PUBLICATION
AI-assisted phenotyping in a zebrafish hypophosphatasia model enables early and precise detection of skeletal alterations
- Authors
- Hark, R., Zürlein, S., Nguyen, V.T., Gust, G., Hekel, L., Liedtke, D.
- ID
- ZDB-PUB-250918-8
- Date
- 2025
- Source
- Scientific Reports 15: 3257832578 (Journal)
- Registered Authors
- Liedtke, Daniel
- Keywords
- ALPL, Deep learning, Explainable AI, Hypophosphatasia, Phenotype classification, Vision Transformers, Zebrafish
- MeSH Terms
-
- Phenotype
- Hypophosphatasia*/diagnosis
- Hypophosphatasia*/genetics
- Hypophosphatasia*/pathology
- Disease Models, Animal
- Animals, Genetically Modified
- Animals
- Artificial Intelligence*
- Zebrafish*
- Bone and Bones*/diagnostic imaging
- Bone and Bones*/pathology
- PubMed
- 40962875 Full text @ Sci. Rep.
Citation
Hark, R., Zürlein, S., Nguyen, V.T., Gust, G., Hekel, L., Liedtke, D. (2025) AI-assisted phenotyping in a zebrafish hypophosphatasia model enables early and precise detection of skeletal alterations. Scientific Reports. 15:3257832578.
Abstract
Hypophosphatasia (HPP) is a rare genetic disorder mainly affecting bone and tooth mineralization in patients due to ALPL gene mutations. Understanding genotype-phenotype correlations in HPP remains challenging due to different severities and the disease's heterogeneity. To address this, we established a novel zebrafish animal model (alplwue7), which mimics severe HPP disease forms. To bypass limitations in human-based phenotypic classification of skeletal alterations in this transgenic line, we developed and trained an artificial intelligence (AI) model capable of image-based classification with 68% accuracy-an improvement of 79% over manual classification. Our AI model could successfully identify early developmental alterations independent of altered image magnification, coloration quality and executing scientists. Using attention rollout, we further visualized AI decision-making, revealing not only expected focus on early bone structures but also unexpected emphasis on the otoliths-parts of the zebrafish's hearing and balancing organ. We see applications of our AI system in analyzing other skeletal disorder models as well as in providing an unbiased, high-throughput phenotypic rescue quantification assay for potential drug screening applications in zebrafish larvae. Overall, our findings establish an integrated platform for studying HPP and open new avenues for AI-assisted phenotyping and therapeutic discovery.
Genes / Markers
Expression
Phenotype
Mutations / Transgenics
Human Disease / Model
Sequence Targeting Reagents
Fish
Orthology
Engineered Foreign Genes
Mapping