@article{GerullBrodehl2020,
  author    = {Gerull, Brenda and Brodehl, Andreas},
  title     = {Genetic Animal Models for Arrhythmogenic Cardiomyopathy},
  series = {Frontiers in Physiology},
  volume    = {11},
  journal   = {Frontiers in Physiology},
  number    = {264},
  issn      = {1664-042X},
  doi       = {10.3389/fphys.2020.00624},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-206903},
  year      = {2020},
  abstract  = {Arrhythmogenic cardiomyopathy has been clinically defined since the 1980s and causes right or biventricular cardiomyopathy associated with ventricular arrhythmia. Although it is a rare cardiac disease, it is responsible for a significant proportion of sudden cardiac deaths, especially in athletes. The majority of patients with arrhythmogenic cardiomyopathy carry one or more genetic variants in desmosomal genes. In the 1990s, several knockout mouse models of genes encoding for desmosomal proteins involved in cell-cell adhesion revealed for the first time embryonic lethality due to cardiac defects. Influenced by these initial discoveries in mice, arrhythmogenic cardiomyopathy received an increasing interest in human cardiovascular genetics, leading to the discovery of mutations initially in desmosomal genes and later on in more than 25 different genes. Of note, even in the clinic, routine genetic diagnostics are important for risk prediction of patients and their relatives with arrhythmogenic cardiomyopathy. Based on improvements in genetic animal engineering, different transgenic, knock-in, or cardiac-specific knockout animal models for desmosomal and nondesmosomal proteins have been generated, leading to important discoveries in this field. Here, we present an overview about the existing animal models of arrhythmogenic cardiomyopathy with a focus on the underlying pathomechanism and its importance for understanding of this disease. Prospectively, novel mechanistic insights gained from the whole animal, organ, tissue, cellular, and molecular levels will lead to the development of efficient personalized therapies for treatment of arrhythmogenic cardiomyopathy.},
  language  = {en}
}
@article{KolokotronisPlutaKlopockietal.2020,
  author    = {Kolokotronis, Konstantinos and Pluta, Natalie and Klopocki, Eva and Kunstmann, Erdmute and Messroghli, Daniel and Maack, Christoph and Tejman-Yarden, Shai and Arad, Michael and Rost, Simone and Gerull, Brenda},
  title     = {New Insights on Genetic Diagnostics in Cardiomyopathy and Arrhythmia Patients Gained by Stepwise Exome Data Analysis},
  series = {Journal of Clinical Medicine},
  volume    = {9},
  journal   = {Journal of Clinical Medicine},
  number    = {7},
  doi       = {10.3390/jcm9072168},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-236094},
  year      = {2020},
  abstract  = {Inherited cardiomyopathies are characterized by clinical and genetic heterogeneity that challenge genetic diagnostics. In this study, we examined the diagnostic benefit of exome data compared to targeted gene panel analyses, and we propose new candidate genes. We performed exome sequencing in a cohort of 61 consecutive patients with a diagnosis of cardiomyopathy or primary arrhythmia, and we analyzed the data following a stepwise approach. Overall, in 64\% of patients, a variant of interest (VOI) was detected. The detection rate in the main sub-cohort consisting of patients with dilated cardiomyopathy (DCM) was much higher than previously reported (25/36; 69\%). The majority of VOIs were found in disease-specific panels, while a further analysis of an extended panel and exome data led to an additional diagnostic yield of 13\% and 5\%, respectively. Exome data analysis also detected variants in candidate genes whose functional profile suggested a probable pathogenetic role, the strongest candidate being a truncating variant in STK38. In conclusion, although the diagnostic yield of gene panels is acceptable for routine diagnostics, the genetic heterogeneity of cardiomyopathies and the presence of still-unknown causes favor exome sequencing, which enables the detection of interesting phenotype-genotype correlations, as well as the identification of novel candidate genes.},
  language  = {en}
}