GREGoR: Accelerating Genomics for Rare Diseases

TL;DR

GREGoR is a collaborative effort that leverages genomics technologies and data sharing to improve diagnosis of rare diseases, addressing the challenge of unsolved cases despite advances in sequencing.

Contribution

It introduces a large-scale, standardized genomics research framework and dataset for rare diseases, facilitating global data sharing and methodological advancements.

Findings

Analysis of ~7500 individuals from ~3000 families.

Identification of novel genetic variants associated with rare diseases.

Enhanced understanding of genetic underpinnings in unsolved cases.

Abstract

Rare diseases are collectively common, affecting approximately one in twenty individuals worldwide. In recent years, rapid progress has been made in rare disease diagnostics due to advances in DNA sequencing, development of new computational and experimental approaches to prioritize genes and genetic variants, and increased global exchange of clinical and genetic data. However, more than half of individuals suspected to have a rare disease lack a genetic diagnosis. The Genomics Research to Elucidate the Genetics of Rare Diseases (GREGoR) Consortium was initiated to study thousands of challenging rare disease cases and families and apply, standardize, and evaluate emerging genomics technologies and analytics to accelerate their adoption in clinical practice. Further, all data generated, currently representing ~7500 individuals from ~3000 families, is rapidly made available to researchers worldwide via the Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL) to catalyze global efforts to develop approaches for genetic diagnoses in rare diseases (https://gregorconsortium.org/data). The majority of these families have undergone prior clinical genetic testing but remained unsolved, with most being exome-negative. Here, we describe the collaborative research framework, datasets, and discoveries comprising GREGoR that will provide foundational resources and substrates for the future of rare disease genomics.