Department of Experimental Medicine, University of Rome "Tor Vergata", Rome, Italy.
Respiratory Diseases Unit, "Tor Vergata" University Hospital, Rome, Italy.
Mol Diagn Ther. 2021 Mar;25(2):111-121. doi: 10.1007/s40291-021-00514-w. Epub 2021 Feb 11.
Asthma is a heterogeneous condition, but firm identification of heterogeneity-focused treatments is still lacking. Dividing patients into subgroups of asthma pheno-/endotypes based on combined clinical and cellular biological characteristics and linking them to targeted treatments could be a potentially useful approach to personalize therapy for better outcomes. Nonetheless, there are still many problems related to the identification and validation of asthma phenotypes and endotypes. Alternatively, a precision-medicine strategy for the management of patients with airways disease that is free from the traditional diagnostic labels and based on identifying "treatable traits" in each patient might be preferable. However, it would represent a quite unsophisticated approach because the definition of a treatable trait is too imprecise. In fact, there is still no understanding of the mechanisms underlying treatable traits that allow directing any targeted therapies against any particular treatable trait. Fortunately, in-depth identification of underlying molecular pathways to guide targeted treatment in individual patients is in progress thanks to the improvement in big data management obtained from '-omic' sciences that is greatly increasing knowledge concerning asthma.
哮喘是一种异质性疾病，但仍缺乏针对异质性的治疗方法的确切识别。根据临床和细胞生物学特征将患者分为哮喘表型/内型亚组，并将其与靶向治疗联系起来，可能是一种个性化治疗以获得更好疗效的有效方法。然而，在识别和验证哮喘表型和内型方面仍然存在许多问题。或者，一种摆脱传统诊断标签、基于识别每位患者“可治疗特征”的气道疾病管理的精准医疗策略可能更为可取。然而，这将是一种相当简单的方法，因为可治疗特征的定义过于不精确。事实上，对于可治疗特征的机制还没有明确的认识，这使得针对任何特定的可治疗特征都无法进行靶向治疗。幸运的是，由于从“组学”科学中获得的大数据管理的改进，正在深入识别潜在的分子途径，以指导个体化患者的靶向治疗，这大大增加了对哮喘的认识。
