Scientists have found that a usually-overlooked signal from MRI scans indicates brain regions of nerve cell death and may help in the understanding of brain development and the early diagnosis of brain disorders like multiple sclerosis (MS), Alzheimer’s disease, and autism.
The signal reflects the type and amount of nerve cells and how interconnected they are with one another, which can help detect brain deterioration even before people experience symptoms of brain disease.
The study, “Genetically defined cellular correlates of the baseline brain MRI signal,” was published in the journal Proceedings of the National Academy of Sciences.
Understanding how the different cell types and molecules relate with the many functions of the human brain is a major goal in neuroscience.
MRI (magnetic resonance imaging) has revolutionized the field, providing researchers with a way to study the human brain in action. Still, many questions remain unanswered about how MRI data relates to the brain’s underlying cellular composition and activity, both during normal development or in brain injury and illness.
A team of researchers at the Washington University School of Medicine in St. Louis, Missouri, decided to address this question by looking at a part of MRI data — its background signal — which usually is neglected by researchers and doctors due to its steady sign, even while a task is being performed.
They used brain scans of 26 healthy volunteers, obtained using a recently developed MRI technique called quantitative gradient recalled echo (qGRE). The MRI data was merged with a map of the active genes across the different regions of the human brain. This map is available from the Allen Human Brain Atlas, and represents a groundbreaking genetic “geography” of the human brain.
After they compared both types of data, the result was surprising. They found that a specific background signal of the qGRE MRI scans, called R2t*, reflects the type of cells, how densely packed they are, and how many connections there were between them. Importantly, a weaker R2t* also could also indicate loss of brain cells in people with MS, traumatic brain injury, or Alzheimer’s disease.
“There’s no easy way to detect the loss of neurons in living people, but such loss plays a role in many neurological diseases,” Dmitriy Yablonskiy, PhD, professor of radiology at the Mallinckrodt Institute of Radiology at Washington University and one of the senior authors of the study, said in a university press release written by Tamara Bhandari.
‘Now we know … ‘
“We’ve shown in the past that there’s a signal that goes down in parts of the brain in people with Alzheimer’s disease, multiple sclerosis and traumatic brain injury, but we didn’t know what it meant. Now, we know it means neurons have died in those areas,” he said.
Researchers found the activity of three sets of gene networks correlated with the intensity of the R2t* signal across the brain. These genes were more active where the signal was strong, and less active where the signal was weak.
This set of genes reflected the different types and numbers of brain cells and how interconnected they were. Specifically, they found that they represented two major types of brain cells: neurons and glial cells, which help keep processes within physiological ranges, form myelin, and provide support and protection to neurons.
“Importantly, higher R2t* reflects tissue containing more neurons with myelinated axons and relatively lower numbers of glial cells and synapses [neuron connections]. It is possible that R2t* represents more ‘mature’ cortical tissue, for example with more myelination and less immature synapses,” researchers wrote in the study.
Since MRI is a broadly available noninvasive tool, the researchers believe their findings will make new opportunities available for understanding and applying MRI to brain functioning in health and disease.
“There are MRI scans now that can detect brain atrophy even before people show symptoms of Alzheimer’s disease,” Yablonskiy said. “Our technique can show the brain degrading even before it begins to atrophy.”
Now, the team is working on applying the technique to brain diseases and disorders including MS, Alzheimer’s, schizophrenia, and autism, as well as to better understand how the brain develops from infancy to adulthood.
“As babies develop, neurons start growing, they connect with each other, they start forming memories. Nobody really knows how this is done,” Yablonskiy said. “But this method could help us understand normal development, as well as how brain diseases develop.”