The DOI matches its Crossref record; 237 of the 237 references it cites were found in a registry or an index.
Aging and age‐related diseases: from mechanisms to therapeutic strategies
Open accessAbstract
Aging is a physiological process mediated by numerous biological and genetic pathways, which are directly linked to lifespan and are a driving force for all age-related diseases. Human life expectancy has greatly increased in the past few decades, but this has not been accompanied by a similar increase in their healthspan. At present, research on aging biology has focused on elucidating the biochemical and genetic pathways that contribute to aging over time. Several aging mechanisms have been identified, primarily including genomic instability, telomere shortening, and cellular senescence. Aging is a driving factor of various age-related diseases, including neurodegenerative diseases, cardiovascular diseases, cancer, immune system disorders, and musculoskeletal disorders. Efforts to find drugs that improve the healthspan by targeting the pathogenesis of aging have now become a hot topic in this field. In the present review, the status of aging research and the development of potential drugs for aging-related diseases, such as metformin, rapamycin, resveratrol, senolytics, as well as caloric restriction, are summarized. The feasibility, side effects, and future potential of these treatments are also discussed, which will provide a basis to develop novel anti-aging therapeutics for improving the healthspan and preventing aging-related diseases.
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2 retracted
Janczura, K. J., Volmar, C.-H., Sartor, G. C., Rao, S. J., Ricciardi, N. R., Lambert, G., Brothers, S. P., & Wahlestedt, C. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1805436115 · Cited by 183
RetractedKalra, N., Roy, P., Prasad, S., & Shukla, Y. (2007) · Life Sciences · doi:10.1016/j.lfs.2007.11.006 · Cited by 93
RetractedLópez-Otín, C., Blasco, M. A., Partridge, L., Serrano, M., & Kroemer, G. (2013) · Cell · doi:10.1016/j.cell.2013.05.039 · Cited by 14,982
The serial cultivation of human diploid cell strains
Hayflick, L., & Moorhead, P. S. (1961) · Experimental Cell Research · doi:10.1016/0014-4827(61)90192-6 · Cited by 8,508
The senescence-associated secretory phenotype: the dark side of tumor suppression
Coppé, J.-P., Desprez, P.-Y., Krtolica, A., & Campisi, J. (2010) · Annual Review of Pathology: Mechanisms of Disease · doi:10.1146/annurev-pathol-121808-102144 · Cited by 5,206
Resveratrol improves health and survival of mice on a high-calorie diet
Baur, J. A., Pearson, K. J., Price, N. L., Jamieson, H. A., Lerin, C., Kalra, A., Prabhu, V. V., Allard, J. S., Lopez-Lluch, G., Lewis, K., et al. (2006) · Nature · doi:10.1038/nature05354 · Cited by 4,290
AMPK Phosphorylation of Raptor Mediates a Metabolic Checkpoint
Gwinn, D. M., Shackelford, D. B., Egan, D. F., Mihaylova, M. M., Mery, A., Vasquez, D. S., Turk, B. E., & Shaw, R. J. (2008) · Molecular Cell · doi:10.1016/j.molcel.2008.03.003 · Cited by 3,849
Small molecule activators of sirtuins extend Saccharomyces cerevisiae lifespan
Howitz, K. T., Bitterman, K. J., Cohen, H. Y., Lamming, D. W., Lavu, S., Wood, J. G., Zipkin, R. E., Chung, P., Kisielewski, A., Zhang, L.-L., et al. (2003) · Nature · doi:10.1038/nature01960 · Cited by 3,796
Rapamycin fed late in life extends lifespan in genetically heterogeneous mice
Harrison, D. E., Strong, R., Sharp, Z. D., Nelson, J. F., Astle, C. M., Flurkey, K., Nadon, N. L., Wilkinson, J. E., Frenkel, K., Carter, C. S., et al. (2009) · Nature · doi:10.1038/nature08221 · Cited by 3,766
Clearance of p16Ink4a-positive senescent cells delays ageing-associated disorders
Baker, D. J., Wijshake, T., Tchkonia, T., LeBrasseur, N. K., Childs, B. G., van de Sluis, B., Kirkland, J. L., & van Deursen, J. M. (2011) · Nature · doi:10.1038/nature10600 · Cited by 3,670
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Fernández-Calle, R., Konings, S. C., Frontiñán-Rubio, J., García-Revilla, J., Camprubí-Ferrer, L., Svensson, M., Martinson, I., Boza-Serrano, A., Venero, J. L., Nielsen, H. M., et al. (2022) · Molecular Neurodegeneration · doi:10.1186/s13024-022-00566-4 · Cited by 278
A panoramic view of cell population dynamics in mammalian aging
Zhang, Z., Schaefer, C., Jiang, W., Lu, Z., Lee, J., Sziraki, A., Abdulraouf, A., Wick, B., Haeussler, M., Li, Z., et al. (2025) · Science · doi:10.1126/science.adn3949 · Cited by 95
Self-citationGlucose metabolism, neural cell senescence and Alzheimer's disease
Wang, Q., Duan, L., Li, X., Wang, Y., Guo, W., Guan, F., & Ma, S. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23084351 · Cited by 90
Self-citationTargeting Cellular Senescence for Healthy Aging: Advances in Senolytics and Senomorphics
Alum, E., Izah, S., Uti, D., Ugwu, O., Betiang, P., Basajja, M., & Ejemot-Nwadiaro, R. (2025) · Drug Design, Development and Therapy · doi:10.2147/dddt.s543211 · Cited by 63
Metadata
- Authors
- Li, Z., Zhang, Z., Ren, Y., Wang, Y., Fang, J., Yue, H., Ma, S., & Guan, F.
- Venue
- Biogerontology
- Published
- 2021-01-27
- Volume
- 22
- Issue
- 2
- Pages
- 165-187
- ISSN
- 1389-5729 (ISSN-L)
- 1573-6768
- OpenAlex
- W3123843327
- Cited by
- 640
- References
- 237
- FWCI
- 23.97
- Type
- journal article
- Language
- en
- Open access
- bronze
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