GA4GH phenopacket-driven characterization of genotype-phenotype correlations in Mendelian disorders.
Document Type
Article
Publication Date
1-8-2026
Original Citation
Rekerle L,
Danis D,
Rehburg F,
Graefe A,
Bily V,
Caballero-Oteyza A,
Cacheiro P,
Chimirri L,
Chong J,
Connelly E,
de Vries B,
Dingemans A,
Duyzend M,
Freiberger T,
Gehle P,
Groza T,
Hansen P,
Jacobsen J,
Klocperk A,
Ladewig M,
Love M,
Marcello A,
Mordhorst A,
Munoz-Torres M,
Reese J,
Schuetz C,
Smedley D,
Strauss T,
Vladyka O,
Zocche D,
Thun S,
Mungall C,
Haendel M,
Robinson P.
GA4GH phenopacket-driven characterization of genotype-phenotype correlations in Mendelian disorders. Am J Hum Genet. 2026;113(1):57–70.
Keywords
JMG, Humans, Phenotype, Genetic Diseases, Inborn, Genetic Association Studies, Software, Genotype, Genomics
JAX Source
Am J Hum Genet. 2026;113(1):57–70.
ISSN
1537-6605
PMID
41443197
DOI
https://doi.org/10.1016/j.ajhg.2025.12.001
Grant
P.N.R. was supported by a Professorship of the Alexander von Humboldt Foundation.
Abstract
Comprehensively characterizing genotype-phenotype correlations (GPCs) in Mendelian disease would create new opportunities for improving clinical management and understanding disease biology. However, heterogeneous approaches to data sharing, reuse, and analysis have hindered progress in the field. We developed Genotype-Phenotype Statistical Evaluation of Associations (GPSEA), a software package that leverages the Global Alliance for Genomics and Health (GA4GH) Phenopacket Schema to represent case-level clinical and genetic data about individuals. GPSEA applies an independent filtering strategy to boost statistical power to detect categorical GPCs represented by Human Phenotype Ontology terms. GPSEA additionally enables visualization and analysis of continuous phenotypes, clinical severity scores, and survival data such as age of onset of disease or clinical manifestations. We applied GPSEA to 85 cohorts with 6,179 previously published individuals with variants in one of 81 genes associated with 122 Mendelian diseases and identified 253 significant GPCs, with 48 cohorts having at least one statistically significant GPC. These results highlight the power of standardized representations of clinical data for scalable discovery of GPCs in Mendelian disease.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.