A Novel COX10 Deletion Polymorphism as a Susceptibility Factor for Sudden Cardiac Death Risk in Chinese Populations

Deep learning-based measurement of echocardiographic data and its application in the diagnosis of sudden cardiac death

This study aimed to evaluate the potential of deep learning applied to the measurement of echocardiographic data in patients with sudden cardiac death (SCD). 320 SCD patients who met the inclusion and exclusion criteria underwent clinical evaluation, including age, sex, BMI, hypertension, diabetes, cardiac function classification, and echocardiography. The diagnostic value of deep learning model was observed by dividing the patients into two groups: training group (n=160) and verification group (n=160), as well as two groups of healthy volunteers (n=200 for each group) during the same period. Logistic regression analysis showed that MLVWT, LVEDD, LVEF, LVOT-PG, LAD, E/e' were all risk factors for SCD. Subsequently, a deep learning-based model was trained using the collected images of the training group. The optimal model was selected based on the identification accuracy of the validation group and showed an accuracy of 91.8%, sensitivity of 80.00%, and specificity of 91.90% in the training group. The AUC value of the ROC curve of the model was 0.877 for the training group and 0.995 for the validation groups. This approach demonstrates high diagnostic value and accuracy in predicting SCD, which is clinically important for the early detection and diagnosis of SCD.

Novel Indel Variation of NPC1 Gene Associates With Risk of Sudden Cardiac Death

Background and Aims: Sudden cardiac death (SCD) was defined as an unexpected death from cardiac causes during a very short duration. It has been reported that Niemann-Pick type C1 (NPC1) gene mutations might be related to cardiovascular diseases. The purpose of the study is to investigate whether common genetic variants of NPC1 is involved in SCD susceptibility.

Methods: Based on a candidate-gene-based approach and systematic screening strategy, this study analyzed an 8-bp insertion/deletion polymorphism (rs150703258) within downstream of NPC1 for the association with SCD risk in Chinese populations using 158 SCD cases and 524 controls. The association of rs150703258 and SCD susceptibility was analyzed using logistic regression. Genotype-phenotype correlation analysis was performed using public database including 1000G, expression quantitative trait loci (eQTL), and further validated by human heart tissues using PCR. Dual-luciferase assay was used to explore the potential regulatory role of rs150703258. Gene expression profiling interactive analysis and transcription factors prediction were performed.

Results: Logistic regression analysis exhibited that the deletion allele of rs150703258 significantly increased the risk of SCD [odds ratio (OR) = 1.329; 95% confidence interval (95%CI):1.03–1.72; p = 0.0289]. Genotype-phenotype correlation analysis showed that the risk allele was significantly associated with higher expression of NPC1 at mRNA and protein expressions level in human heart tissues. eQTL analysis showed NPC1 and C18orf8 (an adjacent gene to NPC1) are both related to rs150703258 and have higher expression level in the samples with deletion allele. Dual-luciferase activity assays indicate a significant regulatory role for rs150703258. Gene expression profiling interactive analysis revealed that NPC1 and C18orf8 seemed to be co-regulated in human blood, arteries and heart tissues. In silico analysis showed that the rs150703258 deletion variant may create transcription factor binding sites. In addition, a rare 12-bp allele (4-bp longer than the insertion allele) of rs150703258 was discovered in the current cohort.

Conclusion: In summary, our study revealed that rs150703258 might contribute to SCD susceptibility by regulating NPC1 and C18orf8 expression. This indel may be a potential marker for risk stratification and molecular diagnosis of SCD. Validations in different ethnic groups with larger sample size and mechanism explorations are warranted to confirm our findings.