Despite significant strides in genetic research, we lack a clear understanding of whether many rare diseases may have genetic origins, and of what those origins may be. However, a powerful new metadata resource, called Rareservoir, provides a promising path forward toward potential breakthroughs. With over 77,000 genomes analyzed through the 100,000 Genomes Project1, the unique Rareservoir database serves as a comprehensive repository of rare variant genotypes and associated phenotypes, offering a valuable resource for unraveling the enigmas of rare diseases.

Recently published work2 describing Rareservoir covers the use of a Bayesian genetic association method called BeviMed. This sophisticated analytical tool scours the vast genomic data to infer associations between genes and specific rare disease classes assigned by clinicians. Through BeviMed, researchers have identified both known and previously undiscovered genetic associations in the rare disease space.

Researchers have reported work focusing on exonic and splicing single-nucleotide variants. However, the exploration of structural variants and rare variation in noncoding genes represent potential avenues for future research which could lead to the discovery of even more genetic associations underlying rare diseases. Tools such as directional Genomic Hybridization (dGH), which generate single-cell data about structural variants without a bioinformatics intermediate have the potential to play a role.

Rareservoir’s efficient storage and organization of large-scale genomic data facilitate a more streamlined approach to genetic analysis of rare diseases, providing a valuable framework for future investigations. These characteristics have aided researchers in confirming known rare disease associations, and also in bringing to light previously unidentified links between specific genes and rare diseases. Through meticulous validation and experimental work, the researchers have solidified the evidence supporting these genetic associations.

Some of the known limitations potentially influencing the data include the predominantly European ancestry of the participants and the focus on SNVs and indels in coding genes. Despite this, researchers report successfully linking specific genes to 269 rare disease classes, potentially a huge step forward for individuals experiencing health problems whose causes neither they nor their physicians fully understand.

The work that went into creating and applying Rareservoir represents a leap in the ongoing quest to unravel the genetic underpinnings of rare diseases. The Rareservoir database, coupled with advanced analytical methods like BeviMed, offers a robust platform for researchers to continue pushing forward within the realm of rare genetic disorders. These advancements augur improved diagnostics, for at least some individuals affected by rare diseases, which may in turn unlock funding streams to further research and healthcare resources.



  1. 100,000 Genomes Project Pilot Investigators. (2021). 100,000 genomes pilot on rare-disease diagnosis in health care—preliminary report. New England Journal of Medicine, 385(20), 1868-1880.
  2. Greene, D., Genomics England Research Consortium, Pirri, D., Frudd, K., Sackey, E., Al-Owain, M., … & Turro, E. (2023). Genetic association analysis of 77,539 genomes reveals rare disease etiologies. Nature Medicine, 29(3), 679-688.