Emil Wirsz

Atlas of the clinical genetics of human dilated cardiomyopathy

AIM Numerous genes are known to cause dilated cardiomyopathy (DCM). However, until now technological limitations have hindered elucidation of the contribution of all clinically relevant disease genes to DCM phenotypes in larger cohorts. We now utilized next-generation sequencing to overcome these limitations and screened all DCM disease genes in a large cohort. METHODS AND RESULTS In this multi-centre, multi-national study, we have enrolled 639 patients with sporadic or familial DCM. To all samples, we applied a standardized protocol for ultra-high coverage next-generation sequencing of 84 genes, leading to 99.1% coverage of the target region with at least 50-fold and a mean read depth of 2415. In this well characterized cohort, we find the highest number of known cardiomyopathy mutations in plakophilin-2, myosin-binding protein C-3, and desmoplakin. When we include yet unknown but predicted disease variants, we find titin, plakophilin-2, myosin-binding protein-C 3, desmoplakin, ryanodine receptor 2, desmocollin-2, desmoglein-2, and SCN5A variants among the most commonly mutated genes. The overlap between DCM, hypertrophic cardiomyopathy (HCM), and channelopathy causing mutations is considerably high. Of note, we find that >38% of patients have compound or combined mutations and 12.8% have three or even more mutations. When comparing patients recruited in the eight participating European countries we find remarkably little differences in mutation frequencies and affected genes. CONCLUSION This is to our knowledge, the first study that comprehensively investigated the genetics of DCM in a large-scale cohort and across a broad gene panel of the known DCM genes. Our results underline the high analytical quality and feasibility of Next-Generation Sequencing in clinical genetic diagnostics and provide a sound database of the genetic causes of DCM.

Towards Personalized Cardiology: Multi-Scale Modeling of the Failing Heart

Background Despite modern pharmacotherapy and advanced implantable cardiac devices, overall prognosis and quality of life of HF patients remain poor. This is in part due to insufficient patient stratification and lack of individualized therapy planning, resulting in less effective treatments and a significant number of non-responders. Methods and Results State-of-the-art clinical phenotyping was acquired, including magnetic resonance imaging (MRI) and biomarker assessment. An individualized, multi-scale model of heart function covering cardiac anatomy, electrophysiology, biomechanics and hemodynamics was estimated using a robust framework. The model was computed on n=46 HF patients, showing for the first time that advanced multi-scale models can be fitted consistently on large cohorts. Novel multi-scale parameters derived from the model of all cases were analyzed and compared against clinical parameters, cardiac imaging, lab tests and survival scores to evaluate the explicative power of the model and its potential for better patient stratification. Model validation was pursued by comparing clinical parameters that were not used in the fitting process against model parameters. Conclusion This paper illustrates how advanced multi-scale models can complement cardiovascular imaging and how they could be applied in patient care. Based on obtained results, it becomes conceivable that, after thorough validation, such heart failure models could be applied for patient management and therapy planning in the future, as we illustrate in one patient of our cohort who received CRT-D implantation.

Genomic structural variations lead to dysregulation of important coding and non-coding RNA species in dilated cardiomyopathy

The transcriptome needs to be tightly regulated by mechanisms that include transcription factors, enhancers, and repressors as well as non‐coding RNAs. Besides this dynamic regulation, a large part of phenotypic variability of eukaryotes is expressed through changes in gene transcription caused by genetic variation. In this study, we evaluate genome‐wide structural genomic variants (SVs) and their association with gene expression in the human heart. We detected 3,898 individual SVs affecting all classes of gene transcripts (e.g., mRNA, miRNA, lncRNA) and regulatory genomic regions (e.g., enhancer or TFBS). In a cohort of patients (n = 50) with dilated cardiomyopathy (DCM), 80,635 non‐protein‐coding elements of the genome are deleted or duplicated by SVs, containing 3,758 long non‐coding RNAs and 1,756 protein‐coding transcripts. 65.3% of the SV‐eQTLs do not harbor a significant SNV‐eQTL, and for the regions with both classes of association, we find similar effect sizes. In case of deleted protein‐coding exons, we find downregulation of the associated transcripts, duplication events, however, do not show significant changes over all events. In summary, we are first to describe the genomic variability associated with SVs in heart failure due to DCM and dissect their impact on the transcriptome. Overall, SVs explain up to 7.5% of the variation of cardiac gene expression, underlining the importance to study human myocardial gene expression in the context of the individual genome. This has immediate implications for studies on basic mechanisms of cardiac maladaptation, biomarkers, and (gene) therapeutic studies alike.

Modeling and simulation of a high-performance PACS based on a shared file system architecture

Siemens and Loral Western Development Labs have designed a Picture Archiving and Communication System capable of supporting a large, fully digital hospital. Its functions include the management, storage and retrieval of medical images. The system may be modeled as a heterogeneous network of processing elements, transfer devices and storage units. Several discrete event simulation models have been designed to investigate different levels of the design. These models include the System Model, focusing on the flow of image traffic throughout the system, the Workstation Models, focusing on the internal processing in the different types of workstations, and the Communication Network Model, focusing on the control communication and host computer processing. The first two of these models are addressed here, with reference being made to a separate paper regarding the Communication Network Model. This paper describes some of the issues addressed with the models, the modeling techniques used and the performance results from the simulations. Important parameters of interest include: time to retrieve images from different possible storage locations and the utilization levels of the transfer devices and other key hardware components. To understand system performance under fully loaded conditions, the proposed system for the Madigan Army Medical Center was modeled in detail, as part of the Medical Diagnostic Imaging Support System (MDIS) proposal.

Validation-driven modeling of a PACS database in a shared-file system environment

Siemens Gammasonics and Loral Western Development Labs have conducted a series of discrete event simulation models to investigate and evaluate different design concepts of large picture archive and communication systems (PACS). The system model, the communication network model, and the workstation model were all initiated to be able to identify the most efficient system capable of supporting large, fully digital hospitals. Siemens and Loral have delivered the first systems. Continuing modeling activity explores opportunities to enhance the performance of the system by investigating new technologies, ideas and changes throughout the life cycle of the Siemens/Loral PACS. This paper describes the database modeling approach based on the validation of currently installed systems, the performance results, how to improve and tune the system under future data growth conditions with minimum costs, and how it fits in the overall Siemens/Loral Modeling Schema.

Hierarchical rapid modeling of picture archiving and communication systems using LANNET II.5 and NETWORK II.5

Siemens and Loral Western Development Labs have designed a Picture Archiving and Communication System capable of supporting a large, fully digital hospital. Its functions include the management, storage and retrieval of medical images. The system may be modeled as a heterogeneous network of processing elements, transfer devices and storage units. A series of discrete event simulation models have been developed to investigate different levels of the design. These models include the Workstation Models, focusing on the internal processing in the different types of workstations, the Communication Network Model, focusing on the control communication and host computer processing, and the System Model, focusing on the flow of image traffic throughout the system. This paper describes some of the issues addressed with the models, the modeling techniques used and the performance results from the simulations. Important parameters of interest include: time to retrieve images from different possible storage locations and the utilization levels of the transfer devices and other key hardware components. The models were an important part of the Loral/Siemens proposal for the Medical Diagnostic Imaging Support System (MDIS), helping to understand system performance under fully loaded conditions while the architecture was still in the design stage. With the first MDIS systems now online, the models continue to be useful in refining the design.