Summary: According to a new study, susceptibility to depression can be affected by tweaking specific gene networks.
Source: Mount Sinai Health System
Researchers show how tweaking gene networks can affect susceptibility to depression.
Depression is a disorder that involves changes in coordinated networks of hundreds of genes across key brain circuits, according to a study conducted at the Icahn School of Medicine at Mount Sinai and published May 12 in the journal Neuron.
The Mount Sinai study focuses on identifying how groups of genes operate in functional clusters or ‘gene networks’ to control communication across distinct areas in the brain or ‘brain circuits’ that are changed in depression.
While previous research has suggested that multiple brain regions play a role in depression, how gene activity controls brain circuits has not been investigated. Most studies looked only at how the activity of individual genes is increased or decreased in isolated brain areas in depression without investigating how the relationship between groups of genes is regulated.
The current team identified large gene networks that are altered in depression-like states, focusing on three specific genes that were “master regulators” of the gene networks. None of these genes had previously been linked to depression. The team demonstrated that manipulating the master regulator genes that control these networks could make mice susceptible or resilient to chronic stress.
“Our study is the first to identify and validate the gene networks at play across brain circuits, showing that manipulating their activity alters the activity of brain cells and ultimately, depression behavior,” says Rosemary C. Bagot, PhD, a postdoctoral researcher in the Nestler Laboratory of Molecular Psychiatry at Mount Sinai. “By considering both activity of individual genes and the relationship between groups of genes in several brain regions, our team found that depression may reflect fundamental changes in the architecture of gene networks, rather than just simple increases or decreases in the activity of genes.”
Using a mouse model of human depression, the current research team systematically examined the multifaceted dysregulation of gene networks within several inter-connected brain regions implicated in depression: the nucleus accumbens (NAc); the prefrontal cortex; the amygdala and the ventral hippocampus.
The brain areas studied form a circuit with the NAc at its center, integrating diverse input from the other three regions to drive motivated behavior. The NAc receives information about executive control and attention from the prefrontal cortex; context, space and emotional data from the ventral hippocampus; and information about both learned associations and emotion from the amygdala.
Using RNA sequencing to create a complete picture of gene expression in these interconnected brain regions, the study team found a striking difference in patterns of gene expression between resilient and susceptible mice.
Specifically, researchers found an opposing relationship between the prefrontal cortex and the ventral hippocampus. By manipulating master regulators of key gene networks within each of these brain regions, they found a key role for the ventral hippocampus in making mice susceptible to depression, whereas the prefrontal cortex was important in making mice resilient.
“Our study is unique in that we took information about coordinated gene networks involved in depression and then actually went back and manipulated these networks within animals to conclusively show that the networks regulate depression-like behavior,” says Dr. Bagot.
The research team is now investigating how to target these gene networks with drugs to make mice that are prone to depression more resilient, as a strategy to discover novel, effective treatments for depression in humans.
“We don’t fully understand how current antidepressant drugs work and many patients don’t respond well to treatment,” says Eric Nestler, MD, PhD, Nash Family Professor of Neuroscience and Director of the Friedman Brain Institute at Mount Sinai. “The hope is that we can develop more effective treatments by first understanding what is actually happening in the brain in depression. This study’s findings suggest that we need drugs that can alter how clusters of genes function within brain circuits. Depression is a circuit-level disorder and needs to be understood and treated at that level.”
The study was led by Drs. Bagot and Nestler and two other senior investigators, Li Shen, PhD, and Bin Zhang, PhD, from the Icahn School of Medicine at Mount Sinai. The research team from Mount Sinai collaborated with researchers from the University of Pittsburgh; the University of California, Los Angeles; and the Massachusetts Institute of Technology.
Funding: The study was financially supported by P50 MH096890, the Hope for Depression Research Foundation (HDRF), a 2014 NARSAD Young Investigator Award 22713 from the Brain & Behavior Research Foundation, grant R01AG046170 from the National Institute on Aging, and grants U01AI111598-01 and K99 MH10237 from the National Institute of Allergy and Infectious Diseases.
Source: Elizabeth Dowling – Mount Sinai Health System
Image Source: This NeuroscienceNews.com image is in the public domain.
Original Research: Abstract for “Circuit-wide Transcriptional Profiling Reveals Brain Region-Specific Gene Networks Regulating Depression Susceptibility” by Rosemary C. Bagot, Hannah M. Cates, Immanuel Purushothaman, Zachary S. Lorsch, Deena M. Walker, Junshi Wang, Xiaojie Huang, Oliver M. Schlüter, Ian Maze, Catherine J. Peña, Elizabeth A. Heller, Orna Issler, Minghui Wang, Won-min Song, Jason. L. Stein, Xiaochuan Liu, Marie A. Doyle, Kimberly N. Scobie, Hao Sheng Sun, Rachael L. Neve, Daniel Geschwind, Yan Dong, Li Shen, Bin Zhang, and Eric J. Nestler in Neuron. Published online April 11 2016 doi:10.1016/j.neuron.2016.04.015
http://neurosciencenews.com/depression-gene-networks-neuroscience-4234/ (accessed May 12, 2016).
Circuit-wide Transcriptional Profiling Reveals Brain Region-Specific Gene Networks Regulating Depression Susceptibility
•A large-scale multi-brain region transcriptomic cohort to probe stress susceptibility
•Reveals susceptible and resilient transcriptional networks across brain regions
•Identifies many novel hub genes that emerge in susceptible mice
•In vivo validation of key regulators at molecular, synaptic, and behavioral levels
Depression is a complex, heterogeneous disorder and a leading contributor to the global burden of disease. Most previous research has focused on individual brain regions and genes contributing to depression. However, emerging evidence in humans and animal models suggests that dysregulated circuit function and gene expression across multiple brain regions drive depressive phenotypes. Here, we performed RNA sequencing on four brain regions from control animals and those susceptible or resilient to chronic social defeat stress at multiple time points. We employed an integrative network biology approach to identify transcriptional networks and key driver genes that regulate susceptibility to depressive-like symptoms. Further, we validated in vivo several key drivers and their associated transcriptional networks that regulate depression susceptibility and confirmed their functional significance at the levels of gene transcription, synaptic regulation, and behavior. Our study reveals novel transcriptional networks that control stress susceptibility and offers fundamentally new leads for antidepressant drug discovery.
“Circuit-wide Transcriptional Profiling Reveals Brain Region-Specific Gene Networks Regulating Depression Susceptibility” by Rosemary C. Bagot, Hannah M. Cates, Immanuel Purushothaman, Zachary S. Lorsch, Deena M. Walker, Junshi Wang, Xiaojie Huang, Oliver M. Schlüter, Ian Maze, Catherine J. Peña, Elizabeth A. Heller, Orna Issler, Minghui Wang, Won-min Song, Jason. L. Stein, Xiaochuan Liu, Marie A. Doyle, Kimberly N. Scobie, Hao Sheng Sun, Rachael L. Neve, Daniel Geschwind, Yan Dong, Li Shen, Bin Zhang, and Eric J. Nestler in Neuron. Published online April 11 2016 doi:10.1016/j.neuron.2016.04.015