Related Experiment Video
Updated: Jun 4, 2025

In Vivo Modeling of the Morbid Human Genome using Danio rerio
Published on: August 24, 2013
Quantitative natural history modeling of HPDL-related disease based on cross-sectional data reveals
Julian E Alecu1, Amy Tam2, Silja Richter3
1Movement Disorders Program, Department of Neurology and F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA; Medical Faculty of the Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany.
Purpose:
Biallelic HPDL variants have been identified as the cause of a progressive childhood-onset movement disorder, with a broad clinical spectrum from severe neurodevelopmental disorder to juvenile-onset pure hereditary spastic paraplegia type 83. This study aims at delineating the geno- and phenotypic spectra of patients with HPDL-related disease, quantitatively modeling the natural history, and uncovering genotype-phenotype associations.
Methods:
A cross-sectional analysis of 90 published and 1 novel case was performed, using a Human-Phenotype-Ontology-based approach. Unsupervised phenotypic clustering was used alongside in silico analyses to identify distinct patient subgroups.
Results:
The study models the natural history of the HPDL-related disease in a global cohort, clarifying the molecular and phenotypic spectrum and identifying 3 distinct subgroups characterized by differences in onset, clinical trajectories, and survival. It establishes genotype-phenotype associations, showing that the presence of moderately pathogenic missense variants in 1 allele leads to a milder, spastic paraplegic phenotype with later disease onset, whereas biallelic, highly pathogenic missense or truncating variants are associated with a more severe phenotype and reduced life span.
Conclusion:
Quantitative and unbiased natural history modeling in HPDL-related disease reveals significant genotype-phenotype associations, providing a foundation for variant interpretation, anticipatory guidance, and choice of outcome measures in future prospective and functional studies.
More Related Videos
Related Concept Videos
Genome-wide Association Studies-GWAS
GWAS does not require the identification of the target gene involved in...
Pleiotropy
Pedigree Analysis
Mechanistic Models: Compartment Models in Individual and Population Analysis
Genetic Lingo
Epistasis

