Typically, research on aging is done in older people. The problem with studying aging in old people is that most of them already have age-related diseases, which anti-aging interventions aim to prevent.
Age-related changes in the body start to accumulate early in life and affect physiological function years before disease diagnosis; atherosclerosis is a prime example. Thus, intervention to reverse or delay the development of age-related diseases must be done while people are still young , before aging-related diseases become established.
Up to this point, the main obstacle to studying aging before old age and before the onset of age-related diseases has been the absence of methods to quantify the pace of aging (i.e. aging rate) in young people. However, a recent study shows that aging processes can be measured in people still young enough for prevention of age-related disease, and that physical manifestations of aging are already present in young adults.
954 young adults were followed from birth to age 38 years. When they were 38 years old, they underwent a series of physiological tests to find out whether this young population would show evidence of individual variation in aging despite remaining free of age-related disease.
To see if those with “older” physiologies at age 38 had actually been aging faster than their same chronologically aged peers who retained “younger” physiologies, indicators of the integrity of their cardiovascular, metabolic, and immune systems, their kidneys, livers, gums, and lungs, and their DNA was investigated in order to see if it had deteriorated more rapidly according to measurements taken repeatedly since a baseline 12 years earlier when they were 26 years old.
The study also aimed to find out if by age 38, young adults who were aging more rapidly already exhibited deficits in their physical functioning, showed signs of early cognitive decline, and looked older to independent observers.
Are Young Adults Aging at Different Rates?
Biological age is useful for examining differences in the pace of aging between individuals of the same chronological age. Currently there is no one single biomarker (indicator) of aging that can tell the true biological age of an individual.[5, 6] However, algorithms that include multiple biomarkers of aging are more reliable than single aging-biomarkers used in isolation.[4, 7-9]
A promising algorithm is the 10-biomarker US National Health and Nutrition Survey (NHANES)-based measure of “biological age.” In more than 9,000 NHANES participants aged 30–75 years at baseline, biological age outperformed chronological age in predicting mortality over a two-decade follow-up.
Table 1 lists the 10 biomarkers in the NHANES algorithm.
However, because the large age span of the NHANES participants (30 to 75 years), the biomarkers were affected by variations in lifestyle characteristics between young and old people. In contrast, in the study reported here, the all subjects had the same birth year and birthplace, and were all chronologically 38 years old at the last assessment. Running the same NHANES algorithm in these subjects, biological age was found to range from 28 to 61 years. This large variation in biological age was found despite that the group of subjects – all being 38 years old - were largely free of chronic disease. Thus, some 38 year olds may be up to 23 years older biologically than their same-age peers, while some may be 9 years younger.
Pace of Aging (i.e. Aging rate)
Biological age reflects the aging process, but it is a taken at a single point in time. To quantify the pace at which an individual is aging, repeated measures are needed in order to track change over time. Therefore, the study next tested the hypothesis that young adults with older biological age were actually aging fasters, using data on 18 biomarkers which are risk factors or markers of chronic disease and mortality (table 1). These biomarkers track the physiological integrity of study members’ cardiovascular, metabolic, and immune systems, their kidneys, livers, and lungs, their dental health, and their DNA.
Within-individual changes in these biomarkers were analyzed over time - from age 26 to age 32 to age 38 – in order to quantify each subject’s personal rate of physiological deterioration, i.e. their “pace of aging.” As expected, those with older biological age had been aging faster biologically over the past 12 years since they were 26 years old. Subjects ranged in their pace of aging from 0 year of biological aging (physiological change) per chronological year to nearly 3 years of biological aging per chronological year. This finding confirms that - even among young adults - some are aging faster than others, and shows that a substantial component of individual differences in biological age at midlife emerges already during adulthood from mid-20s to mid-30s.
Table 1: Description of biological age and pace of aging, and included biomarkers used in the study.
Pace of Aging
What does it reflect?
One point-in-time snapshot of biological age (i.e. physiological
Summary of accumulated biological aging.
Can be used to compare individuals with the same chronological age.
Within-individual rate of biological aging.
Can be used to monitor intra-individual effects of anti-aging interventions and risk factors on the biological aging process.
Requires at least two measurement taken at different time points.
Reflects physiological change in relation to passage of time.
Biomarkes included in algorithms that measure biological age and aging rate.
C-reactive protein (CRP)
Glycated hemoglobin (HBA1c)
Systolic blood pressure
Serum alkaline phosphatase
Forced expiratory volume
Serum urea nitrogen
7 biomarkers overlapped with the biological age algorithm:
Glycated hemoglobin (HBA1c)
Forced expiratory volume in one second (FEV1)
Blood pressure (mean arterial pressure)
C-reactive protein (CRP)
In addition, pace of aging included the following 11 additional biomarkers:
Cardiorespiratory fitness (VO2Max)
Forced vital capacity ratio (FEV1/FVC)
Body mass index (BMI)
Leukocyte telomere length
White blood cell count
apolipoprotein B100/A1 ratio
Does Accelerated Aging in Young Adults Influence Physical Function?
Next the study tested whether individual variation in biological age and pace of aging relates to differences in the functioning of the body and brain, measured with instruments commonly used in medical practice.
Reduced physical capability is an important indication of aging-related health decline and increased risk of morbidity and mortality.[10, 11] Not surprisingly, study subjects with a higher biological age performed less well on objective tests of physical functioning at age 38 than biologically younger peers. They had less muscle strength and more difficulty with balance and motor tests. Their biological ages were also related to their subjective experiences of physical limitation. Biologically older subjects reported having more difficulties with physical functioning than did biologically younger age peers.
Does Accelerated Aging in Young Adults Influence Indicators of Brain Aging?
In neurology, cognitive testing is used to evaluate age-related decline in brain integrity.[12, 13] Neurologists also use high-resolution 2D photographs of the retina to evaluate age-related loss of integrity of blood vessels within the brain. Retinal microvascular abnormalities are associated with age-related brain pathology, including dementia [15, 16] and stroke , and thus provide a simple way to assess brain aging.
The study found that subjects with older biological ages had worse cognitive functioning. Consistent with this, study members with advanced biological age had older retinal vessels, indicative of older brains, compared to peers with younger biological age.
Do Young Adults Who Are Aging Faster Feel and Look Older?
Everybody wants to look young, but does a young look really reflect a person’s biological age and health status? Consistent with tests of physiological function indicators, study subjects with older biological age were perceived to be older by independent observers. Based on the facial images alone, observers scored study subjects with older biological age as looking older than their biologically younger peers.
The study reported here shows that biological measures of aging in young adults are mirrored in their body’s functional status, brain health, self-awareness of their own physical well-being, and their facial appearance. Young people with older biological age were found to have be aging faster and scored lower on tests of balance, strength, and motor coordination, reported more physical limitations, had worse cognitive function, and showed signs of elevated risk for dementia and stroke. They also reported feeling in worse health and looked older in their faces to observers.
These results concur with findings from other studies. An analysis of data from the Framingham Heart Study (FHS) - comprising 5,209 subjects aged 28-62 years at baseline who had not yet developed overt symptoms of cardiovascular disease or suffered a heart attack or stroke – showed that deviation of physiological indices from optimal increases the risk of onset of unhealthy life.
A more recent study demonstrates that individual variation in physiological dysregulation (i.e. decline in physiological function) is substantial, and is strongly predictive of mortality and frailty, as well as chronic diseases (cancer, cardiovascular disease, diabetes), in populations from different continents.
Counterintuitively, it seems that the specific combination of biomarkers does not markedly affect the assessment of biological age and/or aging rate, and prediction of its health outcomes.[19-21] Many analyses have been replicated across a very large number of biomarker combinations. The insensitivity of assessment of biological age and/or aging rate to biomarker choice suggests that there is no single molecule, pathway, or physiological system that in isolation causes biological aging. While inclusion of more biomarkers may increase the accuracy of estimations of biological age and/or aging rate, for most studies for most purposes, choice of biomarkers will not have a major impact on the results as long as 10–15 relatively diverse biomarkers are chosen.
Slowing down (i.e. delaying) aging means having a body and mind of someone who is years younger, and spending a larger proportion of one’s life in good health and free from frailty and disability. This is the ultimate goal of anti-aging interventions. Greater investment in medical research to delay aging appears to be a highly efficient way to forestall disease, extend healthy life, and improve public health, as opposed to the traditional approach of trying to treat established disease and keep sick people alive.
In contrast to what many think, young people are the most attractive targets for anti-aging interventions and extension of healthspan. The reason is that it is still possible to prevent development of irreversible health damage with anti-aging interventions in the young.
However, there is skepticism about whether aging processes can be detected in young adults who do not yet have chronic diseases. Now we know that aging processes can be measured in young people in their mid-20s to mid-30s. This is important news as younger adults are still young enough for prevention of age-related disease, which is a more effective approach than trying to treat disease that is already established.
This opens a new door for effective anti-aging strategies. Thus, up to this point, research on healthspan extension may have been focused on the wrong end of the lifespan; rather than only studying and treating old humans, research should also study the young and investigate how lifestyle interventions affect biological aging, aging rates and health status early in the life course.
1. Weintraub, W.S., et al., Value of primordial and primary prevention for cardiovascular disease: a policy statement from the American Heart Association. Circulation, 2011. 124(8): p. 967-90.
2. Fontana, L., et al., Medical research: treat ageing. Nature, 2014. 511(7510): p. 405-7.
3. Belsky, D.W., et al., Quantification of biological aging in young adults. Proc Natl Acad Sci U S A, 2015. 112(30): p. E4104-10.
4. Levine, M.E., Modeling the rate of senescence: can estimated biological age predict mortality more accurately than chronological age? J Gerontol A Biol Sci Med Sci, 2013. 68(6): p. 667-74.
5. Simm, A., et al., Potential biomarkers of ageing. Biol Chem, 2008. 389(3): p. 257-65.
6. Burkle, A., et al., MARK-AGE biomarkers of ageing. Mech Ageing Dev, 2015.
7. Klemera, P. and S. Doubal, A new approach to the concept and computation of biological age. Mech Ageing Dev, 2006. 127(3): p. 240-8.
8. Gruenewald, T.L., et al., Combinations of biomarkers predictive of later life mortality. Proc Natl Acad Sci U S A, 2006. 103(38): p. 14158-63.
9. Cohen, A.A., et al., Detection of a novel, integrative aging process suggests complex physiological integration. PLoS One, 2015. 10(3): p. e0116489.
10. Seals, D.R. and S. Melov, Translational geroscience: emphasizing function to achieve optimal longevity. Aging (Albany NY), 2014. 6(9): p. 718-30.
11. Seals, D.R., J.N. Justice, and T.J. LaRocca, Physiological geroscience: targeting function to increase healthspan and achieve optimal longevity. J Physiol, 2015.
12. Wakefield, S.J., et al., Differentiating normal from pathological brain ageing using standard neuropsychological tests. Curr Alzheimer Res, 2014. 11(8): p. 765-72.
13. Baltes, P.B. and U. Lindenberger, Emergence of a powerful connection between sensory and cognitive functions across the adult life span: a new window to the study of cognitive aging? Psychol Aging, 1997. 12(1): p. 12-21.
14. Shalev, I., et al., Retinal vessel caliber and lifelong neuropsychological functioning: retinal imaging as an investigative tool for cognitive epidemiology. Psychol Sci, 2013. 24(7): p. 1198-207.
15. Ikram, M.K., et al., Retinal pathology as biomarker for cognitive impairment and Alzheimer's disease. J Neurol Neurosurg Psychiatry, 2012. 83(9): p. 917-22.
16. Heringa, S.M., et al., Associations between retinal microvascular changes and dementia, cognitive functioning, and brain imaging abnormalities: a systematic review. J Cereb Blood Flow Metab, 2013. 33(7): p. 983-95.
17. Wong, T.Y., Is retinal photography useful in the measurement of stroke risk? Lancet Neurol, 2004. 3(3): p. 179-83.
18. Arbeev, K.G., et al., Age trajectories of physiological indices in relation to healthy life course. Mech Ageing Dev, 2011. 132(3): p. 93-102.
19. Milot, E., et al., Trajectories of physiological dysregulation predicts mortality and health outcomes in a consistent manner across three populations. Mech Ageing Dev, 2014. 141-142: p. 56-63.
20. Cohen, A.A., Complex systems dynamics in aging: new evidence, continuing questions. Biogerontology, 2015.
21. Cohen, A.A., et al., Statistical distance as a measure of physiological dysregulation is largely robust to variation in its biomarker composition. PLoS One, 2015. 10(4): p. e0122541.
22. Goldman, D.P., et al., Substantial health and economic returns from delayed aging may warrant a new focus for medical research. Health Aff (Millwood), 2013. 32(10): p. 1698-705.