Introduction

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.

Objectives

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.

Methods

Before data collection, the medical, life science and 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.

Results

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/.

Conclusion

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.

中文翻译：

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NDDRF：个性化预防神经退行性疾病的风险因素知识库

介绍

神经退行性疾病 (NDD) 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NDDs的预防和早期诊断对于降低这些疾病的死亡率和发病率至关重要。

目标

为了系统地了解与不同 NDD（泛神经退行性疾病或泛 NDD）相关的风险因素的异质性，建立知识库以促进 NDD 的个性化和知识指导的诊断、预防和预测。

方法

在数据收集之前，就数据范围和危险因素的分类，与医学、生命 科学 和信息学专家以及数据库的潜在用户进行了磋商和讨论。PubMed 数据库被用作数据和知识提取的资源。NDDs的风险因素是从1975年至2020年间发表的文献中手动收集的。

结果

建立了NDDs综合风险因素数据库（NDDRF），包括998个单一或组合风险因素、2293条记录和1071篇与14个最常见的NDDs相关的文章。单一危险因素分为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个因素是正面和保护性的，而880个因素对NDDs有负面影响。该知识库可在 http://sysbio.org.cn/NDDRF/ 获得。

结论

NDDRF 提供有关 NDD 风险因素的结构化信息和知识资源。它可能有利于未来对泛 NDDs 发生和进展的系统和个性化调查。同时可用于未来可解释的人工智能建模，用于NDDs的智能诊断和预防。