In this study, we extracted top gene candidates from a meta-analysis of 127 publicly available transcriptomic datasets from mice, rats, and humans, identifying a transcriptomic signature of aging across species and tissues (i.e., B2M, C1qA, and SUCLG1) [21], and tested their expression by qPCR and their correlation with disease progression in 48 tissue samples covering several liver disease stages (i.e., fatty liver, hepatitis, cirrhosis, HCC, and CC) and normal tissues, supported by bioinformatics analyses in The Cancer Genome Atlas (TCGA). Here, SUCLG1 is linked to liver disorder.