GoFCards: an integrated database and analytic platform for gain of function variants in humans

Area of Science:

• Genetics
• Genomics
• Molecular Biology

Background:

• Gain-of-function (GOF) variants alter protein functions, playing a key role in disease mechanisms.
• Identifying and analyzing pathogenic GOF variants is challenging due to fragmented data and database limitations.
• Accessing critical genetic information for GOF variants requires efficient tools.

Purpose of the Study:

• To develop a comprehensive database for accessing and analyzing human GOF variants.
• To provide a user-friendly platform for geneticists and clinicians to interpret GOF variants.
• To facilitate genetic research by simplifying the process of GOF variant identification and prioritization.

Main Methods:

• Manual literature review to identify 3089 single-nucleotide variants and 72 insertions/deletions in 579 genes linked to 1299 diseases.
• Integration of identified variants with 3.5 million predicted GOF variants.
• Development of a proprietary scoring system to prioritize GOF variants based on evidence and predictive scores.
• Creation of the GoFCards database (http://www.genemed.tech/gofcards) with data from over 150 sources.

Main Results:

• Pinpointed 3089 single-nucleotide variants and 72 insertions/deletions in 579 genes associated with 1299 diseases.
• Integrated manually curated and predicted GOF variants, creating a comprehensive dataset.
• Developed GoFCards, a database offering variant-level and gene-level annotations from >150 sources.
• Implemented a scoring system to prioritize GOF variants and aid in their interpretation.

Conclusions:

• GoFCards provides an efficient and accessible platform for geneticists and clinicians to obtain and analyze human GOF variants.
• The database simplifies the interpretation of GOF variants, empowering users with limited bioinformatic skills.
• GoFCards aims to advance genetic research by improving access to and understanding of critical GOF variant information.