Class II phosphoinositide 3-kinase regulates exocytosis of insulin granules in pancreatic beta cells

Comprehensive sequencing profile and functional analysis of IsomiRs in human pancreatic islets and beta cells

AIMS/HYPOTHESIS

MiRNAs regulate gene expression, influencing beta cell function and pathways. Isoforms of miRNA (isomiRs), sequence variants of miRNAs with post-transcriptional modifications, exhibit cell-type-specific expression and functions. Despite their biological significance, a comprehensive isomiR profile in human pancreatic islets and beta cells remains unexplored. This study aims to profile isomiR expression in four beta cell sources: (1) laser capture microdissected human islets (LCM-HI); (2) collagenase-isolated human islets (CI-HI); (3) sorted beta cells; and (4) the EndoC-βH1 beta cell line, and to investigate their potential role in beta cell function.

METHODS

Small RNA-seq and/or small RNA dataset analysis was conducted on human pancreatic islets and beta cells. Data were processed using the sRNAbench bioinformatics pipeline to classify isomiRs based on sequence variations. A beta cell-specific isomiR signature was identified via cross-validation across datasets. Correlations between LCM-HI isomiR expression and in vivo clinical parameters were analysed using regression models. Functional validation of isomiR-411-5p-Ext5p(+1) was performed via overexpression in EndoC-βH1 cells and CI-HI, followed by glucose-stimulated insulin secretion (GSIS) assays and/or transcriptomic analysis.

RESULTS

IsomiRs constituted 59.2 ± 1.9% (LCM-HI), 59.6 ± 2.4% (CI-HI), 42.3 ± 7.2% (sorted beta cells) and 43.8 ± 1.2% (EndoC-βH1) of total miRNA reads (data represented as mean ± SD), with 3' end trimming (Trim3p) being the predominant modification. A beta cell-specific isomiR signature of 30 sequences was identified, with isomiR-411-5p-Ext5p(+1) showing a significant inverse correlation with basal insulin secretion (p=0.0009, partial R2=0.68) and total insulin secretion (p=0.005, partial R2=0.54). Overexpression of isomiR-411-5p-Ext5p(+1), but not of its canonical counterpart, importantly reduced GSIS by 51% ( ± 15.2%; mean ± SD) (p=0.01) in EndoC-βH1 cells. Transcriptomic analysis performed in EndoC-βH1 cells and CI-HI identified 47 genes significantly downregulated by isomiR-411-5p-Ext5p(+1) (false discovery rate [FDR]<0.05) but not by the canonical miRNA, with enriched pathways related to Golgi vesicle biogenesis (FDR=0.017) and trans-Golgi vesicle budding (FDR=0.018). TargetScan analysis confirmed seed sequence-dependent target specificity for 81 genes uniquely regulated by the isomiR (p=1.1 × 10⁻⁹).

CONCLUSIONS/INTERPRETATION

This study provides the first comprehensive isomiR profiling in human islets and beta cells, revealing their substantial contribution to miRNA regulation. IsomiR-411-5p-Ext5p(+1) emerges as a distinct key modulator of insulin secretion and granule dynamics in beta cells. These findings highlight isomiRs as potential biomarkers and therapeutic targets for diabetes, warranting further exploration of their roles in beta cell biology.

In-silico discovery of type-2 diabetes-causing host key genes that are associated with the complexity of monkeypox and repurposing common drugs

Monkeypox (Mpox) is a major global human health threat after COVID-19. Its treatment becomes complicated with type-2 diabetes (T2D). It may happen due to the influence of both disease-causing common host key genes (cHKGs). Therefore, it is necessary to explore both disease-causing cHKGs to reveal their shared pathogenetic mechanisms and candidate drugs as their common treatments without adverse side effect. This study aimed to address these issues. At first, 3 transcriptomics datasets for each of Mpox and 6 T2D datasets were analyzed and found 52 common host differentially expressed genes (cHDEGs) that can separate both T2D and Mpox patients from the control samples. Then top-ranked six cHDEGs (HSP90AA1, B2M, IGF1R, ALD1HA1, ASS1, and HADHA) were detected as the T2D-causing cHKGs that are associated with the complexity of Mpox through the protein-protein interaction network analysis. Then common pathogenetic processes between T2D and Mpox were disclosed by cHKG-set enrichment analysis with biological processes, molecular functions, cellular components and Kyoto Encyclopedia of Genes and Genomes pathways, and regulatory network analysis with transcription factors and microRNAs. Finally, cHKG-guided top-ranked three drug molecules (tecovirimat, vindoline, and brincidofovir) were recommended as the repurposable common therapeutic agents for both Mpox and T2D by molecular docking. The absorption, distribution, metabolism, excretion, and toxicity and drug-likeness analysis of these drug molecules indicated their good pharmacokinetics properties. The 100-ns molecular dynamics simulation results (root mean square deviation, root mean square fluctuation, and molecular mechanics generalized born surface area) with the top-ranked three complexes ASS1-tecovirimat, ALDH1A1-vindoline, and B2M-brincidofovir exhibited good pharmacodynamics properties. Therefore, the results provided in this article might be important resources for diagnosis and therapies of Mpox patients who are also suffering from T2D.

Bioinformatics Combined With Biological Experiments to Identify the Pathogenetic Link of Type 2 Diabetes for Breast Cancer

BACKGROUND

Type 2 diabetes mellitus (T2DM) constitutes a significant risk factor for breast cancer (BC), with affected women exhibiting a two- to three-fold increased likelihood of developing BC. Furthermore, women diagnosed with both BC and T2DM tend to experience poorer prognoses and exhibit greater resistance to various treatments compared to their non-diabetic counterparts. Consequently, elucidating the comorbidities associated with T2DM and BC is instrumental in enhancing the diagnostic and therapeutic strategies for BC.

METHODS

A series of bioinformatics methods including weighted gene co-expression network analysis (WGCNA), differentially expressed gene (DEG) analysis, machine learning, and single-cell sequencing analysis were used to identify the pathogenetic molecules of T2DM for BC. Biological experiments including CCK-8, colony formation, wound healing, transwell assay, immunohistochemistry, and immunofluorescence were performed to determine the molecule effect.

RESULTS

By conducting WGCNA and DEG analysis on the profiles of T2DM (GSE25724 and GSE20966) and the TCGA cohort of BC, we identified a total of 27 common hub genes shared between T2DM and BC. These genes were significantly enriched in pathways related to cell differentiation, cellular developmental processes, focal adhesion, and the MAPK signaling pathway. Notably, among these 27 genes, CCNB2, XRCC2, and CENPI were associated with poor prognosis in BC. Moreover, single-cell RNA sequencing analysis revealed that CCNB2, XRCC2, and CENPI are enriched in cancer cells within BC tissues. Additionally, we observed that CCNB2, XRCC2, and CENPI were elevated in BC tissues provided by patients with a diabetes history and associated with KI67 expression. Hyperglycemia treatment elevated the expression levels of CCNB2, XRCC2, and CENPI in BC cells, which correlated with increased cell proliferation and mobility. Conversely, the knockdown of these genes partially mitigated the pro-proliferative and pro-migratory effects induced by hyperglycemia in BC cells.

CONCLUSION

Our findings suggested that CCNB2, XRCC2, and CENPI may serve as key pathogenic mediators linking T2DM and BC. Targeting these molecules could potentially attenuate the adverse impacts of T2DM on BC progression.

Effect of SPTLC1 on type 2 diabetes mellitus

BACKGROUND

Although numerous single nucleotide polymorphism in multiple genes involve in the risk of type 2 diabetes mellitus (T2D), the single gene defects of T2D with strong family history is not clear yet. SPTLC1 are causative for hereditary sensory and autonomic neuropathy, which is clinical overlapping with diabetic peripheral neuropathy. Mice with adipocyte-specific deletion of SPTLC1 had impaired glucose tolerances and insulin sensitivity. Thus, it is necessary to investigate the SPTLC1 mutations in adult-onset T2D with strong family history.

AIM

To analyze the role of SPTLC1 mutation on adult-onset T2D with strong family history.

METHODS

By whole-exome sequence analysis of a patient with T2D and his family members, an uncertain variant in SPTLC1 was identified. Bioinformation analysis was used to evaluate the influence of mutation, rare variant gene-level associations for SPTLC1 in T2D, and the relationship between SPTLC1 mRNA and T2D in human islets from GSE25724. The effect of G371R of SPTLC1 on the characteristics of inflammatory cytokines and apoptosis was also tested on human embryonic kidney (HEK) 293 cells.

RESULTS

A single nucleotide variation in SPTLC1 (c.1111G>A: p.G371R) was identified in a family with T2D. The deleterious variant was predicted by functional analysis through hidden Markov models and mendelian clinically applicable pathogenicity software. This pathogenicity might be derived from the different amino acid properties. In HEK 293T cells, p.G371R of SPTLC1 induced the expression of tumor necrosis factor-α and the percent of apoptosis. Meanwhile, rare variant gene-level associations for SPTLC1 also refer to the high risk of T2D (the overall odds ratio = 2.4968, P = 0.0164). Data from GSE25724 showed that SPTLC1 mRNA was lower in pancreatic islets from T2D human islets (P = 0.046), and was associated with the decreased level of insulin mRNA expression (Spearman r = 0.615, P = 0.025).

CONCLUSION

The study classified SPTLC1 p.G371R mutation as the likely pathogenic mutation from an adult-onset T2D patients with strong family history T2D.

Serum and urinary levels of MIF, CD74, DDT and CXCR4 among patients with type 1 diabetes mellitus, type 2 diabetes and healthy individuals: Implications for further research

Background

Macrophage migration inhibitory factor (MIF) is a highly conserved cytokine with pleiotropic properties, mainly pro-inflammatory. MIF seems to exert its pro-inflammatory features by binding to its transmembrane cellular receptor CD74. MIF also has CXCR4, which acts as a co-receptor in this inflammatory process. Apart from MIF, D-dopachrome tautomerase (DDT) or MIF2, which belongs to the MIF superfamily, also binds to receptor CD74. Therefore, these molecules, MIF, CD74, DDT and CXCR4 are suggested to work together orchestrating an inflammatory process. Diabetes mellitus is characterised by chronic low-grade inflammation. Therefore, the aim of the present study was to evaluate serum and urinary levels of the aforementioned molecules among patients with type 1 diabetes mellitus (T1DM), type 2 diabetes mellitus (T2DM) and among healthy controls.

Methods

We enrolled 13 patients with T1DM, 74 patients with T2DM and 25 healthy individuals as controls. Levels of CD74, CXCR4, DDT, and MIF were measured using ELISA Kits according to the manufacturer's instructions.

Results

We documented increased serum MIF levels together with higher urinary CD74 levels among patients with T1DM, when compared to patients with T2DM and healthy adults. In particular, patients with T1DM showed significantly increased levels of MIF compared to T2DM (p = 0.011) and healthy controls (p = 0.0093). CD74 in urine were significantly higher in patients with T1DM compared to those affected with T2DM (p = 0.0302) and healthy group (p = 0.0099). On the contrary, serum CD74 were similar among the three groups. No statistical differences were identified in CXCR4 levels both in serum and in urine of all groups. Patients with T2DM and overweight/obesity had increased urinary levels of CD74, when compared to lean patients with T2DM.

Conclusion

The increased serum MIF levels and urinary CD74 levels among patients with T1DM may be attributed to the autoimmune milieu, which characterises patients with T1DM, when compared to patients with T2DM. These two findings merit further attention as they could pave the way for further research regarding the potential beneficial effects of inhibitors of MIF among patients with T1DM, especially in the early stages of T1DM. Finally, the role of inhibitors of MIF could be further explored in the context of obesity among patients with T2DM.

Exploring the pathogenesis, biomarkers, and potential drugs for type 2 diabetes mellitus and acute pancreatitis through a comprehensive bioinformatic analysis

Background

Type 2 diabetes mellitus (T2DM) is a chronic metabolic disease that accounts for > 90% of all diabetes cases. Acute pancreatitis (AP) can be triggered by various factors and is a potentially life-threatening condition. Although T2DM has been shown to have a close relationship with AP, the common mechanisms underlying the two conditions remain unclear.

Methods

We identified common differentially expressed genes (DEGs) in T2DM and AP and used functional enrichment analysis and Mendelian randomization to understand the underlying mechanisms. Subsequently, we used several machine learning algorithms to identify candidate biomarkers and construct a diagnostic nomogram for T2DM and AP. The diagnostic performance of the model was evaluated using ROC, calibration, and DCA curves. Furthermore, we investigated the potential roles of core genes in T2DM and AP using GSEA, xCell, and single-cell atlas and by constructing a ceRNA network. Finally, we identified potential small-molecule compounds with therapeutic effects on T2DM and AP using the CMap database and molecular docking.

Results

A total of 26 DEGs, with 14 upregulated and 12 downregulated genes, were common between T2DM and AP. According to functional and DisGeNET enrichment analysis, these DEGs were mainly enriched in immune effector processes, blood vessel development, dyslipidemia, and hyperlipidemia. Mendelian randomization analyses further suggested that lipids may be a potential link between AP and T2DM. Machine learning algorithms revealed ARHGEF9 and SLPI as common genes associated with the two diseases. ROC, calibration, and DCA curves showed that the two-gene model had good diagnostic efficacy. Additionally, the two genes were found to be closely associated with immune cell infiltration. Finally, imatinib was identified as a potential compound for the treatment of T2DM and AP.

Conclusion

This study suggests that abnormal lipid metabolism is a potential crosstalk mechanism between T2DM and AP. In addition, we established a two-gene model for the clinical diagnosis of T2DM and AP and identified imatinib as a potential therapeutic agent for both diseases.

Unveiling the link between arsenic toxicity and diabetes: an in silico exploration into the role of transcription factors

Arsenic-induced diabetes, despite being a relatively newer finding, is now a growing area of interest, owing to its multifaceted nature of development and the diversity of metabolic conditions that result from it, on top of the already complicated manifestation of arsenic toxicity. Identification and characterization of the common and differentially affected cellular metabolic pathways and their regulatory components among various arsenic and diabetes-associated complications may aid in understanding the core molecular mechanism of arsenic-induced diabetes. This study, therefore, explores the effects of arsenic on human cell lines through 14 transcriptomic datasets containing 160 individual samples using in silico tools to take a systematic, deeper look into the pathways and genes that are being altered. Among these, we especially focused on the role of transcription factors due to their diverse and multifaceted roles in biological processes, aiming to comprehensively investigate the underlying mechanism of arsenic-induced diabetes as well as associated health risks. We present a potential mechanism heavily implying the involvement of the TGF-β/SMAD3 signaling pathway leading to cell cycle alterations and the NF-κB/TNF-α, MAPK, and Ca2+ signaling pathways underlying the pathogenesis of arsenic-induced diabetes. This study also presents novel findings by suggesting potential associations of four transcription factors (NCOA3, PHF20, TFDP1, and TFDP2) with both arsenic toxicity and diabetes; five transcription factors (E2F5, ETS2, EGR1, JDP2, and TFE3) with arsenic toxicity; and one transcription factor (GATA2) with diabetes. The novel association of the transcription factors and proposed mechanism in this study may serve as a take-off point for more experimental evidence needed to understand the in vivo cellular-level diabetogenic effects of arsenic.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43188-024-00255-y.

The PI3K/Akt signaling axis and type 2 diabetes mellitus (T2DM): From mechanistic insights into possible therapeutic targets

Type 2 diabetes mellitus (T2DM) is an immensely debilitating chronic disease that progressively undermines the well-being of various bodily organs and, indeed, most patients succumb to the disease due to post-T2DM complications. Although there is evidence supporting the activation of the phosphoinositide 3-kinase (PI3K)/Akt signaling pathway by insulin, which is essential in regulating glucose metabolism and insulin resistance, the significance of this pathway in T2DM has only been explored in a few studies. The current review aims to unravel the mechanisms by which different classes of PI3Ks control the metabolism of glucose; and also to discuss the original data obtained from international research laboratories on this topic. We also summarized the role of the PI3K/Akt signaling axis in target tissues spanning from the skeletal muscle to the adipose tissue and liver. Furthermore, inquiries regarding the impact of disrupting this axis on insulin function and the development of insulin resistance have been addressed. We also provide a general overview of the association of impaired PI3K/Akt signaling pathways in the pathogenesis of the most prevalent diabetes-related complications. The last section provides a special focus on the therapeutic potential of this axis by outlining the latest advances in active compounds that alleviate diabetes via modulation of the PI3K/Akt pathway. Finally, we comment on the future research aspects in which the field of T2DM therapies using PI3K modulators might be developed.

Acidic Nanoparticles Restore Lysosomal Acidification and Rescue Metabolic Dysfunction in Pancreatic β-Cells under Lipotoxic Conditions

Type 2 diabetes (T2D), a prevalent metabolic disorder lacking effective treatments, is associated with lysosomal acidification dysfunction, as well as autophagic and mitochondrial impairments. Here, we report a series of biodegradable poly(butylene tetrafluorosuccinate-co-succinate) polyesters, comprising a 1,4-butanediol linker and varying ratios of tetrafluorosuccinic acid (TFSA) and succinic acid as components, to engineer lysosome-acidifying nanoparticles (NPs). The synthesized NPs are spherical with diameters of ≈100 nm and have low polydispersity and good stability. Notably, TFSA NPs, which are composed entirely of TFSA, exhibit the strongest degradation capability and superior acidifying properties. We further reveal significant downregulation of lysosomal vacuolar (H+)-ATPase subunits, which are responsible for maintaining lysosomal acidification, in human T2D pancreatic islets, INS-1 β-cells under chronic lipotoxic conditions, and pancreatic tissues of high-fat-diet (HFD) mice. Treatment with TFSA NPs restores lysosomal acidification, autophagic function, and mitochondrial activity, thereby improving the pancreatic function in INS-1 cells and HFD mice with lipid overload. Importantly, the administration of TFSA NPs to HFD mice reduces insulin resistance and improves glucose clearance. These findings highlight the therapeutic potential of lysosome-acidifying TFSA NPs for T2D.

The role of m6A modification in type 2 diabetes: A systematic review and integrative analysis

This study focuses on the latest developments in the studies of m6A modification and provides an up-to-date summary of the association between m6A modification and type 2 diabetes (T2D). The possible mechanisms of m6A related to T2D were summarized by literature review. The differentially expressed genes (DEGs) of m6A methylase in T2D were analyzed from 12 datasets in Gene Expression Omnibus (GEO). The associations between m6A level and T2D were explored in four electronic databases, including PubMed, EmBase, Web of Science and CNKI. Standard mean difference (SMD) and 95 % confidence interval (95 %CI) was calculated to assess the total effect in integrative analysis. Differential expression genes detected in at least three of six tissues were ZC3H13, YTHDC1/2, and IGF2BP2. LRPPRC were differentially expressed in five tissues except in arterial tissue. A total of 6 studies were included for integrative analysis. The mean m6A levels were significantly lower in T2D than those in normal controls (SMD = -1.35, 95 %CI: -2.58 to -0.11). This systematic review and integrative analysis summarize the previous studies on the association between m6A modification and T2D and the possible role of m6A modification in the progression of T2D, such as abnormal blood glucose, abnormal pancreatic β-cell function, insulin resistance, and abnormal lipid metabolism. The integrative analysis showed that decreased level of m6A was associated with T2D. These findings provide new targets for early detection and treatment for T2D.

Gene expression analysis reveals diabetes-related gene signatures

BACKGROUND

Diabetes is a spectrum of metabolic diseases affecting millions of people worldwide. The loss of pancreatic β-cell mass by either autoimmune destruction or apoptosis, in type 1-diabetes (T1D) and type 2-diabetes (T2D), respectively, represents a pathophysiological process leading to insulin deficiency. Therefore, therapeutic strategies focusing on restoring β-cell mass and β-cell insulin secretory capacity may impact disease management. This study took advantage of powerful integrative bioinformatic tools to scrutinize publicly available diabetes-associated gene expression data to unveil novel potential molecular targets associated with β-cell dysfunction.

METHODS

A comprehensive literature search for human studies on gene expression alterations in the pancreas associated with T1D and T2D was performed. A total of 6 studies were selected for data extraction and for bioinformatic analysis. Pathway enrichment analyses of differentially expressed genes (DEGs) were conducted, together with protein-protein interaction networks and the identification of potential transcription factors (TFs). For noncoding differentially expressed RNAs, microRNAs (miRNAs) and long noncoding RNAs (lncRNAs), which exert regulatory activities associated with diabetes, identifying target genes and pathways regulated by these RNAs is fundamental for establishing a robust regulatory network.

RESULTS

Comparisons of DEGs among the 6 studies showed 59 genes in common among 4 or more studies. Besides alterations in mRNA, it was possible to identify differentially expressed miRNA and lncRNA. Among the top transcription factors (TFs), HIPK2, KLF5, STAT1 and STAT3 emerged as potential regulators of the altered gene expression. Integrated analysis of protein-coding genes, miRNAs, and lncRNAs pointed out several pathways involved in metabolism, cell signaling, the immune system, cell adhesion, and interactions. Interestingly, the GABAergic synapse pathway emerged as the only common pathway to all datasets.

CONCLUSIONS

This study demonstrated the power of bioinformatics tools in scrutinizing publicly available gene expression data, thereby revealing potential therapeutic targets like the GABAergic synapse pathway, which holds promise in modulating α-cells transdifferentiation into β-cells.

In silico based analysis to explore genetic linkage between atherosclerosis and its potential risk factors

Atherosclerosis (ATH) is a chronic cardiovascular disease characterized by plaque formation in arteries, and it is a major cause of illness and death. Although therapeutic advances have significantly improved the prognosis of ATH, missing therapeutic targets pose a significant residual threat. This research used a systems biology approach to identify the molecular biomarkers involved in the onset and progression of ATH, analysing microarray gene expression datasets from ATH and tissues impacted by risk factors such as high cholesterol, adipose tissue, smoking, obesity, sedentary lifestyle, stress, alcohol consumption, hypertension, hyperlipidaemia, high fat, diabetes to find the differentially expressed genes (DEGs). Bioinformatic analyses of Protein-Protein Interaction (PPI), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) were conducted on differentially expressed genes, revealing metabolic and signaling pathways (the chemokine signaling pathway, cytokine-cytokine receptor interaction, the cytosolic DNA-sensing pathway, the peroxisome proliferator-activated receptors signaling pathway, and the nuclear factor-kappa B signaling pathway), ten hubs proteins (CCL5, CCR1, TLR1, CCR2, FCGR2A, IL1B, CD163, AIF1, CXCL-1 and TNF), five transcription factors (YY1, FOXL1, FOXC1, SRF, and GATA2), and five miRNAs (mir-27a-3p, mir-124-3p, mir-16-5p, mir-129-2-3p, mir-1-3p). These findings identify potential biomarkers that may increase knowledge of the mechanisms underlying ATH and their connection to risk factors, aiding in the development of new therapies.

Integrative bioinformatics analysis of biomarkers and pathways for exploring the mechanisms and molecular targets associated with pyroptosis in type 2 diabetes mellitus

Introduction

Research has shown that pyroptosis contributes greatly to the progression of diabetes and its complications. However, the exact relationship between this particular cell death process and the pathology of type 2 diabetes mellitus (T2DM) remains unclear. In this study, we used bioinformatic tools to identify the pyroptosis-related genes (PRGs) associated with T2DM and to analyze their roles in the disease pathology.

Methods

Two microarray datasets, GSE7014 and GSE25724, were obtained from the GEO database and assessed for differentially expressed genes (DEGs). The T2DM-associated DEGs that overlapped with differentially expressed PRGs were noted as T2DM-PRGs. Subsequently, 25 T2DM-PRGs were validated and subjected to functional enrichment analysis through Gene Ontology annotation analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, and gene set enrichment analysis (GSEA). The diagnostic and predictive value of the T2DM-PRGs was evaluated using receiver operating characteristic curves (ROC). Additionally, a single-sample GSEA algorithm was applied to study immune infiltration in T2DM and assess immune infiltration levels.

Results

We identified 25 T2DM-PRGs that were significantly enriched in the nuclear factor-kappa B signaling and prostate cancer pathways. The top five differentially expressed prognostic T2DM-PRGs targeted by miRNAs were PTEN, BRD4, HSP90AB1, VIM, and PKN2. The top five differentially expressed T2DM-PRGs associated with transcription factors were HSP90AB1, VIM, PLCG1, SCAF11, and PTEN. The genes PLCG1, PTEN, TP63, CHI3L1, SDHB, DPP8, BCL2, SERPINB1, ACE2, DRD2, DDX58, and BTK showed excellent diagnostic performance. The immune infiltration analysis revealed notable differences in immune cells between T2DM and normal tissues in both datasets. These findings suggest that T2DM-PRGs play a crucial role in the development and progression of T2DM and could be used as potential diagnostic biomarkers and therapeutic targets.

Discussion

Investigating the mechanisms and biomarkers associated with pyroptosis may offer valuable insights into the pathophysiology of T2DM and lead to novel therapeutic approaches to treat the disease.

Endoplasmic reticulum stress in pancreatic β cells induces incretin desensitization and β-cell dysfunction via ATF4-mediated PDE4D expression

Pancreatic β-cell dysfunction and eventual loss are key steps in the progression of type 2 diabetes (T2D). Endoplasmic reticulum (ER) stress responses, especially those mediated by the protein kinase RNA-like ER kinase and activating transcription factor 4 (PERK-ATF4) pathway, have been implicated in promoting these β-cell pathologies. However, the exact molecular events surrounding the role of the PERK-ATF4 pathway in β-cell dysfunction remain unknown. Here, we report our discovery that ATF4 promotes the expression of PDE4D, which disrupts β-cell function via a downregulation of cAMP signaling. We found that β-cell-specific transgenic expression of ATF4 led to early β-cell dysfunction and loss, a phenotype that resembles accelerated T2D. Expression of ATF4, rather than C/EBP homologous protein (CHOP), promoted PDE4D expression, reduced cAMP signaling, and attenuated responses to incretins and elevated glucose. Furthermore, we found that β-cells of leptin receptor-deficient diabetic (db/db) mice had elevated nuclear localization of ATF4 and PDE4D expression, accompanied by impaired β-cell function. Accordingly, pharmacological inhibition of the ATF4 pathway attenuated PDE4D expression in the islets and promoted incretin-simulated glucose tolerance and insulin secretion in db/db mice. Finally, we found that inhibiting PDE4 activity with selective pharmacological inhibitors improved β-cell function in both db/db mice and β-cell-specific ATF4 transgenic mice. In summary, our results indicate that ER stress causes β-cell failure via ATF4-mediated PDE4D production, suggesting the ATF4-PDE4D pathway could be a therapeutic target for protecting β-cell function during the progression of T2D.NEW & NOTEWORTHY Endoplasmic reticulum stress has been implied to cause multiple β-cell pathologies during the progression of type 2 diabetes (T2D). However, the precise molecular events underlying this remain unknown. Here, we discovered that elevated ATF4 activity, which was seen in T2D β cells, attenuated β-cell proliferation and impaired insulin secretion via PDE4D-mediated downregulation of cAMP signaling. Additionally, we demonstrated that pharmacological inhibition of the ATF4 pathway or PDE4D activity alleviated β-cell dysfunction, suggesting its therapeutic usefulness against T2D.

Multiparity increases the risk of diabetes by impairing the proliferative capacity of pancreatic β cells

Pregnancy imposes a substantial metabolic burden on women, but little is known about whether or how multiple pregnancies increase the risk of maternal postpartum diabetes. In this study, we assessed the metabolic impact of multiple pregnancies in humans and in a rodent model. Mice that underwent multiple pregnancies had increased adiposity, but their glucose tolerance was initially improved compared to those of age-matched virgin mice. Later, however, insulin resistance developed over time, but insulin secretory function and compensatory pancreatic β cell proliferation were impaired in multiparous mice. The β cells of multiparous mice exhibited aging features, including telomere shortening and increased expression of Cdkn2a. Single-cell RNA-seq analysis revealed that the β cells of multiparous mice exhibited upregulation of stress-related pathways and downregulation of cellular respiration- and oxidative phosphorylation-related pathways. In humans, women who delivered more than three times were more obese, and their plasma glucose concentrations were elevated compared to women who had delivered three or fewer times, as assessed at 2 months postpartum. The disposition index, which is a measure of the insulin secretory function of β cells, decreased when women with higher parity gained body weight after delivery. Taken together, our findings indicate that multiple pregnancies induce cellular stress and aging features in β cells, which impair their proliferative capacity to compensate for insulin resistance.

Beta cell dysfunction induced by bone morphogenetic protein (BMP)-2 is associated with histone modifications and decreased NeuroD1 chromatin binding

Insufficient insulin secretion is a hallmark of type 2 diabetes and has been attributed to beta cell identity loss characterized by decreased expression of several key beta cell genes. The pro-inflammatory factor BMP-2 is upregulated in islets of Langerhans from individuals with diabetes and acts as an inhibitor of beta cell function and proliferation. Exposure to BMP-2 induces expression of Id1-4, Hes-1, and Hey-1 which are transcriptional regulators associated with loss of differentiation. The aim of this study was to investigate the mechanism by which BMP-2 induces beta cell dysfunction and loss of cell maturity. Mouse islets exposed to BMP-2 for 10 days showed impaired glucose-stimulated insulin secretion and beta cell proliferation. BMP-2-induced beta cell dysfunction was associated with decreased expression of cell maturity and proliferation markers specific to the beta cell such as Ins1, Ucn3, and Ki67 and increased expression of Id1-4, Hes-1, and Hey-1. The top 30 most regulated proteins significantly correlated with corresponding mRNA expression. BMP-2-induced gene expression changes were associated with a predominant reduction in acetylation of H3K27 and a decrease in NeuroD1 chromatin binding activity. These results show that BMP-2 induces loss of beta cell maturity and suggest that remodeling of H3K27ac and decreased NeuroD1 DNA binding activity participate in the effect of BMP-2 on beta cell dysfunction.

Phosphoinositide 3-kinase (PI3K) classes: From cell signaling to endocytic recycling and autophagy

Lipid signaling is defined as any biological signaling action in which a lipid messenger binds to a protein target, converting its effects to specific cellular responses. In this complex biological pathway, the family of phosphoinositide 3-kinase (PI3K) represents a pivotal role and affects many aspects of cellular biology from cell survival, proliferation, and migration to endocytosis, intracellular trafficking, metabolism, and autophagy. While yeasts have a single isoform of phosphoinositide 3-kinase (PI3K), mammals possess eight PI3K types divided into three classes. The class I PI3Ks have set the stage to widen research interest in the field of cancer biology. The aberrant activation of class I PI3Ks has been identified in 30-50% of human tumors, and activating mutations in PIK3CA is one of the most frequent oncogenes in human cancer. In addition to indirect participation in cell signaling, class II and III PI3Ks primarily regulate vesicle trafficking. Class III PI3Ks are also responsible for autophagosome formation and autophagy flux. The current review aims to discuss the original data obtained from international research laboratories on the latest discoveries regarding PI3Ks-mediated cell biological processes. Also, we unravel the mechanisms by which pools of the same phosphoinositides (PIs) derived from different PI3K types act differently.

Type 2 Diabetes Mellitus and its comorbidity, Alzheimer's disease: Identifying critical microRNA using machine learning

MicroRNAs (miRNAs) are critical regulators of gene expression in healthy and diseased states, and numerous studies have established their tremendous potential as a tool for improving the diagnosis of Type 2 Diabetes Mellitus (T2D) and its comorbidities. In this regard, we computationally identify novel top-ranked hub miRNAs that might be involved in T2D. We accomplish this via two strategies: 1) by ranking miRNAs based on the number of T2D differentially expressed genes (DEGs) they target, and 2) using only the common DEGs between T2D and its comorbidity, Alzheimer's disease (AD) to predict and rank miRNA. Then classifier models are built using the DEGs targeted by each miRNA as features. Here, we show the T2D DEGs targeted by hsa-mir-1-3p, hsa-mir-16-5p, hsa-mir-124-3p, hsa-mir-34a-5p, hsa-let-7b-5p, hsa-mir-155-5p, hsa-mir-107, hsa-mir-27a-3p, hsa-mir-129-2-3p, and hsa-mir-146a-5p are capable of distinguishing T2D samples from the controls, which serves as a measure of confidence in the miRNAs' potential role in T2D progression. Moreover, for the second strategy, we show other critical miRNAs can be made apparent through the disease's comorbidities, and in this case, overall, the hsa-mir-103a-3p models work well for all the datasets, especially in T2D, while the hsa-mir-124-3p models achieved the best scores for the AD datasets. To the best of our knowledge, this is the first study that used predicted miRNAs to determine the features that can separate the diseased samples (T2D or AD) from the normal ones, instead of using conventional non-biology-based feature selection methods.

Computational workflow and interactive analysis of single-cell expression profiling of islets generated by the Human Pancreas Analysis Program

Type 1 and Type 2 diabetes are distinct genetic diseases of the pancreas which are defined by the abnormal level of blood glucose. Understanding the initial molecular perturbations that occur during the pathogenesis of diabetes is of critical importance in understanding these disorders. The inability to biopsy the human pancreas of living donors hampers insights into early detection, as the majority of diabetes studies have been performed on peripheral leukocytes from the blood, which is not the site of pathogenesis. Therefore, efforts have been made by various teams including the Human Pancreas Analysis Program (HPAP) to collect pancreatic tissues from deceased organ donors with different clinical phenotypes. HPAP is designed to define the molecular pathogenesis of islet dysfunction by generating detailed datasets of functional, cellular, and molecular information in pancreatic tissues of clinically well-defined organ donors with Type 1 and Type 2 diabetes. Moreover, data generated by HPAP continously become available through a centralized database, PANC-DB, thus enabling the diabetes research community to access these multi-dimensional data prepublication. Here, we present the computational workflow for single-cell RNA-seq data analysis of 258,379 high-quality cells from the pancreatic islets of 67 human donors generated by HPAP, the largest existing scRNA-seq dataset of human pancreatic tissues. We report various computational steps including preprocessing, doublet removal, clustering and cell type annotation across single-cell RNA-seq data from islets of four distintct classes of organ donors, i.e. non-diabetic control, autoantibody positive but normoglycemic, Type 1 diabetic, and Type 2 diabetic individuals. Moreover, we present an interactive tool, called CellxGene developed by the Chan Zuckerberg initiative, to navigate these high-dimensional datasets. Our data and interactive tools provide a reliable reference for singlecell pancreatic islet biology studies, especially diabetes-related conditions.

Identification of shared genetic architecture between non-alcoholic fatty liver disease and type 2 diabetes: A genome-wide analysis

BACKGROUND

The incidence of complications of non-alcoholic fatty liver disease (NAFLD) and type 2 diabetes (T2D) has been increasing.

METHOD

In order to identify the shared genetic architecture of the two disease phenotypes of NAFLD and T2D, a European population-based GWAS summary and a cross-trait meta-analysis was used to identify significant shared genes for NAFLD and T2D. The enrichment of shared genes was then determined through the use of functional enrichment analysis to investigate the relationship between genes and phenotypes. Additionally, differential gene expression analysis was performed, significant differentially expressed genes in NAFLD and T2D were identified, genes that overlapped between those that were differentially expressed and cross-trait results were reported, and enrichment analysis was performed on the core genes that had been obtained in this way. Finally, the application of a bidirectional Mendelian randomization (MR) approach determined the causal link between NAFLD and T2D.

RESULT

A total of 115 genes were discovered to be shared between NAFLD and T2D in the GWAS analysis. The enrichment analysis of these genes showed that some were involved in the processes such as the decomposition and metabolism of lipids, phospholipids, and glycerophospholipids. Additionally, through the use of differential gene expression analysis, 15 core genes were confirmed to be linked to both T2D and NAFLD. They were correlated with carcinoma cells and inflammation. Furthermore, the bidirectional MR identified a positive causal relationship between NAFLD and T2D.

CONCLUSION

Our study determined the genetic structure shared between NAFLD and T2D, offering a new reference for the genetic pathogenesis and mechanism of NAFLD and T2D comorbidities.

Bulk and single-cell transcriptome analyses of islet tissue unravel gene signatures associated with pyroptosis and immune infiltration in type 2 diabetes

INTRODUCTION

Type 2 diabetes (T2D) is a common chronic heterogeneous metabolic disorder. However, the roles of pyroptosis and infiltrating immune cells in islet dysfunction of patients with T2D have yet to be explored. In this study, we aimed to explore potential crucial genes and pathways associated with pyroptosis and immune infiltration in T2D.

METHODS

To achieve this, we performed a conjoint analysis of three bulk RNA-seq datasets of islets to identify T2D-related differentially expressed genes (DEGs). After grouping the islet samples according to their ESTIMATE immune scores, we identified immune- and T2D-related DEGs. A clinical prediction model based on pyroptosis-related genes for T2D was constructed. Weighted gene co-expression network analysis was performed to identify genes positively correlated with pyroptosis-related pathways. A protein-protein interaction network was established to identify pyroptosis-related hub genes. We constructed miRNA and transcriptional networks based on the pyroptosis-related hub genes and performed functional analyses. Single-cell RNA-seq (scRNA-seq) was conducted using the GSE153885 dataset. Dimensionality was reduced using principal component analysis and t-distributed statistical neighbor embedding, and cells were clustered using Seurat. Different cell types were subjected to differential gene expression analysis and gene set enrichment analysis (GSEA). Cell-cell communication and pseudotime trajectory analyses were conducted using the samples from patients with T2D.

RESULTS

We identified 17 pyroptosis-related hub genes. We determined the abundance of 13 immune cell types in the merged matrix and found that these cell types were correlated with the 17 pyroptosis-related hub genes. Analysis of the scRNA-seq dataset of 1892 islet samples from patients with T2D and controls revealed 11 clusters. INS and IAPP were determined to be pyroptosis-related and candidate hub genes among the 11 clusters. GSEA of the 11 clusters demonstrated that the myc, G2M checkpoint, and E2F pathways were significantly upregulated in clusters with several differentially enriched pathways.

DISCUSSION

This study elucidates the gene signatures associated with pyroptosis and immune infiltration in T2D and provides a critical resource for understanding of islet dysfunction and T2D pathogenesis.

Uncovering the gene regulatory network of type 2 diabetes through multi-omic data integration

BACKGROUND

Type 2 diabetes (T2D) onset is a complex, organized biological process with multilevel regulation, and its physiopathological mechanisms are yet to be elucidated. This study aims to find out the key drivers and pathways involved in the pathogenesis of T2D through multi-omics analysis.

METHODS

The datasets used in the experiments comprise three groups: (1) genomic (2) transcriptomic, and (3) epigenomic categories. Then, a series of bioinformatics technologies including Marker set enrichment analysis (MSEA), weighted key driver analysis (wKDA) was performed to identify key drivers. The hub genes were further verified by the Receiver Operator Characteristic (ROC) Curve analysis, proteomic analysis, and Real-time quantitative polymerase chain reaction (RT-qPCR). The multi-omics network was applied to the Pharmomics pipeline in Mergeomics to identify drug candidates for T2D treatment. Then, we used the drug-gene interaction network to conduct network pharmacological analysis. Besides, molecular docking was performed using AutoDock/Vina, a computational docking program.

RESULTS

Module-gene interaction network was constructed using MSEA, which revealed a significant enrichment of immune-related activities and glucose metabolism. Top 10 key drivers (PSMB9, COL1A1, COL4A1, HLA-DQB1, COL3A1, IRF7, COL5A1, CD74, HLA-DQA1, and HLA-DRB1) were selected by wKDA analysis. Among these, COL5A1, IRF7, CD74, and HLA-DRB1 were verified to have the capability to diagnose T2D, and expression levels of PSMB9 and CD74 had significantly higher in T2D patients. We further predict the co-expression network and transcription factor (TF) binding specificity of the key driver. Besides, based on module interaction networks and key driver networks, 17 compounds are considered to possess T2D-control potential, such as sunitinib.

CONCLUSIONS

We identified signature genes, biomolecular processes, and pathways using multi-omics networks. Moreover, our computational network analysis revealed potential novel strategies for pharmacologic interventions of T2D.

Reduced miR-184-3p expression protects pancreatic β-cells from lipotoxic and proinflammatory apoptosis in type 2 diabetes via CRTC1 upregulation

The loss of functional β-cell mass in type 2 diabetes (T2D) is associated with molecular events that include β-cell apoptosis, dysfunction and/or dedifferentiation. MicroRNA miR-184-3p has been shown to be involved in several β-cell functions, including insulin secretion, proliferation and survival. However, the downstream targets and upstream regulators of miR-184-3p have not been fully elucidated. Here, we show reduced miR-184-3p levels in human T2D pancreatic islets, whereas its direct target CREB regulated transcription coactivator 1 (CRTC1) was increased and protects β-cells from lipotoxicity- and inflammation-induced apoptosis. Downregulation of miR-184-3p in β-cells leads to upregulation of CRTC1 at both the mRNA and protein levels. Remarkably, the protective effect of miR-184-3p is dependent on CRTC1, as its silencing in human β-cells abrogates the protective mechanism mediated by inhibition of miR-184-3p. Furthermore, in accordance with miR-184-3p downregulation, we also found that the β-cell-specific transcription factor NKX6.1, DNA-binding sites of which are predicted in the promoter sequence of human and mouse MIR184 gene, is reduced in human pancreatic T2D islets. Using chromatin immunoprecipitation analysis and mRNA silencing experiments, we demonstrated that NKX6.1 directly controls both human and murine miR-184 expression. In summary, we provide evidence that the decrease in NKX6.1 expression is accompanied by a significant reduction in miR-184-3p expression and that reduction of miR-184-3p protects β-cells from apoptosis through a CRTC1-dependent mechanism.

Mitoribosome insufficiency in β cells is associated with type 2 diabetes-like islet failure

Genetic variations in mitoribosomal subunits and mitochondrial transcription factors are related to type 2 diabetes. However, the role of islet mitoribosomes in the development of type 2 diabetes has not been determined. We investigated the effects of the mitoribosomal gene on β-cell function and glucose homeostasis. Mitoribosomal gene expression was analyzed in datasets from the NCBI GEO website (GSE25724, GSE76894, and GSE76895) and the European Nucleotide Archive (ERP017126), which contain the transcriptomes of type 2 diabetic and nondiabetic organ donors. We found deregulation of most mitoribosomal genes in islets from individuals with type 2 diabetes, including partial downregulation of CRIF1. The phenotypes of haploinsufficiency in a single mitoribosomal gene were examined using β-cell-specific Crif1 (Mrpl59) heterozygous-deficient mice. Crif1^beta+/− mice had normal glucose tolerance, but their islets showed a loss of first-phase glucose-stimulated insulin secretion. They also showed increased β-cell mass associated with higher expression of Reg family genes. However, Crif1^beta+/− mice showed earlier islet failure in response to high-fat feeding, which was exacerbated by aging. Haploinsufficiency of a single mitoribosomal gene predisposes rodents to glucose intolerance, which resembles the early stages of type 2 diabetes in humans.

Disruptions in the mitochondrial protein synthesis machinery give rise to metabolic disturbances that lay the foundation for type 2 diabetes. As physiological glucose levels rise, the energy-generating machinery of the mitochondria responds with increased activity, which stimulates insulin secretion. Many proteins responsible for mitochondrial metabolism are produced by ribosomes within this cellular organelle. Researchers led by Hyun Jin Kim and Minho Shong at Chungnam National University, Daejon, South Korea, have determined that mutations affecting a mitochondrial ribosomal protein called CRIF1 can lead to impaired insulin release. Mice with reduced CRIF1 were initially healthy, but as they aged, exhibited signs of impaired pancreatic function similar to those seen in patients with early-stage diabetes. This process was accelerated by consumption of a high-fat diet, and the researchers propose that this mechanism may be directly relevant to human disease.

Dietary intervention preserves β cell function in mice through CTCF-mediated transcriptional reprogramming

Pancreatic β cell plasticity is the primary determinant of disease progression and remission of type 2 diabetes (T2D). However, the dynamic nature of β cell adaptation remains elusive. Here, we establish a mouse model exhibiting the compensation-to-decompensation adaptation of β cell function in response to increasing duration of high-fat diet (HFD) feeding. Comprehensive islet functional and transcriptome analyses reveal a dynamic orchestration of transcriptional networks featuring temporal alteration of chromatin remodeling. Interestingly, prediabetic dietary intervention completely rescues β cell dysfunction, accompanied by a remarkable reversal of HFD-induced reprogramming of islet chromatin accessibility and transcriptome. Mechanistically, ATAC-based motif analysis identifies CTCF as the top candidate driving dietary intervention-induced preservation of β cell function. CTCF expression is markedly decreased in β cells from obese and diabetic mice and humans. Both dietary intervention and AAV-mediated restoration of CTCF expression ameliorate β cell dysfunction ex vivo and in vivo, through transducing the lipid toxicity and inflammatory signals to transcriptional reprogramming of genes critical for β cell glucose metabolism and stress response.

The Allelic Variant A391T of Metal Ion Transporter ZIP8 (SLC39A8) Leads to Hypotension and Enhanced Insulin Resistance

The metal ion transporter ZIP8 (SLC39A8) mediates cellular uptake of vital divalent metal ions. Genome-wide association studies (GWAS) showed that the single-nucleotide polymorphism (SNP) variant A391T (rs13107325) is associated with numerous human traits, including reduced arterial blood pressure, increased body mass index and hyperlipidemia. We analyzed in vitro the transport properties of mutant ZIP8 A391T and investigated in vivo in mice the physiological effects of this polymorphism. In vitro, the intrinsic transport properties of mutant ZIP8 were similar to those of wild type ZIP8, but cellular uptake of zinc, cadmium and iron was attenuated due to reduced ZIP8 plasma membrane expression. We then generated the ZIP8 A393T mice (ZIP8KI) that carry the corresponding polymorphism and characterized their phenotype. We observed lower protein expression in lung and kidney membrane extracts in ZIP8KI mice. The ZIP8KI mice exhibited striking changes in metal ion composition of the tissues, including cobalt, palladium, mercury and platinum. In agreement with GWAS, ZIP8KI mice showed reduced arterial blood pressure. Body weight and plasma lipid composition remained unchanged, although these features were reported to be increased in GWAS. ZIP8KI mice also exhibited remarkable insulin resistance and were protected from elevated blood glucose when challenged by dietary sucrose supplementation. We showed that increased hepatic insulin receptor expression and decreased ZnT8 (slc30a8) metal ion transporter mRNA expression are associated with this phenotypic change. In conclusion, our data reveal that ZIP8 plays an important role in blood pressure regulation and glucose homeostasis.

Establishment and Verification of a Gene Signature for Diagnosing Type 2 Diabetics by WGCNA, LASSO Analysis, and In Vitro Experiments

Objective

The incidence and prevalence of type 2 diabetes are increasing with age. Nevertheless, there is lack of sensitive diagnostic tools and effective therapeutic regimens. We aimed to establish and verify a practical and valid diagnostic tool for this disease.

Methods

WGCNA was presented on the expression profiling of type 2 diabetic and normal islets in combined GSE25724 and GSE38642 datasets. By LASSO Cox regression analyses, a gene signature was constructed based on the genes in diabetes-related modules. ROC curves were plotted for assessing the diagnostic efficacy. Correlations between the genes and immune cell infiltration and pathways were analyzed. BST2 and BTBD1 expression was verified in glucotoxicity-induced and normal islet β cells. The influence of BST2 on β cell dysfunction was investigated under si-BST2 transfection.

Results

Totally, 14 coexpression modules were constructed, and red and cyan modules displayed the correlations to diabetes. The LASSO gene signature (BST2, BTBD1, IFIT1, IFIT3, and RTP4) was developed. The AUCs in the combined datasets and GSE20966 dataset were separately 0.914 and 0.910, confirming the excellent performance in diagnosing type 2 diabetes. Each gene in the model was distinctly correlated to immune cell infiltration and key signaling pathways (TGF-β and P53, etc.). The abnormal expression of BST2 and BTBD1 was confirmed in glucotoxicity-induced β cells. BST2 knockdown ameliorated β cell dysfunction and altered the activation of TGF-β and P53 pathways.

Conclusion

Our findings propose a gene signature with high efficacy to diagnose type 2 diabetes, which could assist and improve early diagnosis and therapy.

The nuclear receptor REV-ERBα is implicated in the alteration of β-cell autophagy and survival under diabetogenic conditions

Pancreatic β-cell failure in type 2 diabetes mellitus (T2DM) is associated with impaired regulation of autophagy which controls β-cell development, function, and survival through clearance of misfolded proteins and damaged organelles. However, the mechanisms responsible for defective autophagy in T2DM β-cells remain unknown. Since recent studies identified circadian clock transcriptional repressor REV-ERBα as a novel regulator of autophagy in cancer, in this study we set out to test whether REV-ERBα-mediated inhibition of autophagy contributes to the β-cell failure in T2DM. Our study provides evidence that common diabetogenic stressors (e.g., glucotoxicity and cytokine-mediated inflammation) augment β-cell REV-ERBα expression and impair β-cell autophagy and survival. Notably, pharmacological activation of REV-ERBα was shown to phenocopy effects of diabetogenic stressors on the β-cell through inhibition of autophagic flux, survival, and insulin secretion. In contrast, negative modulation of REV-ERBα was shown to provide partial protection from inflammation and glucotoxicity-induced β-cell failure. Finally, using bioinformatic approaches, we provide further supporting evidence for augmented REV-ERBα activity in T2DM human islets associated with impaired transcriptional regulation of autophagy and protein degradation pathways. In conclusion, our study reveals a previously unexplored causative relationship between REV-ERBα expression, inhibition of autophagy, and β-cell failure in T2DM.

Novel Molecular Networks and Regulatory MicroRNAs in Type 2 Diabetes Mellitus: Multiomics Integration and Interactomics Study

BACKGROUND

Type 2 diabetes mellitus (T2DM) is a metabolic disorder with severe comorbidities. A multiomics approach can facilitate the identification of novel therapeutic targets and biomarkers with proper validation of potential microRNA (miRNA) interactions.

OBJECTIVE

The aim of this study was to identify significant differentially expressed common target genes in various tissues and their regulating miRNAs from publicly available Gene Expression Omnibus (GEO) data sets of patients with T2DM using in silico analysis.

METHODS

Using differentially expressed genes (DEGs) identified from 5 publicly available T2DM data sets, we performed functional enrichment, coexpression, and network analyses to identify pathways, protein-protein interactions, and miRNA-mRNA interactions involved in T2DM.

RESULTS

We extracted 2852, 8631, 5501, 3662, and 3753 DEGs from the expression profiles of GEO data sets GSE38642, GSE25724, GSE20966, GSE26887, and GSE23343, respectively. DEG analysis showed that 16 common genes were enriched in insulin secretion, endocrine resistance, and other T2DM-related pathways. Four DEGs, MAML3, EEF1D, NRG1, and CDK5RAP2, were important in the cluster network regulated by commonly targeted miRNAs (hsa-let-7b-5p, hsa-mir-155-5p, hsa-mir-124-3p, hsa-mir-1-3p), which are involved in the advanced glycation end products (AGE)-receptor for advanced glycation end products (RAGE) signaling pathway, culminating in diabetic complications and endocrine resistance.

CONCLUSIONS

This study identified tissue-specific DEGs in T2DM, especially pertaining to the heart, liver, and pancreas. We identified a total of 16 common DEGs and the top four common targeting miRNAs (hsa-let-7b-5p, hsa-miR-124-3p, hsa-miR-1-3p, and has-miR-155-5p). The miRNAs identified are involved in regulating various pathways, including the phosphatidylinositol-3-kinase-protein kinase B, endocrine resistance, and AGE-RAGE signaling pathways.

Time-restricted feeding prevents deleterious metabolic effects of circadian disruption through epigenetic control of β cell function

Circadian rhythm disruption (CD) is associated with impaired glucose homeostasis and type 2 diabetes mellitus (T2DM). While the link between CD and T2DM remains unclear, there is accumulating evidence that disruption of fasting/feeding cycles mediates metabolic dysfunction. Here, we used an approach encompassing analysis of behavioral, physiological, transcriptomic, and epigenomic effects of CD and consequences of restoring fasting/feeding cycles through time-restricted feeding (tRF) in mice. Results show that CD perturbs glucose homeostasis through disruption of pancreatic β cell function and loss of circadian transcriptional and epigenetic identity. In contrast, restoration of fasting/feeding cycle prevented CD-mediated dysfunction by reestablishing circadian regulation of glucose tolerance, β cell function, transcriptional profile, and reestablishment of proline and acidic amino acid–rich basic leucine zipper (PAR bZIP) transcription factor DBP expression/activity. This study provides mechanistic insights into circadian regulation of β cell function and corresponding beneficial effects of tRF in prevention of T2DM.

Discovering common pathogenetic processes between COVID-19 and diabetes mellitus by differential gene expression pattern analysis

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by the newly discovered coronavirus, SARS-CoV-2. Increased severity of COVID-19 has been observed in patients with diabetes mellitus (DM). This study aimed to identify common transcriptional signatures, regulators and pathways between COVID-19 and DM. We have integrated human whole-genome transcriptomic datasets from COVID-19 and DM, followed by functional assessment with gene ontology (GO) and pathway analyses. In peripheral blood mononuclear cells (PBMCs), among the upregulated differentially expressed genes (DEGs), 32 were found to be commonly modulated in COVID-19 and type 2 diabetes (T2D), while 10 DEGs were commonly downregulated. As regards type 1 diabetes (T1D), 21 DEGs were commonly upregulated, and 29 DEGs were commonly downregulated in COVID-19 and T1D. Moreover, 35 DEGs were commonly upregulated in SARS-CoV-2 infected pancreas organoids and T2D islets, while 14 were commonly downregulated. Several GO terms were found in common between COVID-19 and DM. Prediction of the putative transcription factors involved in the upregulation of genes in COVID-19 and DM identified RELA to be implicated in both PBMCs and pancreas. Here, for the first time, we have characterized the biological processes and pathways commonly dysregulated in COVID-19 and DM, which could be in the next future used for the design of personalized treatment of COVID-19 patients suffering from DM as comorbidity.

Electrogenic sodium bicarbonate cotransporter NBCe1 regulates pancreatic β cell function in type 2 diabetes

Pancreatic β cell failure in type 2 diabetes mellitus (T2DM) is attributed to perturbations of the β cell's transcriptional landscape resulting in impaired glucose-stimulated insulin secretion. Recent studies identified SLC4A4 (a gene encoding an electrogenic Na+-coupled HCO3- cotransporter and intracellular pH regulator, NBCe1) as one of the misexpressed genes in β cells of patients with T2DM. Thus, in the current study, we set out to test the hypothesis that misexpression of SLC4A4/NBCe1 in T2DM β cells contributes to β cell dysfunction and impaired glucose homeostasis. To address this hypothesis, we first confirmed induction of SLC4A4/NBCe1 expression in β cells of patients with T2DM and demonstrated that its expression was associated with loss of β cell transcriptional identity, intracellular alkalinization, and β cell dysfunction. In addition, we generated a β cell-selective Slc4a4/NBCe1-KO mouse model and found that these mice were protected from diet-induced metabolic stress and β cell dysfunction. Importantly, improved glucose tolerance and enhanced β cell function in Slc4a4/NBCe1-deficient mice were due to augmented mitochondrial function and increased expression of genes regulating β cell identity and function. These results suggest that increased β cell expression of SLC4A4/NBCe1 in T2DM plays a contributory role in promotion of β cell failure and should be considered as a potential therapeutic target.

Correlation between Alzheimer's disease and type 2 diabetes using non-negative matrix factorization

Alzheimer's disease (AD) is a complex and heterogeneous disease that can be affected by various genetic factors. Although the cause of AD is not yet known and there is no treatment to cure this disease, its progression can be delayed. AD has recently been recognized as a brain-specific type of diabetes called type 3 diabetes. Several studies have shown that people with type 2 diabetes (T2D) have a higher risk of developing AD. Therefore, it is important to identify subgroups of patients with AD that may be more likely to be associated with T2D. We here describe a new approach to identify the correlation between AD and T2D at the genetic level. Subgroups of AD and T2D were each generated using a non-negative matrix factorization (NMF) approach, which generated clusters containing subsets of genes and samples. In the gene cluster that was generated by conventional gene clustering method from NMF, we selected genes with significant differences in the corresponding sample cluster by Kruskal-Wallis and Dunn-test. Subsequently, we extracted differentially expressed gene (DEG) subgroups, and candidate genes with the same regulation direction can be extracted at the intersection of two disease DEG subgroups. Finally, we identified 241 candidate genes that represent common features related to both AD and T2D, and based on pathway analysis we propose that these genes play a role in the common pathological features of AD and T2D. Moreover, in the prediction of AD using logistic regression analysis with an independent AD dataset, the candidate genes obtained better prediction performance than DEGs. In conclusion, our study revealed a subgroup of patients with AD that are associated with T2D and candidate genes associated between AD and T2D, which can help in providing personalized and suitable treatments.

Network-based analysis of key regulatory genes implicated in Type 2 Diabetes Mellitus and Recurrent Miscarriages in Turner Syndrome

The information on the genotype-phenotype relationship in Turner Syndrome (TS) is inadequate because very few specific candidate genes are linked to its clinical features. We used the microarray data of TS to identify the key regulatory genes implicated with TS through a network approach. The causative factors of two common co-morbidities, Type 2 Diabetes Mellitus (T2DM) and Recurrent Miscarriages (RM), in the Turner population, are expected to be different from that of the general population. Through microarray analysis, we identified nine signature genes of T2DM and three signature genes of RM in TS. The power-law distribution analysis showed that the TS network carries scale-free hierarchical fractal attributes. Through local-community-paradigm (LCP) estimation we find that a strong LCP is also maintained which means that networks are dynamic and heterogeneous. We identified nine key regulators which serve as the backbone of the TS network. Furthermore, we recognized eight interologs functional in seven different organisms from lower to higher levels. Overall, these results offer few key regulators and essential genes that we envisage have potential as therapeutic targets for the TS in the future and the animal models studied here may prove useful in the validation of such targets.

Redox Homeostasis in Pancreatic β-Cells: From Development to Failure

Redox status is a key determinant in the fate of β-cell. These cells are not primarily detoxifying and thus do not possess extensive antioxidant defense machinery. However, they show a wide range of redox regulating proteins, such as peroxiredoxins, thioredoxins or thioredoxin reductases, etc., being functionally compartmentalized within the cells. They keep fragile redox homeostasis and serve as messengers and amplifiers of redox signaling. β-cells require proper redox signaling already in cell ontogenesis during the development of mature β-cells from their progenitors. We bring details about redox-regulated signaling pathways and transcription factors being essential for proper differentiation and maturation of functional β-cells and their proliferation and insulin expression/maturation. We briefly highlight the targets of redox signaling in the insulin secretory pathway and focus more on possible targets of extracellular redox signaling through secreted thioredoxin1 and thioredoxin reductase1. Tuned redox homeostasis can switch upon chronic pathological insults towards the dysfunction of β-cells and to glucose intolerance. These are characteristics of type 2 diabetes, which is often linked to chronic nutritional overload being nowadays a pandemic feature of lifestyle. Overcharged β-cell metabolism causes pressure on proteostasis in the endoplasmic reticulum, mainly due to increased demand on insulin synthesis, which establishes unfolded protein response and insulin misfolding along with excessive hydrogen peroxide production. This together with redox dysbalance in cytoplasm and mitochondria due to enhanced nutritional pressure impact β-cell redox homeostasis and establish prooxidative metabolism. This can further affect β-cell communication in pancreatic islets through gap junctions. In parallel, peripheral tissues losing insulin sensitivity and overall impairment of glucose tolerance and gut microbiota establish local proinflammatory signaling and later systemic metainflammation, i.e., low chronic inflammation prooxidative properties, which target β-cells leading to their dedifferentiation, dysfunction and eventually cell death.

Amino acids-Rab1A-mTORC1 signaling controls whole-body glucose homeostasis

Rab1A is a small GTPase known for its role in vesicular trafficking. Recent evidence indicates that Rab1A is essential for amino acids (aas) sensing and signaling to regulate mTORC1 in normal and cancer cells. However, Rab1A's in vivo function in mammals is not known. Here, we report the generation of tamoxifen (TAM)-induced whole body Rab1A knockout (Rab1A-/-) in adult mice. Rab1A-/- mice are viable but become hyperglycemic and glucose intolerant due to impaired insulin transcription and β-cell proliferation and maintenance. Mechanistically, Rab1A mediates AA-mTORC1 signaling, particularly branched chain amino acids (BCAA), to regulate the stability and localization of the insulin transcription factor Pdx1. Collectively, these results reveal a physiological role of aa-Rab1A-mTORC1 signaling in the control of whole-body glucose homeostasis in mammals. Intriguingly, Rab1A expression is reduced in β-cells of type 2 diabetes (T2D) patients, which is correlated with loss of insulin expression, suggesting that Rab1A downregulation contributes to T2D progression.

Enhancer-Gene Interaction Analyses Identified the Epidermal Growth Factor Receptor as a Susceptibility Gene for Type 2 Diabetes Mellitus

Background

Genetic interactions are known to play an important role in the missing heritability problem for type 2 diabetes mellitus (T2DM). Interactions between enhancers and their target genes play important roles in gene regulation and disease pathogenesis. In the present study, we aimed to identify genetic interactions between enhancers and their target genes associated with T2DM.

Methods

We performed genetic interaction analyses of enhancers and protein-coding genes for T2DM in 2,696 T2DM patients and 3,548 controls of European ancestry. A linear regression model was used to identify single nucleotide polymorphism (SNP) pairs that could affect the expression of the protein-coding genes. Differential expression analyses were used to identify differentially expressed susceptibility genes in diabetic and nondiabetic subjects.

Results

We identified one SNP pair, rs4947941×rs7785013, significantly associated with T2DM (combined P=4.84×10-10). The SNP rs4947941 was annotated as an enhancer, and rs7785013 was located in the epidermal growth factor receptor (EGFR) gene. This SNP pair was significantly associated with EGFR expression in the pancreas (P=0.033), and the minor allele "A" of rs7785013 decreased EGFR gene expression and the risk of T2DM with an increase in the dosage of "T" of rs4947941. EGFR expression was significantly upregulated in T2DM patients, which was consistent with the effect of rs4947941×rs7785013 on T2DM and EGFR expression. A functional validation study using the Mouse Genome Informatics (MGI) database showed that EGFR was associated with diabetes-relevant phenotypes.

Conclusion

Genetic interaction analyses of enhancers and protein-coding genes suggested that EGFR may be a novel susceptibility gene for T2DM.

The molecular mechanisms mediating class II PI 3-kinase function in cell physiology

The phosphoinositide 3-kinase (PI3K) family of lipid-modifying enzymes plays vital roles in cell signaling and membrane trafficking through the production of 3-phosphorylated phosphoinositides. Numerous studies have analyzed the structure and function of class I and class III PI3Ks. In contrast, we know comparably little about the structure and physiological functions of the class II enzymes. Only recent studies have begun to unravel their roles in development, endocytic and endolysosomal membrane dynamics, signal transduction, and cell migration, while the mechanisms that control their localization and enzymatic activity remain largely unknown. Here, we summarize our current knowledge of the class II PI3Ks and outline open questions related to their structure, enzymatic activity, and their physiological and pathophysiological functions.

Identification of Shared Genes and Pathways in Periodontitis and Type 2 Diabetes by Bioinformatics Analysis

INTRODUCTION

It is well known that the presence of diabetes significantly affects the progression of periodontitis and that periodontitis has negative effects on diabetes and diabetes-related complications. Although this two-way relationship between type 2 diabetes and periodontitis could be understood through experimental and clinical studies, information on common genetic factors would be more useful for the understanding of both diseases and the development of treatment strategies.

MATERIALS AND METHODS

Gene expression data for periodontitis and type 2 diabetes were obtained from the Gene Expression Omnibus database. After preprocessing of data to reduce heterogeneity, differentially expressed genes (DEGs) between disease and normal tissue were identified using a linear regression model package. Gene ontology and Kyoto encyclopedia of genes and genome pathway enrichment analyses were conducted using R package 'vsn'. A protein-protein interaction network was constructed using the search tool for the retrieval of the interacting genes database. We used molecular complex detection for optimal module selection. CytoHubba was used to identify the highest linkage hub gene in the network.

RESULTS

We identified 152 commonly DEGs, including 125 upregulated and 27 downregulated genes. Through common DEGs, we constructed a protein-protein interaction and identified highly connected hub genes. The hub genes were up-regulated in both diseases and were most significantly enriched in the Fc gamma R-mediated phagocytosis pathway.

DISCUSSION

We have identified three up-regulated genes involved in Fc gamma receptor-mediated phagocytosis, and these genes could be potential therapeutic targets in patients with periodontitis and type 2 diabetes.

Integrative transcriptomic analysis of pancreatic islets from patients with prediabetes/type 2 diabetes

AIM

To identify new transcriptomic alterations in pancreatic islets associated with metabolic dysfunctions in people with prediabetes (PD)/type 2 diabetes (T2D).

MATERIALS AND METHODS

We collected information from public data repositories T2D related microarray datasets from pancreatic islets. We identified Differential Expressed Genes (DEGs) in non-diabetic (ND) vs people with T2D in each study. To identify relevant DEGs in T2D, we selected those that varied consistently in the different studies for further meta-analysis and functional enrichment analysis. DEGs were also evaluated at the PD stage.

RESULTS

A total of seven microarray datasets were collected and analysed to find the DEGs in each study and meta-analysis was performed with 245 ND and 96 T2D cases. We identified 55 transcriptional alterations potentially associated with specific metabolic dysfunctions in T2D. Meta-analysis showed that 87% of transcripts identified as DEGs (48 out of 55) were confirmed as having statistically significant up- or down-modulation in T2D compared to ND. Notably, nine of these DEGs have not been previously reported as dysregulated in pancreatic islets from people with T2D. Consistently, the most significantly enriched pathways were related to the metabolism and/or development/maintenance of β-cells. Eighteen of the 48 selected DEGs (38%) showed an altered expression in islets from people with PD.

CONCLUSIONS

These results provide new evidence to interpret the pathogenesis of T2D and the transition from PD to T2D. Further studies are necessary to validate its potential use for the development/implementation of efficient new strategies for the prevention, diagnosis/prognosis and treatment of T2D.

Causal Relationship and Shared Genetic Loci between Psoriasis and Type 2 Diabetes through Trans-Disease Meta-Analysis

Psoriasis and type 2 diabetes (T2D) are complex conditions with significant impacts on health. Patients with psoriasis have a higher risk of T2D (∼1.5 OR) and vice versa, controlling for body mass index; yet, there has been a limited study comparing their genetic architecture. We hypothesized that there are shared genetic components between psoriasis and T2D. Trans-disease meta-analysis was applied to 8,016,731 well-imputed genetic markers from large-scale meta-analyses of psoriasis (11,024 cases and 16,336 controls) and T2D (74,124 cases and 824,006 controls), adjusted for body mass index. We confirmed our findings in a hospital-based study (42,112 patients) and tested for causal relationships with multivariable Mendelian randomization. Mendelian randomization identified a causal relationship between psoriasis and T2D (P = 1.6 × 10^‒4, OR = 1.01) and highlighted the impact of body mass index. Trans-disease meta-analysis further revealed four genome-wide significant loci (P < 5 × 10^‒8) with evidence of colocalization and shared directions of effect between psoriasis and T2D not present in body mass index. The proteins coded by genes in these loci (ACTR2, ERLIN1, TRMT112, and BECN1) are connected through NF-κB signaling. Our results provide insight into the immunological components that connect immune-mediated skin conditions and metabolic diseases, independent of confounding factors.

A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes

The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We used an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray data sets generated using human islets from donors with diabetes and islets where type 1 (T1D) and type 2 (T2D) diabetes had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. In parallel, we generated an RNA-sequencing data set from human islets treated with brefeldin A (BFA), a known GA stress inducer. Overlapping the T1D and T2D groups with the BFA data set, we identified 120 and 204 differentially expressed genes, respectively. In both the T1D and T2D models, pathway analyses revealed that the top pathways were associated with GA integrity, organization, and trafficking. Quantitative RT-PCR was used to validate a common signature of GA stress that included ATF3, ARF4, CREB3, and COG6 Taken together, these data indicate that GA-associated genes are dysregulated in diabetes and identify putative markers of β-cell GA stress.

Analysis of long noncoding RNA-associated competing endogenous RNA network in glucagon-like peptide-1 receptor agonist-mediated protection in β cells

BACKGROUND

Long noncoding RNAs (lncRNAs) and mRNAs are widely involved in various physiological and pathological processes. The use of glucagon-like peptide-1 receptor agonists (GLP-1RAs) is a novel therapeutic strategy that could promote insulin secretion and decrease the rate of β-cell apoptosis in type 2 diabetes mellitus (T2DM) patients. However, the specific lncRNAs and mRNAs and their functions in these processes have not been fully identified and elucidated.

AIM

To identify the lncRNAs and mRNAs that are involved in the protective effect of GLP-1RA in β cells, and their roles.

METHODS

Rat gene microarray was used to screen differentially expressed (DE) lncRNAs and mRNAs in β cells treated with geniposide, a GLP-1RA. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to assess the underlying functions of DE mRNAs. Hub mRNAs were filtered using the STRING database and the Cytoscape plugin, CytoHubba. In order to reveal the regulatory relationship between lncRNAs and hub mRNAs, their co-expression network was constructed based on the Pearson coefficient of DE lncRNAs and mRNAs, and competing endogenous RNA (ceRNA) mechanism was explored through miRanda and TargetScan databases.

RESULTS

We identified 308 DE lncRNAs and 128 DE mRNAs with a fold change filter of ≥ 1.5 and P value < 0.05. GO and KEGG pathway enrichment analyses indicated that the most enriched terms were G-protein coupled receptor signaling pathway, inflammatory response, calcium signaling pathway, positive regulation of cell proliferation, and ERK1 and ERK2 cascade. Pomc, Htr2a, and Agtr1a were screened as hub mRNAs using the STRING database and the Cytoscape plugin, CytoHubba. This result was further verified using SwissTargetPrediction tool. Through the co-expression network and competing endogenous (ceRNA) mechanism, we identified seven lncRNAs (NONRATT027738, NONRATT027888, NONRATT030038, etc.) co-expressed with the three hub mRNAs (Pomc, Htr2a, and Agtr1a) based on the Pearson coefficient of the expression levels. These lncRNAs regulated hub mRNA functions by competing with six miRNAs (rno-miR-5132-3p, rno-miR-344g, rno-miR-3075, etc.) via the ceRNA mechanism. Further analysis indicated that lncRNA NONRATT027738 interacts with all the three hub mRNAs, suggesting that it is at a core position within the ceRNA network.

CONCLUSION

We have identified key lncRNAs and mRNAs, and highlighted here how they interact through the ceRNA mechanism to mediate the protective effect of GLP-1RA in β cells.

The type 2 diabetes gene product STARD10 is a phosphoinositide-binding protein that controls insulin secretory granule biogenesis

OBJECTIVE

Risk alleles for type 2 diabetes at the STARD10 locus are associated with lowered STARD10 expression in the β-cell, impaired glucose-induced insulin secretion, and decreased circulating proinsulin:insulin ratios. Although likely to serve as a mediator of intracellular lipid transfer, the identity of the transported lipids and thus the pathways through which STARD10 regulates β-cell function are not understood. The aim of this study was to identify the lipids transported and affected by STARD10 in the β-cell and the role of the protein in controlling proinsulin processing and insulin granule biogenesis and maturation.

METHODS

We used isolated islets from mice deleted selectively in the β-cell for Stard10 (βStard10KO) and performed electron microscopy, pulse-chase, RNA sequencing, and lipidomic analyses. Proteomic analysis of STARD10 binding partners was executed in the INS1 (832/13) cell line. X-ray crystallography followed by molecular docking and lipid overlay assay was performed on purified STARD10 protein.

RESULTS

βStard10KO islets had a sharply altered dense core granule appearance, with a dramatic increase in the number of "rod-like" dense cores. Correspondingly, basal secretion of proinsulin was increased versus wild-type islets. The solution of the crystal structure of STARD10 to 2.3 Å resolution revealed a binding pocket capable of accommodating polyphosphoinositides, and STARD10 was shown to bind to inositides phosphorylated at the 3' position. Lipidomic analysis of βStard10KO islets demonstrated changes in phosphatidylinositol levels, and the inositol lipid kinase PIP4K2C was identified as a STARD10 binding partner. Also consistent with roles for STARD10 in phosphoinositide signalling, the phosphoinositide-binding proteins Pirt and Synaptotagmin 1 were amongst the differentially expressed genes in βStard10KO islets.

CONCLUSION

Our data indicate that STARD10 binds to, and may transport, phosphatidylinositides, influencing membrane lipid composition, insulin granule biosynthesis, and insulin processing.

Phosphatidylinositol 3-monophosphate: A novel actor in thrombopoiesis and thrombosis

Phosphoinositides are lipid second messengers regulating in time and place the formation of protein complexes involved in the control of intracellular signaling, vesicular trafficking, and cytoskeleton/membrane dynamics. One of these lipids, phosphatidylinositol 3 monophosphate (PtdIns3P), is present in small amounts in mammalian cells and is involved in the control of endocytic/endosomal trafficking and in autophagy. Its metabolism is finely regulated by specific kinases and phosphatases including class II phosphoinositide 3-kinases (PI3KC2s) and the class III PI3K, Vps34. Recently, PtdIns3P has emerged as an important regulator of megakaryocyte/platelet structure and functions. Here, we summarize the current knowledge in the role of different pools of PtdIns3P regulated by class II and III PI3Ks in platelet production and thrombosis. Potential new antithrombotic therapeutic perspectives based on the use of inhibitors targeting specifically PtdIns3P-metabolizing enzymes will also be discussed. Finally, we provide report of new research in this area presented at the International Society of Thrombosis and Haemostasis 2019 Annual Congress.