Testing the validity of c-fos expression profiling to aid the therapeutic classification of psychoactive drugs

Rationale. Different stimuli, including pharmacological stimuli, induce different neuroanatomical profiles of c-fos expression. Can these profiles be used in classifying psychoactive drugs and predicting therapeutic utility? <LF>Objective. To test the validity of c-fos expression profiling to aid therapeutic classification. Methods. Anxiolytics, antidepressants, antipsychotics and psychostimulants were compared. (i) A meta-analysis was performed and profiles compiled from literature reports of changes in c-fos expression in rat brain regions, measured by in situ hybridisation histochemistry or immunohistochemistry, after acute injection of psychoactive drugs. (ii) Male rat brains were profiled for changes in c-fos mRNA expression induced by acute injection of psychoactive drugs. Results. (i) The meta-analysis showed that anxiolytics activate few (mostly stress-related) brain regions; antidepressants activate more regions, including the central amygdaloid nucleus; antipsychotics activate more regions still, including the nucleus accumbens and striatal areas; and psychostimulants activate the greatest number of all, including the most cortical regions (especially the piriform cortex). Profiles also varied within drug classes. (ii) Our experimental profiles confirmed and extended meta-analysis profiles, showing more downregulation. (iii) Sites activated by mirtazapine (an antidepressant not previously profiled) matched those of the antidepressant imipramine. <LF>Conclusions. (i) Differences between drug classes support their classification by means of c-fos profiling. Differences within classes may reflect mechanistic variations. (ii) Greater downregulation in our experiments might be because of inclusion of low, clinically relevant, drug doses and fuller coverage of brain regions. (iii) The agreement between mirtazapine and imipramine increases our confidence in the validity of c-fos expression profiling to aid drug classification and predict therapeutic utility.