A genome-wide CRISPR screen identifies CALCOCO2 as a regulator of beta cell function influencing type 2 diabetes risk

EndoC-βH3 pseudoislets are suitable for intraportal transplantation in diabetic mice

BACKGROUND

Islet or β-cell transplantation is a therapeutical approach to substitute the insulin-producing cells which are abolished in type 1 diabetes mellitus. The shortage of human islets as well as the complicated and costly isolation process limit the application of these techniques in daily clinical practice. EndoC-βH is a human β-cell line that readily forms aggregates termed pseudoislets, providing an alternative to primary human islets or β-cells.

METHODS

EndoC-βH3 cells were seeded and incubated to form pseudoislets. Their insulin secretion was analyzed by ELISA and compared with cell monolayers. Pseudoislets were transplanted into streptozotocin-treated NMRi nu/nu mice. Blood glucose was monitored before and after transplantation and compared with wild types. Grafts were analyzed by immunohistology.

RESULTS

This study shows that EndoC-βH cells are able to form pseudoislets by aggregation, leading to an enhanced glucose stimulated insulin secretion in vitro. These pseudoislets were then successfully transplanted into the livers of diabetic mice and produced insulin in vitro. Blood glucose levels of the streptozocin-treated recipient mice were significantly decreased when compared to pre-transplantation and matched the levels found in control mice.

CONCLUSION

We suggest pseudoislets aggregated from EndoC-βH cells as a valuable and promising model for islet transplantation research.

Autophagy and lysosomal dysfunction in diabetes and its complications

Autophagy is critical for energy homeostasis and the function of organelles such as endoplasmic reticulum (ER) and mitochondria. Dysregulated autophagy due to aging, environmental factors, or genetic predisposition can be an underlying cause of not only diabetes through β-cell dysfunction and metabolic inflammation, but also diabetic complications such as diabetic kidney diseases (DKDs). Dysfunction of lysosomes, effector organelles of autophagic degradation, due to metabolic stress or nutrients/metabolites accumulating in metabolic diseases is also emerging as a cause or aggravating element in diabetes and its complications. Here, we discuss the etiological role of dysregulated autophagy and lysosomal dysfunction in diabetes and a potential role of autophagy or lysosomal modulation as a new avenue for treatment of diabetes and its complications.

Implicating type 2 diabetes effector genes in relevant metabolic cellular models using promoter-focused Capture-C

AIMS/HYPOTHESIS

Genome-wide association studies (GWAS) have identified hundreds of type 2 diabetes loci, with the vast majority of signals located in non-coding regions; as a consequence, it remains largely unclear which 'effector' genes these variants influence. Determining these effector genes has been hampered by the relatively challenging cellular settings in which they are hypothesised to confer their effects.

METHODS

To implicate such effector genes, we elected to generate and integrate high-resolution promoter-focused Capture-C, assay for transposase-accessible chromatin with sequencing (ATAC-seq) and RNA-seq datasets to characterise chromatin and expression profiles in multiple cell lines relevant to type 2 diabetes for subsequent functional follow-up analyses: EndoC-BH1 (pancreatic beta cell), HepG2 (hepatocyte) and Simpson-Golabi-Behmel syndrome (SGBS; adipocyte).

RESULTS

The subsequent variant-to-gene analysis implicated 810 candidate effector genes at 370 type 2 diabetes risk loci. Using partitioned linkage disequilibrium score regression, we observed enrichment for type 2 diabetes and fasting glucose GWAS loci in promoter-connected putative cis-regulatory elements in EndoC-BH1 cells as well as fasting insulin GWAS loci in SGBS cells. Moreover, as a proof of principle, when we knocked down expression of the SMCO4 gene in EndoC-BH1 cells, we observed a statistically significant increase in insulin secretion.

CONCLUSIONS/INTERPRETATION

These results provide a resource for comparing tissue-specific data in tractable cellular models as opposed to relatively challenging primary cell settings.

DATA AVAILABILITY

Raw and processed next-generation sequencing data for EndoC-BH1, HepG2, SGBS_undiff and SGBS_diff cells are deposited in GEO under the Superseries accession GSE262484. Promoter-focused Capture-C data are deposited under accession GSE262496. Hi-C data are deposited under accession GSE262481. Bulk ATAC-seq data are deposited under accession GSE262479. Bulk RNA-seq data are deposited under accession GSE262480.

scPrediXcan integrates advances in deep learning and single-cell data into a powerful cell-type-specific transcriptome-wide association study framework

Transcriptome-wide association studies (TWAS) help identify disease causing genes, but often fail to pinpoint disease mechanisms at the cellular level because of the limited sample sizes and sparsity of cell-type-specific expression data. Here we propose scPrediXcan which integrates state-of-the-art deep learning approaches that predict epigenetic features from DNA sequences with the canonical TWAS framework. Our prediction approach, ctPred, predicts cell-type-specific expression with high accuracy and captures complex gene regulatory grammar that linear models overlook. Applied to type 2 diabetes and systemic lupus erythematosus, scPrediXcan outperformed the canonical TWAS framework by identifying more candidate causal genes, explaining more genome-wide association studies (GWAS) loci, and providing insights into the cellular specificity of TWAS hits. Overall, our results demonstrate that scPrediXcan represents a significant advance, promising to deepen our understanding of the cellular mechanisms underlying complex diseases.

Multi-omic human pancreatic islet endoplasmic reticulum and cytokine stress response mapping provides type 2 diabetes genetic insights

Endoplasmic reticulum (ER) and inflammatory stress responses contribute to islet dysfunction in type 2 diabetes (T2D). Comprehensive genomic understanding of these human islet stress responses and whether T2D-associated genetic variants modulate them is lacking. Here, comparative transcriptome and epigenome analyses of human islets exposed ex vivo to these stressors revealed 30% of expressed genes and 14% of islet cis-regulatory elements (CREs) as stress responsive, modulated largely in an ER- or cytokine-specific fashion. T2D variants overlapped 86 stress-responsive CREs, including 21 induced by ER stress. We linked the rs6917676-T T2D risk allele to increased islet ER-stress-responsive CRE accessibility and allele-specific β cell nuclear factor binding. MAP3K5, the ER-stress-responsive putative rs6917676 T2D effector gene, promoted stress-induced β cell apoptosis. Supporting its pro-diabetogenic role, MAP3K5 expression correlated inversely with human islet β cell abundance and was elevated in T2D β cells. This study provides genome-wide insights into human islet stress responses and context-specific T2D variant effects.

Pancreatic β-Cells, Diabetes and Autophagy

PURPOSE

Pancreatic β-cells play a critical role in regulating plasma insulin levels and glucose metabolism balance, with their dysfunction being a key factor in the progression of diabetes. This review aims to explore the role of autophagy, a vital cellular self-maintenance process, in preserving pancreatic β-cell functionality and its implications in diabetes pathogenesis.

METHODS

We examine the current literature on the role of autophagy in β-cells, highlighting its function in maintaining cell structure, quantity, and function. The review also discusses the effects of both excessive and insufficient autophagy on β-cell dysfunction and glucose metabolism imbalance. Furthermore, we discuss potential therapeutic agents that modulate the autophagy pathway to influence β-cell function, providing insights into therapeutic strategies for diabetes management.

RESULTS

Autophagy acts as a self-protective mechanism within pancreatic β-cells, clearing damaged organelles and proteins to maintain cellular stability. Abnormal autophagy activity, either overactive or deficient, can disrupt β-cell function and glucose regulation, contributing to diabetes progression.

CONCLUSION

Autophagy plays a pivotal role in maintaining pancreatic β-cell function, and its dysregulation is implicated in the development of diabetes. Targeting the autophagy pathway offers potential therapeutic strategies for diabetes management, with agents that modulate autophagy showing promise in preserving β-cell function.

BIT: Bayesian Identification of Transcriptional Regulators from Epigenomics-Based Query Region Sets

Transcriptional regulators (TRs) are master controllers of gene expression and play a critical role in both normal tissue development and disease progression. However, existing computational methods for identification of TRs regulating specific biological processes have significant limitations, such as relying on distance on a linear chromosome or binding motifs that have low specificity. Many also use statistical tests in ways that lack interpretability and rigorous confidence measures. We introduce BIT, a novel Bayesian hierarchical model for in-silico TR identification. Leveraging a comprehensive library of TR ChIP-seq data, BIT offers a fully integrated Bayesian approach to assess genome-wide consistency between user-provided epigenomic profiling data and the TR binding library, enabling the identification of critical TRs while quantifying uncertainty. It avoids estimation and inference in a sequential manner or numerous isolated statistical tests, thereby enhancing accuracy and interpretability. BIT successfully identified critical TRs in perturbation experiments, functionally essential TRs in various cancer types, and cell-type-specific TRs within heterogeneous cell populations, offering deeper biological insights into transcriptional regulation.

Exploring the design of clinical research studies on the efficacy mechanisms in type 2 diabetes mellitus

This review examines the complexities of Type 2 Diabetes Mellitus (T2DM), focusing on the critical role of integrating omics technologies with traditional experimental methods. It underscores the advancements in understanding the genetic diversity of T2DM and emphasizes the evolution towards personalized treatment modalities. The paper analyzes a variety of omics approaches, including genomics, methylation, transcriptomics, proteomics, metabolomics, and intestinal microbiomics, delineating their substantial contributions to deciphering the multifaceted mechanisms underlying T2DM. Furthermore, the review highlights the indispensable role of non-omics experimental techniques in comprehending and managing T2DM, advocating for their integration in the development of tailored medicine and precision treatment strategies. By identifying existing research gaps and suggesting future research trajectories, the review underscores the necessity for a comprehensive, multidisciplinary approach. This approach synergistically combines clinical insights with cutting-edge biotechnologies, aiming to refine the management and therapeutic interventions of T2DM, and ultimately enhancing patient outcomes. This synthesis of knowledge and methodologies paves the way for innovative advancements in T2DM research, fostering a deeper understanding and more effective treatment of this complex condition.

CRISPR technology in human diseases

Gene editing is a growing gene engineering technique that allows accurate editing of a broad spectrum of gene-regulated diseases to achieve curative treatment and also has the potential to be used as an adjunct to the conventional treatment of diseases. Gene editing technology, mainly based on clustered regularly interspaced palindromic repeats (CRISPR)-CRISPR-associated protein systems, which is capable of generating genetic modifications in somatic cells, provides a promising new strategy for gene therapy for a wide range of human diseases. Currently, gene editing technology shows great application prospects in a variety of human diseases, not only in therapeutic potential but also in the construction of animal models of human diseases. This paper describes the application of gene editing technology in hematological diseases, solid tumors, immune disorders, ophthalmological diseases, and metabolic diseases; focuses on the therapeutic strategies of gene editing technology in sickle cell disease; provides an overview of the role of gene editing technology in the construction of animal models of human diseases; and discusses the limitations of gene editing technology in the treatment of diseases, which is intended to provide an important reference for the applications of gene editing technology in the human disease.

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.

Multi-omics characterization of type 2 diabetes associated genetic variation

Discerning the mechanisms driving type 2 diabetes (T2D) pathophysiology from genome-wide association studies (GWAS) remains a challenge. To this end, we integrated omics information from 16 multi-tissue and multi-ancestry expression, protein, and metabolite quantitative trait loci (QTL) studies and 46 multi-ancestry GWAS for T2D-related traits with the largest, most ancestrally diverse T2D GWAS to date. Of the 1,289 T2D GWAS index variants, 716 (56%) demonstrated strong evidence of colocalization with a molecular or T2D-related trait, implicating 657 cis-effector genes, 1,691 distal-effector genes, 731 metabolites, and 43 T2D-related traits. We identified 773 of these cis- and distal-effector genes using either expression QTL data from understudied ancestry groups or inclusion of T2D index variants enriched in underrepresented populations, emphasizing the value of increasing population diversity in functional mapping. Linking these variants, genes, metabolites, and traits into a network, we elucidated mechanisms through which T2D-associated variation may impact disease risk. Finally, we showed that drugs targeting effector proteins were enriched in those approved to treat T2D, highlighting the potential of these results to prioritize drug targets for T2D. These results represent a leap in the molecular characterization of T2D-associated genetic variation and will aid in translating genetic findings into novel therapeutic strategies.

Gluco-regulation & type 2 diabetes: entrenched misconceptions updated to new governing principles for gold standard management

Our understanding of type 2 diabetes (T2D) has evolved dramatically. Advances have upended entrenched dogmas pertaining to the onset and progression of T2D, beliefs that have prevailed from the early era of diabetes research-and continue to populate our medical textbooks and continuing medical education materials. This review article highlights key insights that lend new governing principles for gold standard management of T2D. From the historical context upon which old beliefs arose to new findings, this article outlines evidence and perspectives on beta cell function, the underlying defects in glucoregulation, the remediable nature of T2D, and, the rationale supporting the shift to complication-centric prescribing. Practical approaches translate this rectified understanding of T2D into strategies that fill gaps in current management practices of prediabetes through late type 2 diabetes.

Identification of type 2 diabetes- and obesity-associated human β-cells using deep transfer learning

Diabetes affects >10% of adults worldwide and is caused by impaired production or response to insulin, resulting in chronic hyperglycemia. Pancreatic islet β-cells are the sole source of endogenous insulin and our understanding of β-cell dysfunction and death in type 2 diabetes (T2D) is incomplete. Single-cell RNA-seq data supports heterogeneity as an important factor in β-cell function and survival. However, it is difficult to identify which β-cell phenotypes are critical for T2D etiology and progression. Our goal was to prioritize specific disease-related β-cell subpopulations to better understand T2D pathogenesis and identify relevant genes for targeted therapeutics. To address this, we applied a deep transfer learning tool, DEGAS, which maps disease associations onto single-cell RNA-seq data from bulk expression data. Independent runs of DEGAS using T2D or obesity status identified distinct β-cell subpopulations. A singular cluster of T2D-associated β-cells was identified; however, β-cells with high obese-DEGAS scores contained two subpopulations derived largely from either non-diabetic or T2D donors. The obesity-associated non-diabetic cells were enriched for translation and unfolded protein response genes compared to T2D cells. We selected DLK1 for validation by immunostaining in human pancreas sections from healthy and T2D donors. DLK1 was heterogeneously expressed among β-cells and appeared depleted from T2D islets. In conclusion, DEGAS has the potential to advance our holistic understanding of the β-cell transcriptomic phenotypes, including features that distinguish β-cells in obese non-diabetic or lean T2D states. Future work will expand this approach to additional human islet omics datasets to reveal the complex multicellular interactions driving T2D.

Application of CRISPR-Cas9 technology in diabetes research

Diabetes is a chronic disorder with rapidly increasing prevalence that is a major global issue of our current era. There are two major types of diabetes. Polygenic forms of diabetes include type 1 diabetes (T1D) and type 2 diabetes (T2D) and its monogenic forms are maturity-onset diabetes of the young (MODY) and neonatal diabetes mellitus (NDM). There are no permanent therapeutic approaches for diabetes and current therapies rely on regular administration of various drugs or insulin injection. Recently, gene editing strategies have offered new promise for treating genetic disorders. Targeted genome editing is a fast-growing technology, recruiting programmable nucleases to specifically modify target genomic sequences. These targeted nucleases generate double-strand breaks at target regions in the genome, which induce cellular repair pathways including non-homologous end joining (NHEJ) and homology-directed repair (HDR). Clustered regularly interspaced palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) is a novel gene-editing system, permitting precise genome modification. CRISPR/Cas9 has great potential for various applications in diabetic research such as gene screening, generation of diabetic animal models and treatment. In this article, gene-editing strategies are summarized with a focus on the CRISPR/Cas9 approach in diabetes research.

Pooled screening with next-generation gene editing tools

Pooled screening creates a pool of cells with genetic variants, allowing for the simultaneous examination for changes in behavior or function. By selectively inducing mutations or perturbing expression, it enables scientists to systematically investigate the function of genes or genetic elements. Emerging gene editing tools, such as CRISPR, coupled with advances in sequencing and computational capabilities, provide growing opportunities to understand biological processes in humans, animals, and plants as well as to identify potential targets for therapeutic interventions and agricultural research. In this review, we highlight the recent advances of pooled screens using next-generation gene editing tools along with relevant challenges and describe potential future directions of this technology.

Evolution of the search for a common mechanism of congenital risk of coronary heart disease and type 2 diabetes mellitus in the chromosomal locus 9p21.3

9.21.3 chromosomal locus predisposes to coronary heart disease (CHD) and type 2 diabetes mellitus (DM2), but their overall pathological mechanism and clinical applicability remain unclear. The review uses publications of the study results of 9.21.3 chromosomal locus in association with CHD and DM2, which are important for changing the focus of clinical practice. The eligibility criteria are full-text articles published in the PubMed database (MEDLINE) up to December 31, 2022. A total of 56 publications were found that met the inclusion criteria. Using the examples of the progressive stages in understanding the role of the chromosomal locus 9p.21.3, scientific ideas were grouped, from a fragmentary study of independent pathological processes to a systematic study of the overall development of CHD and DM2. The presented review can become a source of new scientific hypotheses for further studies, the results of which can determine the general mechanism of the congenital risk of CHD and DM2 and change the focus of clinical practice.

Pancreatic β-cell mitophagy as an adaptive response to metabolic stress and the underlying mechanism that involves lysosomal Ca2+ release

Mitophagy is an excellent example of selective autophagy that eliminates damaged or dysfunctional mitochondria, and it is crucial for the maintenance of mitochondrial integrity and function. The critical roles of autophagy in pancreatic β-cell structure and function have been clearly shown. Furthermore, morphological abnormalities and decreased function of mitochondria have been observed in autophagy-deficient β-cells, suggesting the importance of β-cell mitophagy. However, the role of authentic mitophagy in β-cell function has not been clearly demonstrated, as mice with pancreatic β-cell-specific disruption of Parkin, one of the most important players in mitophagy, did not exhibit apparent abnormalities in β-cell function or glucose homeostasis. Instead, the role of mitophagy in pancreatic β-cells has been investigated using β-cell-specific Tfeb-knockout mice (TfebΔβ-cell mice); Tfeb is a master regulator of lysosomal biogenesis or autophagy gene expression and participates in mitophagy. TfebΔβ-cell mice were unable to adaptively increase mitophagy or mitochondrial complex activity in response to high-fat diet (HFD)-induced metabolic stress. Consequently, TfebΔβ-cell mice exhibited impaired β-cell responses and further exacerbated metabolic deterioration after HFD feeding. TFEB was activated by mitochondrial or metabolic stress-induced lysosomal Ca2+ release, which led to calcineurin activation and mitophagy. After lysosomal Ca2+ release, depleted lysosomal Ca2+ stores were replenished by ER Ca2+ through ER→lysosomal Ca2+ refilling, which supplemented the low lysosomal Ca2+ capacity. The importance of mitophagy in β-cell function was also demonstrated in mice that developed β-cell dysfunction and glucose intolerance after treatment with a calcineurin inhibitor that hampered TFEB activation and mitophagy.

Reversing pancreatic β-cell dedifferentiation in the treatment of type 2 diabetes

The maintenance of glucose homeostasis is fundamental for survival and health. Diabetes develops when glucose homeostasis fails. Type 2 diabetes (T2D) is characterized by insulin resistance and pancreatic β-cell failure. The failure of β-cells to compensate for insulin resistance results in hyperglycemia, which in turn drives altered lipid metabolism and β-cell failure. Thus, insulin secretion by pancreatic β-cells is a primary component of glucose homeostasis. Impaired β-cell function and reduced β-cell mass are found in diabetes. Both features stem from a failure to maintain β-cell identity, which causes β-cells to dedifferentiate into nonfunctional endocrine progenitor-like cells or to trans-differentiate into other endocrine cell types. In this regard, one of the key issues in achieving disease modification is how to reestablish β-cell identity. In this review, we focus on the causes and implications of β-cell failure, as well as its potential reversibility as a T2D treatment.

Functional interrogation of twenty type 2 diabetes-associated genes using isogenic hESC-derived β-like cells

Genetic studies have identified numerous loci associated with type 2 diabetes (T2D), but the functional role of many loci has remained unexplored. In this study, we engineered isogenic knockout human embryonic stem cell (hESC) lines for 20 genes associated with T2D risk. We systematically examined β-cell differentiation, insulin production and secretion, and survival. We performed RNA-seq and ATAC-seq on hESC-β cells from each knockout line. Analyses of T2D GWAS signals overlapping with HNF4A-dependent ATAC peaks identified a specific SNP as a likely causal variant. In addition, we performed integrative association analyses and identified four genes ( CP, RNASE1, PCSK1N and GSTA2 ) associated with insulin production, and two genes ( TAGLN3 and DHRS2 ) associated with sensitivity to lipotoxicity. Finally, we leveraged deep ATAC-seq read coverage to assess allele-specific imbalance at variants heterozygous in the parental hESC line, to identify a single likely functional variant at each of 23 T2D GWAS signals.

β Cell and Autophagy: What Do We Know?

Pancreatic β cells are central to glycemic regulation through insulin production. Studies show autophagy as an essential process in β cell function and fate. Autophagy is a catabolic cellular process that regulates cell homeostasis by recycling surplus or damaged cell components. Impaired autophagy results in β cell loss of function and apoptosis and, as a result, diabetes initiation and progress. It has been shown that in response to endoplasmic reticulum stress, inflammation, and high metabolic demands, autophagy affects β cell function, insulin synthesis, and secretion. This review highlights recent evidence regarding how autophagy can affect β cells' fate in the pathogenesis of diabetes. Furthermore, we discuss the role of important intrinsic and extrinsic autophagy modulators, which can lead to β cell failure.