Xiang Gao, Dan Li, Weiye Liu, Yingshuang Lu, Zeping Shao, Huan Lv, Yan Zhang, Shuo Wang. 2026. Individual anxiety assessment in zebrafish: development and validation of a sex-specific Individual Anxiety Scoring System (IASS). Zoological Research. DOI: 10.24272/j.issn.2095-8137.2026.036
Citation: Xiang Gao, Dan Li, Weiye Liu, Yingshuang Lu, Zeping Shao, Huan Lv, Yan Zhang, Shuo Wang. 2026. Individual anxiety assessment in zebrafish: development and validation of a sex-specific Individual Anxiety Scoring System (IASS). Zoological Research. DOI: 10.24272/j.issn.2095-8137.2026.036

Individual anxiety assessment in zebrafish: development and validation of a sex-specific Individual Anxiety Scoring System (IASS)

  • Anxiety disorders represent a significant global health challenge, imposing a substantial societal burden. Preclinical models such as the Novel Tank Test (NTT) are crucial for research but are limited to group-level comparisons, masking individual heterogeneity. To bridge this gap, we developed a sex-specific Individual Anxiety Scoring System (IASS) for zebrafish (<i>Danio rerio</i>), based on a foundational analysis of baseline anxiety and sex differences in a cohort of 240 individuals. Principal component analysis (PCA) was employed to identify key sex-specific behavioral parameters from the NTT, which were integrated into a single, quantitative anxiety score. In agreement analyses, the IASS achieved an agreement rate exceeding 96% with the traditional NTT in both sexes. It successfully quantified individual anxiety shifts and identified inter-individual variability in responses to caffeine exposure. Integrated transcriptomic and IASS score analysis using Weighted Gene Co-expression Network Analysis (WGCNA) identified anxiety score-associated gene modules enriched in known anxiety-related pathways, providing exploratory evidence that IASS scores are associated with anxiety-related transcriptional features. In summary, this work established the IASS as a framework for individual-level anxiety assessment that facilitates the integration of behavioral phenotypes with molecular features and provides insights that may be obscured by conventional group-level analyses.
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