A new mathematical model described in eLife suggests there are key similarities between Alzheimer disease and healthy aging. According to the study authors, this model provides insights into the multiscale biological alterations in the elderly and neurodegenerative brain, which have important implications for identifying treatment targets for Alzheimer disease.
The researchers developed this mathematical model using a wide range of biological data, including both microscopic information from gene activity and macroscopic information about the brain's burden of toxic proteins (tau and amyloid), its neuronal function, cerebrovascular flow, metabolism, and tissue structure from molecular PET and MRI scans.
“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,” said Quadri Adewale, a PhD candidate at the Department of Neurology and Neurosurgery, McGill University, Canada, in a press release. “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.”
The study examined 460 patients who had at least 4 different types of brain scan at 4 different time points as part of the Alzheimer Disease Neuroimaging Initiative cohort, with 151 clinically identified as asymptomatic or healthy control, 161 with early mild cognitive impairment (ECMI), 113 with late mild cognitive impairment (LCMI), and 35 with probable Alzheimer disease. The data from these multimodal scans were combined with data on gene activity from the Allen Human Brain Atlas, which provides details on whole-brain gene expression for 20,267 genes.
The researchers then split the brain into 138 different gray matter regions for the purposes of combining the gene data with the structural and functional data from the scans. They then explored causal relationships between the spatial genetic patterns and information from their scans and cross-referenced this to age-related changes in cognitive function.
According to the study, the model was most capable of predicting the extent of decline in cognitive function for the Alzheimer disease cohort, followed by the less pronounced decline in cognition cohort (LCMI, ECMI), and finally the healthy controls. The authors said this shows the model is capable of reproducing the individual multifactorial changes in the brain's accumulation of toxic proteins, neuronal function, and tissue structure seen over time in the clinical scans.
The investigators then used this model to search for genes that result in cognitive decline over time in the healthy aging process, using a subset of healthy control participants who remained clinically stable for nearly 8 years. They found 8 genes that contributed to the imaging dynamics seen in the scans and corresponded with cognitive changes in healthy individuals, according to the results of the study. The genes that changed in healthy aging are also known to affect 2 important proteins in the development of Alzheimer disease, called tau and amyloid beta, according to the study.
They then ran an analysis looking for genes that drive the progression of Alzheimer disease, identifying 111 genes that were linked with the scan data and with associated cognitive changes in Alzheimer disease. Finally, they studied the functions of the 111 genes identified, and found that they belonged to 65 different biological processes, with most of them commonly linked to neurodegeneration and cognitive decline.
“Our study provides unprecedented insight into the multiscale interactions among aging and Alzheimer's disease-associated biological factors and the possible mechanistic roles of the identified genes,” said Yasser Iturria-Medina, assistant professor at the Department of Neurology and Neurosurgery at McGill University, in the release. “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. This personalized model offers novel insights into the multiscale alterations in the elderly brain, with important implications for identifying targets for future treatments for Alzheimer's disease progression.”
Scientists map gene changes underlying brain and cognitive decline in aging [news release]. EurekAlert; May 18, 2021. Accessed May 19, 2021. https://www.eurekalert.org/pub_releases/2021-05/e-smg051821.php