JMIR Publications

ABSTRACT

Background:

National and Ethnic Mutation Frequency Databases (NEMDBs) play a crucial role in documenting gene variations across populations, offering invaluable insights for gene mutation research and the advancement of precision medicine. These databases provide an essential resource for understanding genetic diversity and its implications for health and disease across different ethnic groups.

Objective:

This study systematically evaluates 42 NEMDBs to (a) quantify gaps in standardization (70% non-standard formats, 50% outdated data), (b) propose AI/LOD solutions for interoperability, and (c) highlight clinical implications for precision medicine across NEMDB’s.

Methods:

A systematic approach was employed to assess the databases based on several criteria, including data collection methods, system design, and querying mechanisms. We analyzed the accessibility and user-centric features of each database, noting their ability to integrate with other systems and their role in advancing genetic disorder research. The review also addressed standardization and data quality challenges prevalent in current NEMDBs.

Results:

The analysis revealed significant issues across the databases, with 70% lacking standardized data formats and 60% having notable gaps in the cross-comparison of genetic variations between ethnic groups. Furthermore, 50% of the databases contained incomplete or outdated data, limiting their clinical utility. However, databases developed on open-source platforms such as LOVD showed a 40% increase in usability for researchers, highlighting the benefits of using flexible, open-access systems.

Conclusions:

We propose cloud-based platforms and LOD frameworks to address critical gaps in standardization (70% of databases) and outdated data (50%) alongside AI-driven models for improved interoperability. These solutions prioritize user-centric design to effectively serve clinicians, researchers, and public stakeholders. Clinical Trial: none