Electrophysiological Characterization of Inducible Pluripotent Stem Cell-Derived Human ß-Like Cells and an SLC30A8 Disease Model.

Inducible pluripotent stem cell-derived human ß-like cells (BLCs) hold promise for both therapy and disease modeling, but their generation remains challenging and their functional analyses beyond transcriptomic and morphological assessments remain limited. Here, we validate an approach using multicellular and single-cell electrophysiological tools to evaluate function of BLCs from pioneer protocols that can be easily adapted to more differentiated BLCs. The multi-electrode arrays (MEAs) measuring the extracellular electrical activity revealed that BLCs, like primary ß-cells, are electrically coupled and produce slow potential (SP) signals that are closely linked to insulin secretion. We also used high-resolution single-cell patch clamp measurements to capture the exocytotic properties, and characterize voltage-gated sodium and calcium currents, and found that they were comparable with those in primary ß- and EndoC-ßH1 cells. The KATP channel conductance is greater than in human primary ß-cells, which may account for the limited glucose responsiveness observed with MEA. We used MEAs to study the impact of the type 2 diabetes-protective SLC30A8 allele (p.Lys34Serfs50*) and found that BLCs with this allele have stronger electrical coupling activity. Our data suggest that BLCs can be used to evaluate the functional impact of genetic variants on ß-cell function and coupling.

Diabetes mellitus-Progress and opportunities in the evolving epidemic.

Diabetes, a complex multisystem metabolic disorder characterized by hyperglycemia, leads to complications that reduce quality of life and increase mortality. Diabetes pathophysiology includes dysfunction of beta cells, adipose tissue, skeletal muscle, and liver. Type 1 diabetes (T1D) results from immune-mediated beta cell destruction. The more prevalent type 2 diabetes (T2D) is a heterogeneous disorder characterized by varying degrees of beta cell dysfunction in concert with insulin resistance. The strong association between obesity and T2D involves pathways regulated by the central nervous system governing food intake and energy expenditure, integrating inputs from peripheral organs and the environment. The risk of developing diabetes or its complications represents interactions between genetic susceptibility and environmental factors, including the availability of nutritious food and other social determinants of health. This perspective reviews recent advances in understanding the pathophysiology and treatment of diabetes and its complications, which could alter the course of this prevalent disorder.

HumanIslets: An integrated platform for human islet data access and analysis.

Comprehensive molecular and cellular phenotyping of human islets can enable deep mechanistic insights for diabetes research. We established the Human Islet Data Analysis and Sharing (HI-DAS) consortium to advance goals in accessibility, usability, and integration of data from human islets isolated from donors with and without diabetes at the Alberta Diabetes Institute (ADI) IsletCore. Here we introduce HumanIslets.com, an open resource for the research community. This platform, which presently includes data on 547 human islet donors, allows users to access linked datasets describing molecular profiles, islet function and donor phenotypes, and to perform various statistical and functional analyses at the donor, islet and single-cell levels. As an example of the analytic capacity of this resource we show a dissociation between cell culture effects on transcript and protein expression, and an approach to correct for exocrine contamination found in hand-picked islets. Finally, we provide an example workflow and visualization that highlights links between type 2 diabetes status, SERCA3b Ca2+-ATPase levels at the transcript and protein level, insulin secretion and islet cell phenotypes. HumanIslets.com provides a growing and adaptable set of resources and tools to support the metabolism and diabetes research community.

Proteomic predictors of individualized nutrient-specific insulin secretion in health and disease.

Population-level variation and mechanisms behind insulin secretion in response to carbohydrate, protein, and fat remain uncharacterized. We defined prototypical insulin secretion responses to three macronutrients in islets from 140 cadaveric donors, including those with type 2 diabetes. The majority of donors' islets exhibited the highest insulin response to glucose, moderate response to amino acid, and minimal response to fatty acid. However, 9% of donors' islets had amino acid responses, and 8% had fatty acid responses that were larger than their glucose-stimulated insulin responses. We leveraged this heterogeneity and used multi-omics to identify molecular correlates of nutrient responsiveness, as well as proteins and mRNAs altered in type 2 diabetes. We also examined nutrient-stimulated insulin release from stem cell-derived islets and observed responsiveness to fat but not carbohydrate or protein-potentially a hallmark of immaturity. Understanding the diversity of insulin responses to carbohydrate, protein, and fat lays the groundwork for personalized nutrition.

CD39 delineates chimeric antigen receptor regulatory T cell subsets with distinct cytotoxic & regulatory functions against human islets.

Human regulatory T cells (Treg) suppress other immune cells. Their dysfunction contributes to the pathophysiology of autoimmune diseases, including type 1 diabetes (T1D). Infusion of Tregs is being clinically evaluated as a novel way to prevent or treat T1D. Genetic modification of Tregs, most notably through the introduction of a chimeric antigen receptor (CAR) targeting Tregs to pancreatic islets, may improve their efficacy. We evaluated CAR targeting of human Tregs to monocytes, a human ß cell line and human islet ß cells in vitro. Targeting of HLA-A2-CAR (A2-CAR) bulk Tregs to HLA-A2+ cells resulted in dichotomous cytotoxic killing of human monocytes and islet ß cells. In exploring subsets and mechanisms that may explain this pattern, we found that CD39 expression segregated CAR Treg cytotoxicity. CAR Tregs from individuals with more CD39low/- Tregs and from individuals with genetic polymorphism associated with lower CD39 expression (rs10748643) had more cytotoxicity. Isolated CD39- CAR Tregs had elevated granzyme B expression and cytotoxicity compared to the CD39+ CAR Treg subset. Genetic overexpression of CD39 in CD39low CAR Tregs reduced their cytotoxicity. Importantly, ß cells upregulated protein surface expression of PD-L1 and PD-L2 in response to A2-CAR Tregs. Blockade of PD-L1/PD-L2 increased ß cell death in A2-CAR Treg co-cultures suggesting that the PD-1/PD-L1 pathway is important in protecting islet ß cells in the setting of CAR immunotherapy. In summary, introduction of CAR can enhance biological differences in subsets of Tregs. CD39+ Tregs represent a safer choice for CAR Treg therapies targeting tissues for tolerance induction.

Proteomic predictors of individualized nutrient-specific insulin secretion in health and disease.

Population level variation and molecular mechanisms behind insulin secretion in response to carbohydrate, protein, and fat remain uncharacterized despite ramifications for personalized nutrition. Here, we define prototypical insulin secretion dynamics in response to the three macronutrients in islets from 140 cadaveric donors, including those diagnosed with type 2 diabetes. While islets from the majority of donors exhibited the expected relative response magnitudes, with glucose being highest, amino acid moderate, and fatty acid small, 9% of islets stimulated with amino acid and 8% of islets stimulated with fatty acids had larger responses compared with high glucose. We leveraged this insulin response heterogeneity and used transcriptomics and proteomics to identify molecular correlates of specific nutrient responsiveness, as well as those proteins and mRNAs altered in type 2 diabetes. We also examine nutrient-responsiveness in stem cell-derived islet clusters and observe that they have dysregulated fuel sensitivity, which is a hallmark of functionally immature cells. Our study now represents the first comparison of dynamic responses to nutrients and multi-omics analysis in human insulin secreting cells. Responses of different people's islets to carbohydrate, protein, and fat lay the groundwork for personalized nutrition. ONE-SENTENCE SUMMARY: Deep phenotyping and multi-omics reveal individualized nutrient-specific insulin secretion propensity.

Multiplexed CRISPR gene editing in primary human islet cells with Cas9 ribonucleoprotein.

Successful genome editing in primary human islets could reveal features of the genetic regulatory landscape underlying ß cell function and diabetes risk. Here, we describe a CRISPR-based strategy to interrogate functions of predicted regulatory DNA elements using electroporation of a complex of Cas9 ribonucleoprotein (Cas9 RNP) and guide RNAs into primary human islet cells. We successfully targeted coding regions including the PDX1 exon 1, and non-coding DNA linked to diabetes susceptibility. CRISPR-Cas9 RNP approaches revealed genetic targets of regulation by DNA elements containing candidate diabetes risk SNPs, including an in vivo enhancer of the MPHOSPH9 gene. CRISPR-Cas9 RNP multiplexed targeting of two cis-regulatory elements linked to diabetes risk in PCSK1, which encodes an endoprotease crucial for Insulin processing, also demonstrated efficient simultaneous editing of PCSK1 regulatory elements, resulting in impaired ß cell PCSK1 regulation and Insulin secretion. Multiplex CRISPR-Cas9 RNP provides powerful approaches to investigate and elucidate human islet cell gene regulation in health and diabetes.

Heterogeneity of increased biological age in type 2 diabetes correlates with differential tissue DNA methylation, biological variables, and pharmacological treatments.

Biological age (BA) closely depicts age-related changes at a cellular level. Type 2 diabetes mellitus (T2D) accelerates BA when calculated using clinical biomarkers, but there is a large spread in the magnitude of individuals' age acceleration in T2D suggesting additional factors contributing to BA. Additionally, it is unknown whether BA can be changed with treatment. We hypothesized that potential determinants of the heterogeneous BA distribution in T2D could be due to differential tissue aging as reflected at the DNA methylation (DNAm) level, or biological variables and their respective therapeutic treatments. Publicly available DNAm samples were obtained to calculate BA using the DNAm phenotypic age (DNAmPhenoAge) algorithm. DNAmPhenoAge showed age acceleration in T2D samples of whole blood, pancreatic islets, and liver, but not in adipose tissue or skeletal muscle. Analysis of genes associated with differentially methylated CpG sites found a significant correlation between eight individual CpG methylation sites and gene expression. Clinical biomarkers from participants in the NHANES 2017-2018 and ACCORD cohorts were used to calculate BA using the Klemera and Doubal (KDM) method. Cardiovascular and glycemic biomarkers associated with increased BA while intensive blood pressure and glycemic management reduced BA to CA levels, demonstrating that accelerated BA can be restored in the setting of T2D.

The use of precision diagnostics for monogenic diabetes: a systematic review and expert opinion.

BACKGROUND: Monogenic diabetes presents opportunities for precision medicine but is underdiagnosed. This review systematically assessed the evidence for (1) clinical criteria and (2) methods for genetic testing for monogenic diabetes, summarized resources for (3) considering a gene or (4) variant as causal for monogenic diabetes, provided expert recommendations for (5) reporting of results; and reviewed (6) next steps after monogenic diabetes diagnosis and (7) challenges in precision medicine field. METHODS: Pubmed and Embase databases were searched (1990-2022) using inclusion/exclusion criteria for studies that sequenced one or more monogenic diabetes genes in at least 100 probands (Question 1), evaluated a non-obsolete genetic testing method to diagnose monogenic diabetes (Question 2). The risk of bias was assessed using the revised QUADAS-2 tool. Existing guidelines were summarized for questions 3-5, and review of studies for questions 6-7, supplemented by expert recommendations. Results were summarized in tables and informed recommendations for clinical practice. RESULTS: There are 100, 32, 36, and 14 studies included for questions 1, 2, 6, and 7 respectively. On this basis, four recommendations for who to test and five on how to test for monogenic diabetes are provided. Existing guidelines for variant curation and gene-disease validity curation are summarized. Reporting by gene names is recommended as an alternative to the term MODY. Key steps after making a genetic diagnosis and major gaps in our current knowledge are highlighted. CONCLUSIONS: We provide a synthesis of current evidence and expert opinion on how to use precision diagnostics to identify individuals with monogenic diabetes.

Some diabetes types, called monogenic diabetes, are caused by changes in a single gene. It is important to know who has this kind of diabetes because treatment can differ from that of other types of diabetes. Some treatments also work better than others for specific types, and some people can for example change from insulin injections to tablets. In addition, relatives can be offered a test to see if they are at risk. Genetic testing is needed to diagnose monogenic diabetes but is expensive, so it's not possible to test every person with diabetes for it. We evaluated published research on who should be tested and what test to use. Based on this, we provide recommendations for doctors and health care providers on how to implement genetic testing for monogenic diabetes.

Electrophysiological characterisation of iPSC-derived human ß-like cells and an SLC30A8 disease model.

iPSC-derived human ß-like cells (BLC) hold promise for both therapy and disease modelling, but their generation remains challenging and their functional analyses beyond transcriptomic and morphological assessments remain limited. Here, we validate an approach using multicellular and single cell electrophysiological tools to evaluate BLCs functions. The Multi-Electrode Arrays (MEAs) measuring the extracellular electrical activity revealed that BLCs are electrically coupled, produce slow potential (SP) signals like primary ß-cells that are closely linked to insulin secretion. We also used high-resolution single-cell patch-clamp measurements to capture the exocytotic properties, and characterize voltage-gated sodium and calcium currents. These were comparable to those in primary ß and EndoC-ßH1 cells. The KATP channel conductance is greater than in human primary ß cells which may account for the limited glucose responsiveness observed with MEA. We used MEAs to study the impact of the type 2 diabetes protective SLC30A8 allele (p.Lys34Serfs*50) and found that BLCs with this allele have stronger electrical coupling. Our data suggest that with an adapted approach BLCs from pioneer protocol can be used to evaluate the functional impact of genetic variants on ß-cell function and coupling.

Rare variant association analysis in 51,256 type 2 diabetes cases and 370,487 controls informs the spectrum of pathogenicity of monogenic diabetes genes.

We meta-analyzed array data imputed with the TOPMed reference panel and whole-genome sequence (WGS) datasets and performed the largest, rare variant (minor allele frequency as low as 5×10-5) GWAS meta-analysis of type 2 diabetes (T2D) comprising 51,256 cases and 370,487 controls. We identified 52 novel variants at genome-wide significance (p<5 × 10-8), including 8 novel variants that were either rare or ancestry-specific. Among them, we identified a rare missense variant in HNF4A p.Arg114Trp (OR=8.2, 95% confidence interval [CI]=4.6-14.0, p = 1.08×10-13), previously reported as a variant implicated in Maturity Onset Diabetes of the Young (MODY) with incomplete penetrance. We demonstrated that the diabetes risk in carriers of this variant was modulated by a T2D common variant polygenic risk score (cvPRS) (carriers in the top PRS tertile [OR=18.3, 95%CI=7.2-46.9, p=1.2×10-9] vs carriers in the bottom PRS tertile [OR=2.6, 95% CI=0.97-7.09, p = 0.06]. Association results identified eight variants of intermediate penetrance (OR>5) in monogenic diabetes (MD), which in aggregate as a rare variant PRS were associated with T2D in an independent WGS dataset (OR=4.7, 95% CI=1.86-11.77], p = 0.001). Our data also provided support evidence for 21% of the variants reported in ClinVar in these MD genes as benign based on lack of association with T2D. Our work provides a framework for using rare variant imputation and WGS analyses in large-scale population-based association studies to identify large-effect rare variants and provide evidence for informing variant pathogenicity.

Safe use of the ketogenic diet in an infant with microcephaly, epilepsy, and diabetes syndrome: a case report.

BACKGROUND: Microcephaly, epilepsy, and diabetes syndrome (MEDS) is a rare syndromic form of monogenic diabetes caused by bi-allelic loss of function mutations in IER3IP1. In vitro studies have shown that loss of IER31P leads to apoptosis in both neurons and pancreatic ß-cells. Simultaneous management of seizures and diabetes is challenging in patients with MEDS. We present the challenges and successes in the use of ketogenic diet in an infant with insulinopenic diabetes. CASE PRESENTATION: Our term female proband presented at 2 months of age with new onset multifocal seizures followed by the onset of infantile spasms (IS) at 4 months of age. An epilepsy gene panel identified bi-allelic variants, c.239T > G (p.Leu80*) and c.2T > A (initiator codon), in IER3IP1 that were subsequently shown to be inherited in trans. Following initiation of steroid therapy for IS, the patient developed clinically apparent insulin requiring diabetes. Her epilepsy was ultimately refractory to multiple antiseizure medications, thus the ketogenic diet (KD) was initiated. We were able to successfully titrate to a therapeutic KD ratio of 3:1 and maintain a ketotic state without diabetic ketoacidosis (DKA). With intercurrent illnesses, however, the patient had rapid decompensation and mild DKA due to delays in treatment, and for this reason, KD was discontinued after 5 months. CONCLUSIONS: We report two novel IER31P1 mutations in a patient with MEDS and the successful management of the cooccurring conditions of IS and insulinopenic diabetes with the KD. Our experience underscores the importance of careful monitoring during KD as our patient had DKA more easily when on the KD.

Inferring causal genes at type 2 diabetes GWAS loci through chromosome interactions in islet cells.

Background: Resolving causal genes for type 2 diabetes at loci implicated by genome-wide association studies (GWAS) requires integrating functional genomic data from relevant cell types. Chromatin features in endocrine cells of the pancreatic islet are particularly informative and recent studies leveraging chromosome conformation capture (3C) with Hi-C based methods have elucidated regulatory mechanisms in human islets. However, these genome-wide approaches are less sensitive and afford lower resolution than methods that target specific loci. Methods: To gauge the extent to which targeted 3C further resolves chromatin-mediated regulatory mechanisms at GWAS loci, we generated interaction profiles at 23 loci using next-generation (NG) capture-C in a human beta cell model (EndoC-ßH1) and contrasted these maps with Hi-C maps in EndoC-ßH1 cells and human islets and a promoter capture Hi-C map in human islets. Results: We found improvements in assay sensitivity of up to 33-fold and resolved ~3.6X more chromatin interactions. At a subset of 18 loci with 25 co-localised GWAS and eQTL signals, NG Capture-C interactions implicated effector transcripts at five additional genetic signals relative to promoter capture Hi-C through physical contact with gene promoters. Conclusions: High resolution chromatin interaction profiles at selectively targeted loci can complement genome- and promoter-wide maps.

PAX4 loss of function increases diabetes risk by altering human pancreatic endocrine cell development.

The coding variant (p.Arg192His) in the transcription factor PAX4 is associated with an altered risk for type 2 diabetes (T2D) in East Asian populations. In mice, Pax4 is essential for beta cell formation but its role on human beta cell development and/or function is unknown. Participants carrying the PAX4 p.His192 allele exhibited decreased pancreatic beta cell function compared to homozygotes for the p.192Arg allele in a cross-sectional study in which we carried out an intravenous glucose tolerance test and an oral glucose tolerance test. In a pedigree of a patient with young onset diabetes, several members carry a newly identified p.Tyr186X allele. In the human beta cell model, EndoC-ßH1, PAX4 knockdown led to impaired insulin secretion, reduced total insulin content, and altered hormone gene expression. Deletion of PAX4 in human induced pluripotent stem cell (hiPSC)-derived islet-like cells resulted in derepression of alpha cell gene expression. In vitro differentiation of hiPSCs carrying PAX4 p.His192 and p.X186 risk alleles exhibited increased polyhormonal endocrine cell formation and reduced insulin content that can be reversed with gene correction. Together, we demonstrate the role of PAX4 in human endocrine cell development, beta cell function, and its contribution to T2D-risk.

Multiplexed CRISPR gene editing in primary human islet cells with Cas9 ribonucleoprotein.

Successful genome editing in primary human islets could reveal features of the genetic regulatory landscape underlying ß cell function and diabetes risk. Here, we describe a CRISPR-based strategy to interrogate functions of predicted regulatory DNA elements using electroporation of a complex of Cas9 ribonucleoprotein (Cas9 RNP) and guide RNAs into primary human islet cells. We successfully targeted coding regions including the PDX1 exon 1, and non-coding DNA linked to diabetes susceptibility. CRISPR/Cas9 RNP approaches revealed genetic targets of regulation by DNA elements containing candidate diabetes risk SNPs, including an in vivo enhancer of the MPHOSPH9 gene. CRISPR/Cas9 RNP multiplexed targeting of two cis-regulatory elements linked to diabetes risk in PCSK1, which encodes an endoprotease crucial for insulin processing, also demonstrated efficient simultaneous editing of PCSK1 regulatory elements, resulting in impaired ß cell PCSK1 regulation and insulin secretion. Multiplex CRISPR/Cas9 RNP provides powerful approaches to investigate and elucidate human islet cell gene regulation in health and diabetes.

Management of Neonatal Diabetes due to a KCNJ11 Mutation with Automated Insulin Delivery System and Remote Patient Monitoring.

Neonatal diabetes mellitus (NDM) is a monogenic form of diabetes. Management of hyperglycemia in neonates with subcutaneous insulin is challenging because of frequent feeding, variable quantity of milk intake with each feed, low insulin dose requirements, and high risk for hypoglycemia and associated complications in this population. We present a case of NDM in a proband initially presenting with focal seizures and diabetic ketoacidosis due to a pathologic mutation in the beta cell potassium ATP channel gene KCNJ11 c.679G > A (p.E227K). We describe the use of continuous glucose monitoring (CGM), insulin pump, automated insulin delivery system, and remote patient monitoring technologies to facilitate rapid and safe outpatient cross-titration from insulin to oral sulfonylurea. Our case highlights the safety and efficacy of these technologies for infants with diabetes, including improvements in glycemia, quality of life, and cost-effectiveness by shortening hospital stay.

An Atlas of Variant Effects to understand the genome at nucleotide resolution.

Sequencing has revealed hundreds of millions of human genetic variants, and continued efforts will only add to this variant avalanche. Insufficient information exists to interpret the effects of most variants, limiting opportunities for precision medicine and comprehension of genome function. A solution lies in experimental assessment of the functional effect of variants, which can reveal their biological and clinical impact. However, variant effect assays have generally been undertaken reactively for individual variants only after and, in most cases long after, their first observation. Now, multiplexed assays of variant effect can characterise massive numbers of variants simultaneously, yielding variant effect maps that reveal the function of every possible single nucleotide change in a gene or regulatory element. Generating maps for every protein encoding gene and regulatory element in the human genome would create an 'Atlas' of variant effect maps and transform our understanding of genetics and usher in a new era of nucleotide-resolution functional knowledge of the genome. An Atlas would reveal the fundamental biology of the human genome, inform human evolution, empower the development and use of therapeutics and maximize the utility of genomics for diagnosing and treating disease. The Atlas of Variant Effects Alliance is an international collaborative group comprising hundreds of researchers, technologists and clinicians dedicated to realising an Atlas of Variant Effects to help deliver on the promise of genomics.

A Systematic Review of the use of Precision Diagnostics in Monogenic Diabetes.

Monogenic forms of diabetes present opportunities for precision medicine as identification of the underlying genetic cause has implications for treatment and prognosis. However, genetic testing remains inconsistent across countries and health providers, often resulting in both missed diagnosis and misclassification of diabetes type. One of the barriers to deploying genetic testing is uncertainty over whom to test as the clinical features for monogenic diabetes overlap with those for both type 1 and type 2 diabetes. In this review, we perform a systematic evaluation of the evidence for the clinical and biochemical criteria used to guide selection of individuals with diabetes for genetic testing and review the evidence for the optimal methods for variant detection in genes involved in monogenic diabetes. In parallel we revisit the current clinical guidelines for genetic testing for monogenic diabetes and provide expert opinion on the interpretation and reporting of genetic tests. We provide a series of recommendations for the field informed by our systematic review, synthesizing evidence, and expert opinion. Finally, we identify major challenges for the field and highlight areas for future research and investment to support wider implementation of precision diagnostics for monogenic diabetes.