Identification of genes associated with sudden cardiac death: a network- and pathway-based approach

Jinhuan Wei; Xuejun Ni; Yanfei Dai; Xi Chen; Sujun Ding; Jingyin Bao; Lingyan Xing

doi:10.21037/jtd-21-361

Identification of genes associated with sudden cardiac death: a network- and pathway-based approach

J Thorac Dis. 2021 Jun;13(6):3610-3627. doi: 10.21037/jtd-21-361.

Authors

Jinhuan Wei¹, Xuejun Ni², Yanfei Dai³, Xi Chen², Sujun Ding², Jingyin Bao¹, Lingyan Xing⁴

Affiliations

¹ Basic Medical Research Center, School of Medicine, Nantong University, Nantong, China.
² Department of Medical Ultrasound, Affiliated Hospital of Nantong University, Nantong, China.
³ Radiology Department, Branch of Affiliated Hospital of Nantong University, Nantong, China.
⁴ Key Laboratory of Neuroregeneration of Jiangsu and the Ministry of Education, Co-innovation Center of Neuroregeneration, Nantong University, Nantong, China.

Abstract

Background: Sudden cardiac death (SCD) accounts for a large proportion of the total deaths across different age groups. Although numerous candidate genes related to SCD have been identified by genetic association studies and genome wide association studies (GWAS), the molecular mechanisms underlying SCD are still unclear, and the biological functions and interactions of these genes remain obscure. To clarify this issue, we performed a comprehensive and systematic analysis of SCD-related genes by a network and pathway-based approach.

Methods: By screening the publications deposited in the PubMed and Gene-Cloud Biotechnology Information (GCBI) databases, we collected the genes genetically associated with SCD, which were referred to as the SCD-related gene set (SCDgset). To analyze the biological processes and biochemical pathways of the SCD-related genes, functional analysis was performed. To explore interlinks and interactions of the enriched pathways, pathway crosstalk analysis was implemented. To construct SCD-specific molecular networks, Markov cluster algorithm and Steiner minimal tree algorithm were employed.

Results: We collected 257 genes that were reported to be associated with SCD and summarized them in the SCDgset. Most of the biological processes and biochemical pathways were related to heart diseases, while some of the biological functions may be noncardiac causes of SCD. The enriched pathways could be roughly grouped into two modules. One module was related to calcium signaling pathway and the other was related to MAPK pathway. Moreover, two different SCD-specific molecular networks were inferred, and 23 novel genes potentially associated with SCD were also identified.

Conclusions: In summary, by means of a network and pathway-based methodology, we explored the pathogenetic mechanism underlying SCD. Our results provide valuable information in understanding the pathogenesis of SCD and include novel biomarkers for diagnosing potential patients with heart diseases; these may help in reducing the corresponding risks and even aid in preventing SCD.

Keywords: Sudden cardiac death (SCD); functional enrichment analysis; network analysis; pathway crosstalk.