Biomarkers of aging are biomarkers that could predict functional
capacity at some later age better than chronological age. 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. 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. Ideally, biomarkers of aging should
assay the biological process of aging 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. An assemblage of
biomarker data for an organism could be termed its "ageotype".Although
graying of hair increases with age, 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.Advances in big data analysis allowed for the new
types of "aging clocks" to be developed. The epigenetic clock is a
promising biomarker of aging and can accurately predict human
chronological age. Basic blood biochemistry and cell counts can also
be used to accurately predict the chronological age. Further studies
of the hematological clock on the large datasets from South Korean,
Canadian, and Eastern European populations demonstrated that
biomarkers of aging may be population-specific and predictive of
mortality. It is also possible to predict the human chronological age
using the transcriptomic clock.
capacity at some later age better than chronological age. 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. 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. Ideally, biomarkers of aging should
assay the biological process of aging 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. An assemblage of
biomarker data for an organism could be termed its "ageotype".Although
graying of hair increases with age, 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.Advances in big data analysis allowed for the new
types of "aging clocks" to be developed. The epigenetic clock is a
promising biomarker of aging and can accurately predict human
chronological age. Basic blood biochemistry and cell counts can also
be used to accurately predict the chronological age. Further studies
of the hematological clock on the large datasets from South Korean,
Canadian, and Eastern European populations demonstrated that
biomarkers of aging may be population-specific and predictive of
mortality. It is also possible to predict the human chronological age
using the transcriptomic clock.
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