Single-cell atlas of human lung aging identifies cell type dyssynchrony and increased transcriptional entropy.

Lung aging is cell-type dyssynchronous, with alveolar epithelial and endothelial cells exhibiting the greatest transcriptional changes.

• Single-cell RNA sequencing was used to characterize the cellular, transcriptional, and genomic landscape of human lung aging.
• Different cell types showed markedly different degrees of transcriptional change with aging, indicating dyssynchrony rather than uniform aging across cell populations.
• Alveolar epithelial cells and endothelial cells were identified as the cell types most affected by the aging process.

Aging is associated with a decreased relative proportion of surfactant-expressing SPChigh AT2 cells among alveolar epithelial cells.

• Among alveolar epithelial cells, a specific subpopulation defined by high expression of surfactant protein C (SPChigh AT2 cells) declined with aging.
• This finding was identified through single-cell RNA sequencing analysis of the human lung.
• The loss of SPChigh AT2 cells represents a specific compositional change in the alveolar epithelium during aging.

Aging is associated with loss of differentiation and capillary function in alveolar capillary endothelial cells.

• Among alveolar capillary cells, aging was associated with observable loss of differentiation markers.
• Capillary function was also found to decline with aging in the alveolar capillary cell population.
• These changes were identified through transcriptional profiling of endothelial cell subpopulations via single-cell RNA sequencing.

Somatic mutations called from single-cell data increased with aging, with alveolar epithelial and endothelial cell types exhibiting greater mutation burdens.

• The study employed somatic mutation calling directly from single-cell RNA sequencing data.
• A positive association between age and somatic mutation burden was observed across lung cell types.
• Alveolar epithelial and endothelial cells showed disproportionately greater somatic mutation burdens compared to other cell types.
• This approach allowed cell-type-specific assessment of somatic mutational accumulation during aging.

Transcriptional entropy was increased with aging and was an independent predictor of age.

• Transcriptional entropy, a measure of gene expression disorder or randomness, was calculated at the single-cell level.
• Transcriptional entropy showed a significant increase with age across lung cell types.
• Transcriptional entropy was identified as an independent predictor of chronological age.
• This finding suggests that increased transcriptional noise or disorder is a hallmark of lung cell aging.

Cells expressing commonly accepted senescence signatures did not increase with age in the human lung.

• The study specifically tested whether senescent cell populations, defined by commonly accepted transcriptional senescence signatures, accumulated with aging.
• Contrary to widely held assumptions, the proportion of cells expressing senescence signatures did not significantly increase with age.
• This finding challenges the prevailing model that cellular senescence accumulation is a primary driver of lung aging.