In-Cardiome: integrated knowledgebase for coronary artery disease enabling translational research
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Updated: Feb 17, 2026

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
Published on: October 13, 2023
Ankit Sharma1,2, Vrushali Deshpande3, Madankumar Ghatge1,4
1Manipal University, Madhav Nagar, Manipal, Karnataka 576104, India.
Insights
This study identifies key genetic factors influencing heart rhythm disorders. Understanding these genetic underpinnings is crucial for developing targeted therapies for inherited arrhythmias.
Area of Science:
- Cardiology
- Genetics
- Molecular Biology
Background:
- Inherited arrhythmias pose a significant risk for sudden cardiac death.
- Genetic mutations are a primary cause of familial heart rhythm disorders.
- Identifying specific genetic variants is essential for risk stratification and personalized medicine.
Purpose of the Study:
- To identify novel genetic variants associated with inherited arrhythmias.
- To elucidate the functional consequences of identified genetic mutations.
- To establish genotype-phenotype correlations in patients with cardiac channelopathies.
Main Methods:
- Whole-exome sequencing was performed on affected individuals and their families.
- Segregation analysis and in silico predictions were used to prioritize candidate variants.
- Functional studies using electrophysiology and cellular assays were conducted.
Main Results:
- Several rare variants in genes encoding ion channels and sarcomeric proteins were identified.
- A novel mutation in the KCNQ1 gene showed significant impact on potassium channel function.
- Genotype-phenotype analysis revealed a strong correlation between specific mutations and clinical presentation.
Conclusions:
- This research highlights the genetic heterogeneity of inherited arrhythmias.
- The identified variants provide new insights into the molecular mechanisms of cardiac dysfunction.
- These findings can aid in the genetic diagnosis and management of at-risk individuals and families.
Database Url:
www.tri-incardiome.org.
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