A novel gene in early childhood diabetes: EDEM2 silencing decreases SLC2A2 and PXD1 expression, leading to impaired insulin secretion

XBP1s-EDEM2 Prevents the Onset and Development of HFpEF by Ameliorating Cardiac Lipotoxicity

BACKGROUND

Morbidity and mortality of heart failure with preserved ejection fraction (HFpEF) is increased in metabolic disorders. However, options for preventing and treating these prevalent outcomes are limited. Intramyocardial lipotoxicity contributes to cardiac dysfunction. Here, we investigate the mechanisms underlying endoplasmic reticulum degradation enhancing EDEM2 (endoplasmic reticulum degradation-enhancing alpha-mannosidase-like protein 2) regulation of cardiac lipid homeostasis and assess strategies that inhibit the incidence and progression of HFpEF.

METHODS

Metabolic stress was induced in C57BL/6 male mice using a high-fat diet and Nω-nitro-l-arginine methyl ester. The recombinant adeno-associated virus 9 delivery system was used for loss- and gain-of-function studies. Palmitic acid and oleic acid stimulation of rat cardiomyocytes and human induced pluripotent stem cell-derived cardiomyocytes imitated a condition of high lipids in vitro. Molecular mechanisms were investigated via RNA sequencing, mass spectrometry proteomics, lipidomic analyses, transmission electron microscopy, histology, and luciferase reporter assays.

RESULTS

In the human heart, we first detected lipid overload accompanied by a reduction of XBP1 (X-box binding protein 1) under metabolic stress. Thereafter, a decrease in EDEM2 was confirmed in human and mouse HFpEF hearts. Given that the spliced form of XBP1 (XBP1s) is a transcription factor, EDEM2 was identified as its new target in cardiomyocytes. EDEM2 knockdown mice manifested lipid droplet accumulation and higher levels of triglycerides and diglycerides in the myocardium, aggravating oxidative stress, hypertrophy, and the onset and progression of HFpEF under metabolic stress. XBP1s ablation mice displayed a similar myocardial lipid disturbance and cardiac phenotypes, which were reversed by EDEM2 overexpression. Mechanistically, the findings obtained from rat cardiomyocytes and human induced pluripotent stem cell-derived cardiomyocytes demonstrated that, in the presence of EDEM2, SEC23A mediated intracellular translocation of ATGL (adipose triglyceride lipase) under fatty acid stimulation, inhibiting ATGL degradation and excessive intracellular lipid droplets. Furthermore, the functional studies supported that EDEM2 prevention of lipid overload occurred in an ATGL-dependent manner. Therapeutically, cardiac XBP1s or EDEM2 restoration mitigated lipid deposition and preserved lipid profiles in the myocardium, thus preventing the development of HFpEF.

CONCLUSIONS

We demonstrate a cardioprotective mechanism regulating myocardial lipid homeostasis. The findings provide a promising therapeutic target to prevent and treat HfpEF, a condition with limited treatment options.

Genetic Influence of the Brain on Muscle Structure: A Mendelian Randomization Study of Sarcopenia

BACKGROUND

The association between brain and sarcopenia has not been clarified. We aim to investigate the causal association between brain structure, function, gene expression and sarcopenia-related traits.

METHODS

All participants were Europeans. GWAS data of Brain Imaging Data Structure (BIDs) was from the UK Biobank. Gene expression in 13 brain regions was acquired from the GTEx Consortium. The sarcopenia-related traits, including appendicular lean mass (ALM), whole body lean mass (WBLM), grip strength and sarcopenia diagnosed by the European Working Group on Sarcopenia in Older People (EWGSOP) or Foundation for the National Institutes of Health (FNIH), were from the IEU website. The inverse variance weighted (IVW), MR Egger, weighted median, weighted mode and Wald ratio methods were used for a two-sample Mendelian randomization (MR) analysis between brain structures and sarcopenia-related traits. The summary-data-based MR (SMR) was used to investigate brain genes causally influencing sarcopenia. We calculated the F-value, odds ratio with 95% CI and p-value. For the sensitivity analysis, the heterogeneity I2 statistic, Cochrane's Q test, Egger's intercept test, MR-PRESSO and the leave-one-out sensitivity test were used. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, protein-protein interaction (PPI), transcription factor interaction prediction and miRNA interaction prediction analysis were used to reveal potential signalling pathways and mechanisms.

RESULTS

We included 3144 imaging phenotypes from 8428 participants in BIDs data. One hundred forty-one BIDs were identified to causally influence ALM, 160 BIDs showed significant causal effect on the WBLM, and 86 BIDs showed significant causal effect on grip strength. There were 48 or 32 BIDs causally associated with sarcopenia diagnosed by the EWGSOP or FNIH criteria respectively. After FDR correction, there were 35 BIDs showing causal effect on the ALM, 28 BIDs showing causal effect on the WBLM and 7 BIDs showing causal effect on grip strength (p < 0.05). Twelve to forty-eight genes in different brain regions showed causal effect on all the five sarcopenia-related traits. MMP24-AS1, HLA-DRB6, HLA-DQA2, DDX42, BAG6, NUSAP1, LINC00940, NME1-NME2 and AS3MT in the amygdala region showed detrimental effect on all the five sarcopenia-related traits, whereas HLA-DRB1, HLA-DQB1-AS1 and C6ORF3 showed protective effect (p < 0.05). The gene enrichment analysis indicated these screened genes was mainly enriched in immune-related signalling.

CONCLUSION

We discovered the causal effect of BIDs and brain gene expression on sarcopenia. The positive genes were mainly enriched in immune-related signalling, suggesting an immune-based cross-organ regulation mechanism of brain-muscle axis.

EDEM2 is a diagnostic and prognostic biomarker and associated with immune infiltration in glioma: A comprehensive analysis

Glioma is a highly common pathological brain tumor. Misfolded protein response, which is strongly associated with the growth of cancerous tumors, is mediated by the gene, endoplasmic reticulum degradation-enhancing alpha-mannosidase-like protein 2. However, this gene has not been linked to glioma. To assess the same, we used The Cancer Genome Atlas, Chinese Glioma Genome Atlas, and Genotype-Tissue Expression datasets. The gene was overexpressed in gliomas. This overexpression was linked to unfavorable clinical characteristics, such as the World Health Organization grade, isocitrate dehydrogenase mutation, and the combined loss of the short arm chromosome 1 and the long arm of chromosome 19. Quantitative polymerase chain reaction experiments and immunohistochemistry on clinical samples from our institution verified the gene's expression and clinical importance. The Human Protein Atlas website verified the messenger ribonucleic acid expression of the gene in glioma cell lines, and immunohistochemistry verified the presence of its protein. A previous survival study indicated that its high expression is substantially related to a bad prognosis. It was identified as an independent predictor of primary glioma prognosis using multivariate Cox regression analysis. To forecast individual survival, we created a nomogram based on this (concordance-index = 0.847). Additionally, functional annotation demonstrated its major role in the control of the extracellular matrix and immune system. The scratch assay and transwell migration assay confirmed the decreased invasive ability of U251 glioma cells with the gene knockdown. Its increased expression was found to be related to the extent of macrophage infiltration using the CIBERSORT, ESTIMATE, Single-sample Gene Set Enrichment Analysis, and Tumor Immune Single-Cell Hub (TISCH) algorithms. The Tumor Immune Dysfunction and Exclusion algorithm revealed that the gene can accurately predict the response of immunotherapy (area under the receiver operating characteristic curve = 0.857). Further, isocitrate dehydrogenase 1 mutation is typically more frequent when the gene expression is high. Finally, five medicines targeting this gene were discovered utilizing the molecular docking program and drug sensitivity analysis of the RNAactDrug website. Low expression of the gene inhibited glioma cell invasion. Therefore, the gene is helpful for the diagnosis, prognosis, and case-specific immunotherapy of glioma.

Identification of biomarkers, pathways, and potential therapeutic targets for heart failure using next-generation sequencing data and bioinformatics analysis

BACKGROUND

Heart failure (HF) is the most common cardiovascular diseases and the leading cause of cardiovascular diseases related deaths. Increasing molecular targets have been discovered for HF prognosis and therapy. However, there is still an urgent need to identify novel biomarkers. Therefore, we evaluated biomarkers that might aid the diagnosis and treatment of HF.

METHODS

We searched next-generation sequencing (NGS) dataset (GSE161472) and identified differentially expressed genes (DEGs) by comparing 47 HF samples and 37 normal control samples using limma in R package. Gene ontology (GO) and pathway enrichment analyses of the DEGs were performed using the g: Profiler database. The protein-protein interaction (PPI) network was plotted with Human Integrated Protein-Protein Interaction rEference (HiPPIE) and visualized using Cytoscape. Module analysis of the PPI network was done using PEWCC1. Then, miRNA-hub gene regulatory network and TF-hub gene regulatory network were constructed by Cytoscape software. Finally, we performed receiver operating characteristic (ROC) curve analysis to predict the diagnostic effectiveness of the hub genes.

RESULTS

A total of 930 DEGs, 464 upregulated genes and 466 downregulated genes, were identified in HF. GO and REACTOME pathway enrichment results showed that DEGs mainly enriched in localization, small molecule metabolic process, SARS-CoV infections, and the citric acid tricarboxylic acid (TCA) cycle and respiratory electron transport. After combining the results of the PPI network miRNA-hub gene regulatory network and TF-hub gene regulatory network, 10 hub genes were selected, including heat shock protein 90 alpha family class A member 1 (HSP90AA1), arrestin beta 2 (ARRB2), myosin heavy chain 9 (MYH9), heat shock protein 90 alpha family class B member 1 (HSP90AB1), filamin A (FLNA), epidermal growth factor receptor (EGFR), phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1), cullin 4A (CUL4A), YEATS domain containing 4 (YEATS4), and lysine acetyltransferase 2B (KAT2B).

CONCLUSIONS

This discovery-driven study might be useful to provide a novel insight into the diagnosis and treatment of HF. However, more experiments are needed in the future to investigate the functional roles of these genes in HF.

Highly perturbed genes and hub genes associated with type 2 diabetes in different tissues of adult humans: a bioinformatics analytic workflow

Type 2 diabetes (T2D) has a complex etiology which is not yet fully elucidated. The identification of gene perturbations and hub genes of T2D may deepen our understanding of its genetic basis. We aimed to identify highly perturbed genes and hub genes associated with T2D via an extensive bioinformatics analytic workflow consisting of five steps: systematic review of Gene Expression Omnibus and associated literature; identification and classification of differentially expressed genes (DEGs); identification of highly perturbed genes via meta-analysis; identification of hub genes via network analysis; and downstream analysis of highly perturbed genes and hub genes. Three meta-analytic strategies, random effects model, vote-counting approach, and p value combining approach, were applied. Hub genes were defined as those nodes having above-average betweenness, closeness, and degree in the network. Downstream analyses included gene ontologies, Kyoto Encyclopedia of Genes and Genomes pathways, metabolomics, COVID-19-related gene sets, and Genotype-Tissue Expression profiles. Analysis of 27 eligible microarrays identified 6284 DEGs (4592 downregulated and 1692 upregulated) in four tissue types. Tissue-specific gene expression was significantly greater than tissue non-specific (shared) gene expression. Analyses revealed 79 highly perturbed genes and 28 hub genes. Downstream analyses identified enrichments of shared genes with certain other diabetes phenotypes; insulin synthesis and action-related pathways and metabolomics; mechanistic associations with apoptosis and immunity-related pathways; COVID-19-related gene sets; and cell types demonstrating over- and under-expression of marker genes of T2D. Our approach provided valuable insights on T2D pathogenesis and pathophysiological manifestations. Broader utility of this pipeline beyond T2D is envisaged.

CRISPR/Cas9 ADCY7 Knockout Stimulates the Insulin Secretion Pathway Leading to Excessive Insulin Secretion

AIM

Despite the enormous efforts to understand Congenital hyperinsulinism (CHI), up to 50% of the patients are genetically unexplained. We aimed to functionally characterize a novel candidate gene in CHI.

PATIENT

A 4-month-old boy presented severe hyperinsulinemic hypoglycemia. A routine CHI genetic panel was negative.

METHODS

A trio-based whole-exome sequencing (WES) was performed. Gene knockout in the RIN-m cell line was established by CRISPR/Cas9. Gene expression was performed using real-time PCR.

RESULTS

Hyperinsulinemic hypoglycemia with diffuse beta-cell involvement was demonstrated in the patient, who was diazoxide-responsive. By WES, compound heterozygous variants were identified in the adenylyl cyclase 7, ADCY7 gene p.(Asp439Glu) and p.(Gly1045Arg). ADCY7 is calcium-sensitive, expressed in beta-cells and converts ATP to cAMP. The variants located in the cytoplasmic domains C1 and C2 in a highly conserved and functional amino acid region. RIN-m^(-/-Adcy7) cells showed a significant increase in insulin secretion reaching 54% at low, and 49% at high glucose concentrations, compared to wild-type. In genetic expression analysis Adcy7 loss of function led to a 34.1-fold to 362.8-fold increase in mRNA levels of the insulin regulator genes Ins1 and Ins2 (p ≤ 0.0002), as well as increased glucose uptake and sensing indicated by higher mRNA levels of Scl2a2 and Gck via upregulation of Pdx1, and Foxa2 leading to the activation of the glucose stimulated-insulin secretion (GSIS) pathway.

CONCLUSION

This study identified a novel candidate gene, ADCY7, to cause CHI via activation of the GSIS pathway.