Mathematical model of the brain can identify gene changes responsible for cognitive decline in aging
A new mathematical model described in eLife suggests that there are key similarities between Alzheimer’s disease and healthy aging. According to the study authors, this model provides insight into multiscale biological alterations in elderly and neurodegenerative brains, which have important implications for identifying treatment targets for Alzheimer’s disease.
Researchers developed this mathematical model using a wide range of biological data, including microscopic information on gene activity and macroscopic information on the brain load of toxic proteins (tau and amyloid), its neural function, flow cerebrovascular, metabolism and tissue structure of molecular PET and MRI scans.
“In research on aging and disease, most studies incorporate brain measurements at the micro or macroscopic scale, failing to detect direct causal relationships between multiple biological factors at multiple spatial resolutions,” said Quadri Adewale , doctoral student in the Department of Neurology and Neurosurgery, McGill University, Canada, in a press release. “We wanted to combine measurements of whole brain genetic activity with clinical analysis data into a comprehensive, personalized model, which we then validated in healthy aging and Alzheimer’s disease.”
The study looked at 460 patients who had at least 4 different types of brain scans at 4 different times as part of the Alzheimer’s Disease Neuroimaging Initiative cohort, with 151 clinically identified as asymptomatic or healthy controls, 161 with early mild cognitive impairment (ECMI), 113 with late mild cognitive impairment (LCMI) and 35 with probable Alzheimer’s disease. Data from these multimodal analyzes were combined with data on gene activity from Allen’s human brain Atlas, which provides details on whole brain gene expression for 20,267 genes.
The researchers then divided the brain into 138 different gray matter regions in an attempt to combine the gene data with the structural and functional data from the scans. They then explored the causal relationships between spatial genetic patterns and the information from their analyzes and crossed them with age-related changes in cognitive function.
According to the study, the model was most able to predict the magnitude of the decline in cognitive function for the Alzheimer’s disease cohort, followed by the less pronounced decline in the cognitive cohort (LCMI, ECMI), and finally healthy witnesses. The authors said this shows the model is able to replicate the individual multifactorial changes in brain toxic protein accumulation, neuronal function, and tissue structure seen over time in clinical analyzes.
The researchers then used this model to look for genes that cause cognitive decline over time in the healthy aging process, using a subset of healthy control participants who remained clinically stable for almost 8 years. They found 8 genes that contributed to the imaging dynamics seen in the scans and that corresponded to cognitive changes in healthy individuals, according to the study results. Genes that changed during healthy aging are also known to affect 2 proteins important in the development of Alzheimer’s disease, called tau and beta amyloid, according to the study.
They then performed an analysis looking for genes that drive Alzheimer’s disease progression, identifying 111 genes linked to scan data and cognitive changes associated with Alzheimer’s disease. Finally, they studied the functions of the 111 identified genes and found that they belonged to 65 different biological processes, most of them commonly linked to neurodegeneration and cognitive decline.
“Our study provides unprecedented insight into the multi-scale interactions between aging and biological factors associated with Alzheimer’s disease and the possible mechanistic roles of the genes identified,” said Yasser Iturria-Medina, assistant professor in the Department of Neurology and Neurosurgery from McGill University, in La version. “We have shown that Alzheimer’s disease and healthy aging share complex biological mechanisms, even though Alzheimer’s disease is a separate entity with considerably more modified molecular and macroscopic pathways. This personalized model offers new insights into multiscale alterations in the brains of older adults, with important implications for identifying targets for future treatments for the progression of Alzheimer’s disease.
Scientists map genetic 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