JMIR Publications

ABSTRACT

Background:

Dry eye disease (DED) is a common ocular condition with diverse and heterogeneous symptoms. Current treatment standards of DED include the post-facto management of associated symptoms through topical eye drops. However, there is a need for predictive, preventive, personalized, and participatory medicine (P4 medicine). The DryEyeRhythm mobile health (mHealth) application enables real-time data collection regarding environmental, lifestyle, host, and digital factors in a patient's daily environment. Combining these data with genetic information from biobanks could enhance our understanding of individual variations and develop personalized treatment strategies for DED.

Objective:

This study integrates digital data from the DryEyeRhythm smartphone application with the Tohoku Medical Megabank database to create a comprehensive database that elucidates the interplay between multifactorial factors and the onset and progression of DED.

Methods:

In this prospective observational cohort study, 1,200 and 1,000 participants with data in the Tohoku Medical Megabank database will be recruited from the Community Support Center of Sendai during the discovery and replication stages, respectively. The stages span from March 2021 and March 2027. Participants will provide demographic data, medical histories, lifestyle information, DED symptoms, and maximum blink interval at baseline and after 30 days. The primary outcome will assess the association between genetic polymorphisms and DED using a genome-wide association study.

Results:

The findings will be analyzed by September 2026.

Conclusions:

This study’s approach demonstrates the potential of smartphone applications in enhancing biobank data and improving the understanding of multifactorial DED. Clinical Trial: Not applicable.