Do the telomere ends justify the physical means?

Telomeres are repetitive chromatin structures that protect the DNA ends of chromosomes from uncontrolled nucleolytic degradation, from activating DNA damage responses (DDRs) and from engaging in DNA ligation and recombination processes that can compromise genome stability. These functions are collectively known as “capping”. With cycles of cell replication telomeres can shorten to the point of becoming uncapped, thus triggering cellular apoptosis or senescence. Shortened telomeres are associated with aging, age-related conditions, and stress. Moreover, there is substantial evidence that, on the one hand, telomere shortening contributes protection from the uncontrolled cell division that underlies cancer, but on the other hand is a driver of some age-related degenerative pathologies like cardiovascular disease and pulmonary fibrosis¹. The maintenance of telomere length (TL) is thus apparently balanced between pro-cancer and anti-aging effects, and therefore interventions that counter telomere shortening might, in the proper context, possibly be beneficial.

In the article, “Effect of physical activity and exercise on telomere length: systematic review with meta-analysis” Valente et al.² assessed the effects of physical activity (PA) or structured exercise (versus relatively inactive control groups) on mean TL. A systematic review with meta-analysis was conducted, employing advanced and rigorous risk of bias and statistical analyses. Physically active individuals had longer telomeres, especially in middle-aged individuals and when considering only athletes. However, the authors conclude that there is very-low certainty that physically active individuals in general have longer telomeres with a moderate effect, and that this effect is probably overestimated.

This systematic review with meta-analysis suggested that physical activity or structured exercise has little impact on TL, in contrast to other studies that suggest a strong link between physical activity and TL. This finding is important, given evidence that exercise has apparent anti-aging effects, and raises questions about connections between telomeres and aging, as well as methodologies of TL measurement. It is also important to consider that the benefits of exercise may simply be independent of TL (e.g. the benefits are downstream from or parallel to the impact of telomeres on aging), but prior studies have suggested connections between moderate-intensity exercise and factors that affect TL, including telomerase activity and DNA repair^3–7 (figure 1A).

Figure 1.

Potential relationships between telomere status and physical activity. (A) Possible mechanisms by which physical activity (PA) may abrogate telomere dysfunction (i.e. maintain capping). (B) Telomere attrition (TA) may be inversely related to PA but limitations to confirming this association include multiple confounders. (C) Middle-aged athletes may reap the most benefit from physical activity, in terms of TL maintenance.

The report by Valente et al. highlighted limitations of TL measurement studies. They described several potential confounders of TL analysis including TL measurement methodology, cell/tissue type, and study design/bias (figure 1B). We emphasize that measures of only mean TL can be problematic, because studies in model systems have demonstrated that the shortest telomeres tend to be functionally dominant, with even one uncapped telomere potentially conveying deleterious consequences, and given that each of the 92 telomeres in human diploid cells can have lengths that differ substantially from one another, mean TL measurements may miss rare but important changes^8,9. Furthermore, telomere function can be compromised by length-independent damage¹⁰. Thus, measures that can detect rare, critically shortened telomeres (e.g. telomere fluorescence in situ hybridization, single telomere length analysis, or telomere shortest length assay) or functional capping status (assays of telomere dysfunction induced foci/telomere-associated DDR foci) may be more revealing¹¹. In addition, TLs can differ in different cell types and tissues, and it is unknown whether the accessible tissues typically used for human studies (i.e., peripheral blood leukocytes) should be the most important indicators of exercise benefit. It is also important to consider that antigenic exposure and clonal expansion impacts TL in circulating lymphocytes. Finally, Valente et al. pointed to limitations in some of the original studies, including designs that were unsuitable to evaluate causality and follow-up duration that was unfit to detect the small changes that occur in TL in the course of just one year of exercise.

Potential PA-associated confounders were also described by the authors. Pleotropic responses to PA or exercise is a possible confounder in that there may not be a linear response to the intensity of exercise, i.e. very high or low levels of exercise may be deleterious. PA may also mediate its effects on TL indirectly through the immune system. This would seem to be very important, since immunological clearance of senescent cells (i.e., cells with short TL) is a mechanism that declines with aging and may also explain the benefit of athletic-level exercise in middle-aged individuals (i.e., those that begin to experience insufficient immune clearance). Other confounders include PA exposure and adherence to intervention strategies (figure 1B).

The primary method used in this metanalysis is qPCR-based measurement of mean TL, which is notoriously difficult to perform with high precision and accuracy, and is strongly affected by preanalytic variables^12–21. If the studies showing little impact of exercise happen to be those of poor quality, then their failure to discern a difference in telomere length associated with exercise may be explained by noisy data, whereas noisy data is unlikely by chance to indicate an exercise-associated difference in TL, and thus evidence for correlations could be degraded by poor quality studies. Although the included studies were not evaluated for qPCR quality, the authors used standardized mean differences (SMDs), which measures the effect size of the difference between the groups (less physically active versus more physically active and exercise versus control group). This random-effect model (SMDs) is appropriate when there is considerable between-study heterogeneity in the true effects (which would be the case for different techniques and sources to measure TL data). When using SMD, studies using similar outcome measures can be combined. A SMD=1 indicates that the two group means are one sample standard deviation away from each other. Although SMDs do not determine the raw difference between groups, the magnitude of effect size can be interpreted as weak (SMD=0.2–0.49), moderate (SMD=0.5–0.79) and large (SMD≥0.8). Indeed, if there is residual noisy data, one would expect to see it in both experimental and control groups, perhaps in the same magnitude, and thus the potential of noisy data to impact the pooled effect may be diluted.

The authors suggested that when considering only middle-aged athletics the effect on TL was large even when corrected for publication bias (figure 1C). Several questions arise from this finding. Must the level of physical activity exceed a threshold, above which it is reflected in a reduction in TL? Is the effect in middle-age explained more by the normally greater baseline activity of younger individuals who thus benefit less from athletic-level exercise, or by a relative inability of older adults to achieve athletic-level exercise? The answers remain speculative, and further investigation is warranted.

The use of telomere length measurements in basic and translational research continues to be investigated as biomarkers for aging-related changes. At present, there is limited use for measures of telomere length in clinical care, and no evidence for their general use in the care of older adults (Table 1).

Table 1.

Experimental and clinical roles for measurements of telomere length

Basic and Translational Research	Clinical Practice
Leukocyte telomere length as a biomarker of oxidative stress and injury	Dyskeratosis congenita and other short telomere syndromes
Immune function in older adults
Surrogate for aging and tissue-based, age-related changes
Experimental endpoints in geroscience-based clinical trials