Open Access Articles- Top Results for Biomarkers of aging

Biomarkers of aging

Biomarkers of aging are biomarkers that better predict functional capacity at a later age than chronological age.[1] Stated another way, biomarkers of aging would give the true "biological age", which may be different from the chronological age.

Validated biomarkers of aging would allow for testing interventions to extend lifespan, because changes in the biomarkers would be observable throughout the lifespan of the organism.[1] Although maximum lifespan would be a means of validating biomarkers of aging, it would not be a practical means for long-lived species such as humans because longitudinal studies would take far too much time.[2] Ideally, biomarkers of aging should assay the biological process of ageing and not a predisposition to disease, should cause a minimal amount of trauma to assay in the organism, and should be reproducibly measurable during a short interval compared to the lifespan of the organism.[1]

Although graying of hair increases with age,[3] hair graying cannot be called a biomarker of ageing. Similarly, skin wrinkles and other common changes seen with aging are not better indicators of future functionality than chronological age. Biogerontologists have continued efforts to find and validate biomarkers of aging, but success thus far has been limited. Levels of CD4 and CD8 memory T cells and naive T cells have been used to give good predictions of the expected lifespan of middle-aged mice.[4]

Biological clocks, for example the epigenetic clock, are promising biomarkers of aging.[5]

See also


  1. ^ a b c George T. Baker, III and Richard L. Sprott (1988). "Biomarkers of aging". EXPERIMENTAL GERONTOLOGY 23 (4-5): 223–239. PMID 3058488. doi:10.1016/0531-5565(88)90025-3. 
  2. ^ Harrison, Ph.D., David E. (November 11, 2011). "V. Life span as a biomarker". Jackson Laboratory. Retrieved 2011-12-03. 
  3. ^ Van Neste D, Tobin DJ (2004). "Hair cycle and hair pigmentation: dynamic interactions and changes associated with aging". MICRON 35 (3): 193–200. PMID 15036274. doi:10.1016/j.micron.2003.11.006. 
  4. ^ Miller RA (2001). "Biomarkers of aging: prediction of longevity by using age-sensitive T-cell subset determinations in a middle-aged, genetically heterogeneous mouse population". JOURNALS OF GERONTOLOGY 56 (4): B180–B186. PMID 11283189. doi:10.1093/gerona/56.4.b180. 
  5. ^ Horvath S (2013). "DNA methylation age of human tissues and cell types". Genome Biology 14 (10): R115. PMC 4015143. PMID 24138928. doi:10.1186/gb-2013-14-10-r115. 

External links