研究背景：J 波综合征为一组心电图出现以J波为特征，同时伴随恶性心律失常的临床综合征，主要包含早期复极综合征和 Brugada综合征，其主要临床表现为多形性室速(ventricular tachycardia,VT)及室颤(ventricular fibrillation,VF)，均有发生严重心律失常甚至猝死的风险。JWS作为一种与健康成年人心搏骤停和心源性猝死(sudden cardiac death, SCD)密切相关的遗传性致心律失常性疾病，目前尚无根治手段。

研究目的: 本项目的总体目标是探索利用患者特异性iPSC，通过心肌细胞诱导分化的技术途径，获得与患者遗传特征一致、电生理特征接近的疾病细胞模型；在此基础上，探究SCN5A突变的致病机制，寻找潜在治疗靶点。

研究方法:建立J 波综合征病人特异性诱导多能干细胞，并进一步定向诱导分化为心肌细胞。通过构建编辑质粒并电转的方法，在患者特异性iPSC中修复SCN5A基因的突变位点。采用膜片钳电生理技术分析离子通道功能。采用单细胞转录组测序(scRNA-seq)的方法，检测 SCN5A基因突变患者 iPSC 来源的心肌细胞（iPSC-CMs）基因表达谱的变化。设计引物并测序，确定基因突变后转录本的改变，预测蛋白质的改变。

研究结果:基因测序发现SCN5A（exon3:c.392+5C>T）突变为本病的致病突变，且基因与表型共分离。与正常对照组相比，JWS患者来源的iPSC-CMs钠离子通道电流密度显著降低（P<0. 001），细胞外基质、心肌病等信号通路显著上调，心肌收缩通路显著下调。SCN5A（exon3:c.392+5C>T）突变导致exon3、exon4丢失，翻译提前终止，形成有92个氨基酸残基的肽段。

研究结论:SCN5A（exon3:c.392+5C>T）突变可导致J 波综合征的两种表型即Brugada综合征与早复极综合征，其致病性主要源于钠通道功能的丧失，并可能与心肌病、心肌收缩等信号通路密切相关。

Background：J wave syndrome (JWS) is a group of clinical syndromes characterized by J waves on electrocardiogram, accompanied by malignant arrhythmias, mainly including early repolarization syndrome (ERS) and Brugada syndrome (BrS). The main clinical manifestations of JWS are polymorphic ventricular tachycardia (VT) and ventricular fibrillation (VF). Clinical manifestations of JWS are associated with the life-threatening ventricular arrhythmias. The most sever outcome of JWS patients is sudden cardiac death (SCD). The risk of SCD is very low in patients with the ER model, with a meta-analysis showing a relative risk of idiopathic VF is 1.70 (95% CI 1.19-2.42) and an estimated absolute risk of idiopathic VF is 70 per 100,000 person-years. The risk of life-threatening arrhythmia is significantly higher in patients with BrS compared to those with ERS, and the risk of recurrence of VF is considerable: approximately 35% at 4 years, 44% at 7 years and 48% at 10 years. Although only a minority of currently diagnosed BrS patients (6% in Europe and 18% in Japan) have a history of cardiac arrest, unfortunately, for the majority of patients, the first symptom tends to be cardiac arrest or SCD, which makes interventions in patients with JWS of critical value. There is no definitive prevalence estimate for the hereditary JWS involved in studies of recent years. The two different forms of hereditary JWS, BrS and ERS, have similar pathophysiological mechanisms, and there is partial overlap in pathogenic mutations. Possible ion channel mechanisms include the repolarization and depolarization hypotheses: the repolarization hypothesis suggests that an outward shift of the current balance in the epicardium leads to repolarization abnormalities, leading to the onset of 2-phase refractoriness, which produces premature beats capable of inducing VT/VF; the depolarization hypothesis· suggests that conduction delays in the epicardium play a major role in the development of the electrocardiogram and arrhythmias in JWS. Although each of the two hypotheses has found some basic research and clinical evidence, however, the specific pathogenesis is yet to be further investigated. The only effective strategy for preventing SCD in high-risk ERS and BrS patients is implantation of implantable cardioverter-defibrillator (ICD). Implantation of an ICD is first-line treatment for patients with JWS presenting with aborted SCD or documented ventricular fibrillation or ventricular tachycardia, with or without syncope (Class I recommendation). However, at 10 years after implantation, the incidence of inappropriate shock and lead failure was 37% and 29%, respectively. Based on the pathophysiological mechanisms underlying the pathogenesis of JWS, pharmacological treatments based on the rebalancing of currents active in the early stages of the epicardial action potential in order to reduce the amplitude of the action potential cutoff and/or restore the dome have been the focus of research. Antiarrhythmic drugs such as amiodarone and β-blockers have been shown to be ineffective. Since the presence of significant Ito underlies the pathogenesis of JWS, partial inhibition of Ito currents is considered effective regardless of the ionic mechanism or genetic basis of the disease. However, there are no cardiac-specific Ito blockers available. Quinidine has an Ito blocking effect and can exert a protective effect against hypothermia-induced ventricular tachycardia/ventricular fibrillation in the J-wave syndrome model. However, the limited clinical therapies (ICD implantation and quinidine) have limitations: ICD implantation does not prevent arrhythmias and has side effects such as allergic reactions, infections, and inappropriate shocks; quinidine has potential cardiotoxicity, including arrhythmogenicity, conduction disturbances, hypotension, and congestive heart failure, as well as gastrointestinal and neurological side effects. Therefore, it is important to develop alternative therapeutic agents for J-wave syndrome and to construct a disease model for J-wave syndrome. We have a complete collection of a large J-wave syndrome family line. The antecedent was a 40-year-old man who survived multiple sudden cardiac deaths occurring suddenly one night after emergency treatment in an outside hospital. The patient's electrocardiogram on physical examination before sudden death as well as after the onset of symptoms suggested marked J waves in the inferior wall leads, J-point elevation, and a cut-off at the end of the QRS wave, and the patient was excluded from structural heart disease and diagnosed with premature repolarization syndrome. After obtaining informed consent, the team took medical history, physical examination, whole genome sequencing, and peripheral blood samples from the patient and family members for subsequent pluripotent stem cell induction culture. Investigations of the patient's family revealed significant aggregation of early repolarization (ER)-type ECGs and Brugada-like ECGs. Among 8 patients, 4 were ERS, 2 were BRS, 1 was ERS with BRS, and 1 was sudden cardiac death. The whole genome sequencing was adopted. The association between the gene mutation and the disease phenotype was evaluated. The suspected causative mutation in this study's family line is SCN5A (exon3: c.392+5C>T), which is a splicing mutation, located in a non-classical splice site, affects the splicing of pre-mRNAs, which may lead to the premature termination of protein translation, and has not been reported in databases or studies. In order to study the causative gene mutation of this JWS family line and the developmental mechanism, it is necessary to construct a cardiomyocyte model with the same genotype as the patient as the basis of the study, so as to provide a research platform for further research on the pathogenesis of JWS and therapeutic interventions.

Objectives: This study intends to establish a model of human cardiomyocytes of JWS by differentiating patient-specific iPSC lines into CMs. The effect and the pathogenesis of Nav1.5 (SCN5A) gene mutation in JWS will also be investigated by the multi-omics approach.

Methods: The reprogramming of peripheral blood mononuclear cells (PBMCs) from JWS patients into induced pluripotent stem cells (iPSCs) was followed by their differentiation into induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). The iPSCs underwent morphological analysis, karyotype testing, teratoma formation assessment, and stem cell gene expression profiling. iPSC-CMs were identified based on their morphological characteristics and cardiomyocyte-specific protein expression. By constructing the editing plasmid and electroporating, the mutation site of SCN5A gene was repaired in patient specific iPSCs, which were also differentiated into cardiomyocytes. The function of ion channels was analyzed by patch clamp electrophysiology. We applied microelectrode arrays to assess the electrophysiological and mechanical activity characteristics of cardiomyocytes at the multicellular level. First strand cDNA was synthesized, and second strand cDNA synthesis was subsequently performed. PCR reactions using sticky-end heat-stable DNA polymerase add an "A" to the 3' end of the PCR product, and T vectors are 3' vectors with a "T". T-vectors are 3' carriers with a "T" that are ligated by ligase and used for bacterial transformation. On the X-gal plate, bacteria containing positive recombinant are white colonies, and bacteria transformed with non-recombinant are blue colonies. According to this principle, the white colonies that grow after coating the plate contain the desired target gene fragment. The white colonies were selected and subjected to one-generation sequencing to obtain the new transcripts produced by the splicing mutation. Bulk RNA-seq was performed to detect the change of gene expression. We started with total RNA, which we used as a starting material for preparing the RNA sample. We purified mRNA from the total RNA using magnetic beads bound to poly-T oligos. We used the AMPure XP system to purify the library fragments. Then PCR was performed. At last, we purified the PCR products and checked the quality of the library. We used the DESeq2 R (1.20.0) software package to analyse the differences in expression between two groups. We adjusted the P-values according to the Benjamini and Hochberg approach to control the false discovery rate. We considered genes to be differentially expressed if their adjusted P-value according to DESeq2 was below 0.05. We also analyzed the changes of transcripts after gene mutation and predict the changes of protein. We used the clusterProfiler R package to do a GO enrichment analysis of the genes that were differentially expressed. This package corrects for gene length bias, which is really important. We were really excited to see which GO terms were significantly enriched by the differential expressed genes. We used the clusterProfiler R package to test whether the genes that were different in expression were also different in pathways. We considered Reactome pathways with a corrected P-value of less than 0.05 to be significantly enriched by differential expressed genes. We then looked at pathways with a corrected P-value of less than 0.05 to see if they were significantly enriched by the differentially expressed genes. We also looked at pathways from DisGeNET, and if the corrected P-value was less than 0.05, we considered them to be significantly enriched by the differential expressed genes. We used clusterProfiler software to test the statistical enrichment of differentially expressed genes in the Reactome pathway, the DO pathway, and the DisGeNET pathway. We use the local version of the GSEA analysis tool, GO、KEGG、Reactome、DO and DisGeNET data sets were used for GSEA independently. We performed single-cell transcriptome sequencing analysis using 8000 cells each from iPSC-CMs samples from the disease group, and samples from the healthy control group, and performed GO, KEGG enrichment analysis and GSEA analysis on the differential gene set. The samples were made into single-cell suspensions. Cell counts and cell viability were determined using a cell counter with cell activity higher than 90%, and the cell concentration was adjusted to the ideal concentration of 300-600 cells/μL. The prepared single-cell suspensions were combined with a mixture of gel beads containing barcode information and enzymes, and then encapsulated by oil droplets located in microfluidic "single-cross" junctions to form GEMs, and the validated GEMs contained gel beads (with pre-made 10x primers). Cell lysis and reverse transcription are then carried out in the GEMs and the 10x Barcode is ligated to the cDNA product in the validated GEMs. The GEMs are then crushed, and the oil droplets are broken up and the cDNA is used as a template for PCR amplification. cDNA amplification is completed, and the amplified product is subjected to quality control. In order to deeply analyse the heterogeneity of the samples, Cell ranger clustered the cells based on gene expression levels. PCA maps high-dimensional data to low-dimensional space through linear projection and expects that the variance of the data is the largest in the dimension of the projection. T-SNE maps multidimensional data into two or more dimensions suitable for human observation and is widely used in image processing. After completing the cell clustering for each set of sequencing data, the screening cardiomyocyte-specific marker screened out cardiomyocytes and reclustered the cells. All the differentially expressed genes and background genes were mapped to each entry in the database, the number of genes in each entry was calculated, and the hypothesis test using hypergeometric distribution was used to obtain the p-value of the enrichment results, which would have the problem of high overall false positives, and therefore the p-value needs to be corrected to reduce the false positives. We used BH to conduct multiple hypothesis tests to correct the p-value and obtain the p.adjust value, the lower the p.adjust, the more significant the enrichment results. The differential genes of each cluster TOP in the differential analysis of different clustering results (Graph-based, Seurat) were used to perform GO, KEGG, DO, Reactome enrichment analysis and visual display using the R packages clusterProfiler, ReactomePA, and DOSE. All the genes in the corresponding species database were selected as background genes in the single-cell enrichment analysis. After selecting the top genes according to the difference results, we performed classification and enrichment analysis of the top genes to study the distribution of the differential genes in each term, and to elucidate the gene function of the sample differences in the experiment.

Results: We found that SCN5A (exon3: c.392+5C>T) mutation was the pathogenic mutation, which is consistent with the phenotype. Through cell morphology observation, pluripotent gene detection (immunofluorescence, Oct4, Tra-1-60), genomic stability detection (karyotype analysis), and differentiation potential detection (teratoma assay), it was determined that the PBMCs of the patient's origin were successfully induced into pluripotent stem cells, and it was confirmed that the induced pluripotent stem cell line carrying the causative mutation for the J-wave syndrome had been successfully established with stable progeny and homogeneous morphology. The induced pluripotent stem cell line retains the patient-specific genetic information and also possesses the stem cell property of induced directed differentiation, which facilitates the subsequent directed differentiation into cardiomyocytes. The in vitro transcriptionally purified sgRNA was mixed with Cas9 protein to form RNP, and the corresponding ssODN was added, and electro transferred in with an electro transfer apparatus. The mixed cells were expanded, and single clones were picked, and the cells were expanded and frozen to obtain repaired iPSC cell lines. By establishing patient-derived iPSC lines and targeting them to differentiate into cardiomyocytes, as well as improving the efficiency of cardiomyocyte-induced differentiation through purification, the project team successfully established a patient-specific iPSC-CMs model for J-wave syndrome, a healthy control iPSC-CMs model, and a repaired iPSC-CMs model. We designed primers at 1 exon across upstream and downstream of the splice site for specific amplification and PCR of SCN5A. Compared with the control group, the disease group (JWS) had an extra band of about 100 bp, suggesting the presence of a truncated transcript, and that the splicing mutation might have led to exon jumping. SCN5A (exon3: c.392+5C>T) mutation leads to the loss of exon3 and exon4. The loss of exons leads to the early termination of translation, and the formation of a peptide with 92 amino acid residues. Correction of the mutation resulted in the disappearance of the weak band, further confirming the effect of the splice mutation exon3:c.392+5C>T. Compared with healthy control iPSC-CMs as well as repaired iPSC-CMs, sodium channel current density was significantly lower in the disease group (p<0 001), suggesting loss of sodium channel protein function. Genetic analysis revealed that SCN5A is generally a loss-of-function mutation in JWS, which can lead to a range of abnormalities in sodium channel activity, including no expression, altered voltage- and time-dependent activation, and shortened or prolonged recovery from inactivation, resulting in reduced inward Na flow (INa) during the depolarization phase. Thus, the electrophysiologic changes resulting from this mutation are consistent with the ECG phenotype of patients with J-wave syndrome. We collected iPSC-CM cells from the two J-wave syndrome and mutation repair groups for transcriptome sequencing and analysis, and the gene expression distribution results showed that the nine samples had similar and comparable gene expression distributions. Sample correlation analyses suggested good reproducibility of samples within each group. But it suggested that the gene expression patterns of the JWS-BM group were more similar to those of the healthy control group, so we selected only the JWS-BM group and the healthy control group in the subsequent differential gene analyses. We found that the number of genes with significantly up- and down-regulated expression in the J-wave syndrome group were 508 and 305, respectively. Differential gene enrichment analysis suggested that several metabolism-related signaling pathways, including complement and coagulation cascade response, cholesterol metabolism, fat digestion and absorption, were significantly up-regulated, and extracellular matrix receptor-interacting signaling pathways were significantly down-regulated. The altered genes and signaling pathways obtained from the analyses were not closely related to the J-wave syndrome phenotype, suggesting that a larger amount of data and more diverse research methods may be needed for support. We performed single-cell transcriptome sequencing analysis using 8000 cells each from iPSC-CMs samples from the disease group, and samples from the healthy control group, and performed GO, KEGG enrichment analysis and GSEA analysis on the differential gene set, and found that signaling pathways such as extracellular matrix and cardiomyopathy were significantly down-regulated, and that myocardial contraction, delayed rectifier potassium ion channel, and cardiac conduction channel-related pathways were significantly down-regulated. It is suggested that the relevant pathways may be involved in the pathogenesis of J-wave syndrome. 

Conclusion: The modelling of JWS in specific CM phenotypes through the identification of iPSC-CM phenotypes in JWS patients provides a reliable platform for studying the mechanisms of JWS. Given the substantial heterogeneity in transcriptomic data, it is important to consider that the results may not be generalizable. In order to facilitate the interpretation of the analytical results, it is necessary to gather extensive data. SCN5A (exon3: c.392+5C>T) mutation can lead to two phenotypes of JWS. Its pathogenicity is mainly due to the loss of sodium channel function. The cardiomyopathy pathway, myocardial contraction pathway and other signal pathways may be involved in the JWS. Gene editing is emerging as a therapeutic modality in genetic diseases, and complementary therapeutic options targeting the function of the Nav1.5 protein may become a major direction in this field. It is believed that with the development of stem cell and organoid technologies, the research ideas related to J-wave syndrome will become abundant, and we will eventually find suitable drugs to intervene in the syndrome.