, Volume 221, Issue 2, pp 297-315,
Open Access This content is freely available online to anyone, anywhere at any time.
Date: 24 Nov 2011

Evaluating genetic markers and neurobiochemical analytes for fluoxetine response using a panel of mouse inbred strains

Abstract

Rationale

Identification of biomarkers that establish diagnosis or treatment response is critical to the advancement of research and management of patients with depression.

Objective

Our goal was to identify biomarkers that can potentially assess fluoxetine response and risk to poor treatment outcome.

Methods

We measured behavior, gene expression, and the levels of 36 neurobiochemical analytes across a panel of genetically diverse mouse inbred lines after chronic treatment with water or fluoxetine.

Results

Glyoxylase 1 (GLO1) and guanine nucleotide-binding protein 1 (GNB1) mostly account for baseline anxiety-like and depressive-like behavior, indicating a common biological link between depression and anxiety. Fluoxetine-induced biochemical alterations discriminated positive responders, while baseline neurobiochemical differences differentiated negative responders (p < 0.006). Results show that glial fibrillary acidic protein, S100 beta protein, GLO1, and histone deacetylase 5 contributed most to fluoxetine response. These proteins are linked within a cellular growth/proliferation pathway, suggesting the involvement of cellular genesis in fluoxetine response. Furthermore, a candidate genetic locus that associates with baseline depressive-like behavior contains a gene that encodes for cellular proliferation/adhesion molecule (Cadm1), supporting a genetic basis for the role of neuro/gliogenesis in depression.

Conclusion

We provided a comprehensive analysis of behavioral, neurobiochemical, and transcriptome data across 30 mouse inbred strains that has not been accomplished before. We identified biomarkers that influence fluoxetine response, which, altogether, implicate the importance of cellular genesis in fluoxetine treatment. More broadly, this approach can be used to assess a wide range of drug response phenotypes that are challenging to address in human samples.

Cristina S. Benton, Brooke H. Miller contributed equally to the manuscript.