Building an integrated neurodegenerative disease database at an academic health center.

BACKGROUND: It is becoming increasingly important to study common and distinct etiologies, clinical and pathological features, and mechanisms related to neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and frontotemporal lobar degeneration. These comparative studies rely on powerful database tools to quickly generate data sets that match diverse and complementary criteria set by them.
METHODS: In this article, we present a novel integrated neurodegenerative disease (INDD) database, which was developed at the University of Pennsylvania (Penn) with the help of a consortium of Penn investigators. Because the work of these investigators are based on Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and frontotemporal lobar degeneration, it allowed us to achieve the goal of developing an INDD database for these major neurodegenerative disorders. We used the Microsoft SQL server as a platform, with built-in "backwards" functionality to provide Access as a frontend client to interface with the database. We used PHP Hypertext Preprocessor to create the "frontend" web interface and then used a master lookup table to integrate individual neurodegenerative disease databases. We also present methods of data entry, database security, database backups, and database audit trails for this INDD database.
RESULTS: Using the INDD database, we compared the results of a biomarker study with those using an alternative approach by querying individual databases separately.
CONCLUSIONS: We have demonstrated that the Penn INDD database has the ability to query multiple database tables from a single console with high accuracy and reliability. The INDD database provides a powerful tool for generating data sets in comparative studies on several neurodegenerative diseases.