Some may have heard of the concept of biological versus chronological age or the reality that two people can be 40 years old, yet one person has the body of a 50 year old, while the other could pass for 30.
Though not definitive, biological (also called physical) age is influenced by numerous behavioral factors like diet, exercise, sleep pattern, and tobacco and drug use. While scientists say that, for the most part, aging is determined by our genetic endowment, our health habits do have a say in how rapidly we age.
Science currently has established clinical markers associated with aging in older people, such as high cholesterol; but the detailed discovery of how we age has been lacking.
A recently revealed aging classification could change the landscape.
FOUR TYPES OF AGING
Researchers from Stanford University School of Medicine believe they’re on the right path to determining how common biological markers are related to the aging process.
Earlier this year, in Nature Medicine, a team led by Stanford Medicine Professor and Chair of Genetics, Michael Snyder, Ph.D. published findings from a two to three year study of changing clinical patterns in 106 healthy men and women aged 29-75.1,2 It was the first study to detail age-related changes in the same individuals. Snyder’s team used biological samples such as blood and stool to monitor changes over time in markers such as microbe populations and molecules, including proteins, metabolites (e.g., glucose), and lipids (e.g., cholesterol).
Four distinct biological pathways of aging, coined “ageotypes,” were identified: metabolic, immune, liver (hepatic), and kidney (nephritic). A person with a metabolic ageotype at risk for type 2 diabetes may have increased levels of A1c, a measure of average blood sugar, as they age. Another person may have elevated biomarkers for liver or kidney issues. And, while there were no clear boundaries between ageotypes, it was determined that some individuals remain at risk for more than one disease. Snyder noted that a person’s ageotype represented their most pronounced biological pathway of aging and that those markers rising the most over time are the major contributors.
DIGGING DEEPER
The team looked at another area never before investigated: aging differences between those with normal and higher blood sugar, or normal insulin sensitivity versus insulin resistance and impaired glucose metabolism. Snyder found about 10 markers that were much different in those with insulin resistance as they age. Of particular importance, glucose levels are related to immunity and inflammation.
On the other hand, they also saw people experiencing a decrease in their ageotype markers over time, once changes occurred in their behavior. Participants still aged, but their rate declined after losing weight and changing diet, corresponded to a decrease seen in hemoglobin A1c. Likewise, others saw a decline in creatinine, a marker of improved kidney function, after beginning statins (no mention of side effects was made).
Inexplicably, others saw a decrease in ageotype markers with no visible lifestyle changes, and yet another group maintained a lower-than-average aging rate throughout the study.
The researchers say the results gave a “much more comprehensive” picture of aging patterns. The study used a broad array of molecular markers through multiple samples from the same individuals over several years—enough time for participants to make changes reflected in their ageotypes.2
“We’re able to see clear patterns of how individuals experience aging on a molecular level, and there’s quite a bit of difference,” said Snyder.2
BIOLOGICAL CLOCK
It could be that those who maintained slower-than-average aging throughout Snyder’s study had fewer programmed changes to their DNA.
Population-wide genetic research supports Snyder’s findings in individuals. Studies have shown tissue-specific genetic changes in metabolism, immunity, aging, and cells’ ability to rejuvenate, with these changes accelerating aging.3
There is strong evidence that too much or not enough methylation (the natural addition of methyl groups) to a DNA molecule can turn off gene activity, accelerating aging and promoting
age-related diseases. It’s well established that the biological age of a person’s tissues can be known by markers of methylation, and that these genetic changes can be due to environmental factors like unhealthy eating, lack of exercise, and immune cell injury. Because this can be tracked across a person’s lifespan, DNA methylation “clocks” are now being studied as a way of predicting life expectancy.3
Type 2 diabetes, for example, can be caused by changes in a person’s DNA coding (genetic), altered gene expression/activity (epigenetic), and environmental factors. Preliminary research has shown epigenetic dysfunction in muscle and pancreas cells of diabetic versus healthy people and identified DNA methylation and altered expression in specific genes.3 One study showed the fat mass and obesity-linked (“FTO”) gene to be under-methylated prior to disease onset.4 Researchers feel these epigenetic biomarkers could be a critical addition to the more common factors used in early disease detection (blood sugar, body mass index, chronological age, etc.).3
Another potential aging factor is telomere length. Telomeres are protein “caps” on the ends of DNA chromosomes that prevent them from deteriorating or binding with neighboring chromosomes. These structures determine the lifespan of a cell. When telomeres become shortened, a person is more likely to live an abbreviated life or develop a disease.5 Conversely, one study showed that a healthy lifestyle could lengthen telomeres and
reverse this aging process.6
Generally speaking, the higher one’s chronological age, the shorter their telomeres.
IMPLICATIONS
Snyder’s study made national headlines before the current pandemic, but his findings may hold higher value in the present day.
Americans are now, by and large, more sedentary and not as diligent with healthy eating.8, 9 This not only points them toward the four pathways to age-related disease, but it could also leave them vulnerable to more serious illness from COVID-19 infection.
Furthermore, the Centers for Disease Control and Prevention states that more than one-third of US adults (roughly 88 million people) have prediabetes, with some 80 percent unaware of it. Early identification is essential since, according to the American Diabetes Association, approximately 70 percent of prediabetic people will go on to develop full-blown diabetes, which can affect multiple body systems: cardiovascular, nervous, kidney, and eye.
Combating insulin resistance through lifestyle changes such as starting a weight training program can help prevent prediabetes from progressing to type 2 diabetes. (Snyder, who used his data for the study, began lifting weights and wonders how this will affect his ageotypes.)
In all, Snyder and his team concluded, ageotypes may offer a molecular look at personal aging that could prove useful for tracking and interceding in the aging process, since it’s indicative of lifestyle and medical history.1
“The ageotype is more than a label; it can help individuals zero in on health-risk factors and find the areas in which they’re most likely to encounter problems down the line. Most importantly, our study shows that it’s possible to change the way you age for the better. We’re starting to understand how that happens with behavior, but we’ll need more participants and more measurements over time to fully flesh it out.”2
With a standardized test not yet available, readers may wish to consider RealAge, which calculates biological age and offers useful feedback and resources based on comprehensive user input.7
1. Ahadi, S.; Zhou, W.; Schussler-Fiorenza Rose, S.M.; et al. (2020). Personal aging markers and ageotypes revealed by deep longitudinal profiling. Nature Medicine, 26, 83-90. Retrieved from https://doi.org/10.1038/s41591-019-0719-5
2. Armitage, H. (2020, January 13). ‘Ageotypes’ provide window into how individuals age, Stanford study reports. Stanford Medicine News Center.
3. Salameh, Y.; Bejaoui, Y.; El Hajj, N. (2020, March 10). DNA Methylation Biomarkers in Aging and Age-Related Diseases. Frontiers in Genetics.
4. Toperoff, G.; Aran, D.; Kark, J.D.; et al. (2012). Genome-wide survey reveals predisposing diabetes type 2-related DNA methylation variations in human peripheral blood. Human Molecular Genetics 21, 371–83. Retrieved from doi: 10.1093/hmg/ddr472
5. Anitha, A.; Thanseem, I.; Vasu MM; et al. (2019). Telomeres in neurological disorders. Advances in Clinical Chemistry, 90, 81-132. Retrieved from doi:10.1016/bs.acc.2019.01.003
6. Arsenis, N.C.; You, T.; Ogawa, E.F. (2017). Physical activity and telomere length: Impact of aging and potential mechanisms of action. Oncotarget, 8(27), 45008-19. Retrieved from doi:10.18632/oncotarget.16726
7. Stibich, M. (2020, April 11). RealAge Longevity Calculator Review. Verywell Health.
8. Ducharme, J. (2020, May 12). COVID-19 Is Making Americans Even More Sedentary. The Effects Could Be Long-Lasting. Time.
9. Bomey, N. (2020, April 9). Americans are ‘craving comfort food’ during coronavirus: Cereal, snacks, baked goods fly off shelves. USA Today.
