• 2018-07
  • 2019-04
  • 2019-05
  • 2019-06
  • Causative genes for ARVC and their respective characteristic


    Causative genes for ARVC and their respective characteristics are summarized in Table 1.
    Desmosome genes for ARVC
    Other causative genes for ARVC Although more than half of ARVC patients carry mutations in desmosome genes, other genes have also been reported as causative genes for ARVC (Table 1). In the most of these genes, their loci on purchase UNC2025 were first confirmed by linkage analysis, and then the specific genes were identified in the target families. Other than desmosome genes, 7 loci have been detected in linkage analysis and 5 causative genes for ARVC have been identified. However, the causative genes of ARVC3 in chromosome 14q12-q22 and ARVC6 in chromosome 10q14-p12 have not been identified yet.
    Other causative genes for ARVC
    Genotype–phenotype correlations In certain genetic diseases with multiple genotypes, genotype–phenotype correlations are well studied and used for diagnosis and treatment. For example in long QT syndrome, phenotypes predict the genotypes, and genotyping is useful to predict prognosis of the patients and to decide treatment. However, in ARVC, genotype–phenotype correlations have not been fully examined as of yet. One of the reasons being that most of the mutations are identified in PKP2 [18]. Another reason for the lack of study is the low penetrance of the mutations [17]. Recently, a study that analyzed the phenotypes and gene mutations related to ARVC was reported. In the probands, mutation positive status did not affect clinical characteristics and outcomes. In contrast, family members with mutations were more likely to meet Task Force Criteria for ARVC [4] (40% vs 18%), experience sustained ventricular arrhythmias (11% vs 1%), and die from a cardiac cause (2% vs 0%) than family members without mutations [18]. Among 116 desmosome gene mutation carriers in another study, the event rate was higher among patients with definite ARVC than among borderline or phenotype negative patients [46]. Correlations between mutation type and phenotype have been reported. We compared the disease onset of probands with 12 missense and 7 non-missense mutation carriers. All non-missense mutations were found in PKP2 [19]. In our study, the disease onsets were significantly younger in the patients with non-missense mutations than in those with missense mutations (29.4±12.4 vs 45.8±14.2 years, P=0.027). In contrast, Alcalde et al. reported that the disease onsets in patients with stop gain mutations were later than those in patients with missense mutations (27 vs 39 years old, P<0.05). Although, it is difficult to clarify the reason of the discrepancy, the definition of onset was different between studies. It would be difficult to define disease onsets in the patients whose first symptoms were ventricular arrhythmias, because cardiologists would never recognize that the patients experienced ventricular tachycardia if the patients did not complain of their symptoms or had syncope.
    Progress pertaining to genetic analysis and genetic noise However, we can now approach the new sequencing methods, next generation sequencing (NGS) methods [47]. These methods are useful not only for whole genome or exome sequencing but also for target gene sequencing [48]. Especially for cardiomyopathies, multiple panels for genetic analysis are available on the market. If these panels are used, mutations in ARVC patients can easily be detected in a week. In the NGS era, many rare variants can be detected in genetic analysis, some of which are related with the disease. Therefore, the true mutation(s) causative for the disease need to be distinguished from other genetic noise. In 2011, Kapplinger et al. reported background genetic noise in ARVC [49]. They performed a genetic analysis of PKP2, DSP, DSG2, DSC2, and TMEM43 for 92 probands diagnosed with ARVC and 427 controls. Radical mutations resulting in stop codons were identified in 43% of probands and in 0.5% of controls. In contrast, missense mutations were identified in 21% of the probands and 16% of controls; thus, the frequency of missense mutations was similar between probands and controls. They further analyzed the ARVC related genes and locations of missense mutations that were highly detected in controls and found that missense mutations in DSP and DSG2, especially at the C-terminals of both genes, were highly detected in controls [49]. To avoid misunderstanding of the detected variants in the ARVC related genes, a comparison of the detected mutations with data for ethnically matched controls is needed, for example, the 1000 genome study [50] and the ExAC Browser (