GPB special issue “Computational Cardiology” is newly released
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Genomics, Proteomics & Bioinformatics (GPB), the official journal of Beijing Institute of Genomics, Chinese Academy of Sciences and Genetics Society of China, just released a special issue on “Computational Cardiology” lately as Volume 14, Issue 4, 2016.  


The “Computational Cardiology” special issue is organized by the guest editors Dr. Benjamin Meder and Dr. Hugo A. Katus (from University of Heidelberg and German Center for Cardiovascular Research–DZHK), together with Dr. Andreas Keller (from Saarland University). 


During the last two decades, we have evidenced the improved diagnosis, medication and interventional therapy against fatal diseases, e.g., heart failure, coronary disease, and arrhythmia. Computational cardiology, which integrates molecular, clinical and bioinformatic approaches to investigate the pathogenesis and novel therapeutic methods of cardiac diseases, would be promising in the improvement of personalized approaches for cardiac disease therapy, albeit facing many challenges in the meantime. In this issue, we have published 9 invited articles, including one research highlight, 2 resource reviews, and 6 original research articles. 


  • Dr. Daniel Oehler and Dr. Jan Haas from University of Heidelberg and DZHK highlighted a Science article regarding dwarf open reading frame (DWORF), a peptide “hiding” in a long non-coding RNA (lncRNA), as well as other similar small peptides which can modulate muscle contractility. The search for proteins “hidden in the black space of the genome” will certainly lead to novel surprises as to the complexity in functional regulation of the human heart. Notably, the coding potential of the small peptide in the lncRNA was predicted using bioinformatic methods and later on validated experimentally, demonstrating the important role of bioinformatics in this exciting discovery process.  

  • In a resource review, Dr. Frank Rühle from University of Muenster (Germany) and Dr. Monika Stoll from Maastricht University (The Netherlands) provided an overview of current lncRNA databases covering basic and functional annotation, lncRNA expression and regulation, interactions with other biomolecules, and genomic variants influencing the structure and function of lncRNAs. In particular, they demonstrate the features of examined databases using lncRNA ANRIL as an example and cautioned the users about database selection for data analysis due to occasional inconsistency between databases. 

  • Congenital heart disease (CHD) is the most frequent birth defect. Due to the advance in prenatal and postnatal early diagnosis and treatment, more than 90% of these patients survive into adulthood today. However, several mid- and long-term morbidities dominate the follow-up of these patients. Dr. Thomas Pickardt et al. from the National Register for Congenital Heart Defects, Germany, introduced the CHD-Biobank for long-term and sustainable research in the field of CHD in Germany. Established in 2009, the DNA collection of CHD-Biobank currently comprises samples from approximately 4200 participants with a wide range of CHD phenotypes, whereas the cardiac tissue collection comprises 1143 tissue samples from 556 patients after open heart surgery.  

  • Next-generation sequencing (NGS), which facilitates the identification of disease-relevant mutations, is getting routinely used in the diagnosis of hereditary diseases, such as human cardiomyopathies. Dr. Benjamin Meder et al. analyzed the impact of quality control (QC) during the diverse library preparation steps for sequencing. Intriguingly, there was a high tolerance for variations in all QC steps, indicating that within the boundaries proposed in their study, a considerable variance at each step of QC can be well tolerated without compromising NGS quality. 

  • Understanding how human cardiomyocytes mature is crucial to realizing stem cell-based heart regeneration, modeling adult heart diseases, and facilitating drug discovery. However, it is not feasible to analyze human samples for maturation due to inaccessibility to samples. Dr. Hideki Uosaki from Johns Hopkins University and Dr. Y-h Taguchi from Chuo University (Japan) performed a comparative gene expression analysis of mouse and human samples, providing a list of potential genes for further genetic studies of cardiomyocyte maturation. 

  • MicroRNAs (miRNAs) can be found in a wide range of tissues and body fluids, and their specific signatures can be used to determine diseases or predict clinical courses. Dr. Dirk Lassner et al. from Institute for Cardiac Diagnostics and Therapy, Germany analyzed and compared non-detectable miRNAs in different tissues and body fluids from patients with different diseases, e.g., cardiomyopathies, Alzheimer’s disease, bladder cancer, and ocular cancer. Lists of absent miRNAs of primarily cardiac patients were analyzed for potentially involved pathways using different bioinformatic approaches. There is no evidence of their involvement in heart-related pathways. 

  • Other than microRNAs and lncRNAs, several studies have revealed that circular RNAs (circRNAs) are an emerging player in cardiovascular diseases. Dr. Tobias Jakobi from University of Heidelberg and DZHK combined state-of-the-art circle sequencing with their novel DCC software to explore the circRNA landscape of heart tissue. They provided a comprehensive catalogue of RNase R-resistant circRNA species for the adult murine heart. Further studies of these candidate circRNAs may reveal disease-relevant properties or functions of specific circRNAs. 

  • Prognostic models based on survival data frequently make use of the Cox proportional hazards model, while developing reliable Cox models with few events relative to the number of predictors can be challenging. Based on a prospective cohort of patients with manifest coronary artery disease (CAD), Dr. Francisco M. Ojeda et al. from University Heart Center Hamburg-Eppendorf, Germany performed a simulation study to compare the predictive accuracy, calibration, and discrimination of different approaches. They then suggested applications of different models based on the test situations  

  • Heart failure (HF) with preserved ejection fraction (HF-pEF) is a global health problem. Dr. Benjamin Meder et al. explored the feasibility using patient-specific cardiac computer modeling to capture diastolic parameters in patients suffering from different degrees of systolic HF. Their study showed that multi-modal cardiac models can successfully capture diastolic function, a prerequisite for future clinical trials on HF-pEF.  


These articles are fully accessible at ScienceDirect.


Special issue “Big Data and Precision Medicine”, which is organized by the guest editors Dr. Xiangdong Fang and Dr. Hongxing Lei, will be published on GPB in Oct, 2016. For more details, please find the “Call for Paper” at