Single-cell Analysis Reveals Somatic Mutation Accumulation, Loss of Differentiation, and Increased Transcriptional Entropy in Aged Human Lungs

Abstract RATIONALE: Age is a major risk factor for lung disease. Accumulation of somatic mutations has been implicated in both aging and cellular senescence. Somatic mutations can affect transcriptional stability by mechanisms including affecting gene-regulatory networks and generating aberrant transcripts. We sought to examine the role of somatic mutations in the development of age-related lung dysfunction. METHODS: Single-cell RNAseq was performed on lung tissue cores from healthy donors (32 samples, 11-72 years, 21M/11F). Following standard pre-processing and cell type annotation, mutations were called using SComatic with the default parameters. Mutation burden was calculated by dividing the number of mutations by the number of callable sites. We calculated transcriptional entropy as a means to quantify loss of cell differentiation or phenotype. This was modeled using K-L divergence, with raw count data for each cell being compared to a uniform reference distribution. RESULTS: Our scRNAseq dataset consisted of 199,400 cells, which were clustered annotated to 25 distinct cell types. Mutation burden was positively correlated with age (r=0.28, p<0.001). Globally, the top genes correlated with mutation burden included ubiquitin ligase genes (AMBRA1, ANAPC1, SEL1L, USP25, USP33) and DNA damage response genes (RAD50, PRKDC). Notably, mutation burden also correlated with expression of senescence marker CDKN2A (r=0.48, p<0.05). In capillary endothelial cells, mutation burden was correlated with decreased expression of cell type differentiation markers (Il7R, VIPR1, FCN3), and mitochondrial genes. Similarly, in AT2 cells, mutation burden was associated with reduced expression of differentiation markers (SFTPC) and increased expression of chromatin organization (H2AFJ, ACTL6A) and damage repair genes (MACROD1, RAD17, BCCIP). Transcriptional entropy was increased with aging in most cell types, except for lymphocytes and myeloid cell types [Fig A]. The greatest age-associated difference in transcriptional entropy occurred in gCap cells (p<0.05) and AT2 cells (p<0.05). Finally, transcriptional entropy was strongly positively correlated with mutation burden (r=0.51, p<0.05) [Fig B]. CONCLUSIONS: Our analysis suggests that somatic mutation accumulation is associated with heterogenous transcriptional changes in different cell types, including loss of differentiation markers and increased transcriptional entropy. This process may contribute to phenotypic changes that predispose to age-related lung disease.

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