Understanding Human Brain Metabolism
The human brain is unique in many ways. While it isn’t the largest (elephants and blue whales have larger brains than us), the human brain is exceptionally large relative to our body size. Even more impressive is that the human brain has very high metabolic requirements. Though it is only 2% of the body’s weight, it consumes about 20% of the body’s resting metabolism!
Neuroscience has thus long been interested in measuring the brain’s rate of metabolism. In the 1980’s, Professor Marcus Raichle led efforts to develop methods using brain imaging to measure its metabolism in great detail–first with PET imaging then with MRI.
Our laboratory continues this line of work, under the ongoing mentorship of Professor Raichle. We can now combine multi-tracer PET imaging and MRI to get a detailed view of human brain metabolism in ways never seen before. Read below for some of the projects that are currently going on in our laboratory.
Metabolic Brain Imaging Across the Lifespan (MBIL)
Our laboratory performs multiple studies of brain metabolism across the lifespan. In the Metabolic Brain Imaging Across the Lifespan (MBIL) Project, we aim to study how brain metabolism changes with development and aging. This project builds upon our prior work showing that with age, brain metabolism shifts from a mixture of oxidative and non-oxidative metabolism to one dominated by oxidative metabolism alone. We now aim to determine whether preservation of non-oxidative metabolism–aerobic glycolysis–and patterns of more youthful or ‘neotenous‘ brain metabolism predicts slower brain atrophy and less cognitive decline.
The MBIL Project is currently driven by two large NIH-funded studies (R01AG053503, R01AG057536) and another smaller study funded by the McDonnell Center for Systems Neuroscience, all aiming to determine how brain metabolism relates to brain development, aging and cognitive decline in 1) cognitively normal adults (ages 35+), in 2) individuals with preclinical (brain amyloid positive) and symptomatic Alzheimer’s disease, and 3) in children ranging in age from 3 years to adulthood.
The studies in adults are longitudinal, spanning the typical adult lifespan, and involve a number of imaging and cognitive measures. For more information on volunteering for this project, please click here.
Metabolic Interactions Between the Brain and Body
How does the body’s metabolic state influence the brain? If the body becomes frail does this induce brain frailty as well? How does exercise influence the trajectory of brain aging and metabolism?
This and similar questions are key topics in our lab. We obtain blood samples to assess various aspects of body metabolism. We are also obtaining frailty assessments. Ultimately, we want to rigorously test the hypothesis that a healthy body leads to a healthy mind.
Brain Nutrition Across the Life Span
Nutrition is a key element in determining human metabolism. To what extent does nutrition affect brain metabolism as well?
Our research has identified remarkable changes in brain metabolism during childhood, suggesting that these changes are likely related to brain development. Human brain gene expression studies from the Allen Brain Institute confirm that the regions with a developmental, i.e. neotenous, pattern of gene expression are also the most metabolically active in adults.
These findings prompted us to consider how dependent the developing child’s brain is on adequate nutrition. What does a child’s brain need and how does it get it? Our lab has now collaborated with leading authorities, including Professor Jeffery Gordon and Dr. Sid Venketash, Dr. Ana Maria Arbelaez, as well as Dr. Lora Iannotti, on the worldwide problem of childhood malnutrition to investigate how this affects brain development. Some of our collaborative ideas have been published in reviews in PNAS and an upcoming review in the Annual Reviews of Nutrition.
Advancing the Imaging of Brain Metabolism
Though we currently apply some of the most advanced techniques to assess human brain metabolism in vivo, we are constantly working to improve and advance our methods.
In particular, we are investigating novel methods of analyzing brain PET imaging data, including representation of PET signals to the cortical surface using techniques developed by the Human Connectome Project, in collaboration with Professor Beau Ances. We are also developing new methods to correct for partial volume effects such that PET data can be adequately analyzed at the voxel level.
Given that few institutions have the experience or capability to perform our multi-tracer metabolic PET imaging technique, we are also collaborating with researchers who are either developing new MRI methods to assess brain metabolism (e.g., R21EB024366) or new PET tracers to assess brain function.