Physical activity and telomere length in early stage breast cancer survivors

  • Sheila N Garland1, 2,

    Affiliated with

    • Brad Johnson3,

      Affiliated with

      • Christina Palmer1, 4,

        Affiliated with

        • Rebecca M Speck5, 6,

          Affiliated with

          • Michelle Donelson6,

            Affiliated with

            • Sharon X Xie6,

              Affiliated with

              • Angela DeMichele2, 6 and

                Affiliated with

                • Jun J Mao1, 2, 6Email author

                  Affiliated with

                  Breast Cancer Research201416:413

                  DOI: 10.1186/s13058-014-0413-y

                  Received: 16 December 2013

                  Accepted: 17 July 2014

                  Published: 31 July 2014

                  Abstract

                  Introduction

                  Telomere length (TL) is a biomarker of accumulated cellular damage and human aging. Evidence in healthy populations suggests that TL is impacted by a host of psychosocial and lifestyle factors, including physical activity. This is the first study to evaluate the relationship between self-reported physical activity and telomere length in early stage breast cancer survivors.

                  Methods

                  A cross-sectional sample of 392 postmenopausal women with stage I-III breast cancer at an outpatient oncology clinic of a large university hospital completed questionnaires and provided a blood sample. TL was determined using terminal restriction fragment length analysis of genomic DNA isolated from peripheral blood mononuclear cells. Physical activity was dichotomized into two groups (none versus moderate to vigorous) using the International Physical Activity Questionnaire. Multivariate linear and logistic regression analyses were performed to identify factors associated with mean TL and physical activity.

                  Results

                  Among participants, 66 (17%) did not participate in any physical activity. In multivariate model adjusted for age, compared to those who participated in moderate to vigorous physical activity, women who participated in no physical activity had significantly shorter TL (adjusted coefficient β = −0.22; 95% confidence interval (CI), −0.41 to −0.03; P = .03). Non-white race, lower education and depressive symptoms were associated with lack of self-reported physical activity (P < 0.05 for all) but not TL.

                  Conclusion

                  Lack of physical activity is associated with shortened TL, warranting prospective investigation of the potential role of physical activity on cellular aging in breast cancer survivors.

                  Introduction

                  Improvements in the diagnosis and treatment of breast cancer have created a cohort of breast cancer survivors now surpassing three million women [1]. Physical activity can help improve the long-term psychological and physical health of breast cancer survivors, and potentially reduce the risk of disease recurrence and mortality [24], but questions remain regarding the influence of physical activity on measures of health at a cellular level. Telomere length (TL) is increasingly being examined as a biomarker of accumulated cellular damage and human aging [5]. Telomeres are repetitive nucleoprotein structures on the end of chromosomes with the main purposes of maintaining genomic stability and protecting against unbridled cellular division. As the cell divides with time, TL progressively shortens until critically short telomeres eventually lead to cell death or senescence. The examination of TL holds promise for identifying behavioral and environmental factors that can promote health and recovery in the context of cancer.

                  Previous research has demonstrated that TL can be impacted by a host of lifestyle and psychosocial factors [6]. Specifically, emerging evidence suggest that physical activity and regular exercise may positively impact TL in healthy individuals [7]. A cross-sectional study of 44 postmenopausal women compared the TL of habitual exercisers to women with a sedentary lifestyle [8]. Habitual exercisers had significantly longer TL than sedentary women and, even after adjusting for covariates, habitual exercise accounted for 75% of the variance in TL. The impact of physical activity on TL has also been examined in terms of exercise energy expenditure. In a study of 69 men and women between the ages of 50 and 70 years, individuals reporting moderate levels of physical activity had longer TL than participants at the lower and higher ends of the energy expenditure spectrum [9]. Despite the emerging evidence that physical activity may have a positive impact on TL and the growing interest in survivorship programs that encourage breast cancer survivors to be more active, no study has evaluated the association between physical activity and cellular aging in breast cancer survivors.

                  This study aims to evaluate the association between self-reported physical activity and TL in a large cross-sectional sample of postmenopausal breast cancer survivors. This examination is important as clinical outcomes in the context of breast cancer survivorship (for example, recurrence, cancer-specific mortality and overall mortality) are likely dependent on a complex interplay between cancer and host biology [2]. Identifying a biomarker that can be modified by behavioral approaches such as physical activities will further allow us to examine the specific mechanisms of physical activities underlying the potential positive effect on clinical outcomes. We hypothesized that those who were not participating in physical activity would have shorter telomeres than those who engaged in moderate to rigorous physical activity. As a secondary aim, we also sought to identify factors related to lack of physical activity in this population.

                  Methods

                  Sample and setting

                  We conducted a cross-sectional study of women with early-stage breast cancer between March 2008 and July 2009 at the Rowan Breast Cancer Center of the Abramson Cancer Center of the University of Pennsylvania (Philadelphia, PA, USA). The institutional review board of the University of Pennsylvania and the regulatory committee of the Abramson Cancer Center approved the study and all participants provided informed consent. Research assistants screened medical records and approached potential patients for enrollment at their regular follow-up appointments. After informed consent was obtained, each participant completed a self-administered survey and a blood sample was collected for telomere analysis. Patients were eligible for study inclusion if they were: 18 years or older; had a history of stage I, II, or III breast cancer; postmenopausal; currently or previously on aromatase inhibitors, and able to understand written English. The sample size in the original cross-sectional survey was 476, reflecting a 78% response rate among those eligible. Complete physical activity and telomere data were available for 392 of those patients. There were no differences between our sample and the original sample in terms of age, race, or education.

                  Measures

                  Primary outcome

                  Telomere length was determined using mean terminal restriction fragment (TRF) lengths as described by Lorenzini et al. [10] with minor modifications. Five hundred nanograms of purified DNA isolated from peripheral blood mononuclear cells (PBMCs) were digested to completion with HinfI and RsaI. Digested samples and size markers (32P-end-labeled 1 Kb Plus DNA ladder and HindIII-cut lambda DNA) were separated in a 0.5% agarose gel. Within the gel, DNA was denatured under alkaline conditions, neutralized, and then hybridized with a 32P-end-labeled oligonucleotide (CCCTAA)4 probe overnight at 55°C. Blots were washed to remove non-specifically bound probe, and visualized using a PhosPhorImager (Molecular Dynamics Sunnyvale, CA). Mean TRF length was calculated as:
                  $$ \varSigma \left(\mathrm{O}{\mathrm{D}}_{\mathrm{i}}\right)/\ \varSigma \left(\mathrm{O}{\mathrm{D}}_{\mathrm{i}}/{\mathrm{L}}_{\mathrm{i}}\right), $$

                  where ODi is the total radioactivity above background in interval i and Li is the average length of i in base pairs (bp). The genomic DNA was verified to be of high molecular weight by electrophoresing the undigested DNA samples on 0.5% agarose gels that were subsequently stained with ethidium bromide to show that >99% of the DNA ran at limit-mobility.

                  Primary exposure

                  Physical activity was measured using the international physical activity questionnaire (IPAQ) [11]. The IPAQ is a self-administered 4-item questionnaire assessing the frequency and duration of moderate and vigorous intensity physical activity in the past seven days. Examples of moderate physical activity include brisk walking, bicycling, vacuuming, gardening, or anything else that causes some increase in breathing or heart rate. Vigorous physical activity includes running, aerobics, heavy yard work, or anything else that causes large increases in breathing or heart rate. The IPAQ has acceptable test-retest reliability and concurrent validity. Criterion validity has been adequately demonstrated when measured against accelerometry [11]. Similar to the methods reported in Puterman et al. [12] and Kim et al. [8], and considering the evidence for recall bias in physical activity measurement [13], we dichotomized physical activity into two groups based on habitual exercise levels (none versus moderate to vigorous).

                  Covariates

                  Patient-reported social demographic variables included age, body mass index (BMI), race/ethnicity, education level, and marital status. Clinical factors such as stage, chemotherapy treatment, current aromatase inhibitor use and comorbidities were obtained via chart abstraction. The hospital anxiety and depression scale (HADS) was used to measure depression and anxiety symptoms. The HADS is a 14-item, self-rated instrument for anxiety (7 items) and depression (7 items) in the past week, and was developed for patients with chronic illnesses. Established cutoffs are: 0 to 7, no significant depression/anxiety; 8 to 10, subclinical depression/anxiety; 11 to 21, clinically significant levels of depression/anxiety. The HADS has been extensively used and validated and has demonstrated adequate sensitivity and specificity to detect cases of depression and anxiety in cancer patients [14,15].

                  Analysis

                  Descriptive statistics were performed for demographic characteristics, clinical variables and patient-reported psychological health. Telomere length was compared between physical activity groups using the independent samples t-test. Univariate linear regression analysis was performed to identify variables associated with TL. A series of univariate logistic regression was used to identify independent predictors of not engaging in physical activity. Covariates with P-values <0.10 in univariate analysis was carried forward to the respective multivariate model. Statistical tests were two-sided with P <0.05 indicating significance. All data were analyzed using STATA 12.0 (StataCorp, College Station, TX, USA). Given that our sample size was fixed at 392 and approximately 1/5 of our sample was inactive, we were powered to detect a statistically significant difference of 0.356 of the standard deviation between the inactive and active groups with a two-sided significance of 0.05, and 80% power.

                  Results

                  Participant characteristics

                  Table 1 shows the sociodemographic and disease characteristics for the 392 patients included in this study. The mean age of the women was 62 years (range = 33 to 91). The majority of the women were white (82%). Of the participants in the non-white category (n = 70), the majority of the women were Black/African (14%) followed by Asian (2%), Hispanic/Latino (1%) and other (1%). These categories were collapsed in subsequent analyses. Most of the women were married or partnered (62%) and had either a college (43%) or graduate education (36%). The mean BMI for the sample was in the overweight category at 27.21 (range = 18.53 to 63.47) with 27% in the obese range (BMI >30.00). The most common stages of breast cancer at diagnosis were stage I (39%) and II (49%) and 61% of the women had been treated with chemotherapy. The majority of the women were also taking an aromatase inhibitor, the most common of which was anastrozole (61%). There were fewer respondents in the subclinical and clinical ranges of depression and anxiety; thus, the psychological variables were collapsed into normal and symptomatic categories to maximize statistical power. Roughly 1/4 of women (26%) reported problematic levels of anxiety while 9% of women endorsed significant levels of depressive symptoms. Mean TL in the whole sample was 6.07 kb, (range = 3.28 to 8.19).
                  Table 1

                  Characteristics of participants

                    

                  Number

                  %

                    

                  392

                  100

                  Demographic characteristics

                  Age, years (mean, 61.97; SD, 10.36)

                    

                    <55

                  91

                  23.2

                   

                    55 to 65

                  170

                  43.4

                   

                    >65

                  131

                  33.4

                   

                  BMI (mean, 27.21; SD, 5.85)

                    
                   

                    <25

                  163

                  41.6

                   

                    25 to 30

                  123

                  31.4

                   

                    >30

                  106

                  27.0

                   

                  Smoking status

                    
                   

                    Never

                  207

                  52.9

                   

                    Current

                  13

                  3.3

                   

                    Previous

                  171

                  43.7

                   

                  Race/ethnicity

                    
                   

                    White

                  322

                  82.1

                   

                    Non-white*

                  70

                  17.9

                   

                  Educational level

                    
                   

                    High school or less

                  85

                  21.7

                   

                    College

                  167

                  42.6

                   

                    Graduate or higher

                  139

                  35.5

                   

                  Marital status

                    
                   

                    Married/partnered

                  244

                  62.2

                   

                    Single

                  136

                  34.7

                   

                  Physical activity

                    
                   

                    None

                  66

                  16.8

                   

                    Moderate to vigorous

                  326

                  83.2

                  Clinical characteristics

                  Stage

                    

                    0 and I

                  154

                  39.3

                   

                    II

                  192

                  49.0

                   

                    III

                  46

                  11.7

                   

                  Previous chemotherapy

                    
                   

                    No chemotherapy

                  153

                  39.0

                   

                    Chemotherapy

                  239

                  61.0

                   

                  Current aromatase inhibitors

                    
                   

                    None

                  41

                  10.5

                   

                    Letrozole

                  67

                  17.1

                   

                    Anastrozole

                  240

                  61.2

                   

                    Exemestane

                  44

                  11.2

                   

                  Cormorbid conditions

                    
                   

                    None

                  62

                  15.8

                   

                    One

                  118

                  30.1

                   

                    Two or more

                  212

                  54.1

                  Symptom profile

                  HADS anxiety

                    

                    Normal

                  282

                  71.9

                   

                    Symptomatic

                  101

                  25.8

                   

                  HADS depression

                    
                   

                    Normal

                  344

                  87.8

                   

                    Symptomatic

                  34

                  8.7

                  *Mostly Black; hospital anxiety and depression scale (HADS) categorization: Normal = 0 to 7; symptomatic = 8 to 21. BMI, body mass index.

                  Physical inactivity and telomere length

                  Among participants, 17% of women did not engage in physical activity. These participants had shorter TL compared to those who participated in moderate/vigorous physical activities (mean 5.84 kb versus 6.11 kb; t (390) = −2.757; P = 0.006, see Figure 1). Univariate and multivariate linear regression analyses examining the association between demographic, clinical and psychological variables and TL are presented in Table 2. In unadjusted analyses, compared to women who reported moderate to vigorous physical activity, women who did not report engaging in any physical activity had significantly shorter TL (β = −0.27; 95% CI, −0.08 to −0.46; P = 0.006). As expected TL progressively shortened with age, with significant differences observed when women older than 65 were compared to women below 55 years of age (β = −0.33; 95% CI, −0.52 to −0.13; P = .001). Having had chemotherapy treatment was significantly associated with longer TL (β = 0.19; 95% CI, 0.04 to 0.34; P = 0.01). In the multivariate regression model, lack of physical activity remained significantly associated with shorter TL (adjusted coefficient (Adj β) = −0.22; 95% CI, −0.41 to −0.03; P = 0.03), as did older age (<65) (Adj β = −0.26; 95% CI, −0.47 to 0.04; P = .02). Being treated with chemotherapy was no longer significant in the multivariate model.
                  http://static-content.springer.com/image/art%3A10.1186%2Fs13058-014-0413-y/MediaObjects/13058_2014_413_Fig1_HTML.gif
                  Figure 1

                  Unadjusted mean telomere length (TL, presented in kilobase pairs) in breast cancer survivors according to physical activity. No physical activity mean TL=5.84 (SD= 0.63); Moderate/vigorous physical activity mean TL=6.11 (SD=0.75); p = 0.006.

                  Table 2

                  Linear regression of factors associated with telomere length

                   

                  Univariate analysis

                  Multivariate analysis

                  Coefficient (95% CI)

                  P

                  Adjusted coefficient (95% CI)

                  P

                  Physical activity

                      

                    Moderate to vigorous (reference)

                  1

                   

                  1

                   

                    None

                  −0.27 (−0.08, −0.46)

                  0.006

                  −0.22 (−0.41, −0.03)

                  0.03

                  Age, years

                      

                    <55 (reference)

                  1

                   

                  1

                   

                    55 to 65

                  −0.12 (−0.30, 0.07)

                  0.22

                  −0.09 (−0.28, 0.10)

                  0.33

                    >65

                  −0.33 (−0.52, −0.13)

                  0.001

                  −0.26 (−0.47, 0.04)

                  0.02

                  Body mass index

                      

                    <25

                  a1

                     

                    25 to 30

                  −0.01 (−0.19, 0.16)

                  0.88

                    

                    >30

                  −0.13 (−0.031, 0.05)

                  0.16

                    

                  Smoking status

                      

                    Never (reference)

                  1

                     

                    Current

                  −0.11 (−0.52, 0.30)

                  0.60

                    

                    Previous

                  −0.09 (−0.24, 0.06)

                  0.22

                    

                  Race/ethnicity

                      

                    White

                  a1

                     

                    Non-white*

                  −0.03 (−0.22, 0.16)

                  0.74

                    

                  Educational level

                      

                    High school or less

                  a1

                     

                    College

                  0.07 (−0.12, 0.26)

                  0.48

                    

                    Graduate or higher

                  0.16 (−0.04, 0.36)

                  0.11

                    

                  Marital status

                      

                    Married/partnered

                  a1

                     

                    Single

                  −0.02 (−0.18, 0.13)

                  0.76

                    

                  Stage

                      

                    0 and I (reference)

                  1

                     

                    II

                  0.04 (−0.11, 0.20)

                  0.58

                    

                    III

                  0.06 (−0.18, 0.31)

                  0.60

                    

                  Previous chemotherapy

                      

                    No chemotherapy (reference)

                  1

                   

                  1

                   

                    Chemotherapy

                  0.19 (0.04, 0.34)

                  0.01

                  0.07 (−0.09, 0.24)

                  0.38

                  Current aromatase inhibitor

                      

                    None (reference)

                      

                    Letrozole

                  0.09 (−0.19, 0.38)

                  0.53

                    

                    Anastrozole

                  −0.01 (−0.26, 0.23)

                  0.93

                    

                    Exemestane

                  0.03 (−0.28, 0.34)

                  0.84

                    

                  Cormorbid conditions

                      

                    None (reference)

                  1

                     

                    One

                  −0.02 (−0.25, 0.21)

                  0.86

                    

                    Two or more

                  −0.11 (−0.32, 0.10)

                  0.29

                    

                  Anxiety

                      

                    Normal (reference)

                  1

                     

                    Symptomatic

                  −0.01 (−0.18, 0.16)

                  0.93

                    

                  Depression

                      

                    Normal (reference)

                  1

                     

                    Symptomatic

                  0.05 (−0.21, 0.31)

                  0.70

                    

                  *Mostly Black; hospital anxiety and depression scale (HADS) anxiety and depression categorization: normal = 0 to 7; symptomatic = 8 to 21. Covariates with P-values <0.10 in the univariate analyses were carried forward to the respective multivariate models. P-values in boldface type are statistically significant.

                  Factors associated with physical inactivity

                  A logistic regression model was developed to identify factors related to lack of physical activity in this population (Table 3). The strongest predictors of not being physically active in the multivariate model were lower education, depressive symptoms, and self-identifying as a race other than white. Women with a college education were less likely to be physically inactive compared with women with an education level of high school or less (adjusted odds ratio (AOR) = 0.34; 95% CI, 0.16 to 0.70; P = 0.003). This association was stronger for women with a graduate education or greater (AOR = 0.20; 95% CI, 0.08 to 0.47; P <0.001). Depressed participants were significantly more likely to report being physically inactive (AOR = 4.57; 95% CI, 1.86 to −11.25; P <0.0001), compared to those women without clinically significant depressive symptoms. Women who self-identified as non-white were more likely to be physically inactive than white women (AOR =2.29; 95% CI, 1.07 to 4.90; P = 0.03).
                  Table 3

                  Logistic regression of factors associated with lack of physical activity

                   

                  Univariate analysis

                  Multivariate analysis

                  OR (95% CI)

                  P

                  AOR (95% CI)

                  P

                  Demographic characteristics

                      

                  Age, years

                      

                    <55 (reference)

                  1

                   

                  1

                   

                    55 to 65

                  1.33 (0.61, 2.92)

                  0.48

                  0.96 (0.38, 2.41)

                  0.91

                    >65

                  2.62 (1.21, 5.65)

                  0.01

                  1.44 (0.52, 4.00)

                  0.48

                  BMI

                      

                    <25 (reference)

                  1

                   

                  1

                   

                    25 to 30

                  1.47 (0.74, 2.94)

                  0.27

                  1.32 (0.59, 2.91)

                  0.50

                    >30

                  3.03 (1.58, 5.81)

                  <0.001

                  1.93 (0.88, 4.23)

                  0.10

                  Race/ethnicity

                      

                    White (reference)

                  1

                   

                  1

                   

                    Non-white*

                  3.81 (2.11, 6.86)

                  <0.001

                  2.29 (1.07, 4.90)

                  0.03

                  Educational level

                      

                    High school or less (reference)

                  1

                   

                  1

                   

                    College

                  0.43 (0.23, 0.80)

                  0.007

                  0.34 (0.16, 0.70)

                  0.003

                    Graduate or higher

                  0.18 (0.09, 0.40)

                  <0.001

                  0.20 (0.08, 0.47)

                  <0.001

                  Marital status

                      

                    Married/partnered (reference)

                  1

                   

                  1

                   

                    Single

                  2.57 (1.50, 4.40)

                  <0.001

                  1.52 (0.77, 3.00)

                  0.25

                  Previous chemotherapy

                      

                    No chemotherapy (reference)

                  1

                   

                  1

                   

                    Chemotherapy

                  0.50 (0.29, 0.86)

                  0.01

                  0.81 (0.40, 1.63)

                  0.55

                  Current aromatase inhibitor

                      

                    None (reference)

                  1

                     

                    Letrozole

                  0.98 (0.30, 3.21)

                  0.97

                    

                    Anastrozole

                  1.75 (0.65, 4.71)

                  0.27

                    

                    Exemestane

                  1.14 (0.32, 4.05)

                  0.84

                    

                  Cormorbid conditions

                      

                    None (reference)

                  1

                   

                  1

                   

                    One

                  1.14 (0.44, 2.97)

                  0.78

                  1.11 (0.34, 3.49)

                  0.88

                    Two or more

                  2.06 (0.88, 4.83)

                  0.10

                  1.71 (0.57, 5.05)

                  0.34

                  Anxiety

                      

                    Normal (reference)

                  1

                     

                    Sympomatic

                  0.92 (0.49, 1.70)

                  0.79

                    

                  Depression

                      

                    Normal (reference)

                  1

                   

                  1

                   

                    Symptomatic

                  3.28 (1.53, 7.06)

                  0.002

                  4.57 (1.86, 11.25)

                  <0.001

                  *Mostly Black; hospital anxiety and depression scale (HADS) anxiety and depression categorization: normal = 0 to 7; symptomatic = 8 to 21. Covariates with P-values <0.10 in the univariate analyses were carried forward to the respective multivariate models. P-values in boldface type are statistically significant.

                  Discussion

                  In this study, we found an association between lack of physical activity and shorter TL in a large cross-sectional sample of breast cancer survivors. Adjusting for the impact of age, women reporting no physical activity had significantly shorter TL than women who reported engaging in moderate to vigorous activity. The mean difference between women who were and were not physically active was 270 bp. Research by Slagboom et al. demonstrated that the average decrease in TL was 31 bp per year [16]. This suggests that, independent of age, more sedentary women may be close to 9 years biologically older than women who are more physically active, on a cellular level. To our knowledge, this is the first study to quantify the relationship between physical activity and TL in breast cancer survivors.

                  Telomere length measured from PBMCs reflects the cumulative effects of psychosocial, environmental and behavioral factors, as opposed to current health status, and is predictive of morbidity and mortality [17]. The presence of short TL in peripheral blood cells has been linked to age-related disease and preclinical conditions of diseases including increased mortality from cancer [18]. A recent longitudinal cohort study of 478 women with stage I to IIIa breast cancer examined PBMC TL change from 6 to 30 months post diagnosis [19]. Telomere shortening was associated with increased risk of all cause and breast cancer specific mortality, suggesting that change in blood TL over time could be a biomarker of prognosis. This finding is consistent with an earlier prospective 20-year study of 47,102 individuals suggesting that shorter TL is associated with reduced survival after all cancer diagnoses, including breast [20]. Based on existing research linking TL measured in PBMC and increased mortality from cancer, TL may represent an innovative biomarker to measure the status of host biology of aging; and as the host ages, its ability to perform immune surveillance may decrease, and thereby increase the probability of recurrence of metastasis.

                  Our finding of an association between physical activity and TL may provide an important opportunity to elucidate the mechanism of physical activity on health outcomes in cancer survivors. A recent systematic review of 17 studies examining the impact of physical activity on survival provides support for the role of physical activity in reducing all cause, and cancer specific, mortality in women with breast cancer [21]. This conclusion is echoed by a more generalizable systematic review of 45 studies in heterogeneous cancer populations, of which 13 were randomized and controlled trials [4]. It is possible that physical activity may buffer against the cellular aging process thereby protecting individuals from aging-related diseases; however, the role of physical activity in this relationship remains to be demonstrated. While we know that physical activity reduces breast cancer risk, morbidity and mortality, prospective research is needed to determine whether physical activity may be an effective intervention to slow the rate of further telomere shortening or promote telomere recovery after cancer treatment.

                  Although the precise mechanisms are still unknown, physical activity is likely to influence telomere dynamics via the cumulative reduction in oxidative stress [22], DNA damage [23], and inflammation [24,25]. Initial research also suggests that a reduction in perceived stress may influence the association between exercise and TL [26,27]. Puterman et al. categorized 63 healthy postmenopausal women into two categories based on whether or not they met the daily recommended amount of physical activity [12]. In women who were more active, there was no association between perceived stress and TL whereas in sedentary women, a one-unit increase in perceived stress was related to a 15-fold increase in the odds of having shorter telomeres. Preliminary research has also suggested that a stress reduction intervention may positively impact telomere length in a sample of cervical cancer survivors [28]. Although these results require replication, the modification of stress appraisals via physical activity may be a mechanism to improve health at a cellular level.

                  While our results support the potential benefit of physical activity on cellular aging for early stage breast cancer survivors, we also identified specific characteristics that if present reduce the likelihood of engaging in physical activity. Consistent with previous research, lower education was associated with not being physically active [2931]. In addition, race and depressive symptomotology were identified as significant risk factors for not engaging in physical activity. Targeted interventions to engage these sub-groups of breast cancer survivors, promote healthy lifestyles, and diminish risk of premature age-related disease and decline are a necessary next step.

                  Several limitations need to be considered. Firstly, a cross-sectional design seeks to identify an association rather than infer causation. Future prospective research needs to define the causal relationship between physical activity and TL. Secondly, the physical activity information was obtained via self-report, which has been shown to consistently lead to overestimation of physical activity and thus to underestimation of the effects of physical activity [32,33]. As such, the true effect of physical activity is probably even stronger than estimated. Lastly, our population was postmenopausal early-stage breast cancer, which may limit its generalizability to premenopausal women or those with more advanced cancer.

                  Conclusion

                  In summary, we found that TL was shorter in women with breast cancer who reported a sedentary lifestyle compared to those women who engaged in regular moderate to vigorous exercise, an effect that could not be explained by age. Future research needs to further define the causal relationship and uncover the mechanism of physical activity for enhancing cellular aging among breast cancer survivors.

                  Abbreviations

                  Adj β: 

                  adjusted coefficient beta

                  AOR: 

                  adjusted odds ratio

                  bp: 

                  base pairs

                  BMI: 

                  body mass index

                  HADS: 

                  hospital anxiety and depression scale

                  IPAQ: 

                  international physical activity questionnaire

                  kb: 

                  Kilobase pairs

                  PBMC: 

                  peripheral blood mononuclear cells

                  TL: 

                  telomere length

                  TRF: 

                  terminal restriction fragment

                  Declarations

                  Acknowledgements

                  This study was supported by a Penn Institute of Aging Pilot Grant. Sheila N Garland is a postdoctoral fellow funded by a Canadian Institutes for Health Research (CIHR) Bisby Fellowship. Jun J Mao is funded in part by grants from the National Center for Complementary and Alternative Medicine (K23 AT004112) and the National Cancer Institute (R01 CA158243). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

                  Authors’ Affiliations

                  (1)
                  Department of Family Medicine and Community Health, Perelman School of Medicine at the University of Pennsylvania
                  (2)
                  Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania
                  (3)
                  Department of Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania
                  (4)
                  Department of Family and Community Medicine, University of California San Francisco
                  (5)
                  Department of Anesthesiology and Critical Care, Perelman School of Medicine at the University of Pennsylvania
                  (6)
                  Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine at the University of Pennsylvania

                  References

                  1. Siegel R, Naishadham D, Jemal A: Cancer statistics, 2012. CA Cancer J Clin 2012, 62:10–29.View ArticlePubMed
                  2. Goh J, Kirk EA, Lee SX, Ladiges WC: Exercise, physical activity and breast cancer: the role of tumor-associated macrophages. Exerc Immunol Rev 2012, 18:158–176.PubMed
                  3. Schmidt ME, Chang-Claude J, Vrieling A, Seibold P, Heinz J, Obi N, Flesch-Janys D, Steindorf K: Association of pre-diagnosis physical activity with recurrence and mortality among women with breast cancer. Int J Cancer 2013, 133:1431–1440.View ArticlePubMed
                  4. Ballard-Barbash R, Friedenreich CM, Courneya KS, Siddiqi SM, McTiernan A, Alfano CM: Physical activity, biomarkers, and disease outcomes in cancer survivors: a systematic review. J Natl Cancer Inst 2012, 104:815–840.PubMed CentralView ArticlePubMed
                  5. Andrews NP, Fujii H, Goronzy JJ, Weyand CM: Telomeres and immunological diseases of aging. Gerontology 2010, 56:390–403.PubMed CentralView ArticlePubMed
                  6. Lin J, Epel E, Blackburn E: Telomeres and lifestyle factors: roles in cellular aging. Mutat Res 2012, 730:85–89.View ArticlePubMed
                  7. Du M, Prescott J, Kraft P, Han J, Giovannucci E, Hankinson SE, De Vivo I: Physical activity, sedentary behavior, and leukocyte telomere length in women. Am J Epidemiol 2012, 175:414–422.PubMed CentralView ArticlePubMed
                  8. Kim JH, Ko JH, Lee DC, Lim I, Bang H: Habitual physical exercise has beneficial effects on telomere length in postmenopausal women. Menopause 2012, 19:1109–1115.View ArticlePubMed
                  9. Ludlow AT, Zimmerman JB, Witkowski S, Hearn JW, Hatfield BD, Roth SM: Relationship between physical activity level, telomere length, and telomerase activity. Med Sci Sports Exerc 2008, 40:1764–1771.PubMed CentralView ArticlePubMed
                  10. Lorenzini A, Johnson FB, Oliver A, Tresini M, Smith JS, Hdeib M, Sell C, Cristofalo VJ, Stamato TD: Significant correlation of species longevity with DNA double strand break recognition but not with telomere length. Mech Ageing Dev 2009, 130:784–792.PubMed CentralView ArticlePubMed
                  11. Craig CL, Marshall AL, Sjostrom M, Bauman AE, Booth ML, Ainsworth BE, Pratt M, Ekelund U, Yngve A, Sallis JF, Oja P: International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc 2003, 35:1381–1395.View ArticlePubMed
                  12. Puterman E, Lin J, Blackburn E, O’Donovan A, Adler N, Epel E: The power of exercise: buffering the effect of chronic stress on telomere length. PLoS One 2010, 5:e10837.PubMed CentralView ArticlePubMed
                  13. Johnson-Kozlow M, Sallis JF, Gilpin EA, Rock CL, Pierce JP: Comparative validation of the IPAQ and the 7-Day PAR among women diagnosed with breast cancer. Int J Behav Nutr Phys Act 2006, 3:7.PubMed CentralView ArticlePubMed
                  14. Bjelland I, Dahl AA, Haug TT, Neckelmann D: The validity of the Hospital Anxiety and Depression Scale: an updated literature review. J Psychosom Res 2002, 52:69–77.View ArticlePubMed
                  15. Mitchell AJ, Meader N, Symonds P: Diagnostic validity of the Hospital Anxiety and Depression Scale (HADS) in cancer and palliative settings: a meta-analysis. J Affect Disord 2010, 126:335–348.View ArticlePubMed
                  16. Slagboom PE, Droog S, Boomsma DI: Genetic determination of telomere size in humans: a twin study of three age groups. Am J Hum Genet 1994, 55:876–882.PubMed CentralPubMed
                  17. Lin J, Epel ES, Blackburn EH: Telomeres, Telomerase, Stress, and Aging. In Handbook of Neuroscience for the Behavioral Sciences, Volume 3. Edited by Berntson GG, Cacioppo JT. New Jersey: John Wiley & Sons, Inc; 2009:1280–1295.
                  18. Bojesen SE: Telomeres and human health. J Intern Med 2013, 274:399–413.View ArticlePubMed
                  19. Duggan C, Risques R, Alfano C, Prunkard D, Imayama I, Holte S, Baumgartner K, Baumgartner R, Bernstein L, Ballard-Barbash R, Rabinovitch P, McTiernan A: Change in peripheral blood leukocyte telomere length and mortality in breast cancer survivors. J Natl Cancer Inst 2014, 106:dju035.PubMed CentralView ArticlePubMed
                  20. Weischer M, Nordestgaard BG, Cawthon RM, Freiberg JJ, Tybjaerg-Hansen A, Bojesen SE: Short telomere length, cancer survival, and cancer risk in 47102 individuals. J Natl Cancer Inst 2013, 105:459–468.View ArticlePubMed
                  21. Fontein DB, de Glas NA, Duijm M, Bastiaannet E, Portielje JE, Van de Velde CJ, Liefers GJ: Age and the effect of physical activity on breast cancer survival: a systematic review. Cancer Treat Rev 2013, 39:958–965.View ArticlePubMed
                  22. Sanders JL, Newman AB: Telomere length in epidemiology: a biomarker of aging, age-related disease, both, or neither? Epidemiol Rev 2013. in press.
                  23. Song Z, von Figura G, Liu Y, Kraus JM, Torrice C, Dillon P, Rudolph-Watabe M, Ju Z, Kestler HA, Sanoff H, Lenhard Rudolph K: Lifestyle impacts on the aging-associated expression of biomarkers of DNA damage and telomere dysfunction in human blood. Aging Cell 2010, 9:607–615.PubMed CentralView ArticlePubMed
                  24. O’Donovan A, Pantell MS, Puterman E, Dhabhar FS, Blackburn EH, Yaffe K, Cawthon RM, Opresko PL, Hsueh WC, Satterfield S, Newman AB, Ayonayon HN, Rubin SM, Harris TB, Epel ES, Health Aging and Body Composition Study: Cumulative inflammatory load is associated with short leukocyte telomere length in the health, aging and body composition study. PLoS One 2011, 6:e19687.PubMed CentralView ArticlePubMed
                  25. Woods JA, Vieira VJ, Keylock KT: Exercise, inflammation, and innate immunity. Immunol Allergy Clin North Am 2009, 29:381–393.View ArticlePubMed
                  26. Tomiyama AJ, O’Donovan A, Lin J, Puterman E, Lazaro A, Chan J, Dhabhar FS, Wolkowitz O, Kirschbaum C, Blackburn E, Epel E: Does cellular aging relate to patterns of allostasis? An examination of basal and stress reactive HPA axis activity and telomere length. Physiol Behav 2012, 106:40–45.PubMed CentralView ArticlePubMed
                  27. O’Donovan A, Tomiyama AJ, Lin J, Puterman E, Adler NE, Kemeny M, Wolkowitz OM, Blackburn EH, Epel ES: Stress appraisals and cellular aging: a key role for anticipatory threat in the relationship between psychological stress and telomere length. Brain Behav Immun 2012, 26:573–579.PubMed CentralView ArticlePubMed
                  28. Biegler KA, Anderson AK, Wenzel LB, Osann K, Nelson EL: Longitudinal change in telomere length and the chronic stress response in a randomized pilot biobehavioral clinical study: implications for cancer prevention. Cancer Prev Res (Phila) 2012, 5:1173–1182.View Article
                  29. McNeill LH, Wyrwich KW, Brownson RC, Clark EM, Kreuter MW: Individual, social environmental, and physical environmental influences on physical activity among black and white adults: a structural equation analysis. Ann Behav Med 2006, 31:36–44.View ArticlePubMed
                  30. Pan SY, Cameron C, Desmeules M, Morrison H, Craig CL, Jiang X: Individual, social, environmental, and physical environmental correlates with physical activity among Canadians: a cross-sectional study. BMC Public Health 2009, 9:21–24.PubMed CentralView ArticlePubMed
                  31. Vidrine JI, Stewart DW, Stuyck SC, Ward JA, Brown AK, Smith C, Wetter DW: Lifestyle and cancer prevention in women: knowledge, perceptions, and compliance with recommended guidelines. J Womens Health (Larchmt) 2013, 22:487–493.View Article
                  32. Banda JA, Hutto B, Feeney A, Pfeiffer KA, McIver K, Lamonte MJ, Blair SN, Vena J, Hooker SP: Comparing physical activity measures in a diverse group of midlife and older adults. Med Sci Sports Exerc 2010, 42:2251–2257.View ArticlePubMed
                  33. Troiano RP, Berrigan D, Dodd KW, Masse LC, Tilert T, McDowell M: Physical activity in the United States measured by accelerometer. Med Sci Sports Exerc 2008, 40:181–188.View ArticlePubMed

                  Copyright

                  © Garland et al.; licensee BioMed Central 2014

                  This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://​creativecommons.​org/​licenses/​by/​4.​0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://​creativecommons.​org/​publicdomain/​zero/​1.​0/​) applies to the data made available in this article, unless otherwise stated.

                  Advertisement