The central concept underlying precision medicine is a mechanistic understanding of each disease and its response to therapy sufficient to direct a specific intervention. To execute on this vision requires parsing incompletely defined disease syndromes into discrete mechanistic subsets and developing interventions to precisely address each of these etiologically distinct entities. This will require substantial adjustment of traditional paradigms which have tended to aggregate high-level phenotypes with very different etiologies. In the current environment, where diagnoses are not mechanistic, drug development has become so expensive that it is now impractical to imagine the cost-effective creation of new interventions for many prevalent chronic conditions. The vision of precision medicine also argues for a much more seamless integration of research and development with clinical care, where shared taxonomies will enable every clinical interaction to inform our collective understanding of disease mechanisms and drug responses. Ideally, this would be executed in ways that drive real-time and real-world discovery, innovation, translation, and implementation. Only in oncology, where at least some of the biology is accessible through surgical excision of the diseased tissue or liquid biopsy, has "co-clinical" modeling proven feasible. In most common germline disorders, while genetics often reveal the causal mutations, there still remain substantial barriers to efficient disease modeling. Aggregation of similar disorders under single diagnostic labels has directly contributed to the paucity of etiologic and mechanistic understanding by directly reducing the resolution of any subsequent studies. Existing clinical phenotypes are typically anatomic, physiologic, or histologic, and result in a substantial mismatch in information content between the phenomes in humans or in animal 'models' and the variation in the genome. This lack of one-to-one mapping of discrete mechanisms between disease and animal models causes a failure of translation and is one form of 'phenotype gap.' In this review, we will focus on the origins of the phenotyping deficit and approaches that may be considered to bridge the gap, creating shared taxonomies between human diseases and relevant models, using cardiovascular examples.

中文翻译：

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缩小精密医学领域的“表型鸿沟”：改善我们为了解复杂疾病机制而采取的措施。

精准医学的基本概念是对每种疾病及其对治疗的反应的机械理解，足以指导特定的干预措施。为了实现这一愿景，需要将不完整定义的疾病综合征解析为离散的机制子集，并制定干预措施以精确解决这些病因学上不同的实体。这将需要对传统范式进行实质性调整，这些传统范式往往会聚集病因差异很大的高级表型。在当前的诊断不是机械性的环境中，药物开发变得如此昂贵，以至于现在无法想象以经济有效的方式针对许多普遍的慢性病创建新的干预措施。精密医学的愿景还主张将研发与临床护理更加无缝地整合，在共享医学中，分类法将使每种临床相互作用都能促进我们对疾病机制和药物反应的集体理解。理想情况下，这将以驱动实时和现实世界中的发现，创新，翻译和实施的方式执行。仅在肿瘤学中，通过手术切除患病组织或进行液体活检可以获取至少某些生物学信息，“共同临床”模型才被证明是可行的。在大多数常见的种系疾病中，尽管遗传学通常会揭示因果突变，但仍然存在有效疾病建模的实质性障碍。通过直接降低任何后续研究的分辨率，在单个诊断标签下聚集相似疾病直接导致缺乏病因和机制理解。现有的临床表型通常是解剖的，生理的或组织学的，并导致人类或动物“模型”中的表型与基因组变异之间信息含量的重大失配。疾病和动物模型之间缺乏离散机制的一一对应映射导致翻译失败，并且是“表型缺口”的一种形式。在这篇综述中，我们将重点关注表型缺陷的起源以及可以考虑用来弥合差距，在人类疾病和相关模型之间建立共有分类法的方法，并使用心血管疾病的例子。