Comparison of multi-tissue aging between human and mouse

Abstract

With the rapid growth of the aging population, exploring the biological basis of aging and related molecular mechanisms has become an important topic in modern scientific research. Aging can cause multiple organ function attenuations, leading to the occurrence and development of various age-related metabolic, nervous system, and cardiovascular diseases. In addition, aging is closely related to the occurrence and development of tumors. Although a number of studies have used various mouse models to study aging, further research is needed to associate mouse and human aging at the molecular level. In this paper, we systematically assessed the relationship between human and mouse aging by comparing multi-tissue age-related gene expression sets. We compared 18 human and mouse tissues, and found 9 significantly correlated tissue pairs. Functional analysis also revealed some terms related to aging in human and mouse. And we performed a crosswise comparison of homologous age-related genes with 18 tissues in human and mouse respectively, and found that human Brain_Cortex was significantly correlated with Brain_Hippocampus, which was also found in mouse. In addition, we focused on comparing four brain-related tissues in human and mouse, and found a gene-GFAP-related to aging in both human and mouse.

Figure 1

Workflow of the aging project.

Figure 2

Functional groups in ClueGO Overview. ClueGO analysis of DEGs in Brain_Cerebellum, Brain_Cortex, Brain_Hippocampus and brain from human donors. Overview chart with functional groups including specific terms for DEGs. The percentage of genes per term is shown in each group.

Figure 3

Functionally grouped networks on cerebellum, neocortex, hippocampus and brain for mouse. Functionally grouped network with terms as nodes linked based on their kappa score level (≥ 0.4), where only the label of the most significant term per group is shown. Each node in the figure represents a term, and the node size represents the term enrichment significance. Functionally related groups partially overlap. The connection between the nodes reflects the correlation between the terms, and the color of the node reflects the enrichment classification of the node.