Abstract
Purpose::
To develop a bioinformatic system to capture and share detailed phenotypic data in ocular disorders to facilitate identification of novel phenotypic features and analysis of phenotypic-genotypic correlations.
Methods::
We have designed and implemented a phenotypic repository to manage detailed phenotypic and clinical data for integration with molecular results for use in research. The Collaborative Phenotypic Database (CPDB) system is a collection of Java applications, web-interfaces, API's, and relational databases for storing and sharing detailed phenotypic data. Phenotypic data is collected via "forms" that are dynamic, clinician-specified collections of information derived from our experiences in working with AMD patients. The CPDB system is currently utilizing a custom 35mm slide scanner to digitize clinical photographs for AMD patients.
Results::
We are currently using the CPDB system to capture demographic information, clinical diagnosis data and supporting detailed phenotypic data for 400 individuals with AMD. This system provides a valuable resource for on-going molecular studies including genotyping, mutation screening, and expression analyses. We have acquired images, clinical data (more than 50 fields) and grading information from expert reviewers from 400 AMD patients and placed them in a relational database. The data are more flexibly accessible and interpretable than they would be if gathered and stored by more conventional means.
Conclusions::
Preliminary studies indicate that the high-throughput capture of detailed retina images for phenotypic-molecular correlations are both feasible and valuable for research. Furthering our understanding and development of treatments for ocular diseases with the availability of mature genomic data depends upon a sophisticated intermingling of clinical research and modern molecular genetics. This work describes the development a database system, and attendant interfaces for data entry and information retrieval, to allow clinical researchers to ask questions that span clinical, demographic, patient history, imaging data, and association of phenotype with molecular assays. This will eventually lead to the integration of molecular data (gene expression, genotypic data, proteomics) with detailed phenotypic data.
Keywords: gene screening • age-related macular degeneration • candidate gene analysis