Back

Identification of cell type-specific gene targets underlying thousands of rare diseases and subtraits

Murphy, K. B.; Gordon-Smith, R.; Chapman, J.; Otani, M.; Schilder, B. M.; Skene, N. G.

2023-02-17 genetic and genomic medicine
10.1101/2023.02.13.23285820 medRxiv
Show abstract

Rare diseases (RDs) are an extremely heterogeneous and underserved category of medical conditions. While the majority of RDs are strongly genetic, it remains largely unknown via which physiological mechanisms genetics cause RD. Therefore, we sought to systematically characterise the cell type-specific mechanisms underlying all RD phenotypes with a known genetic cause by leveraging the Human Phenotype Ontology and transcriptomic single-cell atlases of the entire human body from embryonic, foetal, and adult samples. In total we identified significant associations between 201 cell types and 9,575/11,028 (86.7%) unique phenotypes across 8,628 RDs. This greatly the collective knowledge of RD phenotype-cell type mechanisms. Next, we sought to systematically identify phenotypes in which the application of these results would have the greatest clinical impact based on metrics of severity (e.g. lethality, motor/mental impairment) and compatibility with gene therapy (e.g. filtering out physical malformations). Furthermore, we have made these results entirely reproducible and freely accessible to the global community to maximise their impact, including an interactive web portal (https://neurogenomics-ukdri.dsi.ic.ac.uk/). To summarise, this work represents a significant step forward in the mission to treat patients across an extremely diverse spectrum of serious RDs.

Published in Genome Medicine (predicted rank #1) · training set

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.