Cell type-specific contextualisation of the human phenome
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
Background
Rare diseases (RDs) are a highly heterogeneous and underserved group of conditions. Most RDs have a strong genetic basis but their causal pathophysiological mechanisms remain poorly understood, limiting the development of targeted therapies.
Methods
We systematically characterised the cell type-specific mechanisms underlying all genetically defined RD phenotypes by integrating the Human Phenotype Ontology (HPO) with whole-body single-cell transcriptomic atlases from embryonic, foetal, and adult samples. Associations were validated against orthogonal biomedical knowledge graphs and then prioritised by strength of supporting evidence, clinical severity, and gene-therapy compatibility.
Results
We identified significant associations between 201 cell types and 9,575/11,028 (86.7%) phenotypes across 8,628 RDs, substantially expanding knowledge of phenotype-cell type links. Prioritisation by severity (e.g. lethality, motor or mental impairment) and gene-therapy compatibility (e.g. cell type specificity, postnatal treatability) identified candidate phenotypes and cell types for therapeutic targeting.
Conclusions
We present a scalable, reproducible framework for phenome-wide, cell type-specific mechanism prediction in rare diseases, providing a major step toward systematic therapeutic development for patients across a broad spectrum of serious RDs.
Software and data availability
Interactive web portal: https://neurogenomics-ukdri.dsi.ic.ac.uk/. R packages introduced in this study: KGExplorer (https://github.com/neurogenomics/KGExplorer), HPOExplorer (https://github.com/neurogenomics/HPOExplorer), and MSTExplorer (https://github.com/neurogenomics/MSTExplorer). Manuscript analyses and reproducibility code: https://github.com/neurogenomics/rare_disease_celltyping.
Rare diseases (RDs) are a highly heterogeneous and underserved group of conditions. Most RDs have a strong genetic basis but their causal pathophysiological mechanisms remain poorly understood, limiting the development of targeted therapies.
Methods
We systematically characterised the cell type-specific mechanisms underlying all genetically defined RD phenotypes by integrating the Human Phenotype Ontology (HPO) with whole-body single-cell transcriptomic atlases from embryonic, foetal, and adult samples. Associations were validated against orthogonal biomedical knowledge graphs and then prioritised by strength of supporting evidence, clinical severity, and gene-therapy compatibility.
Results
We identified significant associations between 201 cell types and 9,575/11,028 (86.7%) phenotypes across 8,628 RDs, substantially expanding knowledge of phenotype-cell type links. Prioritisation by severity (e.g. lethality, motor or mental impairment) and gene-therapy compatibility (e.g. cell type specificity, postnatal treatability) identified candidate phenotypes and cell types for therapeutic targeting.
Conclusions
We present a scalable, reproducible framework for phenome-wide, cell type-specific mechanism prediction in rare diseases, providing a major step toward systematic therapeutic development for patients across a broad spectrum of serious RDs.
Software and data availability
Interactive web portal: https://neurogenomics-ukdri.dsi.ic.ac.uk/. R packages introduced in this study: KGExplorer (https://github.com/neurogenomics/KGExplorer), HPOExplorer (https://github.com/neurogenomics/HPOExplorer), and MSTExplorer (https://github.com/neurogenomics/MSTExplorer). Manuscript analyses and reproducibility code: https://github.com/neurogenomics/rare_disease_celltyping.
Date Issued
2026-07-28
Date Acceptance
2026-06-04
Citation
Genome Medicine, 2026, 18
ISSN
1756-994X
Publisher
BMC
Journal / Book Title
Genome Medicine
Volume
18
Copyright Statement
© The Author(s) 2026. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
License URL
Identifier
10.1186/s13073-026-01692-0
Subjects
Rare disease
Human phenotype ontology
Single-cell transcriptomics
Cell type specificity
Phenotype-cell type associations
Gene therapy
Therapeutic target identification
Publication Status
Published
Article Number
ARTN 113
Date Publish Online
2026-06-26