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Pharmaceutical breakthroughs for anxiety have been lackluster in the last half-century. Converging behavior and limbic molecular heterogeneity has the potential to revolutionize biomarker-driven interventions. However, current in vivo models too often deploy artificial systems including directed evolution, mutations and fear induction, which poorly mirror clinical manifestations. Here, we explore transcriptional heterogeneity of the amygdala in isogenic mice using an unbiased multi-dimensional computational approach that segregates intra-cohort reactions to moderate situational adversity and intersects it with high content molecular profiling. We show that while the computational approach stratifies known features of clinical anxiety including nitric oxide, opioid and corticotropin signaling, previously unrecognized druggable biomarkers emerge, such as calpain11 and scand1. Through ingenuity pathway analyses, we further describe a role for neurosteroid estradiol signaling, heat shock proteins, ubiquitin ligases and lipid metabolism. In addition, we report a remarkable behavioral pattern that maps to molecular features of anxiety in mice through counterphobic social attitudes, which manifest as increased, yet spatially distant socialization. These findings provide an unbiased approach for interrogating anxiolytics, and hint toward biomarkers underpinning behavioral and social patterns that merit further exploration.

A computationally inspired in-vivo approach identifies a link between amygdalar transcriptional heterogeneity, socialization and anxiety