Fig. 4: Aging lamina propria immune cell composition changes towards pro-inflammatory condition.

a UMAP projection of all 8997 immune cells (4423 young cells and 4574 old cells) presenting nine different clusters, identified via shared nearest neighbor modularity optimization-based clustering algorithm, followed by merging of similar clusters. n \(\ge\) 3 mice per group were analyzed. b Bar chart of odds ratio with 95% confidence interval showing the relative abundance of different immune cells changing in aging. P value was calculated by two-sided hypergeometric test. c Representative FACS plots showing percentages of CCL5⁺ CD4 T (cytotoxic) cells in the indicated ages. d The bar chart shows the percentage of CCL5⁺ cells from CD4 T cells in the indicated ages. n = 4 mice per group were analyzed. Error bars represent the SD. P value was calculated by two-sided Welch’s t test. e Representative FACS plots showing percentages of Klrg1⁺ ILC2s in the indicated ages. f The bar chart shows the percentage of Klrg1⁺ ILC2s in the indicated ages. n = 3 (young) and n = 4 (old) mice per group were analyzed. Error bars represent the SD. P value was calculated by two-sided Welch’s t test. g Hierarchical clustering and heatmap of gene expression for identified cytokines in our scRNA-seq datasets. h Upstream regulators associated with the DEGs from RNA-seq of intestinal crypts cells during aging. X axis shows the activation Z score of each upstream regulator, and color code shows enrichment P value (−log10). P value is calculated using the right-tailed Fisher Exact Test.