1. Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China.
2. NHC Key Laboratory of Combined Multi-organ Transplantation, Hangzhou 310003, China.
3. Key Laboratory of the diagnosis and treatment of organ Transplantation, Research Unit of Collaborative Diagnosis and Treatment for Hepatobiliary and Pancreatic Cancer, Chinese Academy of Medical Sciences (2019RU019), Hangzhou 310003, China.
4. Key Laboratory of Organ Transplantation, Research Center for Diagnosis and Treatment of Hepatobiliary Diseases, Zhejiang Province, Hangzhou 310003, China.
5. Shulan International Medical College, Zhejiang Shuren University, Hangzhou 310015, Zhejiang, China.
6. Shulan (Hangzhou) Hospital Affiliated to Zhejiang Shuren University Shulan International Medical College, Hangzhou 310000, China.
#These authors contributed equally to this work.
Research on liver aging has become prominent and has attracted considerable interest in uncovering the mechanism and therapeutic targets of aging to expand lifespan. In addition, multi-omics studies are widely used to perform further mechanistic investigations on liver aging. In this review, we illustrate the changes that occur with aging in the liver, present the current models of liver aging, and emphasize existing multi-omics studies on liver aging. We integrated the multi-omics data of enrolled studies and reanalyzed them to identify key pathways and targets of liver aging. The results indicated that C-X-C motif chemokine ligand 9 (Cxcl9) was a regulator of liver aging. In addition, we provide a flowchart for liver aging research using multi-omics analysis and molecular experiments to help researchers conduct further research. Finally, we present emerging therapeutic treatments that prolong lifespan. In summary, using cells and animal models of liver aging, we can apply a multi-omics approach to find key metabolic pathways and target genes to mitigate the adverse effects of liver aging.
Keywords: Liver aging, Multi-omics analysis, Model of liver aging, Therapeutic approach.