loci (CDKAL1, MTNR1B, SLC30A8 and PAM) to emphasize how a holistic approach involving genetics, physiology, and cellular and developmental biology can disentangle disease mechanisms at T2DM GWAS signals.
Genome-wide association studies (GWAS) have identified >400 signals associated with the risk of type 2 diabetes mellitus (T2DM).
The pancreatic islet has been identified as a key tissue involved in mediating GWAS signals in T2DM risk.
Integrating genetic, epigenomic and cellular data can unlock the biology behind GWAS signals.
Improvements in human β-cell models coupled with genome-editing technologies offer new possibilities for modelling the pathogenesis of T2DM.
This is a preview of subscription content, access via your institution
Open Access articles citing this article.
Cell Regeneration Open Access 01 August 2022
Scientific Reports Open Access 11 May 2022
Molecular Biology Reports Open Access 15 March 2022
Subscribe to Nature+
Get immediate online access to the entire Nature family of 50+ journals
Subscribe to Journal
Get full journal access for 1 year
only $8.25 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Get time limited or full article access on ReadCube.
All prices are NET prices.
International Diabetes Federation. IDF Diabetes Atlas, 9th edn. Brussels, Belgium (2019).
Newman, B. et al. Concordance for type 2 (non-insulin-dependent) diabetes mellitus in male twins. Diabetologia 30, 763–768 (1987).
Neel, J. V. in The Genetics of Diabetes Mellitus (eds W. Creutzfeldt, J. Köbberling, & J. V. Neel) 1-11 (Springer, 1976).
International HapMap Consortium, et al. A second generation human haplotype map of over 3.1 million SNPs. Nature 449, 851–861 (2007).
Sabeti, P. C. et al. Genome-wide detection and characterization of positive selection in human populations. Nature 449, 913–918 (2007).
Genomes Project, C. et al. A global reference for human genetic variation. Nature 526, 68–74 (2015).
Clarke, L. et al. The International Genome Sample Resource (IGSR): a worldwide collection of genome variation incorporating the 1000 genomes project data. Nucleic Acids Res. 45, D854–D859 (2017).
Sudlow, C. et al. UK Biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 12, e1001779 (2015).
Mahajan, A. et al. Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps. Nat. Genet. 50, 1505–1513 (2018). This GWAS includes just under 1 million Europeans and identifies >400 signals associated with T2DM risk.
Almaca, J. et al. Human β cells produce and release serotonin to inhibit glucagon secretion from α cells. Cell Rep. 17, 3281–3291 (2016).
van der Meulen, T. et al. Urocortin3 mediates somatostatin-dependent negative feedback control of insulin secretion. Nat. Med. 21, 769–776 (2015).
Unger, R. H. & Orci, L. Paracrinology of islets and the paracrinopathy of diabetes. Proc. Natl Acad. Sci. USA 107, 16009–16012 (2010).
Rorsman, P. & Huising, M. O. The somatostatin-secreting pancreatic δ-cell in health and disease. Nat. Rev. Endocrinol. 14, 404–414 (2018).
Dimas, A. S. et al. Impact of type 2 diabetes susceptibility variants on quantitative glycemic traits reveals mechanistic heterogeneity. Diabetes 63, 2158–2171 (2014). This study provides evidence for the central role of the β-cell in T2DM, as many T2DM risk alleles were associated with defects in islet function in individuals without T2DM.
Ingelsson, E. et al. Detailed physiologic characterization reveals diverse mechanisms for novel genetic loci regulating glucose and insulin metabolism in humans. Diabetes 59, 1266–1275 (2010).
Voight, B. F. et al. Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis. Nat. Genet. 42, 579–589 (2010).
Hosker, J. P., Rudenski, A. S., Burnett, M. A., Matthews, D. R. & Turner, R. C. Similar reductions of first- and second-phase β-cell responses at three different glucose levels in type 2 diabetes and the effect of gliclazide therapy. Metabolism 38, 767–772 (1989).
Ashcroft, F. M. & Rorsman, P. Diabetes mellitus and the β cell: the last ten years. Cell 148, 1160–1171 (2012).
Kahn, S. E. Clinical review 135: the importance of β-cell failure in the development and progression of type 2 diabetes. J. Clin. Endocrinol. Metab. 86, 4047–4058 (2001).
Kahn, C. R. Banting Lecture. Insulin action, diabetogenes, and the cause of type II diabetes. Diabetes 43, 1066–1084 (1994).
Mahajan, A. et al. Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes. Nat. Genet. 50, 559–571 (2018). This study demonstrates the value of coding variant associations for improving fine-mapping and identifying effector transcripts at T2DM loci through exome sequence data on 52,000 individuals.
Udler, M. S. et al. Type 2 diabetes genetic loci informed by multi-trait associations point to disease mechanisms and subtypes: a soft clustering analysis. PLoS Med. 15, e1002654 (2018). This study highlights the clinical utility for T2DM risk variants with respect to informing on disease pathophysiology and the potential for stratification.
Thurner, M. et al. Integration of human pancreatic islet genomic data refines regulatory mechanisms at type 2 diabetes susceptibility loci. eLife 7, e31977 (2018).
Khetan, S. et al. Type 2 diabetes-associated genetic variants regulate chromatin accessibility in human islets. Diabetes 67, 2466–2477 (2018).
Pasquali, L. et al. Pancreatic islet enhancer clusters enriched in type 2 diabetes risk-associated variants. Nat. Genet. 46, 136–143 (2014). This study characterizes human islet stretch enhancers and demonstrates enrichment of T2DM risk variants in active islet enhancers.
Parker, S. C. et al. Chromatin stretch enhancer states drive cell-specific gene regulation and harbor human disease risk variants. Proc. Natl Acad. Sci. USA 110, 17921–17926 (2013).
Varshney, A. et al. Genetic regulatory signatures underlying islet gene expression and type 2 diabetes. Proc. Natl Acad. Sci. USA 114, 2301–2306 (2017).
McCarthy, S. et al. A reference panel of 64,976 haplotypes for genotype imputation. Nat. Genet. 48, 1279–1283 (2016).
Pickrell, J. K. Joint analysis of functional genomic data and genome-wide association studies of 18 human traits. Am. J. Hum. Genet. 94, 559–573 (2014).
Tewhey, R. et al. Direct identification of hundreds of expression-modulating variants using a multiplexed reporter assay. Cell 165, 1519–1529 (2016).
van Arensbergen, J. et al. High-throughput identification of human SNPs affecting regulatory element activity. Nat. Genet. 51, 1160–1169 (2019).
Lee, D. et al. A method to predict the impact of regulatory variants from DNA sequence. Nat. Genet. 47, 955–961 (2015).
Zhou, J. et al. Whole-genome deep-learning analysis identifies contribution of noncoding mutations to autism risk. Nat. Genet. 51, 973–980 (2019).
Grotz, A. K., Gloyn, A. L. & Thomsen, S. K. Prioritising causal genes at type 2 diabetes risk loci. Curr. Diab Rep. 17, 76 (2017).
Greenwald, W. W. et al. Pancreatic islet chromatin accessibility and conformation reveals distal enhancer networks of type 2 diabetes risk. Nat. Commun. 10, 2078 (2019).
Miguel-Escalada, I. et al. Human pancreatic islet three-dimensional chromatin architecture provides insights into the genetics of type 2 diabetes. Nat. Genet. 51, 1137–1148 (2019). This study determines interactions between human islet promoters and regulatory elements using promoter capture Hi-C to prioritize effector transcripts at T2DM-associated and fasting glucose-associated loci.
Nica, A. C. & Dermitzakis, E. T. Expression quantitative trait loci: present and future. Philos. Trans. R. Soc. Lond. B Biol. Sci. 368, 20120362 (2013).
van de Bunt, M. et al. Transcript expression data from human islets links regulatory signals from genome-wide association studies for type 2 diabetes and glycemic traits to their downstream effectors. PLoS Genet. 11, e1005694 (2015).
Viñuela, A. et al. Influence of genetic variants on gene expression in human pancreatic islets — implications for type 2 diabetes. bioRxiv https://doi.org/10.1101/655670 (2019). This study is the largest undertaken that investigates the co-localization of T2DM GWAS signals and cis-eQTLs in human islets.
Hattersley, A. T. & Patel, K. A. Precision diabetes: learning from monogenic diabetes. Diabetologia 60, 769–777 (2017).
Gloyn, A. L. et al. Activating mutations in the gene encoding the ATP-sensitive potassium-channel subunit Kir6.2 and permanent neonatal diabetes. N. Engl. J. Med. 350, 1838–1849 (2004).
Ellard, S. et al. Permanent neonatal diabetes caused by dominant, recessive, or compound heterozygous SUR1 mutations with opposite functional effects. Am. J. Hum. Genet. 81, 375–382 (2007).
Babenko, A. P. et al. Activating mutations in the ABCC8 gene in neonatal diabetes mellitus. N. Engl. J. Med. 355, 456–466 (2006).
Pearson, E. R. et al. Switching from insulin to oral sulfonylureas in patients with diabetes due to Kir6.2 mutations. N. Engl. J. Med. 355, 467–477 (2006).
Allen, H. L. et al. GATA6 haploinsufficiency causes pancreatic agenesis in humans. Nat. Genet. 44, 20–22 (2011).
Yamagata, K. et al. Mutations in the hepatocyte nuclear factor-4α gene in maturity-onset diabetes of the young (MODY1). Nature 384, 458–460 (1996).
Froguel, P. et al. Close linkage of glucokinase locus on chromosome 7p to early-onset non-insulin-dependent diabetes mellitus. Nature 356, 162–164 (1992).
Hattersley, A. T. et al. Linkage of type-2 diabetes to the glucokinase gene. Lancet 339, 1307–1310 (1992).
Yamagata, K. et al. Mutations in the hepatocyte nuclear factor-1α gene in maturity-onset diabetes of the young (MODY3). Nature 384, 455–458 (1996).
Stoffers, D. A., Ferrer, J., Clarke, W. L. & Habener, J. F. Early-onset type-II diabetes mellitus (MODY4) linked to IPF1. Nat. Genet. 17, 138–139 (1997).
Kristinsson, S. Y. et al. MODY in Iceland is associated with mutations in HNF-1α and a novel mutation in NeuroD1. Diabetologia 44, 2098–2103 (2001).
Horikawa, Y. et al. Mutation in hepatocyte nuclear factor-1β gene (TCF2) associated with MODY. Nat. Genet. 17, 384–385 (1997).
Haumaitre, C. et al. Severe pancreas hypoplasia and multicystic renal dysplasia in two human fetuses carrying novel HNF1β/MODY5 mutations. Hum. Mol. Genet. 15, 2363–2375 (2006).
Rorsman, P. & Ashcroft, F. M. Pancreatic β-cell electrical activity and insulin secretion: of mice and men. Physiol. Rev. 98, 117–214 (2018).
Kulkarni, R. N. & Stewart, A. F. Summary of the keystone islet workshop (April 2014): the increasing demand for human islet availability in diabetes research. Diabetes 63, 3979–3981 (2014).
Hart, N. J. & Powers, A. C. Use of human islets to understand islet biology and diabetes: progress, challenges and suggestions. Diabetologia 62, 212–222 (2019).
Poitout, V. et al. A call for improved reporting of human islet characteristics in research articles. Diabetes 68, 239–240 (2019).
Weir, G. C. & Bonner-Weir, S. Finally! A human pancreatic β cell line. J. Clin. Invest. 121, 3395–3397 (2011).
Ravassard, P. et al. A genetically engineered human pancreatic β cell line exhibiting glucose-inducible insulin secretion. J. Clin. Invest. 121, 3589–3597 (2011). This paper describes the establishment of the first widely adopted human β-cell line, EndoC-βH1.
Scharfmann, R. et al. Development of a conditionally immortalized human pancreatic β cell line. J. Clin. Invest. 124, 2087–2098 (2014).
Hastoy, B. et al. Electrophysiological properties of human β-cell lines EndoC-βH1 and -βH2 conform with human β-cells. Sci. Rep. 8, 16994 (2018).
Lawlor, N. et al. Multiomic profiling identifies cis-regulatory networks underlying human pancreatic β cell identity and function. Cell Rep. 26, 788–801 (2019).
Benazra, M. et al. A human β cell line with drug inducible excision of immortalizing transgenes. Mol. Metab. 4, 916–925 (2015).
D’Amour, K. A. et al. Production of pancreatic hormone-expressing endocrine cells from human embryonic stem cells. Nat. Biotechnol. 24, 1392–1401 (2006).
Kroon, E. et al. Pancreatic endoderm derived from human embryonic stem cells generates glucose-responsive insulin-secreting cells in vivo. Nat. Biotechnol. 26, 443–452 (2008).
Nostro, M. C. et al. Efficient generation of NKX6-1+ pancreatic progenitors from multiple human pluripotent stem cell lines. Stem Cell Rep. 4, 591–604 (2015).
Nostro, M. C. et al. Stage-specific signaling through TGFβ family members and WNT regulates patterning and pancreatic specification of human pluripotent stem cells. Development 138, 861–871 (2011).
Russ, H. A. et al. Controlled induction of human pancreatic progenitors produces functional β-like cells in vitro. EMBO J. 34, 1759–1772 (2015).
Kelly, O. G. et al. Cell-surface markers for the isolation of pancreatic cell types derived from human embryonic stem cells. Nat. Biotechnol. 29, 750–756 (2011).
Rezania, A. et al. Enrichment of human embryonic stem cell-derived NKX6.1-expressing pancreatic progenitor cells accelerates the maturation of insulin-secreting cells in vivo. Stem Cell 31, 2432–2442 (2013).
Schulz, T. C. et al. A scalable system for production of functional pancreatic progenitors from human embryonic stem cells. PLoS One 7, e37004 (2012).
Pagliuca, F. W. et al. Generation of functional human pancreatic β cells in vitro. Cell 159, 428–439 (2014).
Rezania, A. et al. Reversal of diabetes with insulin-producing cells derived in vitro from human pluripotent stem cells. Nat. Biotechnol. 32, 1121–1133 (2014).
Bruin, J. E. et al. Maturation and function of human embryonic stem cell-derived pancreatic progenitors in macroencapsulation devices following transplant into mice. Diabetologia 56, 1987–1998 (2013).
Rezania, A. et al. Maturation of human embryonic stem cell-derived pancreatic progenitors into functional islets capable of treating pre-existing diabetes in mice. Diabetes 61, 2016–2029 (2012).
Velazco-Cruz, L. et al. Acquisition of dynamic function in human stem cell-derived β cells. Stem Cell Reports 61, 2016–2029 (2019).
Nair, G. G. et al. Recapitulating endocrine cell clustering in culture promotes maturation of human stem-cell-derived β cells. Nat. Cell Biol. 21, 263–274 (2019). This study presents one of the most recent differentiation protocols for generating β-like cells from pluripotent cells and highlights the importance of 3D structure in endocrine cell maturation.
Hrvatin, S. et al. Differentiated human stem cells resemble fetal, not adult, β cells. Proc. Natl Acad. Sci. USA 111, 3038–3043 (2014).
Teo, A. K. et al. Derivation of human induced pluripotent stem cells from patients with maturity onset diabetes of the young. J. Biol. Chem. 288, 5353–5356 (2013).
Stepniewski, J. et al. Induced pluripotent stem cells as a model for diabetes investigation. Sci. Rep. 5, 8597 (2015).
Flanagan, S. E. et al. Activating germline mutations in STAT3 cause early-onset multi-organ autoimmune disease. Nat. Genet. 46, 812–814 (2014).
Saarimaki-Vire, J. et al. An activating STAT3 mutation causes neonatal diabetes through premature induction of pancreatic differentiation. Cell Rep. 19, 281–294 (2017).
Balboa, D. et al. Insulin mutations impair β-cell development in a patient-derived iPSC model of neonatal diabetes. eLife 7, e38519 (2018). This comprehensive study elucidates the mechanisms of diabetes pathogenesis using iPSC differentiation towards β-like cells.
Wang, X. et al. Point mutations in the PDX1 transactivation domain impair human β-cell development and function. Mol. Metab. 24, 80–97 (2019).
Taapken, S. M. et al. Karyotypic abnormalities in human induced pluripotent stem cells and embryonic stem cells. Nat. Biotechnol. 29, 313–314 (2011).
Merkle, F. T. et al. Human pluripotent stem cells recurrently acquire and expand dominant negative P53 mutations. Nature 545, 229–233 (2017).
Kajiwara, M. et al. Donor-dependent variations in hepatic differentiation from human-induced pluripotent stem cells. Proc. Natl Acad. Sci. USA 109, 12538–12543 (2012).
Kyttala, A. et al. Genetic variability overrides the impact of parental cell type and determines iPSC differentiation potential. Stem Cell Rep. 6, 200–212 (2016).
Rouhani, F. et al. Genetic background drives transcriptional variation in human induced pluripotent stem cells. PLoS Genet. 10, e1004432 (2014).
Krentz, N. A. J. & Lynn, F. C. in Genome Editing (ed. Turksen, K.) 127–147 (Springer, 2016).
Zhu, Z. et al. Genome editing of lineage determinants in human pluripotent stem cells reveals mechanisms of pancreatic development and diabetes. Cell Stem Cell 18, 755–768 (2016).
McGrath, P. S., Watson, C. L., Ingram, C., Helmrath, M. A. & Wells, J. M. The basic helix–loop–helix transcription factor NEUROG3 is required for development of the human endocrine pancreas. Diabetes 64, 2497–2505 (2015).
Pascoe, L. et al. Common variants of the novel type 2 diabetes genes CDKAL1 and HHEX/IDE are associated with decreased pancreatic β-cell function. Diabetes 56, 3101–3104 (2007).
Saxena, R. et al. Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science 316, 1331–1336 (2007).
Scott, L. J. et al. A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants. Science 316, 1341–1345 (2007).
Steinthorsdottir, V. et al. A variant in CDKAL1 influences insulin response and risk of type 2 diabetes. Nat. Genet. 39, 770–775 (2007).
Zeggini, E. et al. Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. Science 316, 1336–1341 (2007).
Dehwah, M. A., Wang, M. & Huang, Q. Y. CDKAL1 and type 2 diabetes: a global meta-analysis. Genet. Mol. Res. 9, 1109–1120 (2010).
Peng, F. et al. The relationship between five widely-evaluated variants in CDKN2A/B and CDKAL1 genes and the risk of type 2 diabetes: a meta-analysis. Gene 531, 435–443 (2013).
Sim, X. et al. Transferability of type 2 diabetes implicated loci in multi-ethnic cohorts from Southeast Asia. PLoS Genet. 7, e1001363 (2011).
Miyaki, K. et al. Association of a cyclin-dependent kinase 5 regulatory subunit-associated protein 1-like 1 (CDKAL1) polymorphism with elevated hemoglobin A(1)(c) levels and the prevalence of metabolic syndrome in Japanese men: interaction with dietary energy intake. Am. J. Epidemiol. 172, 985–991 (2010).
Takeuchi, F. et al. Confirmation of multiple risk loci and genetic impacts by a genome-wide association study of type 2 diabetes in the Japanese population. Diabetes 58, 1690–1699 (2009).
Mahajan, A. et al. Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility. Nat. Genet. 46, 234–244 (2014).
Kirchhoff, K. et al. Polymorphisms in the TCF7L2, CDKAL1 and SLC30A8 genes are associated with impaired proinsulin conversion. Diabetologia 51, 597–601 (2008).
Stancakova, A. et al. Association of 18 confirmed susceptibility loci for type 2 diabetes with indices of insulin release, proinsulin conversion, and insulin sensitivity in 5,327 nondiabetic Finnish men. Diabetes 58, 2129–2136 (2009).
Groenewoud, M. J. et al. Variants of CDKAL1 and IGF2BP2 affect first-phase insulin secretion during hyperglycaemic clamps. Diabetologia 51, 1659–1663 (2008).
Wood, A. R. et al. A genome-wide association study of IVGTT-based measures of first-phase insulin secretion refines the underlying physiology of type 2 diabetes variants. Diabetes 66, 2296–2309 (2017).
Stancakova, A. et al. Single-nucleotide polymorphism rs7754840 of CDKAL1 is associated with impaired insulin secretion in nondiabetic offspring of type 2 diabetic subjects and in a large sample of men with normal glucose tolerance. J. Clin. Endocrinol. Metab. 93, 1924–1930 (2008).
Wei, F. Y. et al. Deficit of tRNA(Lys) modification by Cdkal1 causes the development of type 2 diabetes in mice. J. Clin. Invest. 121, 3598–3608 (2011).
Grosjean, H., Sprinzl, M. & Steinberg, S. Posttranscriptionally modified nucleosides in transfer RNA: their locations and frequencies. Biochimie 77, 139–141 (1995).
Okamura, T. et al. Deletion of CDKAL1 affects high-fat diet-induced fat accumulation and glucose-stimulated insulin secretion in mice, indicating relevance to diabetes. PLoS One 7, e49055 (2012).
Ohara-Imaizumi, M. et al. Deletion of CDKAL1 affects mitochondrial ATP generation and first-phase insulin exocytosis. PLoS One 5, e15553 (2010).
Zeng, H. et al. An isogenic human esc platform for functional evaluation of genome-wide-association-study-identified diabetes genes and drug discovery. Cell Stem Cell 19, 326–340 (2016).
Ragvin, A. et al. Long-range gene regulation links genomic type 2 diabetes and obesity risk regions to HHEX, SOX4, and IRX3. Proc. Natl Acad. Sci. USA 107, 775–780 (2010).
Mavropoulos, A. et al. sox4b is a key player of pancreatic α cell differentiation in zebrafish. Dev. Biol. 285, 211–223 (2005).
Wilson, M. E. et al. The HMG box transcription factor Sox4 contributes to the development of the endocrine pancreas. Diabetes 54, 3402–3409 (2005).
Xu, E. E. et al. SOX4 cooperates with neurogenin 3 to regulate endocrine pancreas formation in mouse models. Diabetologia 58, 1013–1023 (2015).
Goldsworthy, M. et al. Role of the transcription factor sox4 in insulin secretion and impaired glucose tolerance. Diabetes 57, 2234–2244 (2008).
Collins, S. C. et al. Increased expression of the diabetes gene SOX4 reduces insulin secretion by impaired fusion pore expansion. Diabetes 65, 1952–1961 (2016).
Xu, E. E., Sasaki, S., Speckmann, T., Nian, C. & Lynn, F. C. SOX4 allows facultative β-cell proliferation through repression of Cdkn1a. Diabetes 66, 2213–2219 (2017).
Bouatia-Naji, N. et al. A variant near MTNR1B is associated with increased fasting plasma glucose levels and type 2 diabetes risk. Nat. Genet. 41, 89–94 (2009).
Lyssenko, V. et al. Common variant in MTNR1B associated with increased risk of type 2 diabetes and impaired early insulin secretion. Nat. Genet. 41, 82–88 (2009).
Prokopenko, I. et al. Variants in MTNR1B influence fasting glucose levels. Nat. Genet. 41, 77–81 (2009).
Langenberg, C. et al. Common genetic variation in the melatonin receptor 1B gene (MTNR1B) is associated with decreased early-phase insulin response. Diabetologia 52, 1537–1542 (2009).
Jonsson, A. et al. Effects of common genetic variants associated with type 2 diabetes and glycemic traits on α- and β-cell function and insulin action in humans. Diabetes 62, 2978–2983 (2013).
t Hart, L. M. et al. Combined risk allele score of eight type 2 diabetes genes is associated with reduced first-phase glucose-stimulated insulin secretion during hyperglycemic clamps. Diabetes 59, 287–292 (2010).
Gaulton, K. J. et al. Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci. Nat. Genet. 47, 1415–1425 (2015).
Tuomi, T. et al. Increased melatonin signaling is a risk factor for type 2 diabetes. Cell Metab. 23, 1067–1077 (2016).
Ramracheya, R. D. et al. Function and expression of melatonin receptors on human pancreatic islets. J. Pineal Res. 44, 273–279 (2008).
Nagorny, C. L., Sathanoori, R., Voss, U., Mulder, H. & Wierup, N. Distribution of melatonin receptors in murine pancreatic islets. J. Pineal Res. 50, 412–417 (2011).
Dubocovich, M. L. et al. International Union of Basic and Clinical Pharmacology. LXXV. Nomenclature, classification, and pharmacology of G protein-coupled melatonin receptors. Pharmacol. Rev. 62, 343–380 (2010).
Peschke, E. et al. Evidence for a melatonin receptor within pancreatic islets of neonate rats: functional, autoradiographic, and molecular investigations. J. Pineal Res. 28, 156–164 (2000).
Peschke, E., Bahr, I. & Muhlbauer, E. Experimental and clinical aspects of melatonin and clock genes in diabetes. J. Pineal Res. 59, 1–23 (2015).
Mulder, H., Nagorny, C. L., Lyssenko, V. & Groop, L. Melatonin receptors in pancreatic islets: good morning to a novel type 2 diabetes gene. Diabetologia 52, 1240–1249 (2009).
Peschke, E., Bach, A. G. & Muhlbauer, E. Parallel signaling pathways of melatonin in the pancreatic β-cell. J. Pineal Res. 40, 184–191 (2006).
Bonnefond, A. et al. Rare MTNR1B variants impairing melatonin receptor 1B function contribute to type 2 diabetes. Nat. Genet. 44, 297–301 (2012).
Mulder, H. Melatonin signalling and type 2 diabetes risk: too little, too much or just right? Diabetologia 60, 826–829 (2017).
Maret, W. Zinc in cellular regulation: the nature and significance of ‘zinc signals’. Int. J. Mol. Sci. 18, 2285 (2017).
Huang, L. & Tepaamorndech, S. The SLC30 family of zinc transporters — a review of current understanding of their biological and pathophysiological roles. Mol. Asp. Med. 34, 548–560 (2013).
Jeong, J. & Eide, D. J. The SLC39 family of zinc transporters. Mol. Asp. Med. 34, 612–619 (2013).
Zalewski, P. D. et al. Video image-analysis of labile zinc in viable pancreatic-islet cells using a specific fluorescent-probe for zinc. J. Histochem. Cytochem. 42, 877–884 (1994).
Hutton, J. C., Penn, E. J. & Peshavaria, M. Low-molecular-weight constituents of isolated insulin-secretory granules. Bivalent cations, adenine nucleotides and inorganic phosphate. Biochem. J. 210, 297–305 (1983).
Dunn, M. F. Zinc–ligand interactions modulate assembly and stability of the insulin hexamer — a review. Biometals 18, 295–303 (2005).
Cruz, K. J., de Oliveira, A. R. & Marreiro Ddo, N. Antioxidant role of zinc in diabetes mellitus. World J. Diabetes 6, 333–337 (2015).
Basaki, M., Saeb, M., Nazifi, S. & Shamsaei, H. A. Zinc, copper, iron, and chromium concentrations in young patients with type 2 diabetes mellitus. Biol. Trace Elem. Res. 148, 161–164 (2012).
Jansen, J. et al. Disturbed zinc homeostasis in diabetic patients by in vitro and in vivo analysis of insulinomimetic activity of zinc. J. Nutr. Biochem. 23, 1458–1466 (2012).
Lemaire, K., Chimienti, F. & Schuit, F. Zinc transporters and their role in the pancreatic β-cell. J. Diabetes Investig. 3, 202–211 (2012).
Nicolson, T. J. et al. Insulin storage and glucose homeostasis in mice null for the granule zinc transporter ZnT8 and studies of the type 2 diabetes-associated variants. Diabetes 58, 2070–2083 (2009).
Pound, L. D. et al. Deletion of the mouse Slc30a8 gene encoding zinc transporter-8 results in impaired insulin secretion. Biochem. J. 421, 371–376 (2009).
Sladek, R. et al. A genome-wide association study identifies novel risk loci for type 2 diabetes. Nature 445, 881–885 (2007).
Horikoshi, M. et al. Variations in the HHEX gene are associated with increased risk of type 2 diabetes in the Japanese population. Diabetologia 50, 2461–2466 (2007).
Omori, S. et al. Association of CDKAL1, IGF2BP2, CDKN2A/B, HHEX, SLC30A8, and KCNJ11 with susceptibility to type 2 diabetes in a Japanese population. Diabetes 57, 791–795 (2008).
Shan, Z. L. et al. Interactions between zinc transporter-8 gene (SLC30A8) and plasma zinc concentrations for impaired glucose regulation and type 2 diabetes. Diabetes 63, 1796–1803 (2014).
Staiger, H. et al. Polymorphisms within novel risk loci for type 2 diabetes determine β-cell function. PLoS One 2, e832 (2007).
Lemaire, K. R. et al. Insulin crystallization depends on zinc transporter ZnT8 expression, but is not required for normal glucose homeostasis in mice. Proc. Natl Acad. Sci. USA 106, 14872–14877 (2009).
Gerber, P. A. et al. Hypoxia lowers SLC30A8/ZnT8 expression and free cytosolic Zn2+ in pancreatic β cells. Diabetologia 57, 1635–1644 (2014).
Wijesekara, N. et al. β cell-specific Znt8 deletion in mice causes marked defects in insulin processing, crystallisation and secretion. Diabetologia 53, 1656–1668 (2010).
Tamaki, M. et al. The diabetes-susceptible gene SLC30A8/ZnT8 regulates hepatic insulin clearance. J. Clin. Invest. 123, 4513–4524 (2013).
Solomou, A. et al. The zinc transporter Slc30a8/ZnT8 is required in a subpopulation of pancreatic α-cells for hypoglycemia-induced glucagon secretion. J. Biol. Chem. 290, 21432–21442 (2015).
Mitchell, R. K. et al. Molecular genetic regulation of Slc30a8/ZnT8 reveals a positive association with glucose tolerance. Mol. Endocrinol. 30, 77–91 (2016).
Fu, Y. et al. Down-regulation of ZnT8 expression in INS-1 rat pancreatic β cells reduces insulin content and glucose-inducible insulin secretion. PLoS One 4, e5679 (2009).
Flannick, J. et al. Exome sequencing of 20,791 cases of type 2 diabetes and 24,440 controls. Nature 570, 71–76 (2019).
Flannick, J. et al. Loss-of-function mutations in SLC30A8 protect against type 2 diabetes. Nat. Genet. 46, 357–363 (2014).
Dwivedi, O. P. et al. Loss of ZnT8 function protects against diabetes by enhanced insulin secretion. Nat. Genet. 51, 1596–1606 (2019). This collaborative mechanistic study investigates how loss-of-function SLC30A8 alleles are protective against T2DM.
Kleiner, S. et al. Mice harboring the human SLC30A8 R138X loss-of-function mutation have increased insulin secretory capacity. Proc. Natl Acad. Sci. USA 115, E7642–E7649 (2018).
Fuchsberger, C. et al. The genetic architecture of type 2 diabetes. Nature 536, 41–47 (2016).
Steinthorsdottir, V. et al. Identification of low-frequency and rare sequence variants associated with elevated or reduced risk of type 2 diabetes. Nat. Genet. 46, 294–298 (2014).
Lek, M. et al. Analysis of protein-coding genetic variation in 60,706 humans. Nature 536, 285–291 (2016).
Xue, A. et al. Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes. Nat. Commun. 9, 2941 (2018).
Huyghe, J. R. et al. Exome array analysis identifies new loci and low-frequency variants influencing insulin processing and secretion. Nat. Genet. 45, 197–201 (2013).
Chen, Y. C., Taylor, A. J. & Verchere, C. B. Islet prohormone processing in health and disease. Diabetes Obes. Metab. 20, 64–76 (2018).
Maltese, J. Y. et al. Ontogenetic expression of peptidyl-glycine α-amidating monooxygenase mRNA in the rat pancreas. Biochem. Biophys. Res. Commun. 158, 244–250 (1989).
Zhou, A. & Thorn, N. A. Evidence for presence of peptide α-amidating activity in pancreatic islets from newborn rats. Biochem. J. 267, 253–256 (1990).
Thomsen, S. K. et al. Type 2 diabetes risk alleles in PAM impact insulin release from human pancreatic β-cells. Nat. Genet. 50, 1122–1131 (2018). This mechanistic study shows how T2DM risk alleles in PAM impact insulin release by reducing catalytic function and/or protein function.
Prigge, S. T., Mains, R. E., Eipper, B. A. & Amzel, L. M. New insights into copper monooxygenases and peptide amindation: structure, mechanism and function. Cell. Mol. Life Sci. 57, 1236–1259 (2000).
Czyzyk, T. A. et al. Deletion of peptide amidation enzymatic activity leads to edema and embryonic lethality in the mouse. Dev. Biol. 287, 301–313 (2005).
Thomsen, S. K. et al. Systematic functional characterization of candidate causal genes for type 2 diabetes risk variants. Diabetes 65, 3805–3811 (2016).
Fang, Z. et al. Single-cell heterogeneity analysis and CRISPR screen identify key β-cell-specific disease genes. Cell Rep. 26, 3132–3144.e7 (2019).
A.L.G. is a Wellcome Trust Senior Fellow in Basic Biomedical Science. A.L.G. is funded by the Wellcome Trust (095101, 200837, 106130, 203141), Medical Research Council (MR/L020149/1), European Union Horizon 2020 Programme (T2D Systems) and NIH (U01-DK105535; U01-DK085545), and by the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC). The views expressed are those of the author(s) and not necessarily those of the National Health Service, the NIHR or the Department of Health.
The authors declare no competing interests.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
1000 Genomes: https://www.internationalgenome.org/
HapMap Project: https://www.genome.gov/10001688/international-hapmap-project
UK Biobank: https://www.ukbiobank.ac.uk/
- Posterior probability of association
The likelihood of a given variant being causal.
- Credible set
The minimal group of disease or trait-associated variants that are the product of fine-mapping.
- Promoter capture Hi-C
A genome-wide experimental technique used to detect interactions between promoters and other regulatory elements.
- Maturity-onset diabetes of the young
(MODY). A rare, autosomal dominantly inherited form of diabetes caused by a mutation in a single gene which typically presents before the age of 25 years.
- Isogenic cell line
A cell line genetically engineered to introduce specific mutations and derived from a parental cell line.
- Recruit by genotype study
A research study where patients are selected based on their genotype.
A measure of β-cell exocytosis based on electrical current.
About this article
Cite this article
Krentz, N.A.J., Gloyn, A.L. Insights into pancreatic islet cell dysfunction from type 2 diabetes mellitus genetics. Nat Rev Endocrinol 16, 202–212 (2020). https://doi.org/10.1038/s41574-020-0325-0
Cell Regeneration (2022)
Scientific Reports (2022)
Molecular Biology Reports (2022)
A dual-quenched ECL immunosensor for ultrasensitive detection of retinol binding protein 4 based on luminol@AuPt/ZIF-67 and MnO2@CNTs
Journal of Nanobiotechnology (2021)
BMC Endocrine Disorders (2021)