Cross-species signaling pathways analysis inspire animal model selections for drug screening and target prediction in vascular aging diseases

Abstract

Age is a significant contributing factor to the occurrence and progression of cardiovascular disease (CVD). Pharmacological treatment can effectively alleviate CVD symptoms caused by aging. However, 90% of the drugs have failed in clinics because of the loss of drug effects or the occurrence of the side effects. One of the reasons is the disparity between animal models used and the actual physiological levels in humans. Therefore, we integrated multiple datasets from single-cell and bulk-seq RNA-sequencing data in rats, monkeys, and humans to identify genes and pathways with consistent/differential expression patterns across these three species. An approach called "Cross-species signaling pathway analysis" was developed to select suitable animal models for drug screening. The effectiveness of this method was validated through the analysis of the pharmacological predictions of four known anti-vascular aging drugs used in animal/clinical experiments. The effectiveness of drugs was consistently observed between the models and clinics when they targeted pathways with the same trend in our analysis. However, drugs might have exhibited adverse effects if they targeted pathways with opposite trends between the models and the clinics. Additionally, through our approach, we discovered four targets for anti-vascular aging drugs, which were consistent with their pharmaceutical effects in literatures, showing the value of this approach. In the end, software was established to facilitate the use of "Cross-species signaling pathway analysis." In sum, our study suggests utilizing bioinformatics analysis based on disease characteristics can help in choosing more appropriate animal models.

Keywords: animal model; cross‐species signaling pathway analysis; drugs in research; single‐cell RNA‐seq; vascular aging.

FIGURE 1

Cross‐species single‐cell transcriptome analysis inspires animal model selections for drug screening. (a) Animal models have been used for vascular aging studies from 2021 to 2024. (b) Species phylogenetic relationship analysis. (c) Schematic diagram of cross‐species single‐cell transcriptome analysis.

FIGURE 2

Cellular composition and interaction analysis of the vascular cells in rats, monkeys, and humans. (a) Uniform manifold approximation and projection (UMAP) plot shows the distribution of vascular cells in rats, monkeys, and humans. (b) Bar plots display the percentage of young and old vascular cells in rats, monkeys, and humans. (c) Circle plot highlights the differences in interaction intensity between old and young cells in rats, monkeys, and humans. The red lines represent increased interaction strength in old cells; while the blue lines represent decreased interaction strength in old cells.

FIGURE 3

The genes encoding collagen proteins are upregulated during vascular aging processes in multiple species. (a) The Venn plots show the overlapping number of differentially expressed genes in rats, monkeys, and humans with fold change >0.1 or <−0.1, p value < 0.05. Among the overlapping differentially expressed genes, the genes with the same relative expression trend between the young and old groups were defined as “same genes (SM genes)”; while the genes with the different expression trends were defined as “different genes (DE genes).” (b) Heatmap presents the 131 SM genes in rats, monkeys, and humans. (c) Protein–protein interaction networks (PPI) based on 131 SM genes in rats, monkeys, and humans.

FIGURE 4

Differences in signaling pathways during vascular aging in rats, monkeys, and humans. (a) Bar plots display overlapping pathways among rats, monkeys, and humans. The pathways above the dashed gray line represent SM signaling pathways (a signal pathway with the same NES symbol); while the pathways below the dashed gray line represent DE signaling pathways (a signal pathway with a different NES symbol). (b) The pathway diagram shows the expression of the “Lipid and atherosclerosis” (KEGG:05417) signaling pathway in blood vessel cells of rats, monkeys, and humans. Red boxes indicate the upregulation in old cells. Blue boxes indicate downregulation in old cells. Yellow boxes indicate no change.

FIGURE 5

Prediction of potential novel targets for anti‐vascular aging drugs. (a) Volcano plot shows the significantly different transcription factors (TFs) during rats and humans' vascular aging. (b) The Venn plots demonstrate the overlap of TFs in rats and humans with fold change >0.1 or <−0.1, p value < 0.05. Heatmap shows FOS, JUN, JUNB, and ATF3 gene expression. (c) Network diagram shows the FOS, JUN, JUNB, and ATF3 regulation of the downstream genes.