ArticlePDF Available

Effects of Competitive Triathlon Training on Telomere Length

Authors:
  • Atlantic Technological University Sligo

Abstract and Figures

Telomeres act as a mitotic clock and telomere-related senescence has been linked to age-related physiological decline. There is increasing evidence lifestyle factors can influence telomere length (TL). The purpose of this study was to determine the effect of competitive triathlon training on TL. Seven competitive male triathletes and seven recreationally active males participated in the study. Relative TL was measured using quantitative polymerase chain reaction. Physiological parameters key to athletic performance such as maximal oxygen intake, lactate threshold, and running economy were also measured. Triathletes had longer telomeres than the recreationally active (1.257 ± 0.028 vs. 1.002 ± 0.014; p < .0001). Positive association was found between TL and maximal oxygen intake, lactate threshold, and running economy (R2 = .677, .683, and .696, respectively). This study indicates that competitive triathlon training buffers against age-related telomere shortening, and there is a correlation between exercise behaviors, higher maximal oxygen intake, and TL.
Content may be subject to copyright.
Effects of Competitive Triathlon Training on Telomere Length
Marcus Colon, Andrew Hodgson, Eimear Donlon, and James E.J. Murphy
Telomeres act as a mitotic clock and telomere-related senescence has been linked to age-related physiological decline. There is
increasing evidence lifestyle factors can inuence telomere length (TL). The purpose of this study was to determine the effect
of competitive triathlon training on TL. Seven competitive male triathletes and seven recreationally active males participated in
the study. Relative TL was measured using quantitative polymerase chain reaction. Physiological parameters key to athletic
performance such as maximal oxygen intake, lactate threshold, and running economy were also measured. Triathletes had longer
telomeres than the recreationally active (1.257 ± 0.028 vs. 1.002 ± 0.014; p<.0001). Positive association was found between TL
and maximal oxygen intake, lactate threshold, and running economy (R
2
= .677, .683, and .696, respectively). This study
indicates that competitive triathlon training buffers against age-related telomere shortening, and there is a correlation between
exercise behaviors, higher maximal oxygen intake, and TL.
Keywords:aging, delayed senescence, physical activity, maximal aerobic capacity
Telomeres are a repeating nucleotide sequence consisting of
TTAGGG (T, thymine; A, adenine; and G, guanine) located at the
end of chromosomes, which help to ensure chromosomal stability
during cell division. Each time a cell replicates, the telomere is pro-
gressively shortened (Harley, Futcher, & Greider, 1990), and loss
of telomere length (TL) provides a measure of replicative senes-
cence (Benetos et al., 2001). Telomeres act as a mitotic clock and
have even been proposed as a marker of biological aging (Butler
et al., 2004). Telomere-related senescence has been linked to age-
related physiological decline and several age-related pathologies
(Bekaert et al., 2007).
There is increasing evidence that lifestyle factors are associ-
ated with TL such as exercise, psychological stress, body mass, and
smoking status (Ludlow, Ludlow, & Roth, 2013). This has led to
an increased number of studies exploring the effects of exercise on
TL. To date, the results of these studies have been inconsistent
(LaRocca, Seals, & Pierce, 2010;Østhus et al., 2012;Shin, Lee,
Song, & Jun, 2008;Woo, Tang, & Leung, 2008). However, the
weight of evidence has begun to lean toward exercise having a
buffering effect on age-related telomere shortening with studies
(LaRocca et al., 2010;Østhus et al., 2012) showing a positive
correlation between maximal oxygen intake
˙
ðVO2maxÞand TL.
Krauss et al. (2011) have even gone as far as showing increased
exercise capacity had longer telomeres equating to around 4 years
of biological age. While, Ludlow et al. (2008) and Savela et al.
(2013) have indicated that the relationship is an inverted Ucurve
where moderate-physical activity has benecial effects on TL
compared with both low- and high-intensity exercises.
Triathlon is an endurance multisport, consisting of three
separate disciplines (swimming, cycling, and running) performed
sequentially during a race. The popularity of triathlon has soared in
recent years with up to 300,000 active triathletes (TA) in the United
States (Burns, Keenan, & Redmond, 2003) and up to 17,000
members in Ireland (Triathlon Ireland, 2017). This surge in popu-
larity is also evidenced by triathlons inception into the Olympic
Games in 2000 where it has been contested at each summer games
since (Lenherr, Knechtle, Rüst, Rosemann, & Lepers, 2012). To
meet the demands of triathlon, athletes undergo rigorous high-
intensity training regimes. This training has been shown to convey
a host of physiological benets including improvements in aerobic
capacity and economy of motion (OToole & Douglas, 1995).
But there is a growing body of evidence showing that the intense
training and competition schedules carried out by endurance ath-
letes can have negative effects at the cellular level (Collins et al.,
2003). Accordingly, the hypothesis of this study was that TL is
positively correlated with physiological parameters key to athletic
performance and as such competitive triathlon training would
preserve TL over regular moderate-intensity exercise.
Methods
Subjects and Experimental Design
Seven competitive male TA and seven recreationally active (RA)
males participated in this study, following informed consent.
All participants were nonsmokers and in good health. All partici-
pants were recruited by e-mail advertisement. TAs were recruited
through a local triathlon club respondents were eligible to be
included if they had participated competitively in triathlons for
the previous 3 years, trained a minimum of 10 hr per week, were
nonsmokers, had never used performance enhancing drugs, and
were not in a period of competition training at the time of study
commencement. The RA males were recruited through the Institute
of Technology Sligo and respondents respondents were eligible to
participate if they performed a minimum of 3 hr of moderate-
intensity exercise per week and did not participate competitively in
any sports. Prior to inclusion, all participants completed a preex-
ercise health questionnaire and were eligible for inclusion if they
were nonsmokers, in good health, and suffered from no chronic
illnesses.
Triathletes were an average of 35.11 ± 5.86 years old,
(height: 180.04 cm ± 6.02 cm; weight: 73.90 ± 5.753), trained
an average of 12.67 ± 3.32 hr per week and had competed at
Colon and Murphy are with Mitochondrial Biology and Radiation Research Centre,
Institute of Technology Sligo, Sligo, Ireland. Colon, Donlon, and Murphy are with
the Dept. of Life Sciences, Institute of Technology Sligo, Sligo, Ireland. Hodgson is
with Sligo University Hospital, Sligo, Ireland. Address author correspondence to
James E.J. Murphy at murphy.james@itsligo.ie.
1
Journal of Aging and Physical Activity, (Ahead of Print)
https://doi.org/10.1123/japa.2018-0248
© 2018 Human Kinetics, Inc. ORIGINAL RESEARCH
national or international level in triathlons for a minimum of
3 years. All TAs were tested during triathlon season in a period of
out of competition training.RA were dened as people who
were engaged in regular endurance-based exercise but do not
participate competitively in any sport.RA group were an average
of 34.14 ± 10.29 years old, (height: 177.13 cm ± 4.96 cm; weight:
78.51 ± 9.657) and exercised and average of 5 ± 1.15 hr per week.
Blood samples were taken by venous blood draw 24 hr post-
exercise testing. All procedures were approved by the research
and ethics committee of Sligo University Hospital in accordance
with the Declaration of Helsinki.
Anthropometric Measurements
Participants were tested in a semifasted state (no food or water
for 3 hr prior). All measurements were performed on individuals
in a rested state. Height was measured in bare feet using a
stadiometer. Body composition was measured using whole-body
densitometry in a BodPod (Cosmed, Concord, CA) using man-
ufacturer protocols. Weight was also measured using a calibrated
scale that accompanies the BodPod. All instruments were cali-
brated on the day of testing using manufacturers quality control
measures.
Treadmill Test for
˙
VO2max, Lactate Threshold, and
Running Economy
The treadmill test was performed in two stages, the rst stage
was used to calculate lactate threshold and running economy. This
employed a discontinuous incremental test of 3 min stages, start
speed was determined as 23 km/hr below participant 5 km or
10 km race pace and increasing by 1 km/hr after each stage until
blood lactate concentration exceeded 4 mmol·L
1
. Participants
carried out ve to seven stages, with a 30-s break in between when
anger prick blood sample was taken for blood lactate concen-
tration and measured using a portable blood lactate analyzer
(Arkray Factor Ltd., Ipswich, United Kingdom). Participants had
a 5-min rest period before completing a second incremental test
to determine
˙
VO2max. This was initiated at the nal speed of
the rst stage with the gradient increasing by 1% every minute
until voluntary exhaustion. Heart rate was recorded using a T31
heart rate monitor (Polar Electro, Kempele, Finland), and oxygen
uptake and carbon dioxide expiration was recorded using a
QuarkB
2
(Cosmed). Heart rate, O
2
,andCO
2
were monitored
continuously throughout.
˙
VO2max are expressed for each partic-
ipant as a 30-s average. Lactate thresholds were calculated using
the software previously described (Newell et al., 2007; available
at: orreco.shinyapps.io/lactate/).
DNA Extraction and Quantitative Polymerase Chain
Reaction
DNA was extracted from whole blood using a DNeasy blood and
tissue kit (Qiagen, Crawley, United Kingdom) and quantied using
a biophotometer (Eppendorf, Hamburg, Germany). Each 20-μL
reaction contained 1820 ng DNA, 1 ×SYBR green fast mix and 6-
Carboxy-X-Rhodamine (ROX) (Quanta Biosciences, Gaithers-
burg, MD), and 1-μM primers in ultrapure water. All reactions
were analyzed on a StepOnePlus system (Applied Biosystems,
Foster City, CA). Housekeeper used for normalization was β-2
microglobulin used at a nal concentration of 500 nM of both
forward and reverse primer. β-2 microglobulin primers were:
forward, 5CGGCTCTGCTTCCCTTAGA 3and reverse,
5TCACAGCCAAGCATTCTACAAAC 3. Data were cal-
culated relative to the RA group using the 2
ΔΔ
CT (Cycle
Threshold) equation (Livak & Schmittgen, 2001).
Relative TL was measured using a quantitative polymerase chain
reactionmethodaspreviouslydescribed(Cawthon, 2002). Telomere
primers used were: forward, 5GGTTTTTGAGGGTGAGGGT-
GAGGGTGAGGGTGAGGGT 3and reverse, 5TCCCGAC-
TATCCCTATCCCTATCCCTATCCCTATCCCTA 3. Cycling
conditions were: 95 °C for 10 min followed by 30 cycles of 95 °C
for15sand5Cfor2min.
Statistics
All statistical analyses were performed on Prism software (version
5.0; Graphpad, San Diego, CA). All data were found to be normally
distributed as determined by a ShapiroWilks test for normality
(p>.05). Signicance was determined using an independent sam-
ples ttest with p<.05 as the limit. Effect sizes were calculated as
Cohensd(Cohen, 1988) to determine the magnitude of the dif-
ference between groups. Linear regression was used to assess the
relationship between Telomere/Single copy gene (T/S) ratio and
physiological variables using Pearsonscoefcient of determina-
tion (R
2
) and relationship strength interpreted as previously described
(Mukaka, 2012).
Results
Physiological and Anthropometric Characteristics
Physiological and anthropometric analysis results are shown in
Table 1. TAs had signicantly greater
˙
VO2max (p= .0066, d=
1.753) and lactate threshold speed (p= .0002, d= 2.791). TAs also
had signicantly lower percentage body fat (p= .0374, d=1.250)
and running economy (p=<.0001, d=3.060). There were no
Table 1 Physiological Characteristics of the Recreationally Active and Competitive Triathlete Participants Tested
During Out of Competition Training
Variable
Recreational
(average result ± SD)
Triathlete
(average result ± SD)
pvalue, [95% CI],
and Cohensd
˙
VO2max (ml·kg
1
·min
1
) 53.89 ± 4.325 65.44 ± 4.240 .0003, [16.54, 6.564], 2.697
Body fat (%) 18.70 ± 8.346 10.89 ± 2.906 .0374, [0.536, 15.09], 1.250
Lactate thresholdspeed (km/hr) 11.66 ± 0.953 16.08 ± 2.026 .0002, [6.266, 2.577], 2.791
Lactate thresholdheart rate (bpm) 156.6 ± 14.77 164.0 ± 10.74 .3012, [22.50, 7.582], 0.573
Running economy (ml·kg
1
·km
1
) 221.2 ± 9.190 193.2 ± 9.109 <.0001, [17.34, 38.66], 3.060
Note. Data are shown as mean ± SD.pvalues and CIs are calculated from an independent samples ttest and effect sizes are calculated as Cohensd.CI=condence
interval.
(Ahead of Print)
2Colon et al.
signicant differences found between the groups bodyweight and
heart rate at lactate threshold (p>.05). However, Cohens effect
sizes show that triathlon training had a moderate effect on body-
weight and pronounced effect on heart rate at lactate threshold.
Relative TL
Figure 1shows that the RA group (1.002 ± 0.014) had signicantly
shorter telomeres than the TA group (1.257 ± 0.028), (p<.0001,
95% condence interval [0.2806, 0.2288], Cohensd= 11.519).
There were signicant positive relationships found between
˙
VO2max, lactate threshold speed, running economy, and relative
TL with moderate- to high-positive relationships, as seen in Table 2.
A low-positive relationship was also found with percentage body
fat. There was no relationship found between age, bodyweight, and
lactate threshold heart rate.
Discussion
The main ndings of this study are (a) TA group had signicantly
longer telomeres than the RA group; (b) a positive relationship
was seen between
˙
VO2max and TL; and (c) TA group showed
the physiological markers associated with high-intensity endur-
ance training (when compared with the RA group) with greater
˙
VO2max, higher lactate threshold, superior running economy, and
lower percentage body fat.
When the physiological test results of the TA and RA groups
are compared, the key performance indicators (
˙
VO2max, lactate
threshold, running economy, and percentage body fat) were as
expected and conrm the validity of the cohort recruitment process.
It has long been known that TAs tend to have high-aerobic capacity
(OToole & Douglas, 1995) and that triathlon training leads to
a greater level of fat metabolism and lower levels of glycogen
depletion (OToole, Douglas, & Hiller, 1989), which allows ath-
letes to rely more on the oxidative energy pathways rather than
anaerobic metabolism leading to the production of lactic acid. The
TA group also showed greater economy of motion which is a key
determinant of race performance among athletes of similar abilities
(Conley & Krahenbuhl, 1980). Sleivert and Rowlands (1996) states
that these TAs would be classied as subelite according to their
˙
VO2max, body mass, and percentage body fat.
It is now widely accepted that regular physical activity reduces
the risk of many age-related diseases and promotes a higher quality
of life. More recently, it has been hypothesized that exercise can
slow cellular aging by decreasing the rate of telomere shortening,
which has been seen in multiple studies showing a positive asso-
ciation between physical activity and TL (Cherkas et al., 2008;
LaRocca et al., 2010;Østhus et al., 2012). However, there have been
inconsistencies in the evidence to support this theory with studies
showing no association (Kadi et al., 2008;Mathur et al., 2013;Shin
et al., 2008). The relationship between physical activity levels and
quality of life/general health status is not necessarily a linear one;
however, several studies show an inverted U-shaped curve relation-
ship with moderate-physical activity having a benecial effect over
both low and high levels of activity (Ludlow et al., 2008;Savela
et al., 2013). The results from this study suggest that high-intensity
endurance training has a positive effect on TL over regular moderate
exercise. In this study, it may have been the case that the training
performed by the athletes was not of sufcient intensity to the
detrimental effects seen in other studies, though the scope and
longevity of the study was too limited to evaluate this. It may
also be the case that as both Ludlow et al. (2008) and Savela et al.
(2013) used older athletes (65 years old), the negative effects ofhigh-
intensity exercise on TL may only be seen are only seen later in life.
Participants in this study were closely matched with respect
to their age, smoking status, body type, and were all in good
health with relatively minor intragroup variation of physiological
parameters. However, the present ndings must be considered
limited due to the small sample sizes and the fact that our design
did not allow for the analysis of cause and effect. LaRocca et al.
(2010)rst showed that there was positive correlation between
maximal aerobic capacity and TL, which has also been shown in
Østhus et al. (2012). Here, it was also observed that there was a
strong correlation between a number of the physiological variables
including maximal aerobic capacity and TL but also with percent-
age body fat, lactate threshold speed, and running economy. These
results lend weight to the hypothesis put forward (LaRocca et al.,
2010) that habitual exercise behavior, higher
˙
VO2max, and lon-
ger TL are part of the same phenotype, as all variables showing
positive correlation have been consistently shown to be directly
correlated with volume and intensity of exercise performed. These
results highlight the importance of exercise and exercise intensity
in healthy aging. TL has previously been shown to contribute
to mortality in age-related diseases such as heart and infectious
Figure 1 Alterations in relative TL (T/S ratio) in blood DNA of the
RA and TA participants tested during a period out of competition training.
Data were calculated relative to the RA group and presented in a boxplot
with minimum to maximum whisker. Signicance was determined using
an independent samples ttest with p<.05 as the limit, ***p<.0001. TL =
telomere length; TA = triathlete; RA = recreationally active.
Table 2 Relationship of Physiological Variables With
Telomere Length in Recreationally Active and Triathlete
Participants During a Period of Out of Competition
Training
Variable R
2
,pvalue
Age .001, .914
˙
VO2max (ml·kg
1
·min
1
) .677, .0003
Bodyweight (kg) .085, .313
Body fat (%) .318, .036
Lactate thresholdspeed (km/hr) .683, .0003
Lactate thresholdheart rate (bpm) .096, .28
Running economy (ml·kg
1
·km
1
) .696, .0002
Note. Linear regression was used to assess the relationship between relative
telomere length and physiological variables. Data are shown as Pearsons coef-
cient of determination (R
2
).
(Ahead of Print)
Triathlon Training and Telomere Length 3
diseases (Cawthon, Smith, OBrien, Sivatchenko, & Kerber,
2003); these results show that exercise could represent a tool to
help reduce mortality from age-related disease. Future research
should use large scale randomized control trials and longitudinal
studies to conrm the relationship between endurance training,
aerobic tness, and TL.
Conclusion
Competitive triathlon training buffers against age-related telomere
shortening over regular moderate exercise. Our data also suggest
that TL is positively correlated with physiological parameters key
to athletic performance including
˙
VO2max, lactate threshold, and
running economy. These results highlight the importance of exer-
cise in healthy aging.
References
Bekaert, S., De Meyer, T., Rietzschel, E.R., De Buyzere, M.L.,
De Bacquer, D., Langlois, M., ::: Van Oostveldt, P. (2007). Telomere
length and cardiovascular risk factors in a middle-aged population
free of overt cardiovascular disease. Aging Cell, 6(5), 639647.
PubMed ID: 17874998 doi:10.1111/j.1474-9726.2007.00321.x
Benetos, A., Okuda, K., Lajemi, M., Kimura, M., Thomas, F., Skurnick, J.,
::: Aviv, A. (2001). Telomere length as an indicator of biological
aging. Hypertension, 37(2), 381385. doi:10.1161/01.HYP.37.2.381
Burns, J., Keenan, A., & Redmond, A.C. (2003). Factors associated with
triathlon-related overuse injuries. Journal of Orthopaedic & Sports
Physical Therapy, 33(4), 177184. PubMed ID: 12723674 doi:10.
2519/jospt.2003.33.4.177
Butler, R.N., Sprott, R., Warner, H., Bland, J., Feuers, R., Forster, M., :::
Wolf, N. (2004). Biomarkers of aging: From primitive organisms to
humans. The Journals of Gerontology. Series A, Biological Sciences
and Medical Sciences, 59(6), B560B567. PubMed ID: 15215265
doi:10.1093/gerona/59.6.B560
Cawthon, R.M. (2002). Telomere measurement by quantitative PCR.
Nucleic Acids Research, 30(10), 47e47. PubMed ID: 12000852
doi:10.1093/nar/30.10.e47
Cawthon, R.M., Smith, K., OBrien, E., Sivatchenko, A., & Kerber, R.
(2003). Association between telomere length in blood and mortality
in people aged 60 years or older. The Lancet.361(9355), 393395.
doi:10.1016/S0140-6736(03)12384-7
Cherkas, L.F., Hunkin, J.L., Kato, B.S., Richards, J.B., Gardner, J.P.,
Surdulescu, G.L., ::: Aviv, A. (2008). The association between
physical activity in leisure time and leukocyte telomere length.
Archives of Internal Medicine, 168(2), 154158. PubMed ID:
18227361 doi:10.1001/archinternmed.2007.39
Cohen, J. (1988). Statistical power analysis for the behavioral sciences
(2nd ed.). Hillsdale, NJ: Lawrence Earlbaum Associates.
Collins, M., Renault, V., Grobler, L.A., St Clair Gibson, A., Lambert, M.I.,
Wayne Derman, E., ::: Mouly, V. (2003). Athletes with exercise-
associated fatigue have abnormally short muscle DNA telomeres.
Medicine & Science in Sports & Exercise, 35(9), 15241528. doi:10.
1249/01.MSS.0000084522.14168.49
Conley, D.L., & Krahenbuhl, G.S. (1980). Running economy and distance
running performance of highly trained athletes. Medicine & Science
in Sports & Exercise, 12(5), 357360. doi:10.1249/00005768-
198025000-00010
Harley, C.B., Futcher, A.B., & Greider, C.W. (1990). Telomeres shorten
during ageing of human broblasts. Nature, 345(6274), 458460.
PubMed ID: 2342578 doi:10.1038/345458a0
Kadi, F., Ponsot, E., Piehl-Aulin, K., MacKey, A., Kjaer, M., Oskarsson,
E., & Holm, L. (2008). The effects of regular strength training
on telomere length in human skeletal muscle. Medicine & Science
in Sports & Exercise, 40(1), 8287. doi:10.1249/mss.
0b013e3181596695
Krauss, J., Farzaneh-Far, R., Puterman, E., Na, B., Lin, J., Epel, E., :::
Whooley, M.A. (2011). Physical tness and telomere length in
patients with coronary heart disease: Findings from the heart
and soul study. PLoS ONE, 6(11), e26983. PubMed ID: 22096513
doi:10.1371/journal.pone.0026983
LaRocca, T.J., Seals, D.R., & Pierce, G.L. (2010). Leukocyte telomere
length is preserved with aging in endurance exercise-trained
adults and related to maximal aerobic capacity. Mechanism of
Ageing and Development, 131(2), 165167. doi:10.1016/j.mad.
2009.12.009
Lenherr, R., Knechtle, B., Rüst, C., Rosemann, T., & Lepers, R. (2012).
From double iron to double deca iron ultra-triathlon-a retrospective
data analysis from 1985 to 2011. Physical Culture and Sport Studies
and Research, 54,5567. doi:10.2478/v10141-012-0013-4
Livak, K.J., & Schmittgen, T.D. (2001). Analysis of relative gene
expression data using real-time quantitative PCR and the 2(-Delta
Delta C(T)) Method. Methods, 25(4), 402408. doi:10.1006/meth.
2001.1262
Ludlow, A.T., Ludlow, L.W., & Roth, S.M. (2013). Do telomeres adapt
to physiological stress? Exploring the effect of exercise on telomere
length and telomere-related proteins. BioMed Research Interna-
tional, 2013,115. PubMed ID: 24455708 doi:10.1155/2013/
601368
Ludlow, A.T., Zimmerman, J.B., Witkowski, S., Hearn, J.W., Hateld,
B.D., & Roth, S.M. (2008). Relationship between physical activity
level, telomere length, and telomerase activity. Medicine & Science
in Sports & Exercise, 40(10), 17641771. PubMed ID: 18799986
doi:10.1249/MSS.0b013e31817c92aa
Mathur, S., Ardestani, A., Parker, B., Cappizzi, J., Polk, D., & Thompson,
P.D. (2013). Telomere length and cardiorespiratory tness in mara-
thon runners. Journal of Investigative Medicine, 61(3), 613615.
PubMed ID: 30385593 doi:10.2310/JIM.0b013e3182814cc2
Mukaka, M.M. (2012). Statistics corner: A guide to appropriate use of
correlation coefcient in medical research denitions of correlation
and clarications. Malawi Medical Journal, 24(3), 6971. PubMed
ID: 23638278
Newell, J., Higgins, D., Madden, N., Cruickshank, J., Einbeck, J.,
McMillan, K., & McDonald, R. (2007). Software for calculating
blood lactate endurance markers. Journal of Sports Sciences,
25(12), 14031409. PubMed ID: 17786693 doi:10.1080/
02640410601128922
Østhus, I.B.Ø., Sgura, A., Berardinelli, F., Alsnes, I.V., Brønstad, E.,
Rehn, T., ::: Nauman, J. (2012). Telomere length and long-term
endurance exercise: Does exercise training affect biological age?
A pilot study. PLoS ONE, 7(12), e52769. PubMed ID: 23300766
doi:10.1371/journal.pone.0052769
OToole, M.L., & Douglas, P.S. (1995). Applied physiology of triathlon.
Sports Medicine, 19(4), 251267. doi:10.2165/00007256-199519040-
00003
OToole, M.L., Douglas, P.S., & Hiller, W.D. (1989). Applied physiology
of a triathlon. Sports Medicine, 8(4), 201225. doi:10.2165/
00007256-198908040-00002
Savela, S., Saijonmaa, O., Strandberg, T.E., Koistinen, P., Strandberg,
A.Y., Tilvis, R.S., ::: Fyhrquist, F. (2013). Physical activity in
midlife and telomere length measured in old age. Experimental
Gerontology, 48(1), 8184. PubMed ID: 22386580 doi:10.1016/j.
exger.2012.02.003
(Ahead of Print)
4Colon et al.
Shin, Y.-A., Lee, J.-H., Song, W., & Jun, T.-W. (2008). Exercise training
improves the antioxidant enzyme activity with no changes of telomere
length. Mechanisms of Ageing and Development, 129(5), 254260.
PubMed ID: 18295822 doi:10.1016/j.mad.2008.01.001
Sleivert, G., & Rowlands, D. (1996). Physical and physiological factors
associated with success in the triathlon. Sports Medicine, 22(l), 818.
doi:10.2165/00007256-199622010-00002
Triathlon Ireland. (2017). Triathlon Ireland annual report. Kilmacanogue.
Retrieved from https://www.triathlonireland.com/Image-Document-
Library/Documents/Triathlon-Ireland-Annual-Report-2017-.pdf
Woo, J., Tang, N., & Leung, J. (2008). No association between physical
activity and telomere length in an elderly Chinese population 65 years
and older. Archives of Internal Medicine, 168(19), 2163. PubMed ID:
18955647 doi:10.1001/archinte.168.19.2163
(Ahead of Print)
Triathlon Training and Telomere Length 5
... As shown in Table 2, several of the interventional cohort studies on TL in high-performance athletes describe a positive association of TL with regular and extended participation in physical exercise [59][60][61][62][63]. However, Nickels et al. [48]. ...
... Amongst the 27 selected observational studies (Table 3), several cross-sectional studies highlight a positive correlation between exercise and telomere biology [60,62,[70][71][72][73][74][75][76][77]. The Helsinki Birth Cohort was utilized by Ästrom et al. [78] to investigate the correlation between physical performance and TL in the elderly with a mean age of 61 years. ...
... In comparison with other levels of exercise intensity, Colon et al. [60] showed that TL was better preserved through high-intensity training in comparison with exercise at moderate intensity. This study was conducted with competitive triathlon athletes at a high level of fitness as the investigated cohort. ...
Article
Full-text available
Background Overall life expectancy continues to rise, approaching 80 years of age in several developed countries. However, healthy life expectancy lags far behind, which has, in turn, contributed to increasing costs in healthcare. One way to improve health and attenuate the socio-economic impact of an aging population is to increase overall fitness through physical activity. Telomere attrition or shortening is a well-known molecular marker in aging. As such, several studies have focused on whether exercise influences health and aging through telomere biology. This systematic review examines the recent literature on the effect of physical activity on telomere length (TL) and/or telomerase activity as molecular markers of aging. Methods A focused search was performed in the databases PubMed and Web of Science for retrieving relevant articles over the past ten years. The search contained the following keywords: exercise, sport, physical activity, fitness, sedentary, physical inactivity, telomere, telomere length, t/s ratio, and telomerase. PRISMA guidelines for systematic reviews were observed. Results A total of 43 articles were identified and categorized into randomized controlled trials (RCT), observational or interventional studies. RCTs ( n = 8) showed inconsistent findings of increased TL length with physical activity in, e.g. obese, post-menopausal women. In comparison with a predominantly sedentary lifestyle, observational studies ( n = 27) showed significantly longer TL with exercise of moderate to vigorous intensity; however, there was no consensus on the duration and type of physical activity and training modality. Interventional studies ( n = 8) also showed similar findings of significantly longer TL prior to exercise intervention; however, these studies had smaller numbers of enrolled participants (mostly of high-performance athletes), and the physical activities covered a range of exercise intensities and duration. Amongst the selected studies, aerobic training of moderate to vigorous intensity is most prevalent. For telomere biology analysis, TL was determined mainly from leukocytes using qPCR. In some cases, especially in RCT and interventional studies, different sample types such as saliva, sperm, and muscle biopsies were analyzed; different leukocyte cell types and potential genetic markers in regulating telomere biology were also investigated. Conclusions Taken together, physical activity with regular aerobic training of moderate to vigorous intensity appears to help preserve TL. However, the optimal intensity, duration of physical activity, as well as type of exercise still need to be further elucidated. Along with TL or telomerase activity, participants’ fitness level, the type of physical activity, and training modality should be assessed at different time points in future studies, with the plan for long-term follow-up. Reducing the amount of sedentary behavior may have a positive effect of preserving and increasing TL. Further molecular characterization of telomere biology in different cell types and tissues is required in order to draw definitive causal conclusions on how physical activity affects TL and aging.
... In the initial search (Figure 1), 1400 articles were identified, of which 83 were included. The detailed characteristics of these studies are presented in Table 1 [45,46,, Table 2 [27,[81][82][83][84][85][86][87][88][89][90][91][92][93], Table 3 [44,[94][95][96][97][98][99][100][101][102][103][104], Table 4 [60,67,77,93,[105][106][107][108][109][110][111][112][113][114][115][116][117][118][119][120], Table 5 [121][122][123][124][125][126][127], and Table 6 [43,[128][129][130][131][132][133][134][135][136][137]. Most studies focused on the association between TL and PA (Tables 1-3), followed by smoking (Tables 4 and 5), and sleep (Table 6). ...
... Cross-sectional studies (n = 23) are presented in Table 1 [45,46,. Table 2 [27,[81][82][83][84][85][86][87][88][89][90][91][92][93] shows observational studies (n = 14) using case-control and longitudinal approaches (n = 3); and Table 3 [44,[94][95][96][97][98][99][100][101][102][103][104] shows intervention studies. In these tables, the details for each study including author, reference, year, design, participants and characteristics, TL analysis methods, tissue for TL analysis, exposure assessment methods, and main results, are presented. ...
... On classifying the subjects into age groups, this association was only significant in adults from 20 to 40 years old [80]. Table 2 [27,[81][82][83][84][85][86][87][88][89][90][91][92][93] shows case-control (n = 11) and longitudinal studies (n = 3) analyzing the association between PA and TL. The results were mixed. ...
Article
Full-text available
Aging is a risk factor for several pathologies, restricting one’s health span, and promoting chronic diseases (e.g., cardiovascular and neurodegenerative diseases), as well as cancer. Telomeres are regions of repetitive DNA located at chromosomal ends. Telomere length has been inversely associated with chronological age and has been considered, for a long time, a good biomarker of aging. Several lifestyle factors have been linked with telomere shortening or maintenance. However, the consistency of results is hampered by some methodological issues, including study design, sample size, measurement approaches, and population characteristics, among others. Therefore, we aimed to systematically review the current literature on the effects of three relevant lifestyle factors on telomere length in human adults: physical activity, smoking, and sleep. We conducted a qualitative systematic review of observational and intervention studies using the Preferred Reporting Item for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. The systematic literature search covered articles published in MEDLINE and EMBASE databases (from 2010 to 2020). A total of 1400 studies were identified; 83 were included after quality control. Although fewer sedentary activities, optimal sleep habits, and non- or ex-smoker status have been associated with less telomere shortening, several methodological issues were detected, including the need for more targeted interventions and standardized protocols to better understand how physical activity and sleep can impact telomere length and aging. We discuss the main findings and current limitations to gain more insights into the influence of these lifestyle factors on the healthy aging process.
... Results from two studies showed that an increase in adiposity measures was related to a decrease in LTL (Rehkopf et al., 2016;Batsis et al., 2018). The observed association between LTL and obesity might also be described by the obesity-associated (FTO) gene-involved pathways and fat mass (FM) (Zhou et al., 2017;Colon et al., 2019). Shorter telomeres have been related to increasing BMI and more recently with increasing waist circumference (WC) and waist-to-hip ratio (WHR) in women (Nordfjäll et al., 2008). ...
Article
Full-text available
Background: Several studies have revealed the negative effects of adiposity on telomere length shortening. However, the results of the studies assessing the negative relationship between obesity and leukocyte telomere length (LTL) are not consistent. This systematic review and meta-analysis are aimed to pool the results of articles assessing the relationship between obesity and LTL among children and adolescents. Methods: To retrieve the related studies, four online databases including PubMed, Embase, ProQuest, and Scopus were searched until May 2022. Observational studies evaluating the relationship between obesity and LTL among apparently healthy children and adolescents (aged ≤18 years) were included in the study. We considered the studies that had reported a mean ± standard deviation of LTL. The random-effects model was used to assess the pooled weighted mean difference (WMD) and a 95% confidence interval (CI). Results: The search yielded seven studies from an initial 3,403 records identified. According to the results of seven articles with 4,546 participants, obesity was associated with LTL shortening among children and adolescents (WMD = −0.081; 95% CI: −0.137 to −0.026; p = 0.004; I ² = 99.9%). Also, no publication bias was observed. According to the results of subgrouping, significant results were only attributed to the studies conducted in Europe, with high quality scores, among overweight and obese adolescents, with a baseline LTL lower than 1, and performed in community-based school settings. Also, according to the subgrouping and meta-regression results, the obesity definition criteria and baseline LTL were the possible sources of between-study heterogeneity. Conclusion : We observed shorter LTL among overweight and obese children and adolescents. To obtain more reliable results, further longitudinal prospective studies with large sample sizes and more consistent and accurate definitions of obesity are required.
... Higher waist-to-hip ratio is considered an independent predictor of TL shortening, and abdominal obesity appeared to have a stronger effect on telomere reduction [41]. Indeed, body fat mass percentages correlate with telomere shortening [42]. In our study, we found that waist circumference can influence telomere shortening, influenced by physical training. ...
Article
Full-text available
Background: Telomere length is inversely associated with the senescence and aging process. Parallelly, obesity can promote telomere shortening. Evidence suggests that physical activity may promote telomere elongation. Objective: This study's objective is to evaluate the effects of combined exercise training on telomere length in obese women. Design and methods: Twenty pre-menopausal women (BMI 30-40 kg/m2, 20-40 years) submitted to combined training (strength and aerobic exercises), but only 13 finished the protocol. Each exercise session lasted 55 min/day, three times a week, throughout 8 weeks. Anthropometric data, body composition, physical performance (Vo2max), and 8-h fasting blood samples were taken before and after 8 weeks of training. Leukocyte DNA was extracted for telomere length by RT-qPCR reaction, using the 2-ΔΔCt methodology. Results: After the training intervention, significant differences (p < 0.05) were observed in telomere length (respectively before and after, 1.03 ± 0.04 to 1.07 ± 0.04 T/S ratio), fat-free mass (46 ± 7 to 48 ± 5 kg), Vo2max (35 ± 3 to 38 ± 3 ml/kg/min), and waist circumference (96 ± 8 to 90 ± 6 cm). In addition, an inverse correlation between waist circumference and telomere length was found, before (r = - 0.536, p = 0.017) and after (r = - 0.655, p = 0.015) exercise training. Conclusion: Combined exercise promoted leukocyte telomere elongation in obese women. Besides, the data suggested that greater waist circumference may predict shorter telomere length. Clinical trial registration: ClinicalTrails.gov, NCT03119350. Retrospectively registered on 18 April 2017.
... Engagement in exercise is associated with longer telomeres and may slow down TL shortening [29]. Higher aerobic capacity is associated with longer leukocyte TL in endurance trained athletes [30][31][32] and young (18-32 yrs) [33] and older exercised-trained adults (55-72yrs) when compared to controls [34]. However, the literature regarding TL in skeletal muscle is conflicting, with only few studies reporting a positive association between higher levels of physical activity and longer telomeres in young and older healthy populations [35][36][37]; while other studies reported no association between skeletal muscle TL and exercise training levels [38,39]. ...
Article
A reduction in aerobic capacity and the shortening of telomeres are hallmarks of the ageing process. We examined whether a lower aerobic capacity is associated with shorter TL in skeletal muscle and/or leukocytes, across a wide age range of individuals. We also tested whether TL in human skeletal muscle (MTL) correlates with TL in leukocytes (LTL). Eighty-two recreationally active, healthy men from the Gene SMART cohort (31.4±8.2 years; body mass index (BMI)=25.3±3.3kg/m2), and 11 community dwelling older men (74.2±7.5years-old; BMI=28.7±2.8kg/m2) participated in the study. Leukocytes and skeletal muscle samples were collected at rest. Relative telomere length (T/S ratio) was measured by RT-PCR. Associations between TL, aerobic capacity (VO2 peak and peak power) and age were assessed with robust linear models. Older age was associated with shorter LTL (45% variance explained, P<0.001), but not MTL (P= 0.7). Aerobic capacity was not associated with MTL (P=0.5), nor LTL (P=0.3). MTL and LTL were correlated across the lifespan (rs=0.26, P=0.03). In healthy individuals, age explain most of the variability of LTL and this appears to be independent of individual aerobic capacity. Individuals with longer LTL also have a longer MTL, suggesting that there might be a shared molecular mechanism regulating telomere length.
Article
Full-text available
BACKGROUND: Telomeres are structures located at the chromosome ends, whose function is protecting DNA from attrition caused during cell division. Telomeric length serves as a mitotic clock, activating senescence and cellular cycle arrest when it reaches a shortening limit, which causes aging. Lifestyle is a factor that can affect telomeric shortening. Unhealthy habits have been linked to accelerated telomeric shortening, while healthy lifestyles are known to reduce this process and slow down aging. Current community has expressed an interest in improving lifestyle choices; however, an increase in unhealthy habits and chronic stressors have been seen. OBJECTIVE: This review aims to show the influence that different lifestyles have on telomeric length. METHODS: The review was carried out following the PRISMA statement in three databases. Twenty-eight research articles and nine review articles were reviewed, identifying six main lifestyles habits. RESULTS: Regular moderate-vigorous physical activity, dietary patterns rich in vegetables and antioxidants, and the stress control techniques were related to greater telomeric lengths and improvements in the oxidative response by reducing the levels of oxidative stress markers. On the contrary, stress, obesity, smoking, and alcoholism showed a negative effect of shorter telomeres, which can be a factor of early aging. CONCLUSION: The previous demonstrates the influences of lifestyles on telomere shortening rates and aging, therefore they should be considered as areas of interest for future research, and personal and community health improvement.
Article
Full-text available
From Double Iron to Double Deca Iron Ultra-Triathlon - A Retrospective Data Analysis from 1985 to 2011 Participation in ultra-endurance performance is of increasing popularity. We analyzed the historic development of the ultra-triathlon scene from 1985 to 2011 focusing on a) worldwide distribution of competition, b) participation, c) gender, and d) athlete nationality. We examined the participation trends of 3,579 athletes, involving 3,297 men (92.1%) and 300 women (7.9%), using linear regression analyses. Between 1985 and 2011, a total of 96 Double Iron ultra-triathlons (7.6km swimming, 360km cycling, and 84.4km running), 51 Triple Iron ultra-triathlons (11.6km swimming, 540km cycling, and 126.6km running), five Quadruple Iron ultra-triathlons (15.2km swimming, 720km cycling, and 168.8km running), five Quintuple Iron ultra-triathlons (19km swimming, 900km cycling, and 211km running), 11 Deca Iron ultra-triathlons (38km swimming, 1,800km cycling, and 422km running), and two Double Deca Iron ultra-triathlons (76km swimming, 3,600km cycling, and 844km running) were held. In total, 56.7% of the races were in Europe, 37.4% in North America, 5.3% in South America, and less than 1% in Asia. Europeans comprised 80% of the athletes. The number of male participants in Double ( r ² = .56; P < .001) and Triple Iron ultra-triathlon ( r ² = .47; P < .001) and the number of female participants in Double Iron ultra-triathlon ( r ² = .66; P < .001) increased significantly. Less than 8% of the athletes total participated in an ultra-triathlon longer than a Triple Iron ultra-triathlon. Europeans won by far the most competitions in every distance. In conclusion, ultra-triathlon popularity is mainly limited to a) European and North American men and b) Double and Triple Iron ultra-triathlons. Future studies need to investigate the motivation of these ultra-endurance athletes to compete in these extreme races.
Article
Full-text available
Aging is associated with a tissue degeneration phenotype marked by a loss of tissue regenerative capacity. Regenerative capacity is dictated by environmental and genetic factors that govern the balance between damage and repair. The age-associated changes in the ability of tissues to replace lost or damaged cells is partly the cause of many age-related diseases such as Alzheimer's disease, cardiovascular disease, type II diabetes, and sarcopenia. A well-established marker of the aging process is the length of the protective cap at the ends of chromosomes, called telomeres. Telomeres shorten with each cell division and with increasing chronological age and short telomeres have been associated with a range of age-related diseases. Several studies have shown that chronic exposure to exercise (i.e., exercise training) is associated with telomere length maintenance; however, recent evidence points out several controversial issues concerning tissue-specific telomere length responses. The goals of the review are to familiarize the reader with the current telomere dogma, review the literature exploring the interactions of exercise with telomere phenotypes, discuss the mechanistic research relating telomere dynamics to exercise stimuli, and finally propose future directions for work related to telomeres and physiological stress.
Article
Full-text available
Telomeres are potential markers of mitotic cellular age and are associated with physical ageing process. Long-term endurance training and higher aerobic exercise capacity (VO(2max)) are associated with improved survival, and dynamic effects of exercise are evident with ageing. However, the association of telomere length with exercise training and VO(2max) has so far been inconsistent. Our aim was to assess whether muscle telomere length is associated with endurance exercise training and VO(2max) in younger and older people. Twenty men; 10 young (22-27 years) and 10 old (66-77 years), were studied in this cross-sectional study. Five out of 10 young adults and 5 out of 10 older were endurance athletes, while other halves were exercising at a medium level of activity. Mean telomere length was measured as telomere/single copy gene-ratio (T/S-ratio) using quantitative real time polymerase chain reaction. VO(2max) was measured directly running on a treadmill. Older endurance trained athletes had longer telomere length compared with older people with medium activity levels (T/S ratio 1.12±0.1 vs. 0.92±0.2, p = 0.04). Telomere length of young endurance trained athletes was not different than young non-athletes (1.47±0.2 vs. 1.33±0.1, p = 0.12). Overall, there was a positive association between T/S ratio and VO(2max) (r = 0.70, p = 0.001). Among endurance trained athletes, we found a strong correlation between VO(2max) and T/S ratio (r = 0.78, p = 0.02). However, corresponding association among non-athlete participants was relatively weak (r = 0.58, p = 0.09). Our data suggest that VO(2max) is positively associated with telomere length, and we found that long-term endurance exercise training may provide a protective effect on muscle telomere length in older people.
Article
Full-text available
Short telomere length (TL) is an independent predictor of mortality in patients with coronary heart disease (CHD). However, the relationship between physical fitness and TL has not been explored in these patients. In a cross sectional study of 944 outpatients with stable CHD, we performed exercise treadmill testing, assessed self-reported physical activity, and measured leukocyte TL using a quantitative PCR assay. We used generalized linear models to calculate mean TL (T/S ratio), and logistic regression models to compare the proportion of patients with short TL (defined as the lowest quartile), among participants with low, medium and high physical fitness, based on metabolic equivalent tasks achieved (METs). 229 participants had low physical fitness (<5 METS), 334 had moderate physical fitness (5-7 METS), and 381 had high physical fitness (>7 METS). Mean ± T/S ratio ranged from 0.86±0.21 (5349±3781 base pairs) in those with low physical fitness to 0.95±0.23 (5566±3829 base pairs) in those with high physical fitness (p<.001). This association remained strong after adjustment for numerous patient characteristics, including measures of cardiac disease severity and physical inactivity (p = 0.005). Compared with participants with high physical fitness, those with low physical fitness had 2-fold greater odds of having TL in the lowest quartile (OR 2.39, 95% CI 1.60-3.55; p<.001). This association was similar after multivariable adjustment (OR 1.94, 95%CI, 1.18-3.20; p = 0.009). Self-reported physical inactivity was associated with shorter TL in unadjusted analyses, but not after multivariable adjustment. We found that worse objectively-assessed physical fitness is associated with shorter leukocyte telomere length in patients with CHD. The clinical implications of this association deserve further study.
Article
It has long been presumed impossible to measure telomeres in vertebrate DNA by PCR amplification with oligonucleotide primers designed to hybridize to the TTAGGG and CCCTAA repeats, because only primer dimer-derived products are expected. Here we present a primer pair that eliminates this problem, allowing simple and rapid measurement of telomeres in a closed tube, fluorescence-based assay. This assay will facilitate investigations of the biology of telomeres and the roles they play in the molecular pathophysiology of diseases and aging.
Article
The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-DeltaDeltaCr) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-DeltaDeltaCr) method. In addition, we present the derivation and applications of two variations of the 2(-DeltaDeltaCr) method that may be useful in the analysis of real-time, quantitative PCR data. (C) 2001 Elsevier science.
Article
Correlation is a statistical method used to assess a possible linear association between two continuous variables. It is simple both to calculate and to interpret. However, misuse of correlation is so common among researchers that some statisticians have wished that the method had never been devised at all. The aim of this article is to provide a guide to appropriate use of correlation in medical research and to highlight some misuse. Examples of the applications of the correlation coefficient have been provided using data from statistical simulations as well as real data. Rule of thumb for interpreting size of a correlation coefficient has been provided.
Article
Background and aim: Physical exercise up-regulates telomere-stabilizing proteins in mice, suggesting that physical activity affects telomere length. Several human studies assessing the relationship between physical activity, measured by health or activity surveys, and telomere length have produced conflicting results. The present study sought to explore the association between telomere length and physical fitness measured objectively as maximal oxygen uptake in endurance-trained athletes and sedentary controls. Methods: Seventeen marathon runners and 15 age- and sex-matched healthy, sedentary control subjects participated in the study. Medical history, demographic information, maximal oxygen uptake (VO2 max), and peripheral blood lymphocyte telomere length were measured in all subjects. Statistical analysis was performed to examine the relationship between telomere length and measured variables. Results: Athletes and sedentary controls had similar lymphocyte (0.97 ± 0.20 vs 1.01 ± 0.18; P = 0.6) and granulocyte (0.89 ± 0.11 vs 0.89 ± 0.12; P = 0.9) telomere lengths. Linear regression analysis showed age as the only variable significantly associated with telomere length (P = 0.007). There was no correlation between VO2 max and telomere length. Conclusion: In a cohort of healthy adult athletes and sedentary controls, there was no association between physical activity measured by VO2 max and peripheral blood lymphocyte and granulocyte telomere length.
Article
Physical activity has been associated with alterations in telomere length, a potential indicator of biological aging, but several inconsistencies exist. Our aim was to investigate the associations between physical activity in midlife and leukocyte telomere length (LTL) measured in old age in the Helsinki Businessmen Study, Finland. At entry, in 1974, 782 men (mean age 47) completed a questionnaire about their physical activity and this was collapsed into 3 categories: low (n=148), moderate (n=398) and high physical activity (n=236, 7 of whom had a competitive activity level). After 29-year follow-up in 2003, mean LTL and the proportion of short (<5kB) telomeres were measured from DNA samples of a random subcohort of survivors (n=204, mean age 76) using the Southern blot technique. Adjusted for age, body mass index (BMI), cholesterol and smoking in 1974, the moderate physical activity group had longer mean LTL (8.27kB, SE 0.05) than the low (8.10kB, SE 0.07), or high (8.10kB, SE 0.05) physical activity groups (P=0.03 between groups). Conversely, the proportion of short telomeres was lowest in the moderate physical activity group (11.35%, SE 0.25), and higher in the high (12.39%, SE 0.29), and the low physical activity (12.21%, SE 0.39) groups (P=0.02 between groups). We conclude that the results of this observational cohort study give support to the idea that both low and high physical activity is in the long-term associated with factors shortening LTL.