The development of robust and reliable biomarkers that reflect biological age is a necessary step for the future development of rejuvenation therapies. The existence of such biomarkers will make it much less expensive and time-consuming to assess the effectiveness of potential new therapies at all stages of the research and development pipeline, which in turn will lead to more rapid progress in this field. Here, researchers assess changes in gene expression in neurons and their supporting cells in brain tissue, and find that the changes in glial cells are those that best correlate with age:
The relationship between aging and neurodegeneration raises the possibility of shared transcriptional and post-transcriptional gene regulation programs; however, we still lack a comprehensive transcriptome-wide picture of the effects of aging across different human brain regions and cell types. Apart from the study of region-dependent microglial response to aging, the importance of both region- and cell-type-specific changes in the aging brain remains poorly understood. Studies have been hampered by the limited availability of cross-regional post-mortem tissue across a range of ages. To overcome these limitations, we analyzed gene expression patterns in ten brain regions (including cortical and sub-cortical areas) using more than 1,800 brain samples from two large independent cohorts, representing the most comprehensive human aging brain gene expression analysis to date. We report striking changes in cell-type-specific expression patterns across different brain regions, which revealed major shifts in glial regional identity upon aging in the human brain.
By current consensus, astrocyte (AC) and neuronal numbers appear generally preserved in aging. It is clear, however, that Alzheimer's disease (AD) and other neurodegenerative diseases for which age is a major risk factor are associated with inflammatory changes mediated by microglia (MG). Our findings show that cell-type-specific genes delineate samples based on both age group and brain region. Aging was the major determinant of glia-specific gene expression shifts in regional identity, while such changes were not evident in neuron-specific genes. Genes specific for neurons and oligodendrocytes (OLGs) generally decreased their expression upon aging, while MG-specific genes increased their expression profiles, consistent with the known MG activation in aging. A trend toward increased expression of MG-specific genes was observed in all regions upon aging, with corresponding upregulation of genes with immune or inflammatory functions.
In addition to glial changes, we also observed a decreased number of neurons with large cell bodies, which represent approximately 20% of neurons in the cortex. Although we did not attempt to directly identify the neuronal subtypes in the present study, neurons with the largest cell bodies are likely to be associative pyramidal neurons. Furthermore, these neurons were previously indicated to be most vulnerable to aging. While our analysis indicates that the decrease in these pyramidal neurons may be the primary source of the downregulation of neuron-specific genes, our findings regarding the cortical neuronal cells remain speculative due to the limited number of individuals used for the imaging analyses.
Age is the major risk factor for both Alzheimer's disease (AD) and Parkinson's disease (PD), the two most prevalent neurodegenerative diseases. It is becoming clear that the pre-clinical stage of AD begins decades before clinical manifestation. This pre-clinical stage has been termed "the cellular phase," because it involves changes in interactions among all cell types in the brain, with the most dramatic changes taking place in AC, MG, and vasculature. We find a corrosion of glial region-specific gene expression in aging, with the genes specific for AC, MG, and endothelial cells being the best predictors of age. By simultaneously assessing changes in cell-type-specific genes across multiple brain areas, our study takes a step toward providing a comprehensive framework of the molecular and cellular changes in human aging. While our primary aim was to deconvolute the cell-type-specific signatures present within large databases of age-related transcriptional changes, we also made a step toward interpreting these in light of changes in counts of OLGs and neuronal cells. Integration of further genome-wide and single-cell data from human tissues samples and cell and animal models will be required to fully understand the cellular and molecular mechanisms underlying the observations in our study. Altogether, our study indicates that the cellular changes during aging involve a dramatic shift in the regional identity of glia, and it provides a resource for further studies of the relationship between aging and the cellular phase of dementia.