Institutes for Systems Genetics, West China Hospital, Sichuan University, Chengdu 610041, China.
Center for Systems Biology, Soochow University, Suzhou 215006, China.
Genomics Proteomics Bioinformatics. 2019 Aug;17(4):415-429. doi: 10.1016/j.gpb.2018.10.007. Epub 2019 Nov 28.
Parkinson's disease (PD) is a common neurological disease in elderly people, and its morbidity and mortality are increasing with the advent of global ageing. The traditional paradigm of moving from small data to big data in biomedical research is shifting toward big data-based identification of small actionable alterations. To highlight the use of big data for precision PD medicine, we review PD big data and informatics for the translation of basic PD research to clinical applications. We emphasize some key findings in clinically actionable changes, such as susceptibility genetic variations for PD risk population screening, biomarkers for the diagnosis and stratification of PD patients, risk factors for PD, and lifestyles for the prevention of PD. The challenges associated with the collection, storage, and modelling of diverse big data for PD precision medicine and healthcare are also summarized. Future perspectives on systems modelling and intelligent medicine for PD monitoring, diagnosis, treatment, and healthcare are discussed in the end.
帕金森病（PD）是一种常见的老年神经系统退行性疾病，随着全球人口老龄化的到来，其发病率和死亡率呈上升趋势。传统的从小数据到生物医学研究大数据的范式正在向基于大数据的小的可操作改变的识别转变。为了强调大数据在精准 PD 医学中的应用，我们回顾了 PD 大数据和信息学，以将基础 PD 研究转化为临床应用。我们强调了一些具有临床可操作性改变的关键发现，如 PD 风险人群筛查的易感性遗传变异、PD 患者诊断和分层的生物标志物、PD 的风险因素以及预防 PD 的生活方式。还总结了与 PD 精准医学和医疗保健相关的各种大数据的收集、存储和建模所面临的挑战。最后讨论了用于 PD 监测、诊断、治疗和医疗保健的系统建模和智能医学的未来展望。
