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Genomics, Proteomics & Bioinformatics (GPB; ISSN 1672-0229, CN11-4926/Q), a peer-reviewed international journal in English, is sponsored by Beijing Institute of Genomics, Chinese Academy of Sciences and Genetics Society of China, and jointly published by Elsevier and Science Press bi-monthly.

The publications of the journal are high-quality papers from all over the world in the fields of genomics, proteomics, and bioinformatics. For manuscripts submitted to GPB,direct rejection,direct acceptance or further review will be decided within 5 days. Besides, GPB offers Article-in-Press, by which all the accepted manuscripts can be available online ahead of its printed issue print for fast dissemination.


Recent Articles (Volume:14, Issue:4)

1. Computational Cardiology — A New Discipline of Translational Research

Benjamin Meder, Hugo A. Katus, Andreas Keller

2. Hide and Seek: Protein-coding Sequences Inside “Non-coding” RNAs

Daniel Oehler, Jan Haas

Die Erregbarkeit von Zellen ist kritisch mit dem Gleichgewicht der Ionenkonzentrationen verknüpft. In Muskelzellen hängt die Kontraktilität von vor allem der Kalziumhomöostase ab. Hierbei ist die SERCA (Calciumpumpe des sarcoplasmatischen und endoplasmatischen Reticulums) entscheidend beteiligt. In einer kürzlich in „Science“ publizierten Arbeit von Nelson et Al. konnte eine bisher als long non-coding RNA annotierte Sequenz als für das DWORF-Protein kodierend identifiziert werden. DWORF ist dabei ein neuer indirekter Aktivator der SERCA und somit im essentiellen Kalziumhaushalt der Muskelzellen beteiligt. Es führt zu einer gesteigerten Kontraktilität durch Verbesserung der Relaxation der Muskelzellen. Aufgrund dessen ist ein potentieller diagnostischer oder therapeutischer Nutzen dieses neuen Proteins bei Patienten mit einer Herzinsuffizienz, zum Beispiel aufgrund einer Kardiomyopathie, denkbar.

3. A Biobank for Long-term and Sustainable Research in the Field of Congenital Heart Disease in Germany

Thomas Pickardt, Eva Niggemeyer, Ulrike M.M. Bauer, Hashim Abdul-Khaliq, Competence Network for Congenital Heart Defects Investigators

Congenital heart disease (CHD) is the most frequent birth defect (0.8%–1% of all live births). 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 are dominating the follow-up of these patients. Due to the rarity and heterogeneity of the phenotypes of CHD, multicenter registry-based studies are required. The CHD-Biobank was established in 2009 with the aim to collect DNA from patients and their parents (trios) or from affected families, as well as cardiovascular tissues from patients undergoing corrective heart surgery for cardiovascular malformations. Clinical/phenotype data are matched to the International Paediatric and Congenital Cardiac Code (IPCCC) and the International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10). The DNA collection currently comprises samples from approximately 4200 participants with a wide range of CHD phenotypes. The collection covers about 430 trios and 120 families with more than one affected member. The cardiac tissue collection comprises 1143 tissue samples from 556 patients after open heart surgery. The CHD-Biobank provides a comprehensive basis for research in the field of CHD with high standards of data privacy, IT management, and sample logistics.

4. Long non-coding RNA Databases in Cardiovascular Research

Frank Rühle, Monika Stoll

With the rising interest in the regulatory functions of long non-coding RNAs (lncRNAs) in complex human diseases such as cardiovascular diseases, there is an increasing need in public databases offering comprehensive and integrative data for all aspects of these versatile molecules. Recently, a variety of public data repositories that specialized in lncRNAs have been developed, which make use of huge high-throughput data particularly from next-generation sequencing (NGS) approaches. Here, we provide 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. The prominent lncRNA antisense noncoding RNA in the INK4 locus (ANRIL), which has been unequivocally associated with coronary artery disease through genome-wide association studies (GWAS), serves as an example to demonstrate the features of each individual database.
Das wachsende Interesse an den regulatorischen Funktionen langer nicht-kodierender RNAs (lncRNAs) in komplexen humanen Erkrankungen, wie Herzkreislauferkrankungen, erfordert zunehmend öffentliche Datenbanken mit umfassenden und integrativen Informationen zu allen Aspekten dieser vielseitigen Moleküle. Viele auf lncRNAs spezialisierte Datenbanken wurden jüngst entwickelt, die auf die Hochdurchsatz-Daten der aktuellen Sequenzierverfahren („Next generation sequencing“, NGS) zugreifen. In diesem Review geben wir eine Übersicht der aktuellen lncRNA Datenbanken mit Informationen zu grundlegenden und funktionalen lncRNA-Annotationen, zur lncRNA-Expression und -Regulation, zu Interaktionen mit anderen Biomolekülen sowie zu genomischen Varianten, die die Struktur und Funktion von lncRNAs beeinflussen können. Anhand der gut dokumentierten lncRNA „antisense noncoding RNA in the INK4 locus“ (ANRIL), die in genomweiten Assoziationsstudien (GWAS) bereits eindeutig mit koronarer Herzkrankheit assoziiert wurde, werden die Eigenschaften der einzelnen Datenbanken beispielhaft demonstriert.

5. The Role of Quality Control in Targeted Next-generation Sequencing Library Preparation

Rouven Nietsch, Jan Haas, Alan Lai, Daniel Oehler, Stefan Mester, Karen S. Frese, Farbod Sedaghat-Hamedani, Elham Kayvanpour, Andreas Keller, Benjamin Meder

Next-generation sequencing (NGS) is getting routinely used in the diagnosis of hereditary diseases, such as human cardiomyopathies. Hence, it is of utter importance to secure high quality sequencing data, enabling the identification of disease-relevant mutations or the conclusion of negative test results. During the process of sample preparation, each protocol for target enrichment library preparation has its own requirements for quality control (QC); however, there is little evidence on the actual impact of these guidelines on resulting data quality. In this study, we analyzed the impact of QC during the diverse library preparation steps of Agilent SureSelect XT target enrichment and Illumina sequencing. We quantified the parameters for a cohort of around 600 samples, which include starting amount of DNA, amount of sheared DNA, smallest and largest fragment size of the starting DNA; amount of DNA after the pre-PCR, and smallest and largest fragment size of the resulting DNA; as well as the amount of the final library, the corresponding smallest and largest fragment size, and the number of detected variants. Intriguingly, there is a high tolerance for variations in all QC steps, meaning that within the boundaries proposed in the current study, a considerable variance at each step of QC can be well tolerated without compromising NGS quality.

6. Comparative Gene Expression Analysis of Mouse and Human Cardiac Maturation

Hideki Uosaki, Y-h Taguchi

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 while cardiomyocytes mature during fetal development and childhood, as well as difficulty in avoiding variations among individuals. Using model animals such as mice can be a useful strategy; nonetheless, it is not well-understood whether and to what degree gene expression profiles during maturation are shared between humans and mice. Therefore, we performed a comparative gene expression analysis of mice and human samples. First, we examined two distinct mice microarray platforms for shared gene expression profiles, aiming to increase reliability of the analysis. We identified a set of genes displaying progressive changes during maturation based on principal component analysis. Second, we demonstrated that the genes identified had a differential expression pattern between adult and earlier stages (e.g., fetus) common in mice and humans. Our findings provide a foundation for further genetic studies of cardiomyocyte maturation.

7. Profiling and Validation of the Circular RNA Repertoire in Adult Murine Hearts

Tobias Jakobi, Lisa F. Czaja-Hasse, Richard Reinhardt, Christoph Dieterich

For several decades, cardiovascular disease has been the leading cause of death throughout all countries. There is a strong genetic component to many disease subtypes (e.g., cardiomyopathy) and we are just beginning to understand the relevant genetic factors. Several studies have related RNA splicing to cardiovascular disease and circular RNAs (circRNAs) are an emerging player. circRNAs, which originate through back-splicing events from primary transcripts, are resistant to exonucleases and typically not polyadenylated. Initial functional studies show clear phenotypic outcomes for selected circRNAs. We provide, for the first time, a comprehensive catalogue of RNase R-resistant circRNA species for the adult murine heart. This work combines state-of-the-art circle sequencing with our novel DCC software to explore the circRNA landscape of heart tissue. Overall, we identified 575 circRNA species that pass a beta-binomial test for enrichment (false discovery rate of 1%) in the exonuclease-treated sequencing sample. Several circRNAs can be directly attributed to host genes that have been previously described as associated with cardiovascular disease. Further studies of these candidate circRNAs may reveal disease-relevant properties or functions of specific circRNAs.

8. Absent MicroRNAs in Different Tissues of Patients with Acquired Cardiomyopathy

Christine S. Siegismund, Maria Rohde, Uwe Kühl, Felicitas Escher, Heinz Peter Schultheiss, Dirk Lassner

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. The miRNA profiles in biological samples (tissue, serum, peripheral blood mononuclear cells or other body fluids) differ significantly even in the same patient and therefore have their own specificity for the presented condition. Complex profiles of deregulated miRNAs are of high interest, whereas the importance of non-expressed miRNAs was ignored. Since miRNAs regulate gene expression rather negatively, absent miRNAs could indicate genes with unaltered expression that therefore are normally expressed in specific compartments or under specific disease situations. For the first time, non-detectable miRNAs in different tissues and body fluids from patients with different diseases (cardiomyopathies, Alzheimer’s disease, bladder cancer, and ocular cancer) were analyzed and compared in this study. miRNA expression data were generated by microarray or TaqMan PCR-based platforms. Lists of absent miRNAs of primarily cardiac patients (myocardium, blood cells, and serum) were clustered and analyzed for potentially involved pathways using two prediction platforms, i.e., miRNA enrichment analysis and annotation tool (miEAA) and DIANA miRPath. Extensive search in biomedical publication databases for the relevance of non-expressed miRNAs in predicted pathways revealed no evidence for their involvement in heart-related pathways as indicated by software tools, confirming proposed approach.

9. Comparison of Cox Model Methods in A Low-dimensional Setting with Few Events

Francisco M. Ojeda, Christian Müller, Daniela Börnigen, David-Alexandre Trégouët, Arne Schillert, Matthias Heinig, Tanja Zeller, Renate B. Schnabel

Prognostic models based on survival data frequently make use of the Cox proportional hazards model. Developing reliable Cox models with few events relative to the number of predictors can be challenging, even in low-dimensional datasets, with a much larger number of observations than variables. In such a setting we examined the performance of methods used to estimate a Cox model, including (i) full model using all available predictors and estimated by standard techniques, (ii) backward elimination (BE), (iii) ridge regression, (iv) least absolute shrinkage and selection operator (lasso), and (v) elastic net. Based on a prospective cohort of patients with manifest coronary artery disease (CAD), we performed a simulation study to compare the predictive accuracy, calibration, and discrimination of these approaches. Candidate predictors for incident cardiovascular events we used included clinical variables, biomarkers, and a selection of genetic variants associated with CAD. The penalized methods, i.e., ridge, lasso, and elastic net, showed a comparable performance, in terms of predictive accuracy, calibration, and discrimination, and outperformed BE and the full model. Excessive shrinkage was observed in some cases for the penalized methods, mostly on the simulation scenarios having the lowest ratio of a number of events to the number of variables. We conclude that in similar settings, these three penalized methods can be used interchangeably. The full model and backward elimination are not recommended in rare event scenarios.
Los módelos pronósticos están basados frecuentemente en el modelo de riesgos proporcionales de Cox. El desarrollo de modelos de Cox fiables con pocos eventos respecto al número de predictores puede ser díficil, aún con datos de baja dimension y con muchas más observaciones que variables. En este escenario examinamos el desempeño de métodos utilizados para estimar un módelo de Cox, incluyendo (i) modelo completo usando todo los predictores disponibles y estimado usando técnicas estándar, (ii) eliminación retrógrada (BE, por sus siglas en inglés), (iii) regresión contraída (ridge), (iv) lazo (lasso, least absolute shrinkage and selection operator), y (v) la red elástica. Basado en estudio de cohorte prospectivo de pacientes con enfermedad de las arterias coronarias (EAC), realizamos un estudio de simulación para comparar la exactitud predictiva, la calibración, y la discriminación de los distintos métodos. Como predictores usamos variables clínicas, biomarcadores, y una selección de variantes genéticas asociadas con EAC. Los métodos penalizados, es decir, la regresión contraída, el lazo y la red elástica mostraron un rendimiento comparable, en términos de exactitud predictiva, calibración y discriminación, y su desempeño fue superior al de BE y el modelo completo. Reducción excesiva fue observada en algunos casos para los métodos penalizados, en su mayoría, en simulaciones que tenían el menor proporción de número de eventos a número de variables. Concluímos que en escenarios similares, los tres métodos penalizados pueden ser usados de manera indistinta. El modelo completo y la eliminación retrógrada no son recomendados en escenarios con pocos eventos.

10. Personalized Computer Simulation of Diastolic Function in Heart Failure

Ali Amr, Elham Kayvanpour, Farbod Sedaghat-Hamedani, Tiziano Passerini, Viorel Mihalef, Alan Lai, Dominik Neumann, Bogdan Georgescu, Sebastian Buss, Derliz Mereles, Edgar Zitron, Andreas E. Posch, Maximilian Würstle, Tommaso Mansi, Hugo A. Katus, Benjamin Meder

The search for a parameter representing left ventricular relaxation from non-invasive and invasive diagnostic tools has been extensive, since heart failure (HF) with preserved ejection fraction (HF-pEF) is a global health problem. We explore here the feasibility using patient-specific cardiac computer modeling to capture diastolic parameters in patients suffering from different degrees of systolic HF. Fifty eight patients with idiopathic dilated cardiomyopathy have undergone thorough clinical evaluation, including cardiac magnetic resonance imaging (MRI), heart catheterization, echocardiography, and cardiac biomarker assessment. A previously-introduced framework for creating multi-scale patient-specific cardiac models has been applied on all these patients. Novel parameters, such as global stiffness factor and maximum left ventricular active stress, representing cardiac active and passive tissue properties have been computed for all patients. Invasive pressure measurements from heart catheterization were then used to evaluate ventricular relaxation using the time constant of isovolumic relaxation Tau (τ). Parameters from heart catheterization and the multi-scale model have been evaluated and compared to patient clinical presentation. The model parameter global stiffness factor, representing diastolic passive tissue properties, is correlated significantly across the patient population with τ. This study shows that multi-modal cardiac models can successfully capture diastolic (dys) function, a prerequisite for future clinical trials on HF-pEF.

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