Department of Molecular Pharmacology & Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA.
J Cardiovasc Transl Res. 2014 Apr;7(3):347-61. doi: 10.1007/s12265-014-9542-z. Epub 2014 Feb 8.
Despite the significant progress that has been made in identifying disease-associated mutations, the utility of the hypertrophic cardiomyopathy (HCM) genetic test is limited by a lack of understanding of the background genetic variation inherent to these sarcomeric genes in seemingly healthy subjects. This study represents the first comprehensive analysis of genetic variation in 427 ostensibly healthy individuals for the HCM genetic test using the "gold standard" Sanger sequencing method validating the background rate identified in the publically available exomes. While mutations are clearly overrepresented in disease, a background rate as high as ∼5 % among healthy individuals prevents diagnostic certainty. To this end, we have identified a number of estimated predictive value-based associations including gene-specific, topology, and conservation methods generating an algorithm aiding in the probabilistic interpretation of an HCM genetic test.
尽管在识别与疾病相关的突变方面已经取得了重大进展,但肥厚型心肌病 (HCM) 基因检测的实用性受到限制,因为人们对这些肌节基因在看似健康的个体中固有的背景遗传变异缺乏了解。本研究首次使用“金标准”Sanger 测序方法对 427 名看似健康的个体进行了 HCM 基因检测的遗传变异全面分析,验证了在公开外显子组中确定的背景率。虽然突变在疾病中明显过多,但高达约 5%的健康个体中的背景率会妨碍诊断的确定性。为此,我们已经确定了一些基于估计预测值的关联,包括基因特异性、拓扑和保守性方法,生成了一种算法,有助于对 HCM 基因检测进行概率解释。