Over half of all chronic pain patients also develop depression. Researchers know that short-term pain affects brain areas implicated in depression, but few studies have scrutinized the effects of long-term pain on gene expression in those regions or examined gene expression alterations in multiple brain regions at once. Now, researchers use network analysis along with a mouse model of chronic pain and a mouse model of stress-induced depression to identify changes in gene expression throughout the brain that may underlie the connection between pain and depression.
The work, from a team led by Venetia Zachariou, Icahn School of Medicine at Mount Sinai, New York, US, harnesses high-throughput next-generation RNA sequencing of tissue from the nucleus accumbens (NAc), the medial prefrontal cortex (mPFC), and the periaqueductal gray (PAG)—regions previously associated with both pain and depression—to create a massive database of genes and the pathways they regulate. This database will serve as a resource for researchers studying the intersection of pain and depression.
“It’s been known for a while that chronic pain and depression activate some of the same brain areas, but the use of RNA sequencing at such a late time point has never been done before,” says Sandrine Géranton, University College London, UK, who was not involved in the study.
“We are sharing a lot of data here so people can find how their favorite molecules are regulated in these brain regions not just at short time points, but also at much later time points,” says Zachariou.
The work was published online March 21 in Science Signaling.
From SNI to changes in gene expression in the brain
Negative emotions that accompany pain are thought to contribute to the increased prevalence of depression in people with pain. Interestingly, antidepressants are effective not only in treating depression in pain patients, but also the underlying pain. This suggests a unique connection between these two conditions (see PRF related story).
Giannina Descalzi, first author on the study, and colleagues were interested in identifying molecular mechanisms in the brain that contribute to pain and comorbid depression. She reasoned that identifying changes in gene expression that occur during chronic pain within brain regions associated with depression might help pinpoint common biological pathways in both disorders and suggest new treatment approaches.
“This intersection is becoming a major interest in my group,” explained Zachariou. “The more information we collect, the easier it will be for us to identify entirely new targets for pain and pain-related depression.”
The team focused their attention on the NAc, mPFC, and PAG. These regions are anatomically and functionally connected, each playing a varying role in both pain and depression. The researchers were most interested in studying the genetic changes that occur in those regions months after an injury, since in mice it can take at least six weeks for signs of depression to emerge in experimental models of pain.
To induce chronic pain, the investigators turned to the spared nerve injury (SNI) model of neuropathic pain, and the sucrose consumption and forced swim tests were used to assess depression-related behaviors in the animals. The group also used the open-field test and elevated plus maze to measure anxiety-related behaviors. As expected, SNI mice exhibited mechanical allodynia two months after the injury, along with anxiety- and depression-like behaviors.
Next, the researchers examined changes in gene expression in the brains of SNI and sham-operated animals by performing next-generation RNA sequencing on tissue from the PAG, NAc, and mPFC two-and-a-half months after surgery. Thousands of genes were found; some were upregulated and others were downregulated. Interestingly, while there was differential expression of genes in each brain region, patterns did emerge. In particular, many of the same genes regulated in the PAG were also regulated similarly within the NAc.
What do the genes do?
To identify the underlying molecular pathways the identified genes might regulate, the researchers used Ingenuity Pathway Analysis (IPA). This allows for comparison of differentially expressed genes to a public database of gene networks that are associated with different biological functions and disorders. IPA is a powerful technique, since it provides information about how genes interact, directing attention to important genes and pathways.
IPA allowed Zachariou’s team to narrow their list to 275 highly relevant genes that could be mapped into biologically meaningful networks such as those for behavior and neurological disease. Thirty-nine of these genes were already suggested to be involved in pain, depression, or anxiety, validating the approach of searching for shared links between these conditions. The IPA analysis then identified common regulators of these genes within the mPFC and PAG including cytokines, kinases, and transcriptional regulators. Finally, the IPA grouped the genes into 19 common signaling pathways that were shared by at least two of the brain regions and five that were shared by all three, including pathways involved in cyclic AMP signaling, pregnenolone biosynthesis, and glucocorticoid receptor signaling. These pathways and regulators could each potentially represent a future therapeutic target.
The authors were also interested to see if some of the genes they identified would still be regulated if depression was induced in a different way. Here, they used the chronic unpredictable stress (CUS) model of anxiety-induced depression in which mice are exposed on a daily basis for a month to stressful situations such as wet bedding, restraint, or the removal of food. The group found that several genes that were similarly regulated across the three brain regions after SNI were also regulated by CUS, suggesting these genes as potential common targets in pain and depression.
“We can now ask whether manipulating these genes affects depression or long-term neuropathic pain behaviors,” Zachariou said.
Exploring two of the genetic "hits”
Digging back into the data, two of the identified genes were particularly interesting. Of all the genes in the initial list that were upregulated similarly in the PAG and NAc, many of them interacted with histone deacetylase 5 (HDAC5). This epigenetic regulator has been implicated in depression.
“We’ve already shown previously a very prominent role of HDAC5 in the function of antidepressants,” said Zachariou (Mitsi et al., 2015).
Thus, the investigators obtained HDAC5 knockout mice and once again performed SNI. Although these animals experienced pain, they did not show anxiety- or depression-like behaviors, suggesting a role of HDAC5 in the emotional but not allodynic aspects of SNI. Interestingly, treatment with duloxetine, an antidepressant with pain-relieving properties, was more effective for relieving pain in HDAC5 knockout mice than in wild-type mice, demonstrating how the absence of HDAC5 could enhance pain-relieving qualities of antidepressants.
A second hit came from a list of the genes that had the most robust changes in expression levels after SNI. Of those genes, calpain-11, a calcium-dependent cysteine protease, was significantly upregulated in all three brain regions. Although other members of the calpain family have been implicated in pain, calpain-11 had not (Kunz et al., 2004).
Treatment with a calpain inhibitor for two weeks reduced pain but had no effect on anxiety or depression, further demonstrating how the type of genetic analysis used in the study could drive the discovery of new therapeutic targets for pain.
More studies are needed, however, to pin down the role of calpain-11 and HDAC5 in the emotional aspects of pain. “These experiments would really benefit from measuring other emotional outcomes in these animals [using other models] such as models of spontaneous pain [in which] pain’s affective aspects” can be assessed, said Géranton. “It would really add another dimension to the study.”
Nonetheless, the current findings provide researchers interested in the pain-depression connection with an extensive resource that will keep them busy for a long time.
“There’s quite a lot in this paper. It’s a huge dataset, so the interpretation of the results is going to take a long time for us to put together,” said Géranton.
Nathan Fried is a postdoctoral fellow at the University of Pennsylvania, Philadelphia, US
Image credit: Vadym Malyshevskyi/123RF stock photo
