Global state measures of the dentate gyrus gene expression system predict antidepressant-sensitive behaviors.
BACKGROUND
Selective serotonin reuptake inhibitors (SSRIs) such as fluoxetine are the most common form of medication treatment for major depression. However, approximately 50% of depressed patients fail to achieve an effective treatment response. Understanding how gene expression systems respond to treatments may be critical for understanding antidepressant resistance.


METHODS
We take a novel approach to this problem by demonstrating that the gene expression system of the dentate gyrus responds to fluoxetine (FLX), a commonly used antidepressant medication, in a stereotyped-manner involving changes in the expression levels of thousands of genes. The aggregate behavior of this large-scale systemic response was quantified with principal components analysis (PCA) yielding a single quantitative measure of the global gene expression system state.


RESULTS
Quantitative measures of system state were highly correlated with variability in levels of antidepressant-sensitive behaviors in a mouse model of depression treated with fluoxetine. Analysis of dorsal and ventral dentate samples in the same mice indicated that system state co-varied across these regions despite their reported functional differences. Aggregate measures of gene expression system state were very robust and remained unchanged when different microarray data processing algorithms were used and even when completely different sets of gene expression levels were used for their calculation.


CONCLUSIONS
System state measures provide a robust method to quantify and relate global gene expression system state variability to behavior and treatment. State variability also suggests that the diversity of reported changes in gene expression levels in response to treatments such as fluoxetine may represent different perspectives on unified but noisy global gene expression system state level responses. Studying regulation of gene expression systems at the state level may be useful in guiding new approaches to augmentation of traditional antidepressant treatments.
Departments of Psychiatry and Neuroscience, Columbia University, New York, New York, United States of America.
Benjamin A
BA
Samuels
Departments of Psychiatry and Neuroscience, Columbia University, New York, New York, United States of America.
E David
ED
Leonardo
Departments of Psychiatry and Neuroscience, Columbia University, New York, New York, United States of America.
Alex
A
Dranovsky
AstraZeneca Pharmaceuticals, CNS Discovery, Wilmington, Delaware, United States of America.
Amanda
A
Williams
AstraZeneca Pharmaceuticals, CNS Discovery, Wilmington, Delaware, United States of America.
Erik
E
Wong
Center for Neurobiology and Behavior, Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
Addie May I
AM
Nesbitt
Center for Neurobiology and Behavior, Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
Richard D
RD
McCurdy
Departments of Psychiatry and Neuroscience, Columbia University, New York, New York, United States of America.
Rene
R
Hen
Center for Neurobiology and Behavior, Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
Mark
M
Alter
D000818:Animals; D000928:Antidepressive Agents / Q000494:pharmacology / Q000627:therapeutic use*; D001522:Behavior, Animal; D018891:Dentate Gyrus / Q000187:drug effects / Q000378:metabolism* / Q000473:pathology; D003863:Depression / Q000188:drug therapy / Q000235:genetics; D004195:Disease Models, Animal; D005473:Fluoxetine / Q000494:pharmacology / Q000627:therapeutic use; D005786:Gene Expression Regulation / Q000187:drug effects; D008297:Male; D051379:Mice; D008810:Mice, Inbred C57BL; D025341:Principal Component Analysis; D015203:Reproducibility of Results; D015398:Signal Transduction / Q000187:drug effects / Q000235:genetics
D000928:Antidepressive Agents; D005473:Fluoxetine