Sparking New Connections: Shared Brain Alterations During Aging and Alzheimer’s Inform Treatment of Neurodegenerative Conditions
Several biological factors, from the accumulation of toxic proteins to brain inflammation and vascular abnormalities, are thought to drive the changes underlying healthy aging and neurodegenerative conditions like Alzheimer’s disease. But, we are just grasping at how different indicators — from genes to neuroimaging to cognition — can be used to further understand both healthy aging and neurodegeneration. This knowledge is critical for developing biomarkers for personalized diagnoses and treatment.
Driven by this motivation, a research team from McGill University, Canada, created a new model for healthy aging and Alzheimer’s disease progression in the brain. This novel approach brings together the direct influence of hundreds of genes on regional effects in the brain, the spreading of aberrations across brain connections and blood vessel networks, and the resultant effects of these alterations on cognition. The proposed framework makes up a promising technique for identifying effective genetic targets to prevent aging-related disorders and improve existing neurodegenerative conditions.
What drives healthy aging in the brain?
Inside of our cells, our genetic code can get altered with age, leading to changes in genetic activity and the function of the proteins they encode. Some of these changes lead to the biological alterations seen in normal aging, while some may lead to the development of diseases and health conditions.
But, we know little about the genetic events that lead to declines in cognition in older age. Researchers understand that conditions like Alzheimer’s disease are not caused by any single event, but by a series of several factors that cause the changes that lead to the disease (1). This is one reason that it has been so difficult to develop effective medication for preventing or treating dementia associated with Alzheimer’s disease.
Strategies for understanding brain aging and cognitive decline
Over the last few years, the ability of scientists to map genes and proteins — fields known as genomics and proteomics — has taken major steps forward. With new technologies, scientists can now identify different genes and the different proteins they encode. Advances in data processing and computing have made it possible to map different parts of our genetic libraries. This allows for a better understanding of the events that happen in tissues at the microscopic and molecular level.
At a more macroscopic level, advancements in imaging allow researchers to observe changes in unique structures that are associated with the development of disease. For example, imaging tests, such as CAT scans and MRIs, enable physicians to observe the abnormal protein accumulation, altered blood flow, and atrophy that are typical of Alzheimer’s disease (2).
Now, with advancements in data modeling, scientists can take these once-isolated findings and cross-reference them together to get a more comprehensive understanding of the changes linked with aging and the development of diseases like Alzheimer’s. This approach allows researchers to identify new targets for research and hopefully new possibilities for treatment.
Gene activation patterns modulate healthy brain aging and Alzheimer’s progression
A group of Canadian researchers recently published an article in the journal eLife providing insight into how aging, cognitive decline, and Alzheimer’s disease are intertwined (3). The study took data from 460 people enrolled in the Alzheimer’s Disease Neuroimaging Initiative Cohort, a long-term study that follows participants and their cognitive performance as they age.
These study participants had routine brain images taken, either through PET scans or through MRIs. By drawing on an existing genetic map of the brain and data from epidemiological studies, this trove of data allowed researchers to observe the microscopic changes that happen at the genetic level, as well as the macroscopic changes, such as abnormal protein deposits and blood flow patterns as these patients age.
"In both aging and disease research, most studies incorporate brain measurements at either micro or macroscopic scale, failing to detect the direct causal relationships between several biological factors at multiple spatial resolutions," explains first author Quadri Adewale, a Ph.D. candidate at the Department of Neurology and Neurosurgery, McGill University, Canada. "We wanted to combine whole-brain gene activity measurements with clinical scan data in a comprehensive and personalized model, which we then validated in healthy aging and Alzheimer's disease."
Aging and Alzheimer’s disease have both common and distinct mechanisms
By comparing the findings from the genetic data against the visible findings seen on the brain scans, the researchers characterized many of the changes that lead to the accumulation of toxic proteins and neuronal dysfunction. By doing this, they were also able to identify the genes that are responsible for cognitive decline in normal aging.
In total, Adewale and colleagues identified 111 genes as responsible for cognitive decline, in addition to at least 65 different biological processes. These findings show that the normal process of aging and Alzheimer’s disease share many of the same biological paths. It also suggests that there is significant overlap in the mechanism of normal aging and the development of Alzheimer’s, although Alzheimer’s-related alterations seem to be sped up.
"Our study provides unprecedented insight into the multi-scale interactions among aging and Alzheimer's disease-associated biological factors and the possible mechanistic roles of the identified genes," concludes senior author Yasser Iturria-Medina, Assistant Professor at the Department of Neurology and Neurosurgery at McGill University. "We've shown that Alzheimer's disease and healthy aging share complex biological mechanisms, even though Alzheimer's disease is a separate entity with considerably more altered molecular and macroscopic pathways.”
Towards a genetic approach to extending healthy aging and treating Alzheimer’s disease
This work has important implications for understanding the underlying factors driving aging and Alzheimer’s disease and, importantly, for implementing a biologically defined patient stratification for personalized medical care. Dr. Yasser Iturria-Medina concluded, “This personalized model offers novel insights into the multi-scale alterations in the elderly brain, with important implications for identifying targets for future treatments for Alzheimer's disease progression."
Future studies that use this approach will further our understanding of cognitive decline, and provide new targets for research into treatments. The researchers also propose that the applicability and generalizability of the current formulation should also be tested in other neurological conditions (e.g., Parkinson’s disease and frontotemporal dementia).
References:
- Dillman AA, Majounie E, Ding J, et al. Transcriptomic profiling of the human brain reveals that altered synaptic gene expression is associated with chronological aging. Sci Rep. 2017;7(1):16890. Published 2017 Dec 4. doi:10.1038/s41598-017-17322-0
- Dukart J, Kherif F, Mueller K, et al. Generative FDG-PET and MRI model of aging and disease progression in Alzheimer's disease. PLoS Comput Biol. 2013;9(4):e1002987. doi:10.1371/journal.pcbi.1002987
- Adewale Q, Khan AF, Carbonell F, Iturria-Medina Y; Alzheimer's Disease Neuroimaging Initiative. Integrated transcriptomic and neuroimaging brain model decodes biological mechanisms in aging and Alzheimer's disease. Elife. 2021;10:e62589. Published 2021 May 18. doi:10.7554/eLife.62589
