A systematic multilevel analysis of age-dependent behavioural decline using data from the International Mouse Phenotyping Consortium

Background

Physiological aging is a multifaceted biological process profoundly impacting brain function and behaviour. Age-associated alterations in neural circuit dynamics, neurotransmitter systems, and systemic physiology lead to reduced adaptability, slowing of neuronal processing, and increased vulnerability to neurodegenerative and neuropsychiatric disorders. Elucidating the mechanisms shaping these aging trajectories is essential for understanding brain resilience and disease susceptibility across lifespan. Mouse models provide a powerful platform for such investigations, as many behavioural, physiological, and neural features of aging are conserved between mice and humans. Despite extensive behavioural phenotyping, the genetic determinants underlying age-dependent functional decline remain incompletely understood.

The International Mouse Phenotyping Consortium (IMPC) is a global effort to systematically determine the function of every protein-coding gene for both sexes through standardized gene disruption and harmonized phenotyping pipelines. To date, over 10,000 mutant lines have been characterized across behavioural, neurological, and physiological domains. While IMPC phenotyping is primarily conducted in early adulthood, available data from late adult mice enable investigation of genetic influences on aging-related trajectories. Integrating these data allows interrogation of how specific gene disruptions modulate functional decline or resilience with age and supports translational comparisons with human aging and brain disorders across the neurological–psychiatric spectrum. This work is conducted within the Infrastructure Model Systems of the German Center for Mental Health (DZPG).

Objectives

The objectives of this study are to: (1) characterize age-related changes in locomotor, behavioural, and physiological parameters in wild-type mice; (2) identify phenotypes that robustly capture physiological and functional aging; (3) determine how specific gene disruptions alter aging trajectories using mutant mouse lines; and (4) integrate cross-species comparisons between mouse and human to prioritize candidate genes relevant for brain development, maintenance, and age-associated dysfunction.

Methods

We analyse wild-type and knockout mouse data generated by the IMPC across two age groups: early adulthood (approximately 12–16 weeks) and late adulthood (≥49 weeks). Standardized behavioural, locomotor, and physiological parameters are compared between age groups and across genotypes using established statistical models to assess age effects and genotype‑by‑age interactions, while accounting for sex. Phenotypes demonstrating consistent age-associated changes are prioritized as candidate markers of physiological and functional aging.

Genes associated with altered aging trajectories are further investigated using enrichment analyses to identify overrepresented biological processes, pathways, and disease associations. These analyses provide functional context for the identified gene sets and support cross‑species comparisons with human aging and neurological disorder–related datasets.

Results

The analysis is ongoing and preliminary results will be presented at the conference.

Conclusions

This large-scale, multimodal analysis of IMPC data can identify key behavioural and physiological markers of aging and reveal previously unrecognized genetic modulators of age-dependent change. By linking gene disruption to altered aging trajectories, this study can elucidate conserved mechanisms contributing to brain resilience and vulnerability. The integration of standardized phenotyping, genetics, and computational analytics provides a powerful framework for dissecting the biology of aging with direct relevance to neuropharmacology, neuropsychiatric research, and the identification of novel therapeutic targets for age-related brain disorders, aligned with DZPG priorities in translational mental research.

References

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