The genome-wide expression effects of escitalopram and its relationship to neurogenesis, hippocampal volume, and antidepressant response.
Timothy R PowellTytus MurphySimone de JongSang Hyuck LeeKatherine E TanseyKaren HodgsonRudolf UherJack PriceSandrine ThuretGerome BreenPublished in: American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics (2017)
Antidepressant-induced hippocampal neurogenesis (AHN) is hypothesized to contribute to increases in hippocampal volume among major depressive disorder patients after long-term treatment. Furthermore, rodent studies suggest AHN may be the cellular mechanism mediating the therapeutic benefits of antidepressants. Here, we perform the first investigation of genome-wide expression changes associated with AHN in human cells. We identify gene expression networks significantly activated during AHN, and we perform gene set analyses to probe the molecular relationship between AHN, hippocampal volume, and antidepressant response. The latter were achieved using genome-wide association summary data collected from 30,717 individuals as part of the ENIGMA Consortium (genetic predictors of hippocampal volume dataset), and data collected from 1,222 major depressed patients as part of the NEWMEDS Project (genetic predictors of response to antidepressants dataset). Our results showed that the selective serotonin reuptake inhibitor, escitalopram evoked AHN in human cells; dose-dependently increasing the differentiation of cells into neuroblasts, as well as increasing gliogenesis. Activated genome-wide expression networks relate to axon and microtubule formation, and ribosomal biogenesis. Gene set analysis revealed that gene expression changes associated with AHN were nominally enriched for genes predictive of hippocampal volume, but not for genes predictive of therapeutic response.
Keyphrases
- genome wide
- major depressive disorder
- dna methylation
- gene expression
- bipolar disorder
- copy number
- cerebral ischemia
- end stage renal disease
- poor prognosis
- newly diagnosed
- chronic kidney disease
- prognostic factors
- peritoneal dialysis
- electronic health record
- temporal lobe epilepsy
- cell proliferation
- genome wide association
- endothelial cells
- single cell
- big data
- deep learning
- cell death
- machine learning
- smoking cessation
- genome wide analysis