Longevity Wiki - User contributions [en-GB]

Epigenetic clock

2021-04-19T20:07:05Z

Survival Bias: Fix headers

Biological age is a measure of our position across our lifespan. '''Epigenetic clocks''' are one way to measure biological age, and are based on DNA methylation levels. These clocks have been [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5076441/ shown] to predict time to death more accurately than chronological age.

== Mechanism ==
Epigenetic clock works by measuring DNA methylation levels, i.e. the number and distribution of methyl groups attached to the DNA molecule. These ‘tags’ signal to genes to be turned on or off.

[[wikipedia:DNA_methylation|DNA methylation]] is attachment of a methyl group to one of the “links” in the DNA strain (specifically, cytosine nucleotide). This does not affect the content of the DNA itself, but it does affect how it’s being read and used by the cell. This is one of the group of changes called epigenetics - changes in the organism's physical function which do not alter the DNA sequence itself, but - under certain conditions - can be inherited.

There has been a [https://clinicalepigeneticsjournal.biomedcentral.com/articles/10.1186/s13148-019-0656-7 number of studies] showing that as humans (and other mammals) age, patterns of methylation in their DNA change in certain ways. The exact patterns of change are quite complex and not yet fully described, but broadly there were two tendencies detected. First, the global level of methylation decreases, unequally in different tissues (for example in mice methylation levels decreased in brain, heart and spleen, but not in lungs or liver). Secondly, the local methylation level increases in certain locations: CpG islands (regions on a DNA strain where the sequence cytosine-guanine occurs with high frequency) and bivalent chromatin domain promoters (promoter is a sequence in DNA which initiates transcription of the gene following it).

These changes can be used to estimate the biological age of the organism, and there’s a [[wikipedia:Epigenetic_clock#Other_age_estimators_based_on_DNA_methylation_levels|number of approaches]] to that, most common being the Horvath’s clock, developed by [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3120753/ Horvath et al. in 2013]. They used publicly available datasets of methylation data collected on [[wikipedia:Illumina,_Inc.|Illumina]] chips, and analyzed 21,369 CpG sites available on both 27k and 450k chips (the number referring to the total number of sites the chip analyzes). The team then used a penalized regression model (Elastic net regularization, which is essentially a linear combination of lasso and ridge regularization penalties which thus drives the model to have both smaller coefficients and fewer of them) to identify 353 sites providing the most signal, of which 193 correlated with age positively and the remaining 160 negatively. The clock then applies a calibration function to the weighted average of these 353 sites methylation levels to determine the biological age.

== Discovery ==
Changes in methylation levels with aging have been observed for some time. First work using epigenetic changes as a basis for biological clocks was [https://www.researchgate.net/publication/344399255_An_epigenetic_clock_Anticorrelation_DNA_methylation_as_biomarker_for_aging?channel=doi&linkId=5f70f837458515b7cf5402bc&showFulltext=true published] in 2009 by Schumacher. In 2013, the labs of Trey Ideker and Kang Zhang at the University of California, San Diego published the Hannum epigenetic clock ([https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3780611/ Hannum 2013]), which consisted of 71 markers that accurately estimate age based on blood methylation levels, and in the same year the first multi-tissue epigenetic clock, was developed by Steve Horvath, a professor of human genetics and of biostatistics at UCLA ([https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4015143/ Horvath 2013]) Horvath’s clock allows to measure the age of different tissues of the same organism with the same clock, so it is most widely used in aging research today.

== Epigenetic clocks and aging ==

It is not fully known whether epigenetic changes are a cause or consequence of other aging processes. Several theories have been proposed, and are explained below:

=== Link with other Hallmarks of Aging ===
There is [https://www.hindawi.com/journals/sci/2020/1047896/ evidence] that changed methylation patterns can be linked to some of the [[Hallmarks of Aging|hallmarks of aging]]: loss of proteostasis, mitochondrial dysfunction, stem cell exhaustion and immunosenescence. [https://pubmed.ncbi.nlm.nih.gov/33268865/ David Sinclair et al.] were able to reverse age-induced loss of sight and even regenerate a mechanically damaged eye nerve by manipulating methylation patterns in mice. They used three out of four so-called Yamanaka factors which are proteins used in pluripotent stem cells. Using the factors in live organisms for prolonged periods of time is known to cause cancer by boosting up cell division. But David's team excluded one of these factors, MYC, known to be oncogenic, and they were able to keep the other three active in mice for over a year without developing any tumors.

They were then able to use these factors to allow mice to regrow a mechanically damaged optic nerve. Normally a mouse's optic nerve can regrow during development but then it loses this ability a few days after birth. In this experiment the grown up mice restored this regeneration ability and have regained around half of their lost visual acuity.

Another result achieved using Yamanaka factors was restoring vision of healthy, middle-aged (one-year-old) mice. These mice scored worse on the tests of visual acuity before treatment than the younger mice, but one month after treatment they had similar results

=== Information theory of aging ===
Another theory, popularised by Professor David Sinclair, is that epigenetic changes might be the master regulator aging - known as [https://hplus.club/blog/a-summary-of-david-sinclairs-information-theory-of-aging/ the information theory of aging].

Since DNA is identical in every somatic cell, each cell in order to differentiate from a stem cell and then perform its function needs to “know” which genes to read, so that e.g. a neuron cell only expresses (i.e. uses) genes relevant for being a neuron, and not a muscle cell or a skin cell. This is achieved through methylation and other epigenetic mechanisms.

The theory goes that aging is fundamentally caused by errors in this process accumulating, eventually causing a cell to stop functioning normally and either become cancerous or die.

== Relevance for longevity research ==

=== Smoking ===
[https://clinicalepigeneticsjournal.biomedcentral.com/articles/10.1186/s13148-019-0777-z#:~:text=The%20statistical%20analyses%20showed%20the,level%20that%20non%2Dsmokers%20had. Research] shows that smoking increases epigenetic age of buccal cells, airway cells, esophagus tissue, and lung tissue. Quitting smoking caused the epigenetic age acceleration in airway cells (but not in lung tissue) to revert to the level of non-smokers.

=== Obesity ===
Obesity (defined as increased BMI) has been shown to correlate with increased epigenetic age in a number of tissues. For liver tissue, [https://www.pnas.org/content/111/43/15538/ this study] found the average increase of ~2.2 years of epigenetic age for each 10 BMI units. There was no correlation for blood cells however. [https://clinicalepigeneticsjournal.biomedcentral.com/articles/10.1186/s13148-019-0754-6#:~:text=Epigenetic%20age%20acceleration%20increases%20with,acceleration%20of%20metabolically%20active%20tissues. Another study] found an increase of ~2.3 years per 10 BMI points for visceral adipose tissue (visceral fat).

=== Depression ===
Major depressive disorder (MDD) was also found to be associated with increased epigenetic age. The study by [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6094380/ Han et al.] found increased epigenetic age in blood cells associated with symptoms of MDD and childhood trauma scores. They also analyzed brain cells (collected post mortem) and found that increased epigenetic age correlated with MDD symptoms.

=== Partial Epigenetic Reprogramming ===
[https://pubmed.ncbi.nlm.nih.gov/33268865/ David Sinclair et al.] were able to reverse age-induced loss of sight and even regenerate a mechanically damaged eye nerve by manipulating methylation patterns in mice. In addition to vision restoration mentioned above they were able to [https://pubmed.ncbi.nlm.nih.gov/33268865/ improve] locomotive and cognitive performance in aged mice, and they also were able to [https://pubmed.ncbi.nlm.nih.gov/32556267/ shift the clocks forward], making the mice biologically older than it should be (obviously not particularly useful in practice but that’s necessary to confirm that their model of aging works).

== Other uses ==
Epigenetic clock also has many other [[wikipedia:Epigenetic_clock#Motivation_for_biological_clocks|applications]]:

* testing the validity of various theories of biological aging,
* diagnosing various age related diseases and for defining cancer subtypes,
* predicting/prognosticating the onset of various diseases,
* serving as surrogate markers for evaluating therapeutic interventions including rejuvenation approaches,
* studying developmental biology and cell differentiation,
* forensic applications, for example to estimate the age of a suspect based on blood left on a crime scene.

Aging clock

2021-04-19T20:03:45Z

Survival Bias: Survival Bias moved page Aging clock to Epigenetic clock: This article is narrowly focused on epigenetic clocks and doesn't cover any other kinds of clocks

#REDIRECT [[Epigenetic clock]]

Epigenetic clock

2021-04-19T20:03:45Z

Survival Bias: Survival Bias moved page Aging clock to Epigenetic clock: This article is narrowly focused on epigenetic clocks and doesn't cover any other kinds of clocks

Biological age is a measure of our position across our lifespan. '''Epigenetic clocks''' are one way to measure biological age, and are based on DNA methylation levels. These clocks have been [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5076441/ shown] to predict time to death more accurately than chronological age.

== Mechanism ==
Epigenetic clock works by measuring DNA methylation levels, i.e. the number and distribution of methyl groups attached to the DNA molecule. These ‘tags’ signal to genes to be turned on or off.

[[wikipedia:DNA_methylation|DNA methylation]] is attachment of a methyl group to one of the “links” in the DNA strain (specifically, cytosine nucleotide). This does not affect the content of the DNA itself, but it does affect how it’s being read and used by the cell. This is one of the group of changes called epigenetics - changes in the organism's physical function which do not alter the DNA sequence itself, but - under certain conditions - can be inherited.

There has been a [https://clinicalepigeneticsjournal.biomedcentral.com/articles/10.1186/s13148-019-0656-7 number of studies] showing that as humans (and other mammals) age, patterns of methylation in their DNA change in certain ways. The exact patterns of change are quite complex and not yet fully described, but broadly there were two tendencies detected. First, the global level of methylation decreases, unequally in different tissues (for example in mice methylation levels decreased in brain, heart and spleen, but not in lungs or liver). Secondly, the local methylation level increases in certain locations: CpG islands (regions on a DNA strain where the sequence cytosine-guanine occurs with high frequency) and bivalent chromatin domain promoters (promoter is a sequence in DNA which initiates transcription of the gene following it).

These changes can be used to estimate the biological age of the organism, and there’s a [[wikipedia:Epigenetic_clock#Other_age_estimators_based_on_DNA_methylation_levels|number of approaches]] to that, most common being the Horvath’s clock, developed by [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3120753/ Horvath et al. in 2013]. They used publicly available datasets of methylation data collected on [[wikipedia:Illumina,_Inc.|Illumina]] chips, and analyzed 21,369 CpG sites available on both 27k and 450k chips (the number referring to the total number of sites the chip analyzes). The team then used a penalized regression model (Elastic net regularization, which is essentially a linear combination of lasso and ridge regularization penalties which thus drives the model to have both smaller coefficients and fewer of them) to identify 353 sites providing the most signal, of which 193 correlated with age positively and the remaining 160 negatively. The clock then applies a calibration function to the weighted average of these 353 sites methylation levels to determine the biological age.

== Discovery ==
Changes in methylation levels with aging have been observed for some time. First work using epigenetic changes as a basis for biological clocks was [https://www.researchgate.net/publication/344399255_An_epigenetic_clock_Anticorrelation_DNA_methylation_as_biomarker_for_aging?channel=doi&linkId=5f70f837458515b7cf5402bc&showFulltext=true published] in 2009 by Schumacher. In 2013, the labs of Trey Ideker and Kang Zhang at the University of California, San Diego published the Hannum epigenetic clock ([https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3780611/ Hannum 2013]), which consisted of 71 markers that accurately estimate age based on blood methylation levels, and in the same year the first multi-tissue epigenetic clock, was developed by Steve Horvath, a professor of human genetics and of biostatistics at UCLA ([https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4015143/ Horvath 2013]) Horvath’s clock allows to measure the age of different tissues of the same organism with the same clock, so it is most widely used in aging research today.

== Epigenetic clocks and aging ==

It is not fully known whether epigenetic changes are a cause or consequence of other aging processes. Several theories have been proposed, and are explained below:

== Link with other Hallmarks of Aging ==
There is [https://www.hindawi.com/journals/sci/2020/1047896/ evidence] that changed methylation patterns can be linked to some of the [[Hallmarks of Aging|hallmarks of aging]]: loss of proteostasis, mitochondrial dysfunction, stem cell exhaustion and immunosenescence. [https://pubmed.ncbi.nlm.nih.gov/33268865/ David Sinclair et al.] were able to reverse age-induced loss of sight and even regenerate a mechanically damaged eye nerve by manipulating methylation patterns in mice. They used three out of four so-called Yamanaka factors which are proteins used in pluripotent stem cells. Using the factors in live organisms for prolonged periods of time is known to cause cancer by boosting up cell division. But David's team excluded one of these factors, MYC, known to be oncogenic, and they were able to keep the other three active in mice for over a year without developing any tumors.

They were then able to use these factors to allow mice to regrow a mechanically damaged optic nerve. Normally a mouse's optic nerve can regrow during development but then it loses this ability a few days after birth. In this experiment the grown up mice restored this regeneration ability and have regained around half of their lost visual acuity.

Another result achieved using Yamanaka factors was restoring vision of healthy, middle-aged (one-year-old) mice. These mice scored worse on the tests of visual acuity before treatment than the younger mice, but one month after treatment they had similar results

== Information theory of aging ==
Another theory, popularised by Professor David Sinclair, is that epigenetic changes might be the master regulator aging - known as [https://hplus.club/blog/a-summary-of-david-sinclairs-information-theory-of-aging/ the information theory of aging].

Since DNA is identical in every somatic cell, each cell in order to differentiate from a stem cell and then perform its function needs to “know” which genes to read, so that e.g. a neuron cell only expresses (i.e. uses) genes relevant for being a neuron, and not a muscle cell or a skin cell. This is achieved through methylation and other epigenetic mechanisms.

The theory goes that aging is fundamentally caused by errors in this process accumulating, eventually causing a cell to stop functioning normally and either become cancerous or die.

== Relevance for longevity research ==

== Smoking ==
[https://clinicalepigeneticsjournal.biomedcentral.com/articles/10.1186/s13148-019-0777-z#:~:text=The%20statistical%20analyses%20showed%20the,level%20that%20non%2Dsmokers%20had. Research] shows that smoking increases epigenetic age of buccal cells, airway cells, esophagus tissue, and lung tissue. Quitting smoking caused the epigenetic age acceleration in airway cells (but not in lung tissue) to revert to the level of non-smokers.

== Obesity ==
Obesity (defined as increased BMI) has been shown to correlate with increased epigenetic age in a number of tissues. For liver tissue, [https://www.pnas.org/content/111/43/15538/ this study] found the average increase of ~2.2 years of epigenetic age for each 10 BMI units. There was no correlation for blood cells however. [https://clinicalepigeneticsjournal.biomedcentral.com/articles/10.1186/s13148-019-0754-6#:~:text=Epigenetic%20age%20acceleration%20increases%20with,acceleration%20of%20metabolically%20active%20tissues. Another study] found an increase of ~2.3 years per 10 BMI points for visceral adipose tissue (visceral fat).

== Depression ==
Major depressive disorder (MDD) was also found to be associated with increased epigenetic age. The study by [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6094380/ Han et al.] found increased epigenetic age in blood cells associated with symptoms of MDD and childhood trauma scores. They also analyzed brain cells (collected post mortem) and found that increased epigenetic age correlated with MDD symptoms.

== Partial Epigenetic Reprogramming ==
[https://pubmed.ncbi.nlm.nih.gov/33268865/ David Sinclair et al.] were able to reverse age-induced loss of sight and even regenerate a mechanically damaged eye nerve by manipulating methylation patterns in mice. In addition to vision restoration mentioned above they were able to [https://pubmed.ncbi.nlm.nih.gov/33268865/ improve] locomotive and cognitive performance in aged mice, and they also were able to [https://pubmed.ncbi.nlm.nih.gov/32556267/ shift the clocks forward], making the mice biologically older than it should be (obviously not particularly useful in practice but that’s necessary to confirm that their model of aging works).

== Other uses ==
Epigenetic clock also has many other [[wikipedia:Epigenetic_clock#Motivation_for_biological_clocks|applications]]:

* testing the validity of various theories of biological aging,
* diagnosing various age related diseases and for defining cancer subtypes,
* predicting/prognosticating the onset of various diseases,
* serving as surrogate markers for evaluating therapeutic interventions including rejuvenation approaches,
* studying developmental biology and cell differentiation,
* forensic applications, for example to estimate the age of a suspect based on blood left on a crime scene.

Epigenetic clock

2021-04-19T20:00:30Z

Survival Bias: Add links and reorder some items

Biological age is a measure of our position across our lifespan. '''Epigenetic clocks''' are one way to measure biological age, and are based on DNA methylation levels. These clocks have been [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5076441/ shown] to predict time to death more accurately than chronological age.

== Mechanism ==
Epigenetic clock works by measuring DNA methylation levels, i.e. the number and distribution of methyl groups attached to the DNA molecule. These ‘tags’ signal to genes to be turned on or off.

[[wikipedia:DNA_methylation|DNA methylation]] is attachment of a methyl group to one of the “links” in the DNA strain (specifically, cytosine nucleotide). This does not affect the content of the DNA itself, but it does affect how it’s being read and used by the cell. This is one of the group of changes called epigenetics - changes in the organism's physical function which do not alter the DNA sequence itself, but - under certain conditions - can be inherited.

There has been a [https://clinicalepigeneticsjournal.biomedcentral.com/articles/10.1186/s13148-019-0656-7 number of studies] showing that as humans (and other mammals) age, patterns of methylation in their DNA change in certain ways. The exact patterns of change are quite complex and not yet fully described, but broadly there were two tendencies detected. First, the global level of methylation decreases, unequally in different tissues (for example in mice methylation levels decreased in brain, heart and spleen, but not in lungs or liver). Secondly, the local methylation level increases in certain locations: CpG islands (regions on a DNA strain where the sequence cytosine-guanine occurs with high frequency) and bivalent chromatin domain promoters (promoter is a sequence in DNA which initiates transcription of the gene following it).

These changes can be used to estimate the biological age of the organism, and there’s a [[wikipedia:Epigenetic_clock#Other_age_estimators_based_on_DNA_methylation_levels|number of approaches]] to that, most common being the Horvath’s clock, developed by [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3120753/ Horvath et al. in 2013]. They used publicly available datasets of methylation data collected on [[wikipedia:Illumina,_Inc.|Illumina]] chips, and analyzed 21,369 CpG sites available on both 27k and 450k chips (the number referring to the total number of sites the chip analyzes). The team then used a penalized regression model (Elastic net regularization, which is essentially a linear combination of lasso and ridge regularization penalties which thus drives the model to have both smaller coefficients and fewer of them) to identify 353 sites providing the most signal, of which 193 correlated with age positively and the remaining 160 negatively. The clock then applies a calibration function to the weighted average of these 353 sites methylation levels to determine the biological age.

== Discovery ==
Changes in methylation levels with aging have been observed for some time. First work using epigenetic changes as a basis for biological clocks was [https://www.researchgate.net/publication/344399255_An_epigenetic_clock_Anticorrelation_DNA_methylation_as_biomarker_for_aging?channel=doi&linkId=5f70f837458515b7cf5402bc&showFulltext=true published] in 2009 by Schumacher. In 2013, the labs of Trey Ideker and Kang Zhang at the University of California, San Diego published the Hannum epigenetic clock ([https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3780611/ Hannum 2013]), which consisted of 71 markers that accurately estimate age based on blood methylation levels, and in the same year the first multi-tissue epigenetic clock, was developed by Steve Horvath, a professor of human genetics and of biostatistics at UCLA ([https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4015143/ Horvath 2013]) Horvath’s clock allows to measure the age of different tissues of the same organism with the same clock, so it is most widely used in aging research today.

== Epigenetic clocks and aging ==

It is not fully known whether epigenetic changes are a cause or consequence of other aging processes. Several theories have been proposed, and are explained below:

== Link with other Hallmarks of Aging ==
There is [https://www.hindawi.com/journals/sci/2020/1047896/ evidence] that changed methylation patterns can be linked to some of the [[Hallmarks of Aging|hallmarks of aging]]: loss of proteostasis, mitochondrial dysfunction, stem cell exhaustion and immunosenescence. [https://pubmed.ncbi.nlm.nih.gov/33268865/ David Sinclair et al.] were able to reverse age-induced loss of sight and even regenerate a mechanically damaged eye nerve by manipulating methylation patterns in mice. They used three out of four so-called Yamanaka factors which are proteins used in pluripotent stem cells. Using the factors in live organisms for prolonged periods of time is known to cause cancer by boosting up cell division. But David's team excluded one of these factors, MYC, known to be oncogenic, and they were able to keep the other three active in mice for over a year without developing any tumors.

They were then able to use these factors to allow mice to regrow a mechanically damaged optic nerve. Normally a mouse's optic nerve can regrow during development but then it loses this ability a few days after birth. In this experiment the grown up mice restored this regeneration ability and have regained around half of their lost visual acuity.

Another result achieved using Yamanaka factors was restoring vision of healthy, middle-aged (one-year-old) mice. These mice scored worse on the tests of visual acuity before treatment than the younger mice, but one month after treatment they had similar results

== Information theory of aging ==
Another theory, popularised by Professor David Sinclair, is that epigenetic changes might be the master regulator aging - known as [https://hplus.club/blog/a-summary-of-david-sinclairs-information-theory-of-aging/ the information theory of aging].

Since DNA is identical in every somatic cell, each cell in order to differentiate from a stem cell and then perform its function needs to “know” which genes to read, so that e.g. a neuron cell only expresses (i.e. uses) genes relevant for being a neuron, and not a muscle cell or a skin cell. This is achieved through methylation and other epigenetic mechanisms.

The theory goes that aging is fundamentally caused by errors in this process accumulating, eventually causing a cell to stop functioning normally and either become cancerous or die.

== Relevance for longevity research ==

== Smoking ==
[https://clinicalepigeneticsjournal.biomedcentral.com/articles/10.1186/s13148-019-0777-z#:~:text=The%20statistical%20analyses%20showed%20the,level%20that%20non%2Dsmokers%20had. Research] shows that smoking increases epigenetic age of buccal cells, airway cells, esophagus tissue, and lung tissue. Quitting smoking caused the epigenetic age acceleration in airway cells (but not in lung tissue) to revert to the level of non-smokers.

== Obesity ==
Obesity (defined as increased BMI) has been shown to correlate with increased epigenetic age in a number of tissues. For liver tissue, [https://www.pnas.org/content/111/43/15538/ this study] found the average increase of ~2.2 years of epigenetic age for each 10 BMI units. There was no correlation for blood cells however. [https://clinicalepigeneticsjournal.biomedcentral.com/articles/10.1186/s13148-019-0754-6#:~:text=Epigenetic%20age%20acceleration%20increases%20with,acceleration%20of%20metabolically%20active%20tissues. Another study] found an increase of ~2.3 years per 10 BMI points for visceral adipose tissue (visceral fat).

== Depression ==
Major depressive disorder (MDD) was also found to be associated with increased epigenetic age. The study by [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6094380/ Han et al.] found increased epigenetic age in blood cells associated with symptoms of MDD and childhood trauma scores. They also analyzed brain cells (collected post mortem) and found that increased epigenetic age correlated with MDD symptoms.

== Partial Epigenetic Reprogramming ==
[https://pubmed.ncbi.nlm.nih.gov/33268865/ David Sinclair et al.] were able to reverse age-induced loss of sight and even regenerate a mechanically damaged eye nerve by manipulating methylation patterns in mice. In addition to vision restoration mentioned above they were able to [https://pubmed.ncbi.nlm.nih.gov/33268865/ improve] locomotive and cognitive performance in aged mice, and they also were able to [https://pubmed.ncbi.nlm.nih.gov/32556267/ shift the clocks forward], making the mice biologically older than it should be (obviously not particularly useful in practice but that’s necessary to confirm that their model of aging works).

== Other uses ==
Epigenetic clock also has many other [[wikipedia:Epigenetic_clock#Motivation_for_biological_clocks|applications]]:

* testing the validity of various theories of biological aging,
* diagnosing various age related diseases and for defining cancer subtypes,
* predicting/prognosticating the onset of various diseases,
* serving as surrogate markers for evaluating therapeutic interventions including rejuvenation approaches,
* studying developmental biology and cell differentiation,
* forensic applications, for example to estimate the age of a suspect based on blood left on a crime scene.