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Defining the aging phenotype

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Shubhankar Kulkarni
Shubhankar Kulkarni Jul 28, 2020
Question: Can we come up with a cumulative age score that can be used as a proxy for aging?

In aging studies, there have been challenges of defining the most relevant phenotype as a comparator. There are differences in the study designs, across study populations or models, and certain genetic effects surface only at extreme ages. Lifespan does not correlate appropriately with the physiological age and hence there is need for another biomarker. Different studies define the aging phenotype differently:
  1. Number of years free of age-related psychological or physiological disease
  2. Epigenetic status of the cells
  3. Telomere length
  4. Changes in metal isotopes
  5. Changes in metabolites like NAD+
Can we come up with a cumulative age score based on all these factors or is there any other highly significant factor that can be used as a proxy for aging? We need to normalize aging to something, which can be more of a universal factor that can be used in scientific empirical studies.

If we cannot, what are the reasons?

[1]Walter S, Atzmon G, Demerath EW, Garcia ME, Kaplan RC, Kumari M, et al. A genome-wide association study of aging. Neurobiol Aging [Internet]. 2011 Nov;32(11):2109.e15-2109.e28. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0197458011002107

[2]Horvath S, Pirazzini C, Bacalini MG, Gentilini D, Di Blasio AM, Delledonne M, et al. Decreased epigenetic age of PBMCs from Italian semi-supercentenarians and their offspring. Aging (Albany NY) [Internet]. 2015 Dec 15;7(12):1159–70. Available from: http://www.aging-us.com/article/100861

[3]Harley CB, Futcher AB, Greider CW. Telomeres shorten during ageing of human fibroblasts. Nature [Internet]. 1990 May;345(6274):458–60. Available from: http://www.nature.com/articles/345458a0

[4]Li X, Snyder MP. Yeast longevity promoted by reversing aging-associated decline in heavy isotope content. npj Aging Mech Dis [Internet]. 2016 Dec 18;2(1):16004. Available from: http://www.nature.com/articles/npjamd20164

[5]Zhang H, Ryu D, Wu Y, Gariani K, Wang X, Luan P, et al. NAD+ repletion improves mitochondrial and stem cell function and enhances life span in mice. Science (80- ) [Internet]. 2016 Jun 17;352(6292):1436–43. Available from: https://www.sciencemag.org/lookup/doi/10.1126/science.aaf2693

Creative contributions

Gender specificity of biological age estimation markers

Juran Oct 27, 2020
Although most of the strong predictors of biological age were shared, many differences between genders and gender-specific aging processes can be seen from the experimental results of integrative research .

While in women, high ALP suggested a higher chance of disease/mortality, no predictive value was associated with ALP in men. On the other hand, high creatinine meant better „fitness“ in men only.

To increase the accuracy of biological age estimation, predictive markers should be not only data-type specific but also gender-specific.


Grip strength

Juran Oct 27, 2020
Two years ago, researchers suggested using stand-alone measurement of grip strength as a predictive biomarker of an older adults .

It is stated that it can explain:
overall strength,
upper limb function,
bone mineral density,
cognitive impairment,
sleep problems,
multimorbidity, and
quality of life.


Shubhankar Kulkarni
Shubhankar Kulkarni7 months ago
Another similar study used 8 different attributes of fitness (muscle strength, endurance, balance, nerve-muscle coordination, agility, core strength, flexibility, and abdominal plsticity) to successfully distinguish between diabetics and non-diabetics. They also propose that increasing the overall fitness score (based on the above-mentioned attributes) helps in alleviating the symptoms of diabetes. I agree, similar reasonable biomarkers can be used to perfectly define age. Reference: https://www.biorxiv.org/content/10.1101/580860v1

Seasonal variances

Juran Oct 27, 2020
While searching for the best markers of biological age that could define the aging phenotype, we need to pay attention to one more factor – seasonal variation. Less than a month ago, researchers stated that concentrations of some molecules exhibit different patterns at different times of the year .

Some of them are:
HbA1C, red blood cells – peaks in spring and summer; low in winter
HDL – peaks in summer
LDL/HDL ratio – peaks in winter
C2, C9, IL5, SIGLEC15, IL1RAP, …

The observed variations of all factors fitted in two distinct patterns – one which consists of genes whose expression peaks in late spring and the other one which peaks in late autumn/winter. Two patterns had strong correlations with meteorological measurements, lab measurements, and gut/nasal microbial shifts, indicating that in the future, all general, disease-specific, or aging marker panels need to be season-specified, adapted, and results corrected.


Shubhankar Kulkarni
Shubhankar Kulkarni7 months ago
Juran K. Interesting! I also assume that the changes observed in these biomarkers with the changes in the season will be different in different locations. For example, the study you have cited was performed in California. I think the results may be different in people living in Scandinavia and those from the equatorial region. I tried but could not find another study from a different region.
Juran7 months ago
Shubhankar Kulkarni I guess they would be different, because the two patterns not only had different peak periods, but also correlated with an average air temperature and average solar radiation (pattern one), or an average air pressure, air humidity, and precipitation (pattern two). So, it is reasonable to think the way you think. It is maybe even predictable.

Biological age estimates using deep phenotyping

Juran Oct 27, 2020
Biological age is often called the „wellness“ - the absence of disease, the organism's resilience to future disease, wellbeing, and energy that enrich our lives. In recent research, estimation of biological age was assessed through a multidimensional deep phenotyping method, on a large cohort with broad age distribution (18-89+) and resulted in a number of potentially good predictive markers of biological age. Researchers integrated and compared data from clinical laboratories, proteomics, metabolomics, and genetics .

Across all data types, the highest correlation with biological age had blood factors corresponding to metabolic health, inflammation, and bioaccumulation of toxins. The highest change in biological age compared to chronological was observed in the population having Type 2 diabetes (T2D), indicating shortened life expectancy. Adiponectin and AgRP were strong positive predictors of BA, meaning that people with high blood concentrations have a higher mortality rate (supported with literature data). A similar study was concluded for HbA1C, CXCL9, GDF15, LTA, PFOS, VMA, bioaccumulation of lead and mercury, …

New markers:

Important conclusion:
Not only do we need more specific markers estimating biological age, but we need to find the most reliable data types (proteomics, metabolomics, genomics, ...) with the highest possible fidelity, calculate their contributions and combine them to get an accurate estimation.


Glycans as biomarkers of aging

Juran Oct 28, 2020
Scientists developed a glycan-based blood test for biological age (BA), more precise than most of the BA predictors until now.


Glycans are the same as polysaccharides - many glycosidicly-linked monosaccharides.
The process of glycan addition to proteins is called glycosylation.
Glycosylation is one of the most important post-translational modifications in Eukaryotes.
That means that our bodies are built of proteins, which are modified by glycans .

Immunoglobulins (Ig), or antibodies, are a group of glycoproteins produced by white blood cells which have a crucial role in detecting and destroying antigens, such as bacteria and viruses . Among various Ig isotypes, IgG is the most abundant and most specific antibody in human serum , principally being used in immunological research and clinical diagnostics.

If the glycan ratio on immunoglobulins is altered, it can affect its activity, resulting in increased/reduced inflammation, which, in the long-term, affects aging.

GlycanAge commercial test

A team of researchers checked the status of IgG glycosylation in 5117 individuals and revealed the patterns of glycosylation correlating with age . Using the collected data, researchers developed an accurate model to estimate biological age using just three glycans (GP6, GP14, and GP15). As stated in the paper, their calculation index called "GlycanAge" appears to be more related to age than telomere lengths and other physiological estimators (guy comparing it with methylation here).

As an end product of many papers like the above mentioned, team from Genos Ltd (Zagreb, Croatia) developed GlycanAge commercial test for estimating biological age with high precision .

Because it's easy to use, it could be used to measure the effect and track how changes in lifestyle, diet, and others reflect on the biological age/fitness of an individual.

Questions that arise:

  • How good can an estimation of biological age based on just glycans be? Should it be combined with other estimators with high-precision?
  • Can we talk about precise estimations, when there are no "prestained ladders" with known biological age?







Shubhankar Kulkarni
Shubhankar Kulkarni6 months ago
The second question pinpoints my concern exactly. That is what I want to find out. There are different biomarkers but we need to identify the ones that estimate the "true" biological age. Biological aging can be a point of incidence of frailty or other age-related diseases. Can it be muscle wasting? Reduced functionality of different organs? The more factors we add, the more precise the estimation becomes. However, the more the factors, the more cumbersome is the test, and researchers will avoid it.
Juran6 months ago
Shubhankar Kulkarni I understand the concern and I understand the idea you have. I agree that more "point of incidence of frailty or other age-related diseases" we have, more precisely we can address the person's current status a.k.a. biological age. One day when the patient's history of disease will be a database connected to his identity, it will be much easier to follow and search for patterns in order to find the ideal points for our "predefined BA ladder".
Now I see I kind of missed the topic with the above contributions, but I hope some of them will be inspirational and helpful.
Shubhankar Kulkarni
Shubhankar Kulkarni6 months ago
Juran K. Your contributions are biomarkers that are very much needed to define and measure the aging phenotype. When we have a comprehensive list, we can decide (only experimentally), which of these absolutely essential to estimate the biological age. Moreover, it may so happen that we find a correlation across multiple biomarkers mentioned in this session. Then we can use the necessary ones to define the phenotype but use some others to measure it (because they will be easily measurable, non-invasive, etc.).

Proteostasis collapse coefficient

Juran Dec 07, 2020
Many diseases and aging-related disorders are proven to be accompanied by the damaged protein accumulation. At the same time, it is widely known that cellular senescence and human aging are highly related. Therefore, a team of researchers wanted to see if there is a relationship between cellular senescence and proteostasis (protein homeostasis) decline, which was, until now, proven on Nematodes.

They exposed young and senescent isogenic populations to stress and analyzed the cell's response to heat shock. After analyzing the transcriptome ribosome footprint profiling data, they observed several key differences between young and senescent heat-shocked cells:
  1. Induction of heat shock-related gene panel was impaired in senescent cells, compared to the young fibroblasts
  2. Nuclear localization and distribution of activated heat shock transcription factor - pHSF1 was compromised in senescent cells
  3. Senescent cells showed highly reduced alternative splicing regulation
  4. Although the unfolded protein response was activated in both cells and even increased in senescent, the coordination between sensing, translation, transcription, and the following transcriptional response was impaired in senescent cells
  5. Proteasome efficiency was reduced upon the heat shock and could not recover in the senescent cells after the return to the normal growth temperature
All the above-mentioned bullet points highlight the impaired response of senescent cells to outside stress and point out the importance of protein homeostasis mechanisms in aging.

As an additional "symptom" of aging, proteostasis collapse coefficient could be computed based on unfolded protein response which takes into account the above-mentioned parameters.


Shubhankar Kulkarni
Shubhankar Kulkarni5 months ago
Great idea! You have mentioned the 5 parameters that can be used to differentiate between young and senescent cells. These 5 can be used to give a cumulative score - "Proteostasis collapse coefficient". I am sure there will be differences between the senescent and the non-senescent old cells, which we need to take into consideration. Considering the parameters (values) of the neonatal cells as the standard for young cells, patient cells can be assigned an age.

We have covered all macromolecules to define the aging phenotype, I guess - nucleic acids, glycans, and proteins. :) I wonder whether anyone has tried estimating the age using just the lipids.

Methylation of DNA changes as we (and other animals) age

Brett M.
Brett M. Nov 26, 2020
Although this is more of a genotype, DNA methylation may serve as a useful and accurate measure of aging in several species. And, only in the last decade or so has this process been utilized as a proxy of human aging. As we know, experience with the environment can lead to changes in gene expression (i.e., epigenetics), and these changes come about via DNA methylation.

In this context, methylation is basically a "switch" that turns on genes or represses them, and genes activate proteins that are involved in maintaining optimal function of the human body.

Methylation has been shown to occur at cytosine guanine dinucleotides (CpGs; I know--acronym doesn't match the term; science can be awkward sometimes, can't it?), which are simply segments of DNA composed of cytosine-guanine pairings (i.e., 2 of the 4 nucleotides that make up DNA). This particular methylation process is regulated by DNA methyltransferase, or DNMT, which is an enzyme that has been shown to regulate established patterns of methylation throughout the lifespan.

In regards to age determination, DNA methylation can be divided into epigenetic drift or clock-type methylation processes. DNMT1 is a type of DNMT known for its role in regulating CpG methylation, and its activity appears to decline with chronological age, causing variation in the degree of methylation throughout the lifespan (i.e., epigenetic drift). Thus, by measuring overall DNA methylation patterns, it may be possible to associated age with DNA methylation.

In dogs, it was found that the relative percentage of DNA methylation was positively associated with chronological age. In contrast, human studies have shown thatDNA methylation occurs in a unique pattern: a sharp increase within the first year of life, a gradual increase throughout adulthood, and a progressive decrease in post-adulthood. The decrease in post-adulthood appears to occur specifically on non-CpG islands within DNA. If replication studies can fortify this finding, this may be useful if we want to find a biomarker for age. For example, we could assess the relative DNA methylation in non-CpG islands of DNA in a blood sample.

Interestingly, there is considerable interest in understanding how accelerating epigenetic drift may arise from early exposure to toxic compounds, which can provide a substantial impact on how we nurture the neonatal and childhood environment.

Investigating other phenomena that may accelerate the process of epigenetic drift is certainly an interesting avenue to explore if we want to "slow down" the biological clock.

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