KCNH6 is essential for insulin secretion by regulating intracellular ER Ca2+ store.

Appropriate Ca2+ concentration in the endoplasmic reticulum (ER), modulating cytosolic Ca2+ signal, serves significant roles in physiological function of pancreatic ß cells. To maintaining ER homeostasis, Ca2+ movement across the ER membrane is always accompanied by a simultaneous K+ flux in the opposite direction. KCNH6 was proven to modulate insulin secretion by controlling plasma membrane action potential duration and intracellular Ca2+ influx. Meanwhile, the specific function of KCNH6 in pancreatic ß-cells remains unclear. In this study, we found that KCNH6 exhibited mainly ER localization and Kcnh6 ß-cell-specific knockout (ßKO) mice suffered from abnormal glucose tolerance and impaired insulin secretion in adulthood. ER Ca2+ store was overloaded in islets of ßKO mice, which contributed to ER stress and ER stress-induced apoptosis in ß cells. Next, we verified that ethanol treatment induced increases in ER Ca2+ store and apoptosis in pancreatic ß cells, whereas adenovirus-mediated KCNH6 overexpression in islets attenuated ethanol-induced ER stress and apoptosis. In addition, tail-vein injections of KCNH6 lentivirus rescued KCNH6 expression in ßKO mice, restored ER Ca2+ overload and attenuated ER stress in ß cells, which further confirms that KCNH6 protects islets from ER stress and apoptosis. These data suggest that KCNH6 on the ER membrane may help to stabilize intracellular ER Ca2+ stores and protect ß cells from ER stress and apoptosis. In conclusion, our study reveals the protective potential of KCNH6-targeting drugs in ER stress-induced diabetes.

KCNH6 channel promotes insulin exocytosis via interaction with Munc18-1 independent of electrophysiological processes.

Glucose-stimulated insulin secretion (GSIS) in pancreatic islet ß-cells primarily relies on electrophysiological processes. Previous research highlighted the regulatory role of KCNH6, a member of the Kv channel family, in governing GSIS through its influence on ß-cell electrophysiology. In this study, we unveil a novel facet of KCNH6's function concerning insulin granule exocytosis, independent of its conventional electrical role. Young mice with ß-cell-specific KCNH6 knockout (ßKO) exhibited impaired glucose tolerance and reduced insulin secretion, a phenomenon not explained by electrophysiological processes alone. Consistently, islets from KCNH6-ßKO mice exhibited reduced insulin secretion, conversely, the overexpression of KCNH6 in murine pancreatic islets significantly enhanced insulin release. Moreover, insulin granules lacking KCNH6 demonstrated compromised docking capabilities and a reduced fusion response upon glucose stimulation. Crucially, our investigation unveiled a significant interaction between KCNH6 and the SNARE protein regulator, Munc18-1, a key mediator of insulin granule exocytosis. These findings underscore the critical role of KCNH6 in the regulation of insulin secretion through its interaction with Munc18-1, providing a promising and novel avenue for enhancing our understanding of the Kv channel in diabetes mechanisms.

All-potassium channel CRISPR screening reveals a lysine-specific pathway of insulin secretion.

OBJECTIVE: Genome-scale CRISPR-Cas9 knockout coupled with single-cell RNA sequencing (scRNA-seq) has been used to identify function-related genes. However, this method may knock out too many genes, leading to low efficiency in finding genes of interest. Insulin secretion is controlled by several electrophysiological events, including fluxes of KATP depolarization and K+ repolarization. It is well known that glucose stimulates insulin secretion from pancreatic ß-cells, mainly via the KATP depolarization channel, but whether other nutrients directly regulate the repolarization K+ channel to promote insulin secretion is unknown. METHODS: We used a system involving CRISPR-Cas9-mediated knockout of all 83 K+ channels and scRNA-seq in a pancreatic ß cell line to identify genes associated with insulin secretion. RESULTS: The expression levels of insulin genes were significantly increased after all-K+ channel knockout. Furthermore, Kcnb1 and Kcnh6 were the two most important repolarization K+ channels for the increase in high-glucose-dependent insulin secretion that occurred upon application of specific inhibitors of the channels. Kcnh6 currents, but not Kcnb1 currents, were reduced by one of the amino acids, lysine, in both transfected cells, primary cells and mice with ß-cell-specific deletion of Kcnh6. CONCLUSIONS: Our function-related CRISPR screen with scRNA-seq identifies Kcnh6 as a lysine-specific channel.

TC-Net: A joint learning framework based on CNN and vision transformer for multi-lesion medical images segmentation.

BACKGROUND: With the rapid advancement of medical imaging technology, the demand for accurate segmentation of medical images is increasing. However, most existing methods are unable to capture locality and long-range dependency information in integrated ways for medical images. METHOD: In this paper, we propose an elegant segmentation framework for medical images named TC-Net, which can utilize both the locality-aware and long-range dependencies in the medical images. As for the locality-aware perspective, we employ a CNN-based encoder and decoder structure. The CNN branch uses the locality of convolution operations to dig out local information in medical images. As for the long-range dependencies, we construct a Transformer branch to focus on the global context. Additionally, we proposed a locality-aware and long-range dependency concatenation strategy (LLCS) to aggregate the feature maps obtained from the two subbranches. Finally, we present a dynamic cyclical focal loss (DCFL) to address the class imbalance problem in multi-lesion segmentation. RESULTS: Comprehensive experiments were conducted on lesion segmentation tasks using two fundus image databases and a skin image database. The TC-Net achieves scores of 0.6985 and 0.5171 in the metric of mean pixel accuracy on the IDRiD and DDR databases, respectively. Moreover, on the skin image database, the TC-Net reached mean pixel accuracy of 0.8886. The experiment results demonstrate that the proposed method achieves better performance than other deep learning segmentation schemes. Furthermore, the proposed DCFL achieves higher performance than other loss functions in multi-lesion segmentation. SIGNIFICANCE: The proposed TC-Net is a promising new framework for multi-lesion medical image segmentation and many other challenging image segmentation tasks. © 2001 Elsevier Science. All rights reserved.

Association between Covid-19 vaccination and incidence of type 1 diabetes in China: Evidence from 14.14 million registered residents between 2007 and 2021.

AIMS: Reports have suggested that COVID-19 vaccination may cause Type 1 diabetes (T1D), particularly fulminant T1D (FT1D). This study aimed to investigate the incidence of T1D in a general population of China, where>90% of the people have received three injections of inactivated SARS-Cov-2 vaccines in 2021. METHODS: A population-based registry of T1D was performed using data from the Beijing Municipal Health Commission Information Center. Annual incidence rates were calculated by age group and gender, and annual percentage changes were assessed using Joinpoint regression. RESULTS: The study included 14.14 million registered residents, and 7,697 people with newly diagnosed T1D were identified from 2007 to 2021. T1D incidence increased from 2.77 in 2007 to 3.84 per 100,000 persons in 2021. However, T1D incidence was stable from 2019 to 2021, and the incidence rate did not increase when people were vaccinated in January-December 2021. The incidence of FT1D did not increase from 2015 to 2021. CONCLUSIONS: The findings suggest that COVID-19 vaccination did not increase the onset of T1D or have a significant impact on T1D pathogenesis, at least not on a large scale.

Integrated Proteomics and Metabolomics Analyses of Serum in Chinese Patients with Severe and Active Graves' Orbitopathy: A Cross-sectional Study.

OBJECTIVE: The present study aims to investigate the alterations of serum proteomic and metabolomic profiles in Chinese patients with severe and active Graves' Orbitopathy (GO). MATERIALS AND METHODS: Thirty patients with GO and 30 healthy volunteers were enrolled. The serum concentrations of FT3, FT4, T3, T4, and thyroid-stimulating hormone (TSH) were analyzed, after which TMT labeling-based proteomics and untargeted metabolomics were performed. Metabo- Analyst and Ingenuity Pathway Analysis (IPA) was used for integrated network analysis. A nomogram was established based on the model to explore the disease prediction ability of the identified feature metabolites. RESULTS: One hundred thirteen proteins (19 up-regulated and 94 down-regulated) and 75 metabolites (20 increased and 55 decreased) were significantly altered in GO compared to the control group. By combining the lasso regression, IPA network, and protein-metabolite-disease sub-networks, we extracted feature proteins (CPS1, GP1BA, and COL6A1) and feature metabolites (glycine, glycerol 3-phosphate, and estrone sulfate). The logistic regression analysis revealed that the full model with the prediction factors and three identified feature metabolites had better prediction performance for GO compared to the baseline model. The ROC curve also indicated better prediction performance (AUC = 0.933 vs. 0.789). CONCLUSION: A new biomarker cluster combined with three blood metabolites with high statistical power can be used to discriminate patients with GO. These findings provide further insights into the pathogenesis, diagnosis, and potential therapeutic targets for this disease.

An approach combining deep learning and molecule docking for drug discovery of cathepsin L.

OBJECTIVES: Cathepsin L (CTSL) is a promising therapeutic target for metabolic disorders and COVID-19. However, there are still no clinically available CTSL inhibitors. Our objective is to develop an approach for the discovery of potential reversible covalent CTSL inhibitors. METHODS: The authors combined Chemprop, a deep learning-based strategy, and the Schrödinger CovDock algorithm to identify potential CTSL inhibitors. First, they used Chemprop to train a deep learning model capable of predicting whether a molecule would inhibit the activity of CTSL and performed predictions on ZINC20 in-stock librarie (~9.2 million molecules). Then, they selected the top-200 predicted molecules and performed the Schrödinger covalent docking algorithm to explore the binding patterns to CTSL (PDB: 5MQY). The authors then calculated the binding energies using Prime MM/GBSA and examined the stability between the best two molecules and CTSL using 100ns molecular dynamics simulations. RESULTS: The authors found five molecules that showed better docking results than the well-known cathepsin inhibitor odanacatib. Notably, two of these molecules, ZINC-35287427 and ZINC-1857528743, showed better docking results with CTSL compared to other cathepsins. CONCLUSION: Our approach enables drug discovery from large-scale databases with little computational consumption, which will save the cost and time required for drug discovery.

The signaling protein GIV/Girdin mediates the Nephrin-dependent insulin secretion of pancreatic islet ß cells in response to high glucose.

Glucose-stimulated insulin secretion of pancreatic ß cells is essential in maintaining glucose homeostasis. Recent evidence suggests that the Nephrin-mediated intercellular junction between ß cells is implicated in the regulation of insulin secretion. However, the underlying mechanisms are only partially characterized. Herein we report that GIV is a signaling mediator coordinating glucose-stimulated Nephrin phosphorylation and endocytosis with insulin secretion. We demonstrate that GIV is expressed in mouse islets and cultured ß cells. The loss of function study suggests that GIV is essential for the second phase of glucose-stimulated insulin secretion. Next, we demonstrate that GIV mediates the high glucose-stimulated tyrosine phosphorylation of GIV and Nephrin by recruiting Src kinase, which leads to the endocytosis of Nephrin. Subsequently, the glucose-induced GIV/Nephrin/Src signaling events trigger downstream Akt phosphorylation, which activates Rac1-mediated cytoskeleton reorganization, allowing insulin secretory granules to access the plasma membrane for the second-phase secretion. Finally, we found that GIV is downregulated in the islets isolated from diabetic mice, and rescue of GIV ameliorates the ß-cell dysfunction to restore the glucose-stimulated insulin secretion. We conclude that the GIV/Nephrin/Akt signaling axis is vital to regulate glucose-stimulated insulin secretion. This mechanism might be further targeted for therapeutic intervention of diabetic mellitus.

Tear-derived exosomal biomarkers of Graves' ophthalmopathy.

Graves' ophthalmopathy (GO), the most frequent extrathyroidal manifestation of Graves' disease (GD), can lead to a significant decline in the quality of life in patients. Exosomes, which contain proteins, lipids and DNA, play important roles in the pathological processes of various diseases. However, their roles in Graves' ophthalmopathy are still unclear. We aimed to isolate exosomes and analyze the different exosomal proteins. Tear fluids were collected from twenty-four GO patients, twenty-four GD patients and sixteen control subjects. The numbers of tear exosomes were assayed using nanoparticle tracking analysis. A Luminex 200 kit and ELISA kit were used to confirm the different cytokine concentrations in serum. Extraocular muscle from GO patients and controls was extracted, and western blotting was used to assay the levels of Caspase-3 and complement C4A. Our study demonstrated that the number of tear exosomes differ from GD patients and control. The expression levels of cytokines, including IL-1 and IL-18, were significantly increased in the tear exosomes and serum from GO patients compared with GD patients and controls. The levels of the exosomal proteins Caspase-3, complement C4A and APOA-IV were significantly increased in GO patients compared to GD patients and controls. Orbital fibroblasts from GO patients showed significantly higher levels of Caspase-3 and complement C4A than those from controls. The levels of serum APOA-IV in GO patients were significantly higher than those in GD patients and controls. Specific proteins showed elevated expression in tear exosomes from GO patients, indicating that they may play important roles in GO pathogenesis.

Cisapride induced hypoglycemia via the KCNH6 potassium channel.

Mutations in KCNH6 has been proved to cause hypoinsulinemia and diabetes in human and mice. Cisapride is a stomach-intestinal motility drug used to treat gastrointestinal dysfunction. Cisapride has been reported to be a potential inhibitor of the KCNH family, but it remained unclear whether cisapride inhibited KCNH6. Here, we discovered the role of cisapride on glucose metabolism, focusing on the KCNH6 potassium channel protein. Cisapride reduced blood glucose level and increased serum insulin secretion in wild-type (WT) mice fed standard normal chow/a high-fat diet or in db/db mice, especially when combined with tolbutamide. This effect was much stronger after 4 weeks of intraperitoneal injection. Whole-cell patch-clamp showed that cisapride inhibited KCNH6 currents in transfected HEK293 cells in a concentration-dependent manner. Cisapride induced an increased insulin secretion through the disruption of intracellular calcium homeostasis in a rat pancreatic ß-cell line, INS-1E. Further experiments revealed that cisapride did not decrease blood glucose or increase serum insulin in KCNH6 ß-cell knockout (Kcnh6-ß-KO) mice when compared with WT mice. Cisapride also ameliorated glucose-stimulated insulin secretion (GSIS) in response to high glucose in WT but not Kcnh6-ß-KO mice. Thus, our data reveal a novel way for the effect of KCNH6 in cisapride-induced hypoglycemia.

The purine metabolite inosine monophosphate accelerates myelopoiesis and acute pancreatitis progression.

Hyperglycemia-induced myelopoiesis and atherosclerotic progression occur in mice with type I diabetes. However, less is known about the effects of metabolites on myelopoesis in type 2 diabetes. Here, we use fluorescence-activated cell sorting to analyze the proliferation of granulocyte/monocyte progenitors (GMP) in db/db mice. Using targeted metabolomics, we identify an increase in inosine monophosphate (IMP) in GMP cells of 24-week-old mice. We show that IMP treatment stimulates cKit expression, ribosomal S6 activation, GMP proliferation, and Gr-1+ granulocyte production in vitro. IMP activates pAkt in non-GMP cells. In vivo, using an established murine acute pancreatitis (AP) model, administration of IMP-treated bone marrow cells enhances the severity of AP. This effect is abolished in the presence of a pAkt inhibitor. Targeted metabolomics show that plasma levels of guanosine monophosphate are significantly higher in diabetic patients with AP. These findings provid a potential therapeutic target for the control of vascular complications in diabetes.

KCNH6 Enhanced Hepatic Glucose Metabolism through Mitochondrial Ca2+ Regulation and Oxidative Stress Inhibition.

KCNH6 has been proven to affect glucose metabolism and insulin secretion both in humans and mice. Further study revealed that Kcnh6 knockout (KO) mice showed impaired glucose tolerance. However, the precise function of KCNH6 in the liver remains unknown. Mitochondria have been suggested to maintain intracellular Ca2+ homeostasis; ROS generation and defective mitochondria can cause glucose metabolism disorders, including type 2 diabetes (T2D). Here, we found that Kcnh6 attenuated glucose metabolism disorders by decreasing PEPCK and G6pase abundance and induced Glut2 and IRS2 expression. Overexpression of Kcnh6 increased hepatic glucose uptake and glycogen synthesis. Kcnh6 attenuated intracellular and mitochondrial calcium levels in primary hepatocytes and reduced intracellular ROS and mitochondrial superoxide production. Kcnh6 suppressed oxidative stress by inhibiting mitochondrial pathway activation and NADPH oxidase expression. Experiments demonstrated that Kcnh6 expression improved hepatic glucose metabolism disorder through the c-Jun N-terminal kinase and p38MAPK signaling pathways. These results were confirmed by experiments evaluating the extent to which forced Kcnh6 expression rescued metabolic disorder in KO mice. In conclusion, KCNH6 enhanced hepatic glucose metabolism by regulating mitochondrial Ca2+ levels and inhibiting oxidative stress. As liver glucose metabolism is key to T2D, understanding KCNH6 functions may provide new insights into the causes of diabetes.

The cAMP-PKA signalling pathway regulates hyphal growth, conidiation, trap morphogenesis, stress tolerance, and autophagy in Arthrobotrys oligospora.

The cyclic adenosine monophosphate-protein kinase A (cAMP-PKA) signalling pathway is evolutionarily conserved in eukaryotes and plays a crucial role in defending against external environmental challenges, which can modulate the cellular response to external stimuli. Arthrobotrys oligospora is a typical nematode-trapping fungus that specializes in adhesive networks to kill nematodes. To elucidate the biological roles of the cAMP-PKA signalling pathway, we characterized the orthologous adenylate cyclase AoAcy, a regulatory subunit (AoPkaR), and two catalytic subunits (AoPkaC1 and AoPkaC2) of PKA in A. oligospora by gene disruption, transcriptome, and metabolome analyses. Deletion of Aoacy significantly reduced the levels of cAMP and arthrobotrisins. Results revealed that Aoacy, AopkaR, and AopkaC1 were involved in hyphal growth, trap morphogenesis, sporulation, stress resistance, and autophagy. In addition, Aoacy and AopkaC1 were involved in the regulation of mitochondrial morphology, thereby affecting energy metabolism, whereas AopkaC2 affected sporulation, nuclei, and autophagy. Multi-omics results showed that the cAMP-PKA signalling pathway regulated multiple metabolic and cellular processes. Collectively, these data highlight the indispensable role of cAMP-PKA signalling pathway in the growth, development, and pathogenicity of A. oligospora, and provide insights into the regulatory mechanisms of signalling pathways in sporulation, trap formation, and lifestyle transition.

Early-onset diabetes involving three consecutive generations had different clinical features from age-matched type 2 diabetes without a family history in China.

PURPOSE: Early-onset, multigenerational diabetes is a heterogeneous disease, which is often simplistically classified as type 1 diabetes (T1D) or type 2 diabetes(T2D). However, its clinical and genetic characteristics have not been clearly elucidated. The aim of our study is to investigate the clinical features of early-onset diabetes involving three consecutive generations (eDia3) in a Chinese diabetes cohort. METHODS: Of 6470 type 2 diabetic patients, 105 were identified as eDia3 (1.6%). After a case-control match on age, we compared the clinical characteristics of 89 eDia3 patients with 89 early-onset T2D patients without a family history of diabetes (eDia0). WES was carried out in 89 patients with eDia3. We primarily focused on 14 known maturity-onset diabetes of the young (MODY) genes. Variants were predicted by ten tools (SIFT, PolyPhen2_HDIV, PolyPhen2_HVAR, LRT, Mutation Assessor, Mutation Taster, FATHMM, GERP++, PhyloP, and PhastCons). All suspected variants were then validated by Sanger sequencing and further investigated in the proband families. RESULTS: Compared to age-matched eDia0, eDia3 patients had a younger age at diagnosis (26.5 ± 5.8 vs. 29.4 ± 5.3 years, P = 0.001), lower body mass index (25.5 ± 3.9 vs. 27.4 ± 4.6 kg/m2, P = 0.003), lower systolic blood pressure (120 ± 15 vs. 128 ± 18 mmHg, P = 0.003), and better metabolic profiles (including glucose and lipids). Of the 89 eDia3 patients, 10 (11.2%) carried likely pathogenic variants in genes (KLF11, GCK, ABCC8, PAX4, BLK and HNF1A) of MODY. CONCLUSIONS: eDia3 patients had unique clinical features. Known MODY genes were not common causes in these patients.

Diagnosing Diabetic Retinopathy in OCTA Images Based on Multilevel Information Fusion Using a Deep Learning Framework.

Objective: As an extension of optical coherence tomography (OCT), optical coherence tomographic angiography (OCTA) provides information on the blood flow status at the microlevel and is sensitive to changes in the fundus vessels. However, due to the distinct imaging mechanism of OCTA, existing models, which are primarily used for analyzing fundus images, do not work well on OCTA images. Effectively extracting and analyzing the information in OCTA images remains challenging. To this end, a deep learning framework that fuses multilevel information in OCTA images is proposed in this study. The effectiveness of the proposed model was demonstrated in the task of diabetic retinopathy (DR) classification. Method: First, a U-Net-based segmentation model was proposed to label the boundaries of large retinal vessels and the foveal avascular zone (FAZ) in OCTA images. Then, we designed an isolated concatenated block (ICB) structure to extract and fuse information from the original OCTA images and segmentation results at different fusion levels. Results: The experiments were conducted on 301 OCTA images. Of these images, 244 were labeled by ophthalmologists as normal images, and 57 were labeled as DR images. An accuracy of 93.1% and a mean intersection over union (mIOU) of 77.1% were achieved using the proposed large vessel and FAZ segmentation model. In the ablation experiment with 6-fold validation, the proposed deep learning framework that combines the proposed isolated and concatenated convolution process significantly improved the DR diagnosis accuracy. Moreover, inputting the merged images of the original OCTA images and segmentation results further improved the model performance. Finally, a DR diagnosis accuracy of 88.1% (95%CI ± 3.6%) and an area under the curve (AUC) of 0.92 were achieved using our proposed classification model, which significantly outperforms the state-of-the-art classification models. As a comparison, an accuracy of 83.7 (95%CI ± 1.5%) and AUC of 0.76 were obtained using EfficientNet. Significance. The visualization results show that the FAZ and the vascular region close to the FAZ provide more information for the model than the farther surrounding area. Furthermore, this study demonstrates that a clinically sophisticated designed deep learning model is not only able to effectively assist in the diagnosis but also help to locate new indicators for certain illnesses.

Novel cleavage sites identified in SARS-CoV-2 spike protein reveal mechanism for cathepsin L-facilitated viral infection and treatment strategies.

The spike (S) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an important target for vaccine and drug development. However, the rapid emergence of variant strains with mutated S proteins has rendered many treatments ineffective. Cleavage of the S protein by host proteases is essential for viral infection. Here, we discovered that the S protein contains two previously unidentified Cathepsin L (CTSL) cleavage sites (CS-1 and CS-2). Both sites are highly conserved among all known SARS-CoV-2 variants. Our structural studies revealed that CTSL cleavage promoted S to adopt receptor-binding domain (RBD) "up" activated conformations, facilitating receptor-binding and membrane fusion. We confirmed that CTSL cleavage is essential during infection of all emerged SARS-CoV-2 variants (including the recently emerged Omicron variant) by pseudovirus (PsV) infection experiment. Furthermore, we found CTSL-specific inhibitors not only blocked infection of PsV/live virus in cells but also reduced live virus infection of ex vivo lung tissues of both human donors and human ACE2-transgenic mice. Finally, we showed that two CTSL-specific inhibitors exhibited excellent In vivo effects to prevent live virus infection in human ACE2-transgenic mice. Our work demonstrated that inhibition of CTSL cleavage of SARS-CoV-2 S protein is a promising approach for the development of future mutation-resistant therapy.

New-onset COVID-19-related diabetes: an early indicator of multi-organ injury and mortally of SARS-CoV-2 infection.

Objective: The pandemic of 2019 coronavirus (SARS-CoV-2) disease (COVID-19) has imposed a severe public health burden worldwide. Most patients with COVID-19 were mild. Severe patients progressed rapidly to critical condition including acute respiratory distress syndrome (ARDS), multi-organ failure and even death. This study aims to find early multi-organ injury indicators and blood glucose for predicting mortality of COVID-19. Methods: Fasting blood glucose (FBG) ≥7.0 mmol/L for two times during hospitalization and without a history of diabetes were defined as new-onset COVID-19-related diabetes (CRD). Indicators of injuries for multiple organs, including the lung, heart, kidney and liver, and glucose homeostasis were specifically analyzed for predicting death. Results: A total of 120 patients with a severity equal to or greater than Moderate were hospitalized. After excluding patients with history of diabetes, chronic heart, kidney, and liver disease, 69 patients were included in the final analysis. Of the 69 patients, 23 were Moderate, 20 were Severe, and 26 were Critical (including 16 deceased patients). Univariable analysis indicated that CRD, lactate dehydrogenase (LDH), hydroxybutyrate dehydrogenase (HBDH), creatine kinase (CK) and creatinine (Cr) were associated with death. Multivariable analysis indicated that CRD was an independent predictor for death (HR = 3.75, 95% CI 1.26-11.15). Abnormal glucose homeostasis or CRD occurred earlier than other indicators for predicting poor outcomes. Indicators of multiple organ injury were in parallel with the expression patterns of ACE2 (the SARS-CoV-2 receptor) in different organs including pancreatic islet. Conclusions: New-onset COVID-19-related diabetes is an early indicator of multi-organ injury and predictor for poor outcomes and death in COVID-19 patients. As it is easy to perform for clinical practices and self-monitoring, glucose testing will be helpful for predicting poor outcomes to facilitate appropriate intensive care.

A high TSH level is associated with diabetic macular edema: a cross-sectional study of patients with type 2 diabetes mellitus.

Aims: In this study, we determined the association between thyroid-stimulating hormone (TSH) and diabetic macular edema (DME) by assessing the prevalence and risk factors for DME in type 2 diabetes mellitus (T2DM) patients with different thyroid dysfunctions. Methods: This was a retrospective cross-sectional study including 1003 euthyroid and 92 subclinical hypothyroidism (SCH) T2DM patients. DME status was detected by optical coherence tomography (OCT). The association between TSH and DME and the impact of TSH on DME were analyzed. Results: The DME prevalence was 28.3% in the SCH patients and 14.0% in the euthyroid population. The serum FT4 (P = 0.001) and FT3 (P < 0.001) levels were significantly higher in the non-DME group than in the DME group, and the TSH level (P < 0.001) was significantly lower. Four subgroups (G1-G4) were divided by TSH level, and the chi-square test indicated that even in the normal range, the TSH level was positively related to DME prevalence (P = 0.001). Subgroup data indicated that the association between TSH and DME detected by OCT (P = 0.001) was stronger than the correlation between TSH and diabetic retinopathy detected by digital retinal photographs (P = 0.027). The logistic regression model confirmed that elevated TSH was an independent risk factor for DME. The odds ratio was 1.53 (P = 0.02). Conclusions: A high TSH level was an independent risk factor for DME. More attention should be given to the TSH level in T2DM patients due to its relationship with diabetic complications.

ß-Klotho promotes glycolysis and glucose-stimulated insulin secretion via GP130.

Impaired glucose-stimulated insulin secretion (GSIS) is a hallmark of type-2 diabetes. However, cellular signaling machineries that control GSIS remain incompletely understood. Here, we report that ß-klotho (KLB), a single-pass transmembrane protein known as a co-receptor for fibroblast growth factor 21 (FGF21), fine tunes GSIS via modulation of glycolysis in pancreatic ß-cells independent of the actions of FGF21. ß-cell-specific deletion of Klb but not Fgf21 deletion causes defective GSIS and glucose intolerance in mice and defective GSIS in islets of type-2 diabetic mice is mitigated by adenovirus-mediated restoration of KLB. Mechanistically, KLB interacts with and stabilizes the cytokine receptor subunit GP130 by blockage of ubiquitin-dependent lysosomal degradation, thereby facilitating interleukin-6-evoked STAT3-HIF1α signaling, which in turn transactivates a cluster of glycolytic genes for adenosine triphosphate production and GSIS. The defective glycolysis and GSIS in Klb-deficient islets are rescued by adenovirus-mediated replenishment of STAT3 or HIF1α. Thus, KLB functions as a key cell-surface regulator of GSIS by coupling the GP130 receptor signaling to glucose catabolism in ß-cells and represents a promising therapeutic target for diabetes.