Urtis Mario, Tagliani Marilena, Bondavalli Davide, Paganini Chiara, Cavaliere Claudia, Vilardo Viviana, Buccieri Edward, Tescari Antonio, Ferrari Michela, Arbustini Eloisa
Scientific Department, Centre for Inherited Cardiovascular Diseases, Fondazione IRCCS Policlinico San Matteo, V.le Golgi 19, Pavia 27100, Italy.
Department of Electrical Computer and Biomedical Engineering, University of Pavia, Via Ferrata 5, Pavia 27100, Italy.
Eur Heart J Suppl. 2025 Feb 19;27(Suppl 1):i67-i72. doi: 10.1093/eurheartjsupp/suae107. eCollection 2025 Feb.
The diagnostic work-up of cardiovascular genetic diseases is emerging as a reference model for precision (cause and phenotype) and personalized medicine (tailored individual management). This approach is expanding across all areas of cardiovascular medicine, ranging from monogenic diseases to multifactorial disorders where 'risk factors' such as familial hypercholesterolaemia may play a role in the risk profile. In this context, cardiomyopathies provide an ideal reference because they are monogenic yet genetically heterogeneous diseases, much like many other cardiovascular genetic disorders. In this model, the genetic path starts with deep phenotyping of the patient and relatives and progresses with genetic testing including extensive multigene panels, up to whole-exome sequencing and whole-genome sequencing. Although genetic work-ups are increasingly successful, several unresolved challenges and limitations remain. These include the interpretation and reinterpretation of variants, as many pre-American College of Medical Genetics variants previously classified as likely pathogenic or pathogenic are now recognized as variants of uncertain significance or benign/likely benign; pathogenic variants missed with short-read next generation sequencing (NGS) technologies (e.g. deep intronic variants or Copy Number Variations); gene-specific issues such as pseudogenes and pseudo-exons; and differing interpretations of pathogenicity for the same gene defects by commercial pipelines. Despite widespread NGS-based testing, about half of suspected Mendelian conditions still lack a precise molecular diagnosis. New organizational models are needed to integrate emerging knowledge and innovations incorporating both clinical and genetic data into intelligent platforms that may support shared management pathways.
心血管遗传疾病的诊断检查正逐渐成为精准医学（病因和表型）及个性化医疗（量身定制的个体管理）的参考模式。这种方法正在心血管医学的各个领域不断扩展，从单基因疾病到多因素疾病，诸如家族性高胆固醇血症等“风险因素”可能在风险状况中发挥作用。在这种背景下，心肌病提供了一个理想的参考范例，因为它们是单基因但基因异质性的疾病，这与许多其他心血管遗传疾病很相似。在这个模式中，遗传诊断路径始于对患者及其亲属进行深入的表型分析，然后通过基因检测推进，包括广泛的多基因检测板，直至全外显子测序和全基因组测序。尽管遗传诊断检查越来越成功，但仍存在一些未解决的挑战和局限性。这些包括变异的解读和重新解读，因为许多美国医学遗传学学会之前分类为可能致病或致病的变异，现在被认为是意义未明的变异或良性/可能良性变异；短读长下一代测序（NGS）技术遗漏的致病变异（例如内含子深处的变异或拷贝数变异）；诸如假基因和假外显子等基因特异性问题；以及商业检测流程对同一基因缺陷的致病性解读存在差异。尽管基于NGS的检测广泛应用，但约一半疑似孟德尔疾病仍缺乏精确的分子诊断。需要新的组织模式来整合新兴知识和创新，将临床和遗传数据纳入智能平台，以支持共享的管理路径。
