Novel PET imaging agent could help guide therapy for brain diseases

Researchers have developed a new imaging agent that could help guide and assess treatments for people with various neurological diseases, including Alzheimer’s, Parkinson’s, and multiple sclerosis. The agent, which is used in positron emission tomography (PET) scans, targets receptors in nerve cells in the brain that are involved in learning and memory. The study is featured in the April issue of The Journal of Nuclear Medicine.

Swiss and German scientists developed the new PET radioligand, 11C-Me-NB1, for imaging GluN1/GluN2B-containing N-methyl-D-aspartate (NMDA) receptors (a class of glutamate receptor) in nerve cells. When NMDA receptors are activated, there is an increase of calcium (Ca2+) in the cells, but Ca2+ levels that are too high can cause cell death. Medications that block NMDA receptors are therefore used for the treatment of a wide range of neurological conditions from depression, neuropathic pain and schizophrenia to ischemic stroke and diseases causing dementia.

“The significance of the work lies in the fact that we have for the first time developed a useful PET radioligand that can be applied to image the GluN2B receptor subunit of the NMDA receptor complex in humans,” explains Simon M. Ametamey, PhD, of the Institute of Pharmaceutical Sciences, ETH Zurich, in Switzerland. “The availability of such a PET radioligand would not only help to better understand the role of NMDA receptors in the pathophysiology of the many brain diseases in which the NMDA receptor is implicated, but it would also help to select appropriate doses of clinically relevant GluN2B receptor candidate drugs. Administering the right dose of the drugs to patients will help minimize side-effects and lead to improvement in the efficacy of the drugs.”

Full story at Science Daily

Brain’s immune cells linked to Alzheimer’s, Parkinson’s, schizophrenia

Scientists have, for the first time, characterized the molecular markers that make the brain’s front lines of immune defense — cells called microglia — unique. In the process, they discovered further evidence that microglia may play roles in a variety of neurodegenerative and psychiatric illnesses, including Alzheimer’s, Parkinson’s and Huntington’s diseases as well as schizophrenia, autism and depression.

“Microglia are the immune cells of the brain, but how they function in the human brain is not well understood,” says Rusty Gage, professor in Salk’s Laboratory of Genetics, the Vi and John Adler Chair for Research on Age-Related Neurodegenerative Disease, and a senior author of the new work. “Our work not only provides links to diseases but offers a jumping off point to better understand the basic biology of these cells.”

Full story of brain’s immune cells linked to mental health at Science Daily

Causal links between cannabis, schizophrenia: New evidence

People who have a greater risk of developing schizophrenia are more likely to try cannabis, according to new research, which also found a causal link between trying the drug and an increased risk of the condition.

The study from the University of Bristol comes on the back of public health warnings issued earlier this year by scientists who voiced concerns about the increased risk of psychosis for vulnerable people who use the drug. Those warnings followed evidence to suggest an increased use of particularly high potency strains of cannabis among young people. However, experts cautioned that the risks should not be overstated given the need for greater research into links between mental health and illicit drugs.

Full story of cannabis and schizophrenia link at Science Daily

Elevating brain protein allays symptoms of Alzheimer’s, improves memory

Boosting levels of a specific protein in the brain alleviates hallmark features of Alzheimer’s disease in a mouse model of the disorder, according to new research published online August 25, 2016 in Scientific Reports.

The protein, called neuregulin-1, has many forms and functions across the brain and is already a potential target for brain disorders such as Parkinson’s disease, amyotrophic lateral sclerosis and schizophrenia.

“Neuregulin-1 has broad therapeutic potential, but mechanistically, we are still learning about how it works,” says the study’s senior investigator Kuo-Fen Lee, a professor in the Salk Institute’s Clayton Foundation Laboratories for Peptide Biology and holder of the Helen McLoraine Chair in Molecular Neurobiology. “We’ve shown that it promotes metabolism of the brain plaques that are characteristic of Alzheimer’s disease.”

Full story of elevating brain protein symptoms of Alzheimer’s at Science Daily

New tool may help predict patients’ motor function recovery after stroke

Graph theoretical analysis is proving to be helpful in understanding complex networks in the brain. Investigators in the Republic of Korea used a graph theoretical approach in examining the changes in the configuration of the two hemispheres of the brain in 12 patients after stroke. They found it helped understand the dynamic reorganization of both hemispheric networks in the brain and to predict recovery of motor function. Their findings are published in Restorative Neurology and Neuroscience.

Graph theoretical analysis is a powerful new tool for characterizing functional neural networks that is being used to improve understanding of neurological disorders such as Alzheimer’s disease, schizophrenia, epilepsy, and traumatic brain injury.

“The physiological effects of neurological disorders are best assessed over an entire network, rather than just being locally assessed at the site of damage,” explained lead investigator Yun-Hee Kim, MD, PhD, Professor in the Department of Physical and Rehabilitation Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea. “We therefore investigated the reorganization of network topology in both the ipsilesional hemisphere (the side of the brain affected by stroke) and the contralesional hemisphere. We also tried to predict the recovery of motor function by examining the relationship between specific network measures immediately after onset and an enhanced motor function score three months after stroke.”

Full story of predicting motor function recovery after strokes at Science Daily