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 multidimensional
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