1. Aim of the NDDRF Knowledgebase
Neurodegenerative diseases (NDDs) are chronic diseases that lead to progressive loss of neuronal structure or function. The complex etiologies of many NDDs remain unclear, and prevention and early prediction of NDDs are critical. Since a systematic analysis of the diverse risk factors for NDDs would facilitate prevention and personalized medicine, we aim to build a knowledge base related to NDDs risk factors. Before collecting data, we discussed with clinicians, biostatisticians and others what needed to be collected and how to classify risk factors, as well as determining the requirements of potential users. In the end, we had completed a scientific and effective comprehensive data collection program, and defined the classification criteria for the risk factors of NDDs. We have now constructed a knowledge base of NDDs risk factors, NDDRF, by manually collecting risk factors from literature published between 1975 and 2020. NDDRF contains 998 single or combined risk factors, 2293 records and 1071 articles relevant to the 14 most common NDDs. Single risk factors are classified into three categories, epidemiological factors (469), genetic factors (324) and biochemical factors (153). Among these factors, 179 are positive and protective and 880 are negative. This knowledge base will be curated and updated for the systematic understanding and future prevention of NDDs.


2. How to search the database
The search function includes both basic and advanced searches. The basic search facility mainly allows ‘fuzzy’ queries and is most suitable for direct queries of risk factor names. When users enter the keywords of a risk factor in the search box, we have added a keyword association function that will display a list of the top ten related suggestions for the keywords below the search box, which will greatly help users to search for risk factors. After the keyword is selected, clicking the search button will take the user to the page that displays all the search results, which shows basic information (ID, disease name, species, name, association, condition and PMID) for the risk factors searched by the keywords. Users can click on the item they want to view to see the details of the risk factor. Detailed information of risk factors, including risk factor information, reference information and experimental information, is presented in tables and all the results of the data collection are displayed in this module. If users want to know more about this risk factor, they can click on the PMID in the reference, and we have provided a hyperlink so that users can view the original article.

The advanced search facility allows combined searches. On this page, we have provided five drop-down lists for different types of query: risk factor category drop-down list (includes epidemiological factors, genetic factors, biochemical factors and combination factors), association drop-down list (includes risk factors and protective factors), disease name drop-down list (includes the 14 types of NDDs recorded in the NDDRF), species drop-down list (human and animal) and literature year (from 1984 to 2020). Users can thus search terms individually or in combination, according to their needs.



3. Items in the database

Attributes

Description

RF_ID:

Risk factor ID

RF_category:

risk factor category,such as genetic factor

RF_Group:

Population of risk factor,such as Han Chinese population

RF_Condition:

Prerequisites for becoming a risk factor

RF_Association:

Risk factor of Protective factor

Pubmed ID:

Pubmed ID

Year:

Year of article

RF_name:

Risk factor name

Comorbidity:

Comorbidity,such as Gaucher disease.

Famliy history:

Famliy history,such as non-hereditary idiopathic PD

Key sentence:

Concluding key sentences in the article

Polymorphisms Category:

such as SNP

Gene_name:

Gene name

Case:

Case information(number,gender,age)

Control:

Control information(number,gender,age)

Life style:

such as creatine 5 grams twice daily or to placebo for 5 years;caffeine intake during the prior week

Gender:

Gender of risk factor