To go along with a recent open access paper on progress in the development of biomarkers of aging, I though I'd point out another top to bottom review of the presently available means to measure aging in humans. This is an especially important topic now the first rejuvenation therapies, those based on targeted removal of senescent cells, are close to availability. Most of the drug candidates are in fact available now to some degree for the adventurous who would like to try self-experimentation. But if you self-experiment with a potential rejuvenation therapy, how do you know that it works? If you cannot answer that question, you should certainly hold back rather than forge ahead.
Since there are a number of distinct root causes of aging, at this stage in the field a given therapy will only target one of them, these first therapies will most likely be only partially effective, and biology is complicated and contrary, it would be entirely possible to try something and experience no obvious immediate outcome, whether or not it worked in the strict sense. Further, while one can measure the outcome appropriate to the therapy, for example the degree to which it does in fact remove lingering senescent cells, proof is still required to show that this outcome did in fact produce rejuvenation. Thus other measures of function and health are needed, and those must be generally agreed upon across the research community to accurately reflect the state of biological age.
While there are plenty of options to form the basis for a generally applicable measure of biological age, ranging from metrics built of a combination of simple measure such as grip strength to characteristic age-related changes in the patterns of DNA methylation, the "generally agreed upon" part of the process has yet to happen. Firstly there is the matter of proving that a given metric is actually useful, something that will probably only happen in conjunction with proving that the first rejuvenation therapies are in fact rejuvenation therapies. Secondly, the research community tends to move very slowly on the matter of establishing standards of any sort, and the more possibilities there are to debate and refine, the slower that progression.
This paper is somewhat illustrative of that point, given the scope and length of work that the authors foresee for the future. I suspect that things will move more rapidly than the future that these researchers envisage, however. My prediction is that the marketplace of biotech companies and clinics will settle on one or more forms of DNA methylation assessments of biological age as good enough at the cost required for their implementation, and move ahead to standardize on them long before the academic research community has finished their more painstaking efforts.
In the 20th century, decreased mortality and lengthening of average human lifespan shifted the worldwide demographic structure toward the aged. This shift stemmed initially from treatment of infectious diseases and subsequently cardiovascular disorders. However, an increase in late-life disability has accompanied gains in healthy years lived (health span) and longevity. Biological aging is associated with a reduction in the regenerative potential in tissues and organs. Individuals with the same chronological age and their organs exhibit differential trajectories of age-related decline, and it follows that we should assess biological age distinctly from chronological age. Understanding the molecular and physiological phenomena that drive the complex and multifactorial processes underlying biological aging in humans will inform how researchers assess and investigate health and disease over the life course. In this review, we outline mechanisms of aging, discuss normal human aging at the organ-system level, suggest methods to measure biological age, and propose a framework to integrate molecular and physiological data into a composite score that measures biological aging in humans.
The heritable contribution to aging is limited for most humans, with genetics accounting for only 20-30% of lifespan variability in human twin and founder population family studies. However, heritable factors may represent a significantly larger contribution to lifespan at extreme ages, and the exceptionally aged may offer an opportunity to find rare genetic variants associated with longevity. Inter-related molecular and cellular phenomena occur during normal aging, intensify during accelerated or premature aging, and can be mitigated to increase lifespan. Researchers have proposed nine so-called hallmarks of aging - genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, and altered intercellular communication - that frame mechanisms underlying senescence. As we discuss in this section, many hallmarks suggest potential therapeutic targets to restore age-associated functional decline, although potential therapies are not completely benign. Translation of these hallmarks with surrogate measurements are important to include in a composite biological age score (BAS) because of their direct relationship with the molecular basis of aging.
Physiological aging involves a progressive detrimental change in maximal organ function with differential trajectories across organ systems. Importantly, multiple factors including genetics, environmental conditions, and developmental programming determine maximal organ function, which varies significantly between individuals. Aging affects all organ systems and must be assessed through a variety of physiological measures, as aging varies greatly organ-to-organ and person-to-person and results in impaired reserve capacity and limited ability to respond to stress. While there appears to be an organ-specific or organ-differential resilience and vulnerability of aging, frailty refers to the cumulative decline and increasing homeostatic imbalance that precedes the ultimate consequence of aging: death.
Chronological age offers limited information regarding the complex processes driving biological aging. Individuals with the same chronological age vary greatly in health and in disease and disability prompting the utility of defining a 'biological age'. The conceptualization of such a biological age distinct from chronological age has been proposed by many researchers with measures as crude as functional 'frailty' and as sophisticated as patterns of DNA methylation. While much research has focused on quantification of biological aging, a comprehensive and integrative score incorporating molecular biomarkers and physiological functional parameters is lacking. Current strategies to assess systemic biological age carry significant limitations as individual parameters to accurately reflect an individual's global loss of homeostasis have been elusive. Further, biological plausibility suggests that no single biomarker is likely to suffice given the underlying multisystem nature of the aging process with changes occurring on a molecular and organ-based level underscoring the utility of an aggregate score of biological aging. Scoring systems require careful integration of molecular markers (surrogates of the hallmarks of aging) with longitudinal physiological functional measures, yet little consensus exists regarding optimal methods for creation and evaluation of a composite biological age score (BAS).
We propose a conceptual framework for a composite BAS, which integrates available molecular measurements based on the hallmarks of aging and functional organ physiology measurements across the life course. Comprehensive and repeated assessments over time of existing and emerging molecular biomarkers and organ-specific functional measures in longitudinal epidemiologic cohorts in parallel with the use of sophisticated bioinformatics methodologies are needed to derive a global BAS. In general, components of the BAS should be i) highly correlated with chronological age, ii) predict organ-system and global age-related decline, and iii) be minimally invasive, readily observable, and reliably measured. Investigation into the optimal parameters used to derive a BAS will require collection and analysis of data sets that include successful agers without morbidity as well as accelerated agers with genetic progeroid syndromes, inflammatory pathologic conditions, and disease-related morbidity. Derivation and validation of a BAS will require multiple types of study designs including observational prospective population-based cohorts, leveraging large sample sizes with repeated measures over several decades as well as case-control studies and family-based studies to incorporate less common phenotypes of interest, including successful agers and accelerated agers with nongenetic and genetic conditions.