Markos Michail Chatzigiannis1,2, Hirotaka Shoji2 , Daiki Sato2,3,4 , Keizo Takao, Tsuyoshi Miyakawa2

Behavioral phenotyping across genetically modified mouse strains is extensive but lacks a coherent framework for cross strain comparison. We assembled a large scale dataset comprising more than 10,000 mice from 167 strains across 15 behavioral assays. Multifactor analysis identified two principal dimensions, locomotor activity and learning/memory, that captured the dominant components of cross strain covariance. Clustering along these axes defined six behavioral phenotypes reflecting systematic variation in activity and cognitive performance. To assess clinical relevance, each strain was assigned a disorder association score derived independently of mouse behavioral data from publicly available human gene–disease association resources. Scores were calculated for intellectual disability (ID), autism spectrum disorder (ASD), schizophrenia, and major depressive disorder. Disorder association differed across endotypes, with the strongest and most consistent enrichment observed for ID and ASD. Strains with high ID or ASD burden were concentrated in the same two profiles characterized by comparable learning impairments but opposite locomotor patterns: one predominantly hypoactive and the other hyperactive. Across disorders, specific behavioral indices showed selective correlation with disorder burden, identifying the most informative measures for distinguishing disorder relevant models. These results indicate that clinically distinct diagnostic categories share underlying behavioral structure in mouse models that is not captured by disorder titles alone. This framework enables the interpretation of large scale behavioral data and the evaluation of disorder relevance for genetically modified mice.

1. Department of Systems Medical Science, Fujita Health University Graduate School of Medicine, Kutsukake-cho, Toyoake, Japan 2. Division of Systems Medical Science, Center for Medical Science, Fujita Health University, Kutsukake-cho, Toyoake, Japan 3. Institute for Advanced Academic Research, Chiba University, Chiba, Japan 4. Graduate School of Science, Chiba University, Chiba, Japan