Chinese panel of aging biomarkers
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Molecular and phenotypic biomarkers of aging.


What are aging biomarkers for?

Aging is a time-dependent physiological functional decline that affects most living organisms. And this process is directly related to molecular changes. It is also the most important risk factor for many non-communicable diseases. On the one hand, the identification of biomarkers of aging will contribute to the differentiation of people who have the same chronological age, but different variants of aging. Quantitative biomarkers of aging can also form a group of measurements for “healthy aging” and, in addition, predict longevity.

On the other hand, aging biomarkers can also help researchers narrow the scope of research to specific biological aspects in an attempt to explain the biological processes associated with aging and age-related diseases. Here we look at the phenotypic and molecular biomarkers of aging.

Phenotypic biomarkers can be non-invasive, panoramic and easily accessible, whereas molecular biomarkers can reflect some of the molecular mechanisms underlying age status. This review mainly considers the results obtained in studies with people (and in some rare cases with laboratory animals (mice) and nematodes).

Molecular Biomarkers of Aging

This section is based on two high-performance reviews on the basis of aging 1, 2. In these reviews, we focus on events starting in 2013. The American Federation for Aging Research (AFAR) has proposed the following criteria for an aging biomarker:
(1) it must predict the rate of aging;
(2) it must control the underlying process underlying the aging process, not the effects of the disease;
(3) he should be able to re-test without harming the person;
(4) it must be something that works on humans and laboratory animals.

Biomarkers that meet all the criteria proposed by AFAR are unlikely to exist 3, so in the molecular part of this review we follow the first two criteria: the biomarker must predict the rate of aging and must control the underlying process underlying aging. For the first criterion, we tried to have a biomarker correlated with aging; for the second criterion, we organized the first part of this review in accordance with molecular pathways that undermine aging.

DNA and chromosomes.


Telomeres are ribonucleoprotein complexes at the end of chromosomes. They become shorter after each replication, since telomerase, the enzyme responsible for their replication, is not regularly expressed in somatic cells 4. The length of telomeres in leukocytes is associated with aging and longevity 5, as well as with age-related diseases such as cardiovascular diseases 6, 7, cancer 8 and neurological disorders 9.

DNA repair.

The link between damage and DNA repair is associated with aging through the accumulation of senescent cells 10 or genomic rearrangements 11. More recently, this relationship was directly demonstrated: the induction of double-stranded DNA breaks in the mouse liver caused age-related pathologies and gene expression 12. Immunohistochemistry γ-H2AX is an established quantitative aging biomarker, because H2AX is a variant of the family of histone proteins H2A, and phosphorylated H2AX, γ-H2AX is the initial and essential component of foci of damage DNA Ia.

Therefore, it can be considered a reliable marker of the degree of DNA damage 13 - 15. Serum markers of DNA damage, including cathelin-related antimicrobial peptide (CRAMP), eukaryotic translation elongation factor EF-1a, statmin, N-acetyl-β-D-glucosaminidase ( NAG), and chitinase, as described 16.

it should be noted that dermal fibroblasts from donor centenarians were less sensitive to DNA damage induced by hydrogen peroxide than fibroblasts from other donors younger 17. Such ex vivo experiments can also be potential biomarkers Old i.

Epigenetic modifications.

Age-related changes in the structure of DNA methylation, in particular, as epigenetic hours, are among the most studied biomarkers of aging 18-20. Analysis of blood methylation profiles showed that only three CpG sites can predict age with an average absolute deviation from chronological age of less than 5 years 21. The relationship between age and DNA methylation can be extended to age-related diseases such as diabetes 22. For a complete review of the epigenetic regulation of aging, see Sen et al. 23.
RNA and transcript.

Transcript Profiles. With the rapid progress in the technology of full-genome sequencing of RNA (RNA-seq), it has been actively used in the study and search for aging biomarkers. Lu et al. recently showed that the change in expression in cells measured in sorted T cells by sequencing single cell RNA-seq together with flow cytometry is associated with aging and susceptibility to disease 24.

In a recent study, whole blood gene expression profiles were used taken from 14,983 people to identify 1457 genes with age-dependent differential expression. And then the data obtained used them to calculate the “transcriptome age” of the individual, assuming that transcriptome signatures can be used to measure aging 25.

Non-coding RNA.

MicroRNAs (miRNAs) are a class of small (from 21 to 23 nucleotide) non-coding RNAs that regulate a wide range of biological processes, including metabolism 26 and aging 27. Among them are circulating miRNAs that can be stable in plasma due to being in exosomes or binding to protein or lipoprotein factors, making them available for biomarkers. miR-34a was the first observed circulating miRNA with an altered expression pattern during aging in mice28.

Its expression was found to correlate with age-related hearing loss in mice and humans 29. miR-21 was identified as an inflammatory biomarker in 365 miRNAs in the plasma of healthy and old people 30. Levels of miR-151a-3p, miR-181a-5p and miR -1248 was reported to decrease significantly with age in humans, and all three miRNAs also show an association with inflammation 31. It was found that miR-126-3p positively correlates with age in 136 healthy subjects from 20 to 90 years 32.

By expression GFP, Pincus et al. found that mir-71, mir-246 and mir-239 levels in early adulthood differ from individuals and predict longevity 33. A recent review 27 summarizes associations of other types of circulating non-coding small RNA, such as tRNA and YRNA.

Long non-coding RNAs (lncRNAs) are a heterogeneous class of non-coding RNAs that are defined as transcripts longer than 200 nucleotides that do not have obvious open reading frames 34. In the last two reviews, the role of lncRNAs in aging 35, 36 is summarized. Consideration of the various functional mechanisms of lncRNA goes beyond the scope of this review, and readers may read a recent review on this topic 37; here we provide a list of lncRNAs that function in the process of aging. It was found that lncRNA MIR31HG is activated in oncogene-induced aging, and is required for replication mediated by the polykombic group of the INK4A 38 locus.

A decrease in the lncRNA AK156230 level occurs in replicative aging, and its knockdown in mouse embryonic fibroblasts induces aging through the dysregulation of autophagy and cell cycle pathways, as shown by expression profiles 39. Meg3 levels increase during cardiovascular aging and also in human heart paps, as well as in human cords, as well as in the components of the human void, as well as in the human chambers, as well as in the human chambers, as well as in the components of the human void, as well as in the components of the human void, as well as in the human chambers and heart rate patterns, as well as in the human chambers, as well as in the components of the human void, as well as in the components of the human void, as well as in the components of the human circuit, 39 cells 40.


Dietary restriction (calorie restriction) is the most conservative means of increasing life expectancy, from yeast to mammals. 42 Studies indicate the main role of metabolism in the regulation of aging and the possibility of metabolic factors acting as biomarkers.

Nutrient Sensitivity.

The insulin / IGF-1 (IIS) signaling pathway, which is involved in glucose consumption, is the earliest detected and best known way to counteract longevity. Paradoxically, IGF-1 is reduced in wild-type mice or in mouse models of premature aging, while a decrease in IIS activity increases longevity 43. Such observations have led to the potential inclusion of elements of the IIS pathway, such as growth hormone and IGF-1, as biomarkers aging 44, 45.

Protein target of rapamycin in mammals (mTOR) depends on high concentrations of amino acids. Inhibition of mTOR can prolong lifespan 46. Unlike the IIS pathway, mTOR activity increases with age in the human and mouse ovarian epithelium, which contributes to pathological changes 47. Phosphorylated ribosomal S6 protein (p-S6RP or pS6) is a downstream target, as well as a well-known a marker of active signaling mTOR 47, 48, and is a potential biomarker of aging, as indicated in the study of aging ovaries 47.

Unlike IIS and mTOR, 5'-adenosine monophosphate (AMP) -activated protein kinase (AMPK) and sirtuins are sensitive to nutritional deficiencies instead of their abundance. AMPK detects high levels of AMP, whereas sirtuins are high-level sensors of NAD +, and both of them indicate states associated with a decrease in energy reserves. Increasing the activity of AMPK with metformin, a drug for type II diabetes, can mimic some of the benefits of calorie restriction, metformin increased the lifespan of mice 49. AMPK increases with skeletal muscle 50.

Sirtuins have the ability to directly bind cellular signaling metabolism (through NAD +) with post-translational protein modifications through a chemical reaction (lysine deacetylation). During aging, NAD + decreases 51, and the activity of the sirtuins is suppressed 52, 53. An analysis of primary human dermal fibroblasts showed a decrease in SIRT1 and SIRT6 54 activity. Similarly, the SIRT1, SIRT3 and SIRT6 levels detected by Western blot showed a significant decrease in ovaries of old mice 55. In mononuclear cells from human peripheral blood, SIRT2 also decreases with age 56.

Protein metabolism.

Protein carbamylation is one of the non-enzymatic post-translational modifications that occur throughout the life of the organism, leading to tissue accumulation of carbamate proteins 57. What is considered a sign of molecular aging and is associated with age-related diseases, such as cardiovascular diseases 58.

Advanced glycation end products (AGE) are a heterogeneous group of bioactive molecules that are formed as a result of non-enzymatic glycation of proteins, lipids and nucleic acids 59. The accumulation of AGE in tissues during aging leads to inflammation 60, apoptosis 61, obesity 62 and other age-related deviations 63 AGEs can be detected by high performance liquid chromatography, gas chromatography-mass spectrometry and immunochemical methods 64. N-glycans are a class of glycoproteins with ca char chains linked to asparagine amide nitrogen.

The spectrum of N-linked glycans (N-glycome) can now be investigated due to the development of high-throughput methods. The accumulation of N-linked glycation in Asn297 from the Fc-part of IgG (IgG-G0) may contribute to pro-inflammatory status with aging 65.

Lipid metabolism.

Triglyceride levels have been found to gradually increase with age and, therefore, may be an aging biomarker 66. Studies of lipid long-livers and elderly people have shown that phospho / sphingolipids are supposed markers and biological modulators of healthy aging 67. Nevertheless, the design of these studies is questionable in that there is a group of older people as “not healthy control of aging,” which is compared to a “successfully aging” group of centenarians of centenarians 67, 68. But these two groups are obviously very different ages. Therefore, it is unclear whether age differences or healthy aging contributed to differences in lipidomics.

Oxidative stress and mitochondria.

Oxidative stress biomarkers have long been considered the biomarker class of aging. Products of oxidative damage to proteins include o-tyrosine, 3-chlorothyrosine and 3-nitrotyrosine. 8-iso prostaglandin F 2α is a biomarker of phospholipid damage. 8-hydroxy-2'-deoxyguanosine and 8-hydroxyguanosine show oxidative damage to nucleic acids69.

The concentration of these biomarkers in body fluids can be detected by high performance liquid chromatography and mass spectrometry. Shen et al. A circularly rearranged yellow fluorescent protein (cpYFP), expressed in the mitochondrial matrix Caenorhabditis elegans, was designed as a sensor for oxidative stress and metabolic changes 70.

Although free radicals, a source of oxidative stress, are mainly produced in mitochondria, dysfunctional mitochondria can promote aging, regardless of reactive oxygen species. Analytical strategies for measuring mitochondrial function are available for respiratory profiling based on blood and muscle 71 or phenotypes, such as 72 walking speeds. The extracellular components of mitochondria can function as molecules associated with damage (DAMPs) (see also Inflammation and Intercellular Communication). They induce neuroinflammation when introduced into the mouse hippocampus 73.

Cell aging.

Gradual accumulation of senescent cells is believed to be one of the causal factors of aging 74 - 76 in mitotic tissues. Thus, biomarkers of cell aging can also be used as markers. Such biomarkers have been summarized in recent reviews 77, 78. The most widely used marker is aging-associated β-galactosidase (SAβ-gal) 79 and protein p16 INK4A 80, 81. SAβ-gal reflects an increased mass of lysosome 82, but may give false 83 because of its low specificity. SAβ-gal is a marker of cell damage, and p16INK4A is required to completely stop the cell cycle 81.

Other markers of aging cells include an activated and sustained response to DNA damage (see “DNA repair”), shortening and dysfunction of telomeres (see “Telomeres”) and aging-related secretory phenotype (SASP) (see “Inflammation and intercellular communication ").

Inflammation and intercellular communication.

SASP is a consequence of cellular aging and can occur in cells that are still metabolically active and secrete proteins. SASP functions autocrine and paracrine 84, 85. The main components of SASP factors are soluble signaling factors, including interleukins, chemokines, and growth factors. Proteins that are associated with SASP, such as interleukin-6, tumor necrosis factor-alpha, monocytic chemotactic factor-1 (MCP-1), matrix metalloproteinases and IGF-binding proteins, contribute to the aging of tissues in conjunction with inflammation 86.

Comprehensive SASP catalogs also include secreted proteases and secreted insoluble proteins / components of the extracellular matrix and are summarized by Coppé et al. 87 and in the Reactome databases (

Molecules of the DAMPs group (molecular fragment associated with damage), such as heat shock proteins, histones, amphoterin (HMGB1), and calcium binding protein S100, make up a class of molecules released after injury or cell death 88 that mediate the immune response. There is a link between DAMPs and other signs of aging; it was reviewed by Huang et al. 89.

Phenotypic biomarkers of aging.

Following the criteria proposed by AFAR 3, we classify phenotypic biomarkers of aging. Phenotypic biomarkers are difficult to control the basic molecular process that underlies the aging process, so we follow three standards: a biomarker must predict the rate of aging, it must be able to be retested without harming a person, and it controls one or more physiological processes.

Physical functions and anthropometry are the most practical measurements among phenotypic biomarkers of aging. In this regard, measurements such as walking speed, standing up from a chair, standing balance, hand compressive strength, body mass index, waist circumference and muscle mass are well known 90. These physical functional measurements, although simple, can be really better. than DNA methylation in terms of attitudes to health in demographic studies 91.

The quantitative phenotypes of external human characteristics also show significant relationships with aging 92, 93. Quantitative facial features based on three-dimensional images of the face, such as the width of the mouth, the width of the nose, and the angle of the eyes, are strongly associated with age. In fact, three-dimensional facial images can be used to quantify a person’s biological age 92.

Conclusion and perspectives

As expected, due to the complex nature of the aging process, aging biomarkers are multi-layered and multi-faceted and consist of a dizzying array of parameters that are summarized below. This, however, does not mean that they are equally useful. We must point out that not all factors, although they may be involved in the disruptive biological aging process, have proven to be useful in terms of measuring human aging at this stage.

Appendix 1. Biomarkers of aging.

I. Molecular biomarkers.

1. DNA and chromosomes.
a) γ-H2AX
b) leukocyte telomere length
c) DNA methylation.

2.RNAi transcription.
a) CD38 heterogeneity in CD4 + CD27 + T cells
b) CD197 heterogeneity in CD4 + CD25 + T cells
c) circulating miRNA (miR-34a, miR-21, miR-126-3p, miR-151a-3p, miR-181a-5p, miR-1248)
d) long non-coding RNA (MIR31HG, AK156230, Meg3)

3. Metabolism
a) growth homo, insulin, IGF-1
b) mTOR, pS6RP
d) protein carbamylation
e) glycation end products and N-glycans
e) triglycerides

4. Oxidative stress and mitochondria
a) o-tyrosine, 3-chlorothyrosine, 3-nitrotyrosine,
b) 8-isoprostane
) 8-hydroxy-2'- deoxyguanosine
d) 8-hydroxyguanosine

5. Cell aging
a) A-galactosidase associated with aging
b) p16INK4A protein.

6. Inflammation and intercellular communication.
a) Aging-related secretory phenotype (SASP)

II. Phenotypic biomarkers.

1. Physical functions and anthropometry
a) walking speed, rising from a chair, standing balance, hand compressive strength, muscle mass
b) body mass index, waist circumference.

2. Facial features
a) the width of the oral cavity
b) the width of the nose
c) the distance from the mouth to the nose
d) the slope of the angle of the eye

Prepared by Alexei Rzheshevsky.

Xian Xia, Weiyang Chen, Joseph McDermott, and Jing-Dong Jackie Hana. Molecular and phenotypic biomarkers of aging Version 1. F1000Res. 2017; 6: 860.

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