Source: Precision Medical News
A newly-developed sensor can evaluate transmissions in the brain at both the microscopic and the nanoscopic level, accelerating Alzheimer’s precision medicine, according to a study published in Molecular Psychiatry.
The new method combines a biological sensor with two different forms of cutting-edge imaging. The approach can quantify neuromodulatory transmissions, which are associated with major brain disorders like Alzheimer’s, addiction, depressive disorders, and schizophrenia. These transmissions are also linked to autism, epilepsy, eating disorders, and sleep disorders.
Neuromodulatory transmissions are the slower transmissions in the brain, researchers noted. These transmissions are typically thought to involve a lot of neurons in large regions, as opposed to the much faster transmissions that happen neuron-to-neuron.
With the new tool, researchers found that it may not be that simple. The team discovered a surprising degree of control and precision in the supposedly shotgun neuromodulatory transmissions. Widely used Alzheimer’s drugs known as acetylcholinesterase inhibitors may impede this precise communication, which could explain the limited effectiveness of the drugs.
Researchers went on to identify potential changes in the brain that could be brought about by long-term use of the drugs, which could explain why patients often get much worse when they stop taking them.
“The new method points out Alzheimer’s defects in the unprecedented spatial and temporal resolution, defining the precise targets for medicine,” said lead researcher J. Julius Zhu of UVA’s Department of Pharmacology.
The team expects that the new method will have a significant impact on our understanding of depression, sleep disorders, autism, neurological diseases, and major psychiatric conditions. The tool will speed scientific research into the workings of the brain and support the development of new targeted treatments.
“We can now ‘see’ how brain cells communicate in sharp detail in both the healthy and diseased brains,” said Zhu.
With the new sensor, Alzheimer’s is just the beginning. The new system has broad applicability across the spectrum of neurological and psychiatric diseases and disorders – most notably addiction.
“Addiction, a leading health problem that results in multiple millions of human disabilities every year, represents a complex reinforcement behavior manifested by compulsive substance use despite harmful consequence,” researchers stated.
“Addictive disorders involve primary disturbances of the dopaminergic system, although the significance of non-dopaminergic systems, which has been less understood, should not be underestimated. Genetically encoded DA sensors can qualify dynamics of individual dopaminergic releases with microscopic spatiotemporal resolution, and subsequently define synaptic parameters and alternations responsible for specific addictive behavioral events.”
Researchers predict that in the future, the tool will help doctors understand neurological illnesses and psychiatric problems, screen drugs for potential treatments, identify disease-causing genes and develop better, more personalized medicine tailored for specific patient needs.
“If we see problems, we will be ready to treat them,” said Zhu.
Researchers are getting closer to realizing the vision of precision medicine for neurological diseases like Alzheimer’s. In January 2021, a team from Mount Sinai used RNA sequencing to detect three molecular subtypes of Alzheimer’s disease that could advance precision medicine treatments for the condition.
The group used a computational biology approach to understand the relationships among different types of RNA, clinical and pathological traits, and other biological factors that potentially drive the disease’s progress.
“Our systematic identification and characterization of the robust molecular subtypes of Alzheimer’s disease reveal many new signaling pathways dysregulated in Alzheimer’s and pinpoint new targets,” said Bin Zhang, PhD, the lead author of the study, Director of the Center for Transformative Disease Modeling, and Professor of Genetics and Genomic Sciences at the Icahn School of Medicine.
“These findings lay down a foundation for determining more effective biomarkers for early prediction of Alzheimer’s, studying causal mechanisms of Alzheimer’s, developing next-generation therapeutics for Alzheimer’s, and designing more effective and targeted clinical trials, ultimately leading to precision medicine for the disease.”
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