Scientists discover how aging re-warps the brain's molecular landscape

Scientists discover how aging re-warps the brain's molecular landscape

New research reveals the cellular secrets of aging, using cutting-edge single-cell data showing the neurons, glial cells and immune systems that remake the aging brain.

In a study recently published in the journalNatureScientists at the Allen Institute for Brain Science in the USA investigated how different cell types in the mouse brain change at the genetic level with age. By analyzing over 1.2 million single-cell transcriptomes from young and old mice, researchers identified key gene expression shifts associated with aging. These shifts highlight specific molecular mechanisms such as immune activation and structural integrity decline across different cell types. These results could help reveal brain regions and cells most affected by aging.

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Hypothalamus as an aging hub: The study identified the hypothalamus, particularly the third ventricular region, as a central hotspot for aging, with significant molecular changes in tanycytes, ependymal cells and neurons associated with energy homeostasis.

Aging is a natural process characterized by cellular and molecular changes that affect overall function. In the brain, aging manifests itself as, among other things, altered cell activity, inflammation and reduced neurogenesis. Previous studies have identified general aging markers across tissues and some brain-specific changes. However, given the complexity of the brain and its numerous cell types and functions, it remains unclear how specific cell types contribute to aging. ENTRAGE REQUIREMENTS has shown that certain regions, such as the third ventricle of the hypothalamus, serve as a focus for age-related changes. Recent advances in single-cell transcriptomics have provided unprecedented insights into cellular diversity, allowing researchers to identify changes at high resolution.

While these studies have shown age-related shifts in neurons and glial cells, comprehensive mapping across the entire brain is lacking. This mapping has now revealed distinct cell type-specific aging patterns, including immune activation and neuronal decline. Furthermore, specific changes in smaller, overlooked cell populations and their contribution to brain health and aging remain unexplored. Understanding these dynamics is critical to uncovering the mechanisms driving age-related cognitive and functional decline and their potential links to neurodegenerative diseases.

About the study

In the present study, single-cell ribonucleic acid sequencing (SCRNA-Seq) was used to examine the brains of young (2-month-old) and aged (18-month-old) mice. The researchers targeted 16 key brain regions and included the forebrain, midbrain and hindbrain. These regions were selected for their involvement in aging and age-related diseases. Using the 10x genomics platform, the researchers generated a dataset of approximately 1.2 million high-quality single-cell transcriptomes from neurons and non-neuronal cells. Notably, this is one of the most comprehensive single-cell datasets for aging research to date. Additional cell sorting strategies provided comprehensive sampling between cell types, and the study included fluorescence-activated cell sorting (FACS) for unbiased sampling of neurons and other cells.

Pro-inflammatory microglial clusters: Research revealed the formation of new, anti-inflammatory microglial clusters in aged brains, associated with senescence and increased immune signaling, particularly in subcortical regions.

The Allen Brain Cell Atlas, an open resource developed by the Allen Institute that allows researchers to examine numerous datasets across the brain, was used to annotate the data. The results identified 847 cell clusters representing 172 subclasses in 25 cell classes. In addition, the changes in gene expression were modeled using computational methods to detect differentially expressed genes associated with aging. Spatial transcriptomics was also used to obtain additional validation and visualize gene expression in brain regions of brain regions of interest.

Numerous other analyzes have been used to categorize differentially expressed genes by cell class and subclass while distinguishing age-related changes in neurons, glial cells, and other cell types. This included identifying specific pro-inflammatory microglial clusters and age-matched neural stem cell populations. Particular attention has been paid to sparsely distributed populations such as ependymal cells and tanycytes, specialized glial cells in the hypothalamus and involved in the regulation of physiological processes such as energy balance.

In addition, Gene Ontology or GO enrichment analyzes were performed to identify the biological processes affected by aging, such as: B. Immune signaling and maintenance of neuronal structure. These analyzes discovered significant losses in neurogenic potential and structural maintenance, particularly in tanycytes and neurons near the hypothalamic third ventricle. Key gene expression patterns were identified using in situ hybridization to complement the transcriptomic findings.

Results

The study found that aging leads to significant changes in gene expression in different brain cell types and identified 2,449 differentially expressed genes with unique and shared signatures across cell types. Neurons, glial and vascular cells showed distinct gene expression patterns, with many differentially expressed genes associated with immune activation, structural integrity and cellular senescence.

Myelin integrity in oligodendrocytes: The study found that age-related disturbances in oligodendrocyte function with altered expression of lipid transport and biosynthesis genes, indicating impaired myelin sheath maintenance.

Notably, neurons showed reduced expression of synaptic signaling and structural genes such as CCND2, while microglia showed an increase in inflammatory markers such as ILDR2 and CCL4. Glial cells such as astrocytes and oligodendrocytes showed reduced expression of support-related genes. In contrast, expression of immune-related genes was higher in microglia, macrophages, and other immune cell types.

Furthermore, region-specific changes were observed to be pronounced near the hypothalamic third ventricle, where tanycytes and ependymal cells showed notable age-associated shifts. These shifts included increased interferon response signaling and reduced markers of structural maintenance. Similarly, oligodendrocytes in aged brains showed altered gene expression patterns, suggesting impaired myelin integrity.

Vascular cells, particularly endothelial cells, also showed age-related gene expression changes associated with the genes involved in major histocompatibility complex (MHC) representation, with signs of impaired vascular function. Furthermore, the microglial cells in aged brains formed new clusters that were associated with pro-inflammatory and senescent states. The spatial analyzes confirmed increased immune activity localized in subcortical areas, particularly in the midbrain and hindbrain.

Conclusions

The results provided a detailed single-cell transcriptomic map of brain aging and no longer focused on cell-specific and region-specific molecular changes associated with aging. These findings highlight the hypothalamus as a hub for aging-related changes with significant implications for understanding neurodegenerative diseases. Key findings demonstrated the role of immune activation, neuronal decline and glial dysfunction in aging. These findings laid the foundation for research into how aging affects brain function and its intersection with neurodegenerative diseases.

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