Zeiler Frederick A, Iturria-Medina Yasser, Thelin Eric P, Gomez Alwyn, Shankar Jai J, Ko Ji Hyun, Figley Chase R, Wright Galen E B, Anderson Chris M
Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada.
Department of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada.
Front Neurol. 2021 Sep 7;12:729184. doi: 10.3389/fneur.2021.729184. eCollection 2021.
Despite changes in guideline-based management of moderate/severe traumatic brain injury (TBI) over the preceding decades, little impact on mortality and morbidity have been seen. This argues against the "one-treatment fits all" approach to such management strategies. With this, some preliminary advances in the area of personalized medicine in TBI care have displayed promising results. However, to continue transitioning toward individually-tailored care, we require integration of complex "-omics" data sets. The past few decades have seen dramatic increases in the volume of complex multi-modal data in moderate and severe TBI care. Such data includes serial high-fidelity multi-modal characterization of the cerebral physiome, serum/cerebrospinal fluid proteomics, admission genetic profiles, and serial advanced neuroimaging modalities. Integrating these complex and serially obtained data sets, with patient baseline demographics, treatment information and clinical outcomes over time, can be a daunting task for the treating clinician. Within this review, we highlight the current status of such multi-modal omics data sets in moderate/severe TBI, current limitations to the utilization of such data, and a potential path forward through employing integrative neuroinformatic approaches, which are applied in other neuropathologies. Such advances are positioned to facilitate the transition to precision prognostication and inform a top-down approach to the development of personalized therapeutics in moderate/severe TBI.
尽管在过去几十年中，基于指南的中度/重度创伤性脑损伤（TBI）管理方式有所变化，但在死亡率和发病率方面几乎未见成效。这表明这种管理策略不宜采用“一刀切”的方法。鉴于此，TBI护理领域个性化医疗方面的一些初步进展已显示出令人鼓舞的结果。然而，要继续向个性化护理过渡，我们需要整合复杂的“组学”数据集。在过去几十年中，中度和重度TBI护理中复杂的多模态数据量急剧增加。此类数据包括大脑生理组的系列高保真多模态特征、血清/脑脊液蛋白质组学、入院时的基因图谱以及系列先进的神经成像模式。对于治疗临床医生而言，将这些复杂且连续获取的数据集与患者的基线人口统计学数据、治疗信息以及随时间变化的临床结果进行整合，可能是一项艰巨的任务。在本综述中，我们重点介绍了中度/重度TBI中此类多模态组学数据集的现状、利用此类数据的当前局限性，以及通过采用整合神经信息学方法（这些方法已应用于其他神经病理学）的潜在前进道路。这些进展有助于向精准预后过渡，并为中度/重度TBI中个性化治疗的开发提供自上而下的方法依据。
