De novo loss-of-function KCNMA1 variants are associated with a new multiple malformation syndrome and a broad spectrum of developmental and neurological phenotypes.

KCNMA1 encodes the large-conductance Ca2+- and voltage-activated K+ (BK) potassium channel α-subunit, and pathogenic gain-of-function variants in this gene have been associated with a dominant form of generalized epilepsy and paroxysmal dyskinesia. Here, we genetically and functionally characterize eight novel loss-of-function (LoF) variants of KCNMA1. Genome or exome sequencing and the participation in the international Matchmaker Exchange effort allowed for the identification of novel KCNMA1 variants. Patch clamping was used to assess functionality of mutant BK channels. The KCNMA1 variants p.(Ser351Tyr), p.(Gly356Arg), p.(Gly375Arg), p.(Asn449fs) and p.(Ile663Val) abolished the BK current, whereas p.(Cys413Tyr) and p.(Pro805Leu) reduced the BK current amplitude and shifted the activation curves toward positive potentials. The p.(Asp984Asn) variant reduced the current amplitude without affecting kinetics. A phenotypic analysis of the patients carrying the recurrent p.(Gly375Arg) de novo missense LoF variant revealed a novel syndromic neurodevelopmental disorder associated with severe developmental delay, visceral and cardiac malformations, connective tissue presentations with arterial involvement, bone dysplasia and characteristic dysmorphic features. Patients with other LoF variants presented with neurological and developmental symptoms including developmental delay, intellectual disability, ataxia, axial hypotonia, cerebral atrophy and speech delay/apraxia/dysarthria. Therefore, LoF KCNMA1 variants are associated with a new syndrome characterized by a broad spectrum of neurological phenotypes and developmental disorders. LoF variants of KCNMA1 cause a new syndrome distinctly different from gain-of-function variants in the same gene.

Ubiquitination-activating enzymes UBE1 and UBA6 regulate ubiquitination and expression of cardiac sodium channel Nav1.5.

Cardiac sodium channel Nav1.5 is associated with cardiac arrhythmias and heart failure. Protein ubiquitination is catalyzed by an E1-E2-E3 cascade of enzymes. However, the E1 enzyme catalyzing Nav1.5 ubiquitination is unknown. Here, we show that UBE1 and UBA6 are two E1 enzymes regulating Nav1.5 ubiquitination and expression. Western blot analysis and patch-clamping recordings showed that overexpression of UBE1 or UBA6 increased the ubiquitination of Nav1.5 and significantly reduced Nav1.5 expression and sodium current density, and knockdown of UBE1 or UBA6 expression significantly increased Nav1.5 expression and sodium current density in HEK293/Nav1.5 cells. Similar results were obtained in neonatal cardiomyocytes. Bioinformatic analysis predicted two ubiquitination sites at K590 and K591. Mutations of K590 and K591 to K590A and K591A abolished the effects of overexpression or knockdown of UBE1 or UBA6 on Nav1.5 expression and sodium current density. Western blot analysis showed that the effects of UBE1 or UBA6 overexpression on the ubiquitination and expression of Nav1.5 were abolished by knockdown of UBC9, a putative E2 enzyme reported for Nav1.5 ubiquitination by us. Interestingly, real-time RT-PCR analysis showed that the expression level of UBE1, but not UBA6, was significantly up-regulated in ventricular tissues from heart failure patients. These data establish UBE1 and UBA6 as the E1 enzymes involved in Nav1.5 ubiquitination, and suggest that UBE1 and UBA6 regulate ubiquitination of Nav1.5 through UBC9. Our study is the first to reveal the regulatory role of the UBE1 or UBA6 E1 enzyme in the ubiquitination of an ion channel and links UBE1 up-regulation to heart failure.

UBC9 regulates cardiac sodium channel Nav1.5 ubiquitination, degradation and sodium current density.

Voltage-gated sodium channel Nav1.5 is critical for generation and conduction of cardiac action potentials. Mutations and expression level changes of Nav1.5 are associated with cardiac arrhythmias and sudden death. The ubiquitin (Ub) conjugation machinery utilizes three enzyme activities, E1, E2, and E3, to regulate protein degradation. Previous studies from us and others showed that Nedd4-2 acts as an E3 ubiquitin-protein ligase involved in ubiquitination and degradation of Nav1.5, however, more key regulators remain to be identified. In this study, we show that UBC9, a SUMO-conjugating enzyme, regulates ubiquitination and degradation of Nav1.5. Overexpression of UBC9 significantly decreased Nav1.5 expression and reduced sodium current densities, whereas knockdown of UBC9 expression significantly enhanced Nav1.5 expression and increased sodium current densities, in both HEK293 cells and primary neonatal cardiomyocytes. Overexpression of UBC9 increased ubiquitination of Nav1.5, and proteasome inhibitor MG132 blocked the effect of UBC9 overexpression on Nav1.5 degradation. Co-immunoprecipitation showed that UBC9 interacts with Nedd4-2. UBC9 with mutation C93S, which suppresses SUMO-conjugating activity of UBC9, was as active as wild type UBC9 in regulating Nav1.5 levels, suggesting that UBC9 regulates Nav1.5 expression levels in a SUMOylation-independent manner. Our findings thus identify a key structural element of the ubiquitin-conjugation machinery for Nav1.5 and provide important insights into the regulatory mechanism for ubiquitination and turnover of Nav1.5.

Mechanistic insights into the interaction of the MOG1 protein with the cardiac sodium channel Nav1.5 clarify the molecular basis of Brugada syndrome.

Nav1.5 is the α-subunit of the cardiac sodium channel complex. Abnormal expression of Nav1.5 on the cell surface because of mutations that disrupt Nav1.5 trafficking causes Brugada syndrome (BrS), sick sinus syndrome (SSS), cardiac conduction disease, dilated cardiomyopathy, and sudden infant death syndrome. We and others previously reported that Ran-binding protein MOG1 (MOG1), a small protein that interacts with Nav1.5, promotes Nav1.5 intracellular trafficking to plasma membranes and that a substitution in MOG1, E83D, causes BrS. However, the molecular basis for the MOG1/Nav1.5 interaction and how the E83D substitution causes BrS remains unknown. Here, we assessed the effects of defined MOG1 deletions and alanine-scanning substitutions on MOG1's interaction with Nav1.5. Large deletion analysis mapped the MOG1 domain required for the interaction with Nav1.5 to the region spanning amino acids 146-174, and a refined deletion analysis further narrowed this domain to amino acids 146-155. Site-directed mutagenesis further revealed that Asp-148, Arg-150, and Ser-151 cluster in a peptide loop essential for binding to Nav1.5. GST pulldown and electrophysiological analyses disclosed that the substitutions E83D, D148Q, R150Q, and S151Q disrupt MOG1's interaction with Nav1.5 and significantly reduce its trafficking to the cell surface. Examination of MOG1's 3D structure revealed that Glu-83 and the loop containing Asp-148, Arg-150, and Ser-151 are spatially proximal, suggesting that these residues form a critical binding site for Nav1.5. In conclusion, our findings identify the structural elements in MOG1 that are crucial for its interaction with Nav1.5 and improve our understanding of how the E83D substitution causes BrS.

14-3-3ε/YWHAE regulates the transcriptional expression of cardiac sodium channel NaV1.5.

BACKGROUND: Cardiac voltage-gated sodium channel alpha subunit 5 (NaV1.5) encoded by SCN5A is associated with arrhythmia disorders. However, the molecular mechanism underlying NaV1.5 expression remains to be fully elucidated. Previous studies have reported that the 14-3-3 family acts as an adaptor involved in regulating kinetic characteristics of cardiac ion channels. OBJECTIVE: The purpose of this study was to establish 14-3-3ε/YWHAE, a member of the 14-3-3 family, as a crucial regulator of NaV1.5 and to explore the potential role of 14-3-3ε in the heart. METHODS: Western blotting, patch clamping, real-time reverse transcription-polymerase chain reaction, RNA immunoprecipitation, electrocardiogram recording, echocardiography, and histologic analysis were performed. RESULTS: YWHAE overexpression significantly reduced the expression level of SCN5A mRNA and sodium current density, whereas YWHAE knockdown significantly increased SCN5A mRNA expression and sodium current density in HEK293/NaV1.5 and H9c2 cells. Similar results were observed in mice injected with adeno-associated virus serotype 9-mediated YWHAE knockdown. The effect of 14-3-3ε on NaV1.5 expression was abrogated by knockdown of TBX5, a transcription factor of NaV1.5. An interaction between 14-3-3ε protein and TBX5 mRNA was identified, and YWHAE overexpression significantly decreased TBX5 mRNA stability without affecting SCN5A mRNA stability. In addition, mice subjected to adeno-associated virus serotype 9-mediated YWHAE knockdown exhibited shorter R-R intervals and higher prevalence of premature ventricular contractions. CONCLUSION: Our data unveil a novel regulatory mechanism of NaV1.5 by 14-3-3ε and highlight the significance of 14-3-3ε in transcriptional regulation of NaV1.5 expression and cardiac arrhythmias.

Immune Cell Infiltration Analysis Based on Bioinformatics Reveals Novel Biomarkers of Coronary Artery Disease.

Background: Coronary artery disease (CAD) is a multifactorial immune disease, but research into the specific immune mechanism is still needed. The present study aimed to identify novel immune-related markers of CAD. Methods: Three CAD-related datasets (GSE12288, GSE98583, GSE113079) were downloaded from the Gene Expression Integrated Database. Gene ontology annotation, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis and weighted gene co-expression network analysis were performed on the common significantly differentially expressed genes (DEGs) of these three data sets, and the most relevant module genes for CAD obtained. The immune cell infiltration of module genes was evaluated with the CIBERSORT algorithm, and characteristic genes accompanied by their diagnostic effectiveness were screened by the machine-learning algorithm least absolute shrinkage and selection operator (LASSO) regression analysis. The expression levels of characteristic genes were evaluated in the peripheral blood mononuclear cells of CAD patients and healthy controls for verification. Results: A total of 204 upregulated and 339 downregulated DEGs were identified, which were mainly enriched in the following pathways: "Apoptosis", "Th17 cell differentiation", "Th1 and Th2 cell differentiation", "Glycerolipid metabolism", and "Fat digestion and absorption". Five characteristic genes, LMAN1L, DOK4, CHFR, CEL and CCDC28A, were identified by LASSO analysis, and the results of the immune cell infiltration analysis indicated that the proportion of immune infiltrating cells (activated CD8 T cells and CD56 DIM natural killer cells) in the CAD group was lower than that in the control group. The expressions of CHFR, CEL and CCDC28A in the peripheral blood of the healthy controls and CAD patients were significantly different. Conclusion: We identified CHFR, CEL and CCDC28A as potential biomarkers related to immune infiltration in CAD based on public data sets and clinical samples. This finding will contribute to providing a potential target for early noninvasive diagnosis and immunotherapy of CAD.

Comprehensive Analysis of circRNA-miRNA-mRNA Regulatory Network and Novel Potential Biomarkers in Acute Myocardial Infarction.

Background: Circular RNA (circRNA) plays an important role in the regulation of gene expression and the occurrence of human diseases. However, studies on the role of circRNA in acute myocardial infarction (AMI) are limited. This study was performed to explore novel circRNA-related regulatory networks in AMI, aiming to better understand the molecular mechanism of circRNAs involvement in AMI and provide basis for further scientific research and clinical decision-making. Methods: The AMI-related microarray datasets GSE160717 (circRNA), GSE31568 (miRNA), GSE61741 (miRNA), and GSE24519 (mRNA) were obtained from the Gene Expression Omnibus (GEO) database. After differential expression analysis, the regulatory relationships between these DERNAs were identified by online databases circBank, circInteractome, miRDB, miRWalk, Targetscan, and then two circRNA-miRNA-mRNA regulatory networks were constructed. Differentially expressed genes (DEGs) in this network were selected followed by enrichment analysis and protein-protein interaction (PPI) analysis. Hub genes were identified using Cytohubba plug-in of Cytoscape software. Hub genes and hub gene-related miRNAs were used for receiver operating characteristic curve (ROC) analysis to identify potential biomarkers. The relative expression levels of these biomarkers were further assessed by GSE31568 (miRNA) and GSE66360 (mRNA). Finally, on the basis of the above analysis, myocardial hypoxia model was constructed to verify the expression of Hub genes and related circRNAs. Results: A total of 83 DEcircRNAs, 109 CoDEmiRNAs and 1204 DEGs were significantly differentially expressed in these datasets. The up-regulated circRNAs and down-regulated circRNAs were used to construct a circRNA-miRNA-mRNA regulatory network respectively. These circRNA-related DEGs were mainly enriched in the terms of "FOXO signaling pathway," "T cell receptor signaling pathway," "MAPK signaling pathway," "Insulin resistance," "cAMP signaling pathway," and "mTOR signaling pathway." The top 10 hub genes ATP2B2, KCNA1, GRIN2A, SCN2B, GPM6A, CACNA1E, HDAC2, SRSF1, ANK2, and HNRNPA2B1 were identified from the PPI network. Hub genes GPM6A, SRSF1, ANK2 and hub gene-related circRNAs hsa_circ_0023461, hsa_circ_0004561, hsa_circ_0001147, hsa_circ_0004771, hsa_circ_0061276, and hsa_circ_0045519 were identified as potential biomarkers in AMI. Conclusion: In this study, the potential circRNAs associated with AMI were identified and two circRNA-miRNA-mRNA regulatory networks were constructed. This study explored the mechanism of circRNA involvement in AMI and provided new clues for the selection of new diagnostic markers and therapeutic targets for AMI.

Expression pattern and diagnostic value of ferroptosis-related genes in acute myocardial infarction.

Background: Ferroptosis is a form of regulatory cell death (RCD) caused by iron-dependent lipid peroxidation. The role of ferroptosis in the process of acute myocardial infarction (AMI) is still unclear and requires further study. Therefore, it is helpful to identify ferroptosis related genes (FRGs) involved in AMI and explore their expression patterns and molecular mechanisms. Methods: The AMI-related microarray datasets GSE66360 and GSE61144 were obtained using the Gene Expression Omnibus (GEO) online database. GO annotation, KEGG pathway enrichment analysis and Protein-protein interaction (PPI) analysis were performed for the common significant differential expression genes (CoDEGs) in these two datasets. The FRGs were obtained from the FerrDb V2 and the differentially expressed FRGs were used to identify potential biomarkers by receiver operating characteristic (ROC) analysis. The expression of these FRGs was verified using external dataset GSE60993 and GSE775. Finally, the expression of these FRGs was further verified in myocardial hypoxia model. Results: A total of 131 CoDEGs were identified and these genes were mainly enriched in the pathways of "inflammatory response," "immune response," "plasma membrane," "receptor activity," "protein homodimerization activity," "calcium ion binding," "Phagosome," "Cytokine-cytokine receptor interaction," and "Toll-like receptor signaling pathway." The top 7 hub genes ITGAM, S100A12, S100A9, TLR2, TLR4, TLR8, and TREM1 were identified from the PPI network. 45 and 14 FRGs were identified in GSE66360 and GSE61144, respectively. FRGs ACSL1, ATG7, CAMKK2, GABARAPL1, KDM6B, LAMP2, PANX2, PGD, PTEN, SAT1, STAT3, TLR4, and ZFP36 were significantly differentially expressed in external dataset GSE60993 with AUC ≥ 0.7. Finally, ALOX5, CAMKK2, KDM6B, LAMP2, PTEN, PTGS2, and ULK1 were identified as biomarkers of AMI based on the time-gradient transcriptome dataset of AMI mice and the cellular hypoxia model. Conclusion: In this study, based on the existing datasets, we identified differentially expressed FRGs in blood samples from patients with AMI and further validated these FRGs in the mouse time-gradient transcriptome dataset of AMI and the cellular hypoxia model. This study explored the expression pattern and molecular mechanism of FRGs in AMI, providing a basis for the accurate diagnosis of AMI and the selection of new therapeutic targets.

Small GTPases SAR1A and SAR1B regulate the trafficking of the cardiac sodium channel Nav1.5.

BACKGROUND: The cardiac sodium channel Nav1.5 is essential for the physiological function of the heart and causes cardiac arrhythmias and sudden death when mutated. Many disease-causing mutations in Nav1.5 cause defects in protein trafficking, a cellular process critical to the targeting of Nav1.5 to cell surface. However, the molecular mechanisms underlying the trafficking of Nav1.5, in particular, the exit from the endoplasmic reticulum (ER) for cell surface trafficking, remain poorly understood. METHODS AND RESULTS: Here we investigated the role of the SAR1 GTPases in trafficking of Nav1.5. Overexpression of dominant-negative mutant SAR1A (T39N or H79G) or SAR1B (T39N or H79G) significantly reduces the expression level of Nav1.5 on cell surface, and decreases the peak sodium current density (INa) in HEK/Nav1.5 cells and neonatal rat cardiomyocytes. Simultaneous knockdown of SAR1A and SAR1B expression by siRNAs significantly reduces the INa density, whereas single knockdown of either SAR1A or SAR1B has minimal effect. Computer modeling showed that the three-dimensional structure of SAR1 is similar to RAN. RAN was reported to interact with MOG1, a small protein involved in regulation of the ER exit of Nav1.5. Co-immunoprecipitation showed that SAR1A or SAR1B interacted with MOG1. Interestingly, knockdown of SAR1A and SAR1B expression abolished the MOG1-mediated increases in both cell surface trafficking of Nav1.5 and the density of INa. CONCLUSIONS: These data suggest that SAR1A and SAR1B are the critical regulators of trafficking of Nav1.5. Moreover, SAR1A and SAR1B interact with MOG1, and are required for MOG1-mediated cell surface expression and function of Nav1.5.