Unraveling the transcriptomic landscape of healthy aging

Abstract

AbstractBackgroundAging leads to physiological deterioration and structural changes in the human brain that might lead to cognitive decline. Also, aging in the brain has been associated with a decrease in the number of neurons and synapses. Additionally, the risk of developing neurodegenerative diseases such as Alzheimer’s and Parkinson’s increases with age. This close relationship between aging and neurodegenerative diseases suggests the existence of common molecular mechanisms that regulate gene expression in specific cell types in the brain. It has been challenging to identify these cell specific changes using current gene expression data, as it tends to be confounded by cellular heterogeneity.MethodHere we generate and analyze single‐nucleus RNA libraries from prefrontal cortex of n = 269 postmortem controls of age ranging from 2.5‐100 years from various ethnic groups (n = 153 Caucasian, n = 93 Afro‐American, n = 19 Hispanic, n = 4 Asian). Based on age, we stratified the samples into 5 stages ranging from 1) 2.5‐12 years, 2)13‐39 years, 3) 40‐59 years, 4) 60‐80 years and 5) >80 years to compare the transcriptomic changes.ResultWe compared changes in gene expression in different cell types across 5 stages and identified genes that changed as a function of age. We also looked at sex‐specific transcriptomic changes across these stages. After that, we used age specific genes to predict the biological age of samples across all cell types. Finally, we used a method called WGCNA (weighted gene co‐expression network analysis) to investigate specific molecular mechanisms that are unique to each stage.ConclusionOur study provides the comprehensive view of changes in specific cell types that underlies the aging process. Also, provides a cell‐specific list of biomarkers for every stage that can predict normal age that has no effect of disease and is independent of chronological age.