We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us
LGC Clinical Diagnostics

Download Mobile App




fMRI Scanning of Biomarker Predicts Response to Rapid Antidepressant Agent

By LabMedica International staff writers
Posted on 12 Feb 2013
Print article
Image: Working memory task: Over several trials, participants were required to attend to either the identity (non-emotional feature) or the emotion of a face, remember it during a 9 second delay, and match the feature to a subsequent face. Neural activity in the visual cortex elicited by the emotion trials predicted a patient’s subsequent responsiveness to scopolamine treatment (Photo courtesy of Maura Furey, PhD, NIMH Experimental Therapeutics and Pathophysiology Branch).
Image: Working memory task: Over several trials, participants were required to attend to either the identity (non-emotional feature) or the emotion of a face, remember it during a 9 second delay, and match the feature to a subsequent face. Neural activity in the visual cortex elicited by the emotion trials predicted a patient’s subsequent responsiveness to scopolamine treatment (Photo courtesy of Maura Furey, PhD, NIMH Experimental Therapeutics and Pathophysiology Branch).
A characteristic jump in activity in the back of the brain while processing emotional data has been shown to predict which depressed patients would respond to an investigational rapid-acting antidepressant agent.

US researchers reported new research on functional magnetic resonance imaging (fMRI) of a pretreatment biomarker for the antidepressant response to scopolamine, and the study’s findings were published January 30, 2013, online in JAMA Psychiatry. “We have discovered a potential neuroimaging biomarker that may eventually help to personalize treatment selection by revealing brain-based differences between patients,” explained Maura Furey, PhD, of US National Institutes of Health’s National Institute of Mental Health (NIMH; Bethesda, MD, USA).

Scopolamine, typically recognized as a treatment for motion sickness, has been researched since Dr. Furey and colleagues discovered its fast-acting antidepressant properties in 2006. Dissimilar to ketamine, scopolamine works through the brain’s acetylcholine chemical messenger system. The NIMH scientists’ research has shown that by suppressing receptors for acetylcholine on neurons, scopolamine can lift depression in many patients within a few days; conventional antidepressants typically take weeks to work. But not all patients respond, prompting interest in a predictive biomarker.

The acetylcholine system plays a key role in working memory, retaining information in the mind temporarily, but appears to act by influencing the processing of data instead of through memory. fMRI scanning studies suggest that visual working memory performance can be enhanced by modulating acetylcholine-induced activity in the brain’s visual processing region, called the visual cortex, when processing information that is vital to the task. Because functional memory performance can predict response to traditional antidepressants and ketamine, Dr. Furey and coworkers looked at a working memory task and imaging visual cortex activity as potential tools to identify a biomarker for scopolamine response.

Depressed patients have a well-known tendency to process and remember negative emotional information. The researchers suggest that this bias stems from dysregulated acetylcholine systems in some patients. They rationalized that such patients would show abnormal visual cortex activity in response to negative emotional features of a working memory task. They also expected to find that patients with more dysfunctional acetylcholine systems would respond better to scopolamine treatment.

Before receiving scopolamine, participants performed a working memory task while their brain activity was monitored via fMRI. For some trials, it required that they pay attention to, and remember, the emotional expression (i.e., happy, sad) of faces flashing on a computer monitor. For other studies, they had to pay attention to only the identity, or non-emotional feature, of the faces. After scanning, and over the following several weeks, 15 patients with depression and 21 healthy participants randomly received infusions of a placebo (salt solution) and/or scopolamine. Mood changes were tracked with depression rating scales.

Overall, scopolamine treatment reduced depression symptoms by 63%, with 11 of the patients showing a significant clinical response. The strength of this response correlated considerably with visual cortex activity during key phases of the working memory task--while participants were paying attention to the emotional content of the faces. There was no such correlation for trials when they attended to the facial identity.

The evidence suggests that acetylcholine system activity triggers visual cortex activity that predicts treatment response—and that dissimilarities seen between depressed patients and controls may be traceable to acetylcholine dysfunction. Overall, patients showed lower visual cortex activity than controls during the emotion phase of the task. Patients demonstrating activity levels most unlike the control subjects experienced the greatest antidepressant response to scopolamine treatment. Visual cortex activity in patients who did not respond to scopolamine more closely resembled that of the controls. As theorized, the pretreatment level of visual cortex activity seems to reflect the extent of patients’ acetylcholine system dysfunction and to predict their response to the investigational medication, according to the researchers.

Early findings suggest that such visual cortex activity in response to emotional stimuli may also apply to other treatments and may prove to be a shared biomarker of rapid antidepressant response, according to Dr. Furey.

Related Links:
National Institute of Mental Health

Gold Member
Blood Gas Analyzer
GEM Premier 7000 with iQM3
Antipsychotic TDM AssaysSaladax Antipsychotic Assays
New
Urine Drug Test
Instant-view Methadone Urine Drug Test
New
ELISA System
ABSOL HS DUO

Print article

Channels

Clinical Chemistry

view channel
Image: The new saliva-based test for heart failure measures two biomarkers in about 15 minutes (Photo courtesy of Trey Pittman)

POC Saliva Testing Device Predicts Heart Failure in 15 Minutes

Heart failure is a serious condition where the heart muscle is unable to pump sufficient oxygen-rich blood throughout the body. It ranks as a major cause of death globally and is particularly fatal for... Read more

Hematology

view channel
Image: QScout CBC will give a complete blood count in 2 minutes from fingerstick or venous blood (Photo courtesy of Ad Astra Diagnostics)

Next Gen CBC and Sepsis Diagnostic System Targets Faster, Earlier, Easier Results

Every hour is critical in protecting patients from infections, yet there are currently limited tools to assist in early diagnosis before patients reach a hospital. The complete blood count (CBC) is a common... Read more

Immunology

view channel
Image: An immune response is initiated when an antigen-presenting cell (pink) presents foreign material to a T-cell (blue) (Photo courtesy of JAX)

Advanced Imaging Method Maps Immune Cell Connections to Predict Cancer Patients Survival

A growing tumor is influenced not only by the tumor cells themselves but also by the surrounding tissue, which alters its biology. Immune cells communicate by transferring vital signaling proteins to their... Read more

Microbiology

view channel
Image: The InfectoSynovia test has the potential to revolutionize the diagnosis of periprosthetic joint infection (Photo courtesy of 123RF)

High-Accuracy Bedside Test to Diagnose Periprosthetic Joint Infection in Five Minutes

Periprosthetic joint infection (PJI) represents a significant global issue that is worsening as the number of joint replacements increases due to aging populations. In the United States alone, the anticipated... Read more

Pathology

view channel
Image: LMU’s Professor Frederick Klauschen developed the novel approach that can improve diagnostic accuracy (Photo courtesy of LMU Munich)

AI Tool Uses Imaging Data to Detect Less Frequent GI Diseases

Artificial intelligence (AI) is already being utilized in various medical fields, demonstrating significant potential in aiding doctors in diagnosing diseases through imaging data. However, training AI... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.