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Updated: Jun 8, 2025
Author Spotlight: Advancing the Analysis of Plasma Extracellular Vesicle Proteome for Cardiovascular Biomarker Studies
Published on: January 31, 2025
Use of mendelian randomization to assess the causal associations of circulating plasma proteins with 12-lead ECG
Peng Zhao1, Li Meng2, Feiyuan Han2
1Department of Cardiology, The Second Affiliated Hospital of Harbin Medical University, 150086, Xuefu Road 246, Harbin, Province Heilongjiang, China; Key Laboratory of Myocardial Ischemia, Ministry of Education, 150086, Xuefu Road 246, Harbin, Province Heilongjiang, China; Heilongjiang Provincial Key Laboratory of Panvascular Disease, China.
Insights
This study found 18 plasma proteins causally linked to electrocardiogram (ECG) traits, offering new insights into cardiac conduction and potential drug targets for arrhythmias.
Area of Science:
- Cardiovascular Research
- Proteomics
- Genetics
Background:
- Cardiac conduction disorders can lead to arrhythmias, but the underlying mechanisms are not fully understood.
- Identifying links between plasma proteins and electrocardiogram (ECG) traits is crucial for understanding cardiac conduction.
Purpose of the Study:
- To investigate the causal relationship between circulating plasma proteins and ECG traits.
- To provide biological insights and clinical guidance for cardiac conduction disorders.
Main Methods:
- Proteome-wide Mendelian randomization (MR) analysis was used to assess associations between plasma proteins and five ECG traits.
- Sensitivity, reverse MR, colocalization, and replication analyses were performed to ensure result reliability.
- Gene ontology, KEGG enrichment, and drug database analyses were conducted to explore biological functions and druggability.
Main Results:
- Significant causal associations were found between 18 plasma proteins and ECG traits, including P wave duration, PR interval, QRS duration, and QT interval.
- Reverse MR analysis did not find significant causal effects of ECG traits on proteins.
- Five identified proteins (VEGFA, ADK, PAM, Cathepsin_S, PKC_A) were found to be druggable targets.
Conclusions:
- This study establishes significant causal links between genetically predicted plasma protein levels and ECG traits.
- The findings underscore the role of plasma proteins in cardiac conduction and suggest potential for novel arrhythmia drug development.
Background:
Cardiac conduction disorders predispose individuals to arrhythmias, currently but the exact mechanisms of cardiac conduction remain elusive. The study sought to identify the causal association between circulating plasma proteins and electrocardiogram (ECG) traits, offer valuable biological insights and clinical guidance into cardiac conduction.
Methods:
Proteome-wide Mendelian randomization (MR) analysis was firstly conducted to assess causal associations between plasma proteins and five ECG traits, including P wave duration (PWD), QRS duration, PR, QT and RR intervals. Multiple sensitivity analyses were implemented. The reverse MR analysis, colocalization analysis and replication analysis were used to consolidate the reliability of our results. Then, we conducted mediation analysis to explore potential mechanism between plasma proteins and ECG traits. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were applied to clarify the biological functions of target proteins. Finally, phenome-wide MR (Phe-MR) and drug databases were searched.
Results:
We identified 3 proteins (FAM151A, VEGF165, VEGF121) associated with PWD, 12 proteins (ABHD10, ADK, Cathepsin_S, DUSP13, Ephrin_A3, MAPRE2, OMG, PAM, PMM1, SH3BGRL3, TCP4, SYT11) linked to PR interval, 1 protein (PKC_A) related to QRS duration, and 2 proteins (MXRA7, SVEP1) associated with QT interval. A significant causal effects of ECG traits on them was not found in reverse MR. Colocalization and replication analyses strengthened our findings further. The impacts were partly mediated by anthropometric measures. Enrichment analysis of target proteins mainly enriched for multiple key pathways such as regulation of hydrolase activity and fibronectin binding. Through drug databases searching, 5 identified proteins (VEGFA, ADK, PAM, Cathepsin_S, PKC_A) were considered druggable.
Conclusions:
We discovered significant causal associations between genetically predicted levels of 18 plasma proteins and ECG traits. These results highlight the importance of circulating plasma proteins in cardiac conduction and open up the possibility of novel arrhythmia drug development.
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