Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610212, Sichuan, China; Center for Systems Biology, Soochow University, Suzhou 215006, Jiangsu, China.
Center for Systems Biology, Soochow University, Suzhou 215006, Jiangsu, China.
J Adv Res. 2022 Sep;40:223-231. doi: 10.1016/j.jare.2021.06.015. Epub 2021 Jun 20.
Neurodegenerative diseases (NDDs) are a series of chronic diseases, which are associated with progressive loss of neuronal structure or function. The complex etiologies of the NDDs remain unclear, thus the prevention and early diagnosis of NDDs are critical to reducing the mortality and morbidity of these diseases.
To provide a systematic understanding of the heterogeneity of the risk factors associated with different NDDs (pan-neurodegenerative diseases or pan-NDDs), the knowledgebase is established to facilitate the personalized and knowledge-guided diagnosis, prevention and prediction of NDDs.
Before data collection, the medical, lifescienceand informatics experts as well as the potential users of the database were consulted and discussed for the scope of data and the classification of risk factors. The PubMed database was used as the resource of the data and knowledge extraction. Risk factors of NDDs were manually collected from literature published between 1975 and 2020.
The comprehensive risk factors database for NDDs (NDDRF) was established including 998 single or combined risk factors, 2293 records and 1071 articles relevant to the 14 most common NDDs. The single risk factors are classified into 3 categories, i.e. epidemiological factors (469), genetic factors (324) and biochemical factors (153). Among all the factors, 179 factors are positive and protective, while 880 factors have negative influence for NDDs. The knowledgebase is available at http://sysbio.org.cn/NDDRF/.
NDDRF provides the structured information and knowledge resource on risk factors of NDDs. It could benefit the future systematic and personalized investigation of pan-NDDs genesis and progression. Meanwhile it may be used for the future explainable artificial intelligence modeling for smart diagnosis and prevention of NDDs.
神经退行性疾病(NDDs)是一系列慢性疾病,与神经元结构或功能的进行性丧失有关。NDDs 的复杂病因尚不清楚,因此,预防和早期诊断 NDDs 对于降低这些疾病的死亡率和发病率至关重要。
为了系统地了解与不同 NDD(泛神经退行性疾病或泛 NDDs)相关的风险因素的异质性,建立知识库,以促进 NDD 的个性化和知识引导诊断、预防和预测。
在收集数据之前,咨询并讨论了医学、生命科学和信息学专家以及数据库的潜在用户,以确定数据范围和风险因素分类。使用 PubMed 数据库作为数据和知识提取的资源。从 1975 年至 2020 年发表的文献中手动收集 NDD 的风险因素。
建立了神经退行性疾病综合风险因素数据库(NDDRF),其中包括 998 个单一或组合风险因素、2293 条记录和 1071 篇与 14 种最常见 NDD 相关的文章。单一风险因素分为 3 类,即流行病学因素(469)、遗传因素(324)和生化因素(153)。在所有因素中,有 179 个因素具有阳性和保护作用,而 880 个因素对 NDD 有负面影响。该知识库可在 http://sysbio.org.cn/NDDRF/ 上获得。
NDDRF 提供了 NDD 风险因素的结构化信息和知识库。它有助于未来对泛 NDD 发病机制和进展进行系统的个性化研究。同时,它也可用于未来可解释的人工智能模型,以实现 NDD 的智能诊断和预防。