NIMH prioritizes research on suicide prevention, neural circuits and computation
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The NIMH is working to further research efforts in three priority areas — suicide prevention, neural circuits and computation, according to a presenter at the American Psychiatric Association Spring Highlights Meeting.
“In the last 5 years, we’ve received consecutive increases [in funding], so the amount of our buying power has increased, which has enabled us to fund scientists at a higher rate than we’ve been able to in the past,” Joshua A. Gordon, MD, PhD, director of the NIMH, said during the presentation. “We continue to select only the most meritorious awards to give out, but we’ve also been able to [help] accomplish more of what our applicants would like to accomplish.”
Regarding the NIMH’s priority of suicide prevention, Gordon noted that suicide rates have consistently increased over the past 20 years in the United States; however, data are sparse and inconclusive on the reasons behind this increase. One research area the NIMH continues to focus on for reversing this upward trend is improving identification of those at risk for death by suicide.
“In order to find out whether someone is at risk for suicide, the first thing [psychiatrists] must do is ask,” Gordon said. “It has become standard practice across all of psychiatry to ask every patient who walks in the door and to continually ask them over time whether they have thought about dying by suicide or harming themselves.”
A specific place for suicide identification efforts may be EDs, according to findings of the Suicide Prevention in an Emergency Department Population, or ED-SAFE, study. Gordon noted that a majority of the individuals who die by suicide will have visited an ED over the past few months before they attempted suicide, which makes EDs one of several places to potentially identify at-risk individuals.
Beyond asking patients if they have suicidal thoughts, there are “more modern ways” psychiatrists can identify and classify those at risk for suicide, according to Gordon.
“We’ve identified over the last few years that [it is possible] to use predictive modelling and data analytics to identify individuals who [clinicians] may not otherwise suspect as being at risk and get them into treatment,” Gordon said.
Findings of an NIMH-funded study, in partnership with the VA, revealed that using a combination of demographic information and health care records, computer algorithms can identify different levels of suicide risk. For instance, those at highest risk may have a 100-fold increased risk for dying by suicide, according to Gordon, who noted that the NIMH is currently working to determine how to implement these algorithms in real-world practice.
Gordon also discussed long-term research efforts, including neural circuits. Specifically, he highlighted research in animals that has shown promise for understanding how different parts of the brain influence behavior, as well as tools that successfully manipulated activity in animal brains and had “tremendous effects” on their behavior.
“We can cure and cause anxiety in a mouse, but of course, we don't want to do it in mice; we want to be able to cure anxiety in human beings,” Gordon said. “We can imagine doing that by either one of two approaches. [These include] taking the neuro-biologic knowledge that we gained from studying mice and other animal systems and developing traditional therapies, be they drugs or brain stimulation therapies that might help us reduce anxiety based upon that circuit-based knowledge. The second approach would be a technological approach — can we develop the technology to be able to do in human beings what we can do in mice?”
According to Gordon, the NIMH is agnostic as to which approach will help patients faster, so it is conducting research on both.
The NIMH is focusing on computational approaches as another long-term research effort. Gordon noted that the organization plans to apply revolutionary advances in data science and artificial intelligence to psychiatry.
“We can learn about how behavior works by trying to quantify and mathematically describe behavior in an initiative we're calling computational phenotyping,” Gordon said. “We can use data-mining approaches and large data sets to [help] classify our patients and to develop ways of understanding what kinds of patients might respond to what kinds of treatments.” – by Joe Gramigna
Reference:
Gordon JA. The NIMH: Programs, priorities and plans. Presented at: American Psychiatric Association Spring Highlights Meeting; April 25-26, 2020 (virtual meeting).
Disclosures: Healio Psychiatry could not determine relevant financial disclosures at time of reporting.