Fig. 5: Spatial omics for decoding aging.

a Prior research works have generally followed the pipeline shown above. Samples are collected from various age groups and characterized at the single-cell level for their gene expression. b This gene expression is analyzed and plots are generated for the different cell types, regions, and age points, as well as summarized together. c Furthermore, analysis can be done spatially based on the phenotypes of the cells; neighborhood networks can be created that show how differences in the assessed age of the cell and their location result in differences in the composition of the nearest neighboring cells. d Finally, these results can be combined to create a metric to measure age state at the single cell level, as well as map different phenomena throughout the various age groups (inflammation shown in the figure above). Created with Biorender.com.