Background: Telomeres are specialized chromatin structures essential for maintenance of chromosomal integrity and stability. Abnormal alteration of telomere length has been linked to several cancers; however, epidemiologic evidence about the association of telomere length with colorectal cancer risk has been conflicting.

Methods: We conducted a nested case–control study to evaluate the association between telomere length and colorectal cancer risk using peripheral blood samples collected before cancer diagnosis. The study included 441 women with incident colorectal cancer and 549 matched controls. Monochrome multiplex quantitative PCR was applied to measure relative telomere length. Multiple logistic regressions were used to derive adjusted OR with 95% confidence intervals (CI) as the measure of association between telomere length and subsequent colorectal cancer risk.

Results: A U-shaped association was observed between telomere length and colorectal cancer risk (test for nonlinearity P = 0.0112). Women with telomere length in the third quintile (40th–60th percentiles) had the lowest risk of colorectal cancer, and the risks were elevated with a shorter or longer telomere length. This U-shaped association did not statistically differ for colon cancer and rectum cancer.

Conclusions and Impact: Our prospective study revealed a U-shaped association between telomere length in peripheral blood cells and colorectal cancer risk. Our findings provide strong evidence that both very short and very long telomeres are associated with increased risk of colorectal cancer. Cancer Epidemiol Biomarkers Prev; 21(10); 1807–13. ©2012 AACR.

Telomeres are specialized dynamic chromatin structures at the termini of eukaryotic chromosomes, composed of highly conserved tandem hexameric nucleotide repeats (TTAGGG)n (1). Telomeres cap the ends of chromosomes and are essential for preserving chromosomal integrity and stability by preventing fatal incidents such as chromosome ends fusion, nucleolytic degradation, and aberrant recombination (2). Telomere length is maintained by the expression of telomerase, a ribonucleoprotein complex consisting of a reverse transcriptase catalytic subunit and an RNA component (TERC), which adds (TTAGGG) repeats onto the telomeric ends of the chromosome (3, 4). In normal somatic cells, telomerase is not expressed or presents at very low levels of activity. Thus, telomeres undergo progressive shortening with each mitotic cell division because of the inability of DNA polymerase to completely synthesize the daughter strand at chromosomal ends (2, 5). The rate of telomere shortening is also modified by factors other than the mitotic replication rate, such as oxidative stress and chronic inflammation (6). When telomeres shorten to a critical length, they become dysfunctional, and Rb and p53 signal pathways are triggered to initiate either cell senescence or apoptosis (5, 7). On rare occasions, cells that aberrantly bypass replicative senescence with critically short telomeres may develop genomic instability and potentially become tumorigenic (5). In cancer cells, however, telomerase is highly expressed, and reactivation of telomerase helps compensate telomere erosion, allowing cancer cells to escape the normal limits of cellular proliferation, or preventing them from undergoing senescence/apoptosis (4, 8–10). Thus, telomere length reflects the result of the balance between processes that shorten telomeres or lengthen telomeres (11).

In humans, the best example of short telomere phenotype is dyskeratosis congenita. Patients with this disease carry mutations in the components of telomerase complex, which results in short telomeres leading to bone-marrow failure and elevated risk of cancer (12). Mouse models also support the notion that telomerase deficiency and short telomere length increase the risk of tumor (4, 13). Studies using histopathological samples obtained from patients with solid tumors have well documented that telomere length in neoplastic tissues and/or noninvasive precursor lesions alters frequently, showing telomere attrition or elongation, as compared with matched adjacent normal tissues (6, 14). Recently, several epidemiologic studies have evaluated telomere length as a potential predictor for cancer risk and prognosis, measured using DNA from peripheral blood cells or buccal cells (6, 15, 16). About colorectal cancer, results from previous studies have been mixed, reporting shorter telomeres associated with increased colorectal cancer risk in one retrospective study (17), null associations between telomere length and colorectal cancer risk in 3 prospective, nested case–control studies (17–19), and longer telomeres associated with increased colorectal cancer risk among carriers of the common allele at a single-nucleotide polymorphism (SNP) near TERC in the most recent study (20). Reasons for the apparently contradictory results remain unknown. Differences in study populations, study designs, sample sizes, analytic approaches, and background exposures could contribute to inconsistent findings. To investigate the association between telomere length and colorectal cancer risk, we conducted a large case–control study nested within the Shanghai Women's Health Study (SWHS) using blood samples collected before cancer diagnosis.

Study population

Subjects of this study were participants of the SWHS, an ongoing prospective cohort study of environmental and genetic risk factors for cancer. A detailed description of the rationale and methods for the SWHS has been reported elsewhere (21). Briefly, from December 1996 through May 2000, 74,942 Chinese women ages 40 to 70 years who were permanent residents in 7 urban communities were enrolled in the cohort study with a participation rate of 92.7%. The baseline survey included an in-person interview and self-administered questionnaire for collecting information about socio-demographic characteristics, lifestyle-related factors, and medical history. Anthropometric measurements were taken by trained interviewers using standardized protocols at enrollment. Of the study participants, 56,831 (75.8%) provided a blood sample. All participants provided written informed consent at enrollment. Study protocols were approved by the relevant Institutional Review Boards for human research.

The cohort has been followed using a combination of biennial home visits and record linkage to cancer incidence and mortality data collected by the Shanghai Cancer Registry and death certificate data collected by the Shanghai Vital Statistics Unit. For cohort members who were diagnosed with cancer, medical charts were reviewed to verify the diagnosis, and detailed information was obtained about pathologic characteristics of the cancer.

The current nested case–control study included 441 incident colorectal cancer cases identified during follow-up of the cohort through December 2009, as well as their 549 matched controls. Incidence-density sampling method was used to select controls. Cases and controls were individually matched on age (≤730 days), date (≤30 days), and time (morning or afternoon) of sample collection, time interval since last meal (≤2 hours), antibiotic use in the past week (yes/no), and menopausal status at time of sample collection.

Measurement of telomere length and quality control

Genomic DNA was extracted from buffy coats using QIAamp DNA kit (Qiagen) following the manufacturer's protocol. Relative telomere length was measured using a monochrome multiplex quantitative PCR method described recently by Cawthon (22) with minor modifications (23). Briefly, telomere length assay was carried out in a 15 μL PCR reaction consisting of 1 × QuantiFast SYBR Green PCR Master Mix (Qiagen), 700 nmol/L telomere primers telg and telc, 200 nmol/L albumin primers albugcr1 and albdgcr1, and 5 ng DNA. A multistep thermal cycling procedure was conducted on a Bio-Rad CFX384 Real-Time System. Following amplification, a dissociation curve was conducted to confirm the specificity of the reaction. For each standard curve, 2-fold serial dilutions of a reference DNA sample were used to produce a standard curve. In addition, a calibrator DNA (same as the reference DNA), 2 negative controls, and 2 quality-control (QC) DNA samples–one with a long and one with a short telomere length (Roche, Telo TAGGG Telomere Length Assay kit) were included in each of the 384-well assay plates. Bio-Rad CFX manager software (version 1.6) was used to determine the relative telomere length through a 2-step relative quantification. In the first step, the ratio of telomere repeat copy number to single-copy gene copy number (T/S), as a measure of relative telomere length, was determined for each sample based on the standard curve. In the second step, the T/S ratio for each sample was normalized to the calibrator DNA to standardize sample values across all reaction plates. Laboratory personnel were blinded to each subject's case–control status. Inter-plate T/S CVs were 15.6%, and 16.2%, respectively, for the long and short telomere QC samples. Inter- and intraplate CVs of calibrator DNA samples were 12.2%, and 5.3%, respectively. Mean ratio of long to short telomere QC samples in our assays was 2.9, very close to the mean ratio of 2.7 determined by Southern Blot method (Roche, Telo TAGGG Telomere Length Assay kit).

Statistical methods

Means and percentages of selected baseline characteristics for cases and controls were calculated and compared using t test (for continuous variables) and χ2 test (for categorical variables). Data about relative telomere length were log-transformed so that these data were approximately normally distributed.

We compared the case–control difference of the geometric means of the log-transformed telomere length using a 2-way (case–control status and matched sets) ANOVA. As DNA samples for cases and controls in the same matched sets were assayed on the same plates, interplate differences for the matched sets were accounted for automatically. To evaluate the association between colorectal cancer risk and telomere length, ratio for telomere length was categorized into quintiles based on distribution among controls. ORs and 95% confidence intervals (CI) were estimated using conditional logistic regression models to account for the matched sets. Tests for linear trend were estimated using the median value for each telomere-length quintile. Restricted cubic spline function with 3 knots (24), which resulted in the best fit of the model, was used in the conditional logistic regression model to evaluate the shape of the association. Likelihood ratio tests were used to evaluate linear effect, nonlinear effect, and overall effect of telomere length with colorectal cancer risk. Stratified analyses were conducted to evaluate potential interactions. All statistical tests were based on 2-sided probability.

Table 1 presents baseline characteristics of 441 cases and 549 matched controls, including age at blood collection, educational levels, menopausal status, obesity status [measured by body mass index (BMI)], cigarette-smoking status, alcohol use, physical activity, fruit and vegetable intake, meat intake, history of inflammatory bowel disease, and family history of colorectal cancer. Overall, distributions were comparable between cases and controls. Telomere length was inversely correlated with age at blood collection (r = −0.22, P < 0.0001; data not shown in table). Geometric means of telomere length were approximately 7.4% (cases) and 5.6% (controls) shorter in women aged 50 to 59 years, and 8.7% (cases) and 7.3% (controls) shorter in those aged 60 and older, compared with those younger than 50 years (data not shown in table).

Table 1.

Comparison of demographic characteristics and known colorectal cancer risk factors between cases and their matched controls

Baseline characteristicsCases (N = 441)Controls (N = 549)P for difference
Age, mean ± SD 58.5 ± 8.7 58.6 ± 8.6 0.9732 
Postmenopause, % 76.6 76.9 0.9342 
Body mass index, BMI, mean ± SD 24.6 ± 3.3 24.8 ± 3.5 0.3608 
Education ≥ high school, % 31.8 31.7 0.9860 
Family history of colorectal cancer, % 3.2 2.4 0.4386 
History of inflammatory bowel disease, % 0.9 0.5 0.5010 
Ever smoked cigarettes regularly, % 2.5 3.8 0.2393 
Ever consumed alcohol regularly, % 3.2 2.9 0.8124 
Ever exercised regularly, % 46.9 44.1 0.3692 
Ever used aspirin regularly, % 2.5 4.4 0.1119 
Fruit and vegetable intake, g/d; mean ± SD 556.9 ± 292.4 549.8 ± 282.0 0.6983 
Meat intake, g/d; mean ± SD 48.9 ± 41.6 49.6 ± 37.2 0.7818 
Baseline characteristicsCases (N = 441)Controls (N = 549)P for difference
Age, mean ± SD 58.5 ± 8.7 58.6 ± 8.6 0.9732 
Postmenopause, % 76.6 76.9 0.9342 
Body mass index, BMI, mean ± SD 24.6 ± 3.3 24.8 ± 3.5 0.3608 
Education ≥ high school, % 31.8 31.7 0.9860 
Family history of colorectal cancer, % 3.2 2.4 0.4386 
History of inflammatory bowel disease, % 0.9 0.5 0.5010 
Ever smoked cigarettes regularly, % 2.5 3.8 0.2393 
Ever consumed alcohol regularly, % 3.2 2.9 0.8124 
Ever exercised regularly, % 46.9 44.1 0.3692 
Ever used aspirin regularly, % 2.5 4.4 0.1119 
Fruit and vegetable intake, g/d; mean ± SD 556.9 ± 292.4 549.8 ± 282.0 0.6983 
Meat intake, g/d; mean ± SD 48.9 ± 41.6 49.6 ± 37.2 0.7818 

P values were derived from t tests for continuous variables or χ2 tests for categorical variables.

Overall, no significant difference was found in geometric mean of telomere length between cases and controls (P = 0.1620; Table 2), and no linear association between telomere length and colorectal cancer risk was detected (Ptrend = 0.1633; Table 3). However, a U-shaped association was observed: the lowest risk was observed in women with telomere length in the third quintile (40th–60th percentiles), and risks were elevated with a shorter or longer telomere length as compared with the lowest risk group (Table 3). A similar pattern of the association was also seen after excluding cases diagnosed within the first year after blood collection, or grouping study subjects based on the interval between blood collection and cancer diagnosis (<5 years or ≥5 years), or being examined by colon cancer or rectum cancer separately (Tables 2 and 3).

Table 2.

Comparison of adjusted geometric means of telomere length between cases and controls

Relative telomere length
Subjects, NMean (95% CI)aRatio (95% CI)bP
All subjects 
 Cases (441) 0.976 (0.959, 0.993)   
 Controls (549) 0.960 (0.945, 0.975) 1.017 (0.993, 1.040) 0.162 
Excluding cases diagnosed within 1 year since blood collection 
 Cases (413) 0.975 (0.958, 0.992)   
 Controls (511) 0.963 (0.947, 0.979) 1.012 (0.988, 1.037) 0.325 
Interval between blood collection and cancer diagnosis less than 5 years 
 Cases (178) 1.008 (0.979, 1.039)   
 Controls (236) 0.982 (0.956, 1.009) 1.027 (0.987, 1.068) 0.190 
Interval between blood collection and cancer diagnosis 5 years or more 
 Cases (263) 0.954 (0.935, 0.974)   
 Controls (313) 0.946 (0.928, 0.964) 1.009 (0.981, 1.038) 0.513 
 Colon cancer 
 Cases (276) 0.948 (0.929, 0.967)   
 Controls (345) 0.944 (0.926, 0.961) 1.004 (0.977, 1.032) 0.760 
Rectum cancer 
 Cases (165) 1.024 (0.993, 1.056)   
 Controls (204) 0.987 (0.959, 1.016) 1.037 (0.995, 1.082) 0.085 
Relative telomere length
Subjects, NMean (95% CI)aRatio (95% CI)bP
All subjects 
 Cases (441) 0.976 (0.959, 0.993)   
 Controls (549) 0.960 (0.945, 0.975) 1.017 (0.993, 1.040) 0.162 
Excluding cases diagnosed within 1 year since blood collection 
 Cases (413) 0.975 (0.958, 0.992)   
 Controls (511) 0.963 (0.947, 0.979) 1.012 (0.988, 1.037) 0.325 
Interval between blood collection and cancer diagnosis less than 5 years 
 Cases (178) 1.008 (0.979, 1.039)   
 Controls (236) 0.982 (0.956, 1.009) 1.027 (0.987, 1.068) 0.190 
Interval between blood collection and cancer diagnosis 5 years or more 
 Cases (263) 0.954 (0.935, 0.974)   
 Controls (313) 0.946 (0.928, 0.964) 1.009 (0.981, 1.038) 0.513 
 Colon cancer 
 Cases (276) 0.948 (0.929, 0.967)   
 Controls (345) 0.944 (0.926, 0.961) 1.004 (0.977, 1.032) 0.760 
Rectum cancer 
 Cases (165) 1.024 (0.993, 1.056)   
 Controls (204) 0.987 (0.959, 1.016) 1.037 (0.995, 1.082) 0.085 

aAdjusted for matched sets.

bThe ratio (95% CI) of the geometric means in cases over geometric means in controls.

Table 3.

ORs and 95% confidence intervals for the association between telomere length and colorectal cancer risk

Telomere length (by quintile)No. of casesNo. of controlsOR (95% CI)a,b
All subjects 
 Q1 (short) 95 109 1.56 (0.92–2.64) 
 Q2 91 110 1.30 (0.86–1.97) 
 Q3 72 110 1.00 (reference) 
 Q4 92 110 1.38 (0.90–2.11) 
 Q5 (long) 91 110 1.61 (0.94–2.75) 
 Linear   P = 0.1633 
 Nonlinear   P = 0.0122 
 Overall   P = 0.0152 
Excluding cases diagnosed within 1 year since blood collection 
 Q1 (short) 90 98 1.59 (0.92–2.74) 
 Q2 83 105 1.21 (0.79–1.86) 
 Q3 68 101 1.00 (reference) 
 Q4 87 104 1.30 (0.84–2.02) 
 Q5 (long) 85 109 1.53 (0.88–2.65) 
 Linear   P = 0.3229 
 Nonlinear   P = 0.0088 
 Overall   P = 0.0199 
Interval between blood collection and cancer diagnosis less than 5 years 
 Q1 (short) 33 43 1.99 (0.82–4.80) 
 Q2 35 44 1.55 (0.82–2.92) 
 Q3 30 51 1.00 (reference) 
 Q4 37 50 1.35 (0.72–2.55) 
 Q5 (long) 43 48 2.02 (0.93–4.39) 
 Linear   P = 0.2073 
 Nonlinear   P = 0.0208 
 Overall   P = 0.0312 
Interval between blood collection and cancer diagnosis 5 years or more 
 Q1 (short) 62 66 1.33 (0.68–2.59) 
 Q2 56 66 1.16 (0.66–2.02) 
 Q3 42 59 1.00 (reference) 
 Q4 55 60 1.37 (0.77–2.45) 
 Q5 (long) 48 62 1.33 (0.63–2.82) 
 Linear   P = 0.5166 
 Nonlinear   P = 0.2667 
 Overall   P = 0.4372 
Colon cancer 
 Q1 (short) 65 75 1.50 (0.79–2.85) 
 Q2 61 70 1.35 (0.79–2.31) 
 Q3 44 69 1.00 (reference) 
 Q4 59 60 1.55 (0.90–2.68) 
 Q5 (long) 47 71 1.11 (0.55–2.26) 
 Linear   P = 0.7558 
 Nonlinear   P = 0.0700 
 Overall   P = 0.1846 
Rectum cancer 
 Q1 (short) 30 34 1.78 (0.69–4.65) 
 Q2 30 40 1.28 (0.66–2.74) 
 Q3 28 41 1.00 (reference) 
 Q4 33 50 1.16 (0.59–2.26) 
 Q5 (long) 44 39 2.54 (1.08–5.96) 
 Linear   P = 0.0899 
 Nonlinear   P = 0.1478 
 Overall   P = 0.0833 
Telomere length (by quintile)No. of casesNo. of controlsOR (95% CI)a,b
All subjects 
 Q1 (short) 95 109 1.56 (0.92–2.64) 
 Q2 91 110 1.30 (0.86–1.97) 
 Q3 72 110 1.00 (reference) 
 Q4 92 110 1.38 (0.90–2.11) 
 Q5 (long) 91 110 1.61 (0.94–2.75) 
 Linear   P = 0.1633 
 Nonlinear   P = 0.0122 
 Overall   P = 0.0152 
Excluding cases diagnosed within 1 year since blood collection 
 Q1 (short) 90 98 1.59 (0.92–2.74) 
 Q2 83 105 1.21 (0.79–1.86) 
 Q3 68 101 1.00 (reference) 
 Q4 87 104 1.30 (0.84–2.02) 
 Q5 (long) 85 109 1.53 (0.88–2.65) 
 Linear   P = 0.3229 
 Nonlinear   P = 0.0088 
 Overall   P = 0.0199 
Interval between blood collection and cancer diagnosis less than 5 years 
 Q1 (short) 33 43 1.99 (0.82–4.80) 
 Q2 35 44 1.55 (0.82–2.92) 
 Q3 30 51 1.00 (reference) 
 Q4 37 50 1.35 (0.72–2.55) 
 Q5 (long) 43 48 2.02 (0.93–4.39) 
 Linear   P = 0.2073 
 Nonlinear   P = 0.0208 
 Overall   P = 0.0312 
Interval between blood collection and cancer diagnosis 5 years or more 
 Q1 (short) 62 66 1.33 (0.68–2.59) 
 Q2 56 66 1.16 (0.66–2.02) 
 Q3 42 59 1.00 (reference) 
 Q4 55 60 1.37 (0.77–2.45) 
 Q5 (long) 48 62 1.33 (0.63–2.82) 
 Linear   P = 0.5166 
 Nonlinear   P = 0.2667 
 Overall   P = 0.4372 
Colon cancer 
 Q1 (short) 65 75 1.50 (0.79–2.85) 
 Q2 61 70 1.35 (0.79–2.31) 
 Q3 44 69 1.00 (reference) 
 Q4 59 60 1.55 (0.90–2.68) 
 Q5 (long) 47 71 1.11 (0.55–2.26) 
 Linear   P = 0.7558 
 Nonlinear   P = 0.0700 
 Overall   P = 0.1846 
Rectum cancer 
 Q1 (short) 30 34 1.78 (0.69–4.65) 
 Q2 30 40 1.28 (0.66–2.74) 
 Q3 28 41 1.00 (reference) 
 Q4 33 50 1.16 (0.59–2.26) 
 Q5 (long) 44 39 2.54 (1.08–5.96) 
 Linear   P = 0.0899 
 Nonlinear   P = 0.1478 
 Overall   P = 0.0833 

aAdjusted for matched sets.

bSubjects with telomere length in the third quintile (40th–60th percentiles) had the lowest risk of colorectal cancer and were used as reference.

To further evaluate the shape of the association, restricted cubic spline function was used in a conditional logistic regression model (Fig. 1). Similar to the categorical analysis presented in Table 3, a clear U-shaped, statistically significant association between telomere length and colorectal cancer risk (test for linearity: P = 0.1633; test for nonlinearity: P = 0.0112; and overall: P = 0.0152). Again, excluding cases diagnosed within the first year after blood collection, or stratifying women based on the time interval between blood collection and cancer diagnosis, or based on colon cancer or rectum cancer did not apparently affect the overall association observed (figures not shown).

Figure 1.

ORs (solid line) and their 95% CIs (dotted lines) for the association between telomere length and colorectal cancer risk (in all subjects). P values for tests of overall association, linearity, and nonlinearity are 0.0152, 0.1633, and 0.0122, respectively.

Figure 1.

ORs (solid line) and their 95% CIs (dotted lines) for the association between telomere length and colorectal cancer risk (in all subjects). P values for tests of overall association, linearity, and nonlinearity are 0.0152, 0.1633, and 0.0122, respectively.

Close modal

We also investigated potential interactions of telomere length with age, BMI, or physical activity in relation to colorectal cancer risk. However, we did not detect a significant interaction in our study population (data not shown).

Recently, a few epidemiologic studies investigated the association between leukocyte telomere length and colorectal cancer risk, with conflicting results. Pooley and colleagues (17) conducted a retrospective study using data from the SEARCH colorectal cancer case–control study (2,249 cases; 2,161 controls) and a prospective study using data from the EPIC-Norfolk cohort (185 cases; 406 controls) and found a strong association between short telomeres and colorectal cancer risk in the retrospective study (OR, 2.14; 95% CI, 1.77–2.59; quartile 1 versus quartile 4; Ptrend < 0.0001), but not in the prospective study (OR, 1.13; 95% CI, 0.54–2.36; Ptrend = 0.82). No statistically significant association between mean telomere length and colorectal cancer risk was reported by 2 other relatively small prospective, nested case–control studies: among white men from the Physicians' Health Study (cases/controls = 191/306; OR, 1.25; 95% CI, 0.86–1.81; ref. 19), and among white women from the Women's Health Study (cases/controls = 134/357; OR, 0.94; 95% CI, 0.65–1.38; ref. 18). Intriguingly, in a most recent study examining a large white, European ancestry sample, (3,921 controls and 2,157 cases), Jones and colleagues found that carriers of the common allele at a SNP near the TERC had significantly longer telomeres in leukocytes and found the same allele to be associated with increased colorectal cancer risk (20). Differing from previous reports, our study found a U-shaped association between telomere length and colorectal cancer risk, indicating both long and short telomeres to be associated with increased risk of colorectal cancer. Discrepancies between our results and previous reports may be attributed partially to differences in study population (e.g., ethnicity, sex, and age), sample size, and analytical method used. In the prospective arm of the Pooley and colleagues study (17), colorectal cancer risk was shown to be lowest in the third quartile of telomere length, which is similar to our finding. However, Pooley and colleagues did not specifically evaluate the nonlinear association between telomere length and colorectal cancer risk.

The U-shaped association between telomere length and colorectal cancer risk observed in our study is unexpected, but it is biologically plausible. Experimental studies and animal models have shown that telomeres at the end of chromosomes play important roles in maintaining genomic integrity and stability (2). When telomeres become critically shortened, Rb and p53 signal pathways are triggered, and cells undergo either replicative senescence or apoptosis (5, 7). If such processes are bypassed, cells continue to proliferate through activation of telomeres, genetic lesions, and inactivated suppressor checkpoints, ultimately resulting in tumorigenesis (4–7, 13). In humans, it has been well documented that short telomeres are associated with multiple premature aging syndromes, including ataxia telangiectasia, ataxia-telangiectasia-like disorder, aplastic anemia, Bloom syndrome, Fanconi anemia, Nijmegen breakage syndrome, and dyskeratosis congenita (4, 12). On the other hand, although short telomeres have been associated with cancer risk, it is evident that very long telomeres may also increase risk of carcinogenic transformation. In specimens from solid tumors, including colorectal cancer, histopathological studies have shown that telomeres were significantly shorter in most cases; however, tumors from a subset of patients showed elongated telomeres, compared with their adjacent noncancerous tissues (14). In epidemiologic studies analyzing telomeres in leukocytes and cancer risk, both short and long telomeres have been found to be associated with increased risk of several types of cancer (17), including breast cancer (17, 23, 25–27), colorectal cancer (17, 20), lung cancer (28–31), renal cell carcinoma (32, 33), and non-Hodgkin lymphoma (34, 35). It has been proposed that cells with long telomeres may favor a delayed cell senescence and apoptosis; therefore, these cells could have an increased chance of exposure to various genetic and environmental insults and acquirement/accumulation of genetic abnormalities, thus being at higher risk of carcinogenic transformation (11, 34). Our study is the first to provide evidence in the same study cohort that both short and long telomeres may contribute to increased risk of colorectal cancer. Our study, together with others, suggests that telomere length in an “appropriate range” may be necessary to maintain chromosomal stability and normal programmed cell death—functions that are protective against tumor development.

A major strength of our study is the use of prediagnostic blood samples. However, lifestyle changes over time could affect the association between telomere length and colorectal cancer risk. In particular, cigarette smoking and regular aspirin use could affect telomere length. However, less than 5% of study participants smoked cigarettes or used aspirin regularly and thus these 2 variables should not have any major impact on our study results. Similar to other studies, the precision of relative telomere measurement was not optimal, and a relatively large CV was observed. However, this measurement error should be random, which tends to attenuate the association between telomere length and breast cancer risk. To minimize the effect of interplate variation on study results, we used the same plate to analyze samples from each case–control set and used monochrome multiplex quantitative PCR method. Although our study is the largest prospective study conducted to date addressing the association of telomere length with colorectal cancer risk, the sample size for some analyses remains relatively small. Further research is warranted to evaluate the association in large prospective studies and by different racial/ethnic groups.

In conclusion, our prospective study revealed a U-shaped association between telomere length in peripheral blood cells and colorectal cancer risk. Our findings provide strong evidence that both very short and very long telomeres are associated with increased risk of colorectal cancer.

No potential conflicts of interest were disclosed.

Conception and design: S. Qu, W. Wen, N. Rothman, X.-O. Shu, W. Zheng

Development of methodology: Q. Cai, S. Qu, W. Wen, J. Wu, W. Zheng

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): Q. Cai, S. Qu, Y.-B. Xiang, J. Wu, N. Rothman, G. Yang, X.-O. Shu, Y.-T. Gao, W. Zheng

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): Y. Cui, S. Qu, W.-H. Chow, W. Wen, W. Zheng

Writing, review, and/or revision of the manuscript: Y. Cui, S. Qu, W.-H. Chow, W. Wen, Y.-B. Xiang, N. Rothman, G. Yang, X.-O. Shu, Y.-T. Gao, W. Zheng

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): Y.-B. Xiang, J. Wu, Y.-T. Gao, W. Zheng

Study supervision: Q. Cai, Y.-B. Xiang, X.-O. Shu, Y.-T. Gao, W. Zheng

The authors wish to thank Ms. Regina Courtney for her excellent laboratory assistance in sample handling and preparation. Sample preparations and telomere length assays were conducted at the Survey and Biospecimen Shared Resource, which is supported in part by the Vanderbilt-Ingram Cancer Center (P30 CA68485).

Funding support for this work was provided by NIH grant (R37 CA 070867).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1.
Blackburn
EH
. 
Telomere states and cell fates
.
Nature
2000
;
408
:
53
6
.
2.
Stewart
SA
,
Weinberg
RA
. 
Telomeres: cancer to human aging
.
Annu Rev Cell Dev Biol
2006
;
22
:
531
57
.
3.
Greider
CW
,
Blackburn
EH
. 
Tracking telomerease
.
Cell
2004
;
116
:
S83
S86
81p following S86
.
4.
Blasco
MA
. 
Telomeres and human disease: ageing, cancer and beyond
.
Nat Rev Genet
2005
;
6
:
611
22
.
5.
Gilley
D
,
Herbert
B
,
Huda
N
,
Tanka
H
,
Reed
T
. 
Factors impacting human telomere homeostasis and age-related disease
.
Mech Ageing Dev
2008
;
129
:
27
34
.
6.
Prescott
J
,
Wentzensen
IM
,
Savage
SA
,
De Vivo
I
. 
Epidemiologic evidence for a role of telomere dysfunction in cancer etiology
.
Mutat Res
2012
;
730
:
75
84
.
7.
Mathon
NF
,
Lloyd
AC
. 
Cell senescence and cancer
.
Nat Rev Cancer
2001
;
1
:
203
13
.
8.
Greider
CW
. 
Telomerase activity, cell proliferation, and cancer
.
Proc Natl Acad Sci USA
1998
;
95
:
90
2
.
9.
Mooi
WJ
,
Peeper
DS
. 
Oncogene-induced cell senescence–halting on the road to cancer
.
N Engl J Med
2006
;
355
:
1037
46
.
10.
Stewart
JA
,
Chaiken
MF
,
Wang
F
,
Price
CM
. 
Maintaining the end: Roles of telomere proteins in end-protection, telomere replication and length regulation
.
Mutat Res
2012
;
730
:
12
9
.
11.
Hou
L
,
Zhang
X
,
Gawron
AJ
,
Liu
J
. 
Surrogate tissue telomere length and cancer risk: shorter or longer?
Cancer Lett
2012
;
319
:
130
5
.
12.
Alter
BP
,
Giri
N
,
Savage
SA
,
Rosenberg
PS
. 
Cancer in dyskeratosis congenita
.
Blood
2009
;
113
:
6549
57
.
13.
Lee
HW
,
Blasco
MA
,
Gottlieb
GJ
,
Horner
JW
 II
,
Greider
CW
,
DePinho
RA
. 
Essential role of mouse telomerase in highly proliferative organs
.
Nature
1998
;
392
:
569
74
.
14.
Bisoffi
M
,
Heaphy
CM
,
Griffith
JK
. 
Telomeres: prognostic markers for solid tumors
.
Int J Cancer
2006
;
119
:
2255
60
.
15.
Ma
H
,
Zhou
Z
,
Wei
S
,
Liu
Z
,
Pooley
KA
,
Dunning
AM
, et al
Shortened telomere length is associated with increased risk of cancer: a meta-analysis
.
PLoS One
2011
;
6
:
e20466
.
16.
Wentzensen
IM
,
Mirabello
L
,
Pfeiffer
RM
,
Savage
SA
. 
The association of telomere length and cancer: a meta-analysis
.
Cancer Epidemiol Biomarkers Prev
2011
;
20
:
1238
50
.
17.
Pooley
KA
,
Sandhu
MS
,
Tyrer
J
,
Shah
M
,
Driver
KE
,
Luben
RN
, et al
Telomere length in prospective and retrospective cancer case-control studies
.
Cancer Res
2010
;
70
:
3170
6
.
18.
Lee
IM
,
Lin
J
,
Castonguay
AJ
,
Barton
NS
,
Buring
JE
,
Zee
RY
. 
Mean leukocyte telomere length and risk of incident colorectal carcinoma in women: a prospective, nested case-control study
.
Clin Chem Lab Med
2010
;
48
:
259
62
.
19.
Zee
RY
,
Castonguay
AJ
,
Barton
NS
,
Buring
JE
. 
Mean telomere length and risk of incident colorectal carcinoma: a prospective, nested case-control approach
.
Cancer Epidemiol Biomarkers Prev
2009
;
18
:
2280
2
.
20.
Jones
AM
,
Beggs
AD
,
Carvajal-Carmona
L
,
Farrington
S
,
Tenesa
A
,
Walker
M
, et al
TERC polymorphisms are associated both with susceptibility to colorectal cancer and with longer telomeres
.
Gut
2012
;
61
:
248
54
.
21.
Zheng
W
,
Chow
WH
,
Yang
G
,
Jin
F
,
Rothman
N
,
Blair
A
, et al
The Shanghai Women's Health Study: rationale, study design, and baseline characteristics
.
Am J Epidemiol
2005
;
162
:
1123
31
.
22.
Cawthon
RM
. 
Telomere length measurement by a novel monochrome multiplex quantitative PCR method
.
Nucleic Acids Res
2009
;
37
:
e21
.
23.
Qu
S
,
Wen
W
,
Shu
XO
,
Chow
WH
,
Xiang
YB
,
Wu
J
, et al
Association of leukocyte telomere length with breast cancer risk: nested case-control findings from the Shanghai Women's Health Study
.
Am J Epidemiol
. 
2012
(
In press
).
24.
Harrell
F
. 
Regression modeling strategies
.
New York, NY
:
Springer
; 
2001
.
25.
Svenson
U
,
Nordfjall
K
,
Stegmayr
B
,
Manjer
J
,
Nilsson
P
,
Tavelin
B
, et al
Breast cancer survival is associated with telomere length in peripheral blood cells
.
Cancer Res
2008
;
68
:
3618
23
.
26.
Gramatges
MM
,
Telli
ML
,
Balise
R
,
Ford
JM
. 
Longer relative telomere length in blood from women with sporadic and familial breast cancer compared with healthy controls
.
Cancer Epidemiol Biomarkers Prev
2010
;
19
:
605
13
.
27.
Levy
T
,
Agoulnik
I
,
Atkinson
EN
,
Tong
XW
,
Gause
HM
,
Hasenburg
A
, et al
Telomere length in human white blood cells remains constant with age and is shorter in breast cancer patients
.
Anticancer Res
1998
;
18
:
1345
9
.
28.
Shen
M
,
Cawthon
R
,
Rothman
N
,
Weinstein
SJ
,
Virtamo
J
,
Hosgood
HD
 3rd
, et al
A prospective study of telomere length measured by monochrome multiplex quantitative PCR and risk of lung cancer
.
Lung Cancer
2011
;
54
:
482
9
.
29.
Jang
JS
,
Choi
YY
,
Lee
WK
,
Choi
JE
,
Cha
SI
,
Kim
YJ
, et al
Telomere length and the risk of lung cancer
.
Cancer Sci
2008
;
99
:
1385
9
.
30.
Hosgood
HD
 III
,
Cawthon
R
,
He
X
,
Chanock
S
,
Lan
Q
. 
Genetic variation in telomere maintenance genes, telomere length, and lung cancer susceptibility
.
Lung Cancer
2009
;
66
:
157
61
.
31.
Wu
X
,
Amos
CI
,
Zhu
Y
,
Zhao
H
,
Grossman
BH
,
Shay
JW
, et al
Telomere dysfunction: a potential cancer predisposition factor
.
J Natl Cancer Inst
2003
;
95
:
1211
8
.
32.
Svenson
U
,
Ljungberg
B
,
Roos
G
. 
Telomere length in peripheral blood predicts survival in clear cell renal cell carcinoma
.
Cancer Res
2009
;
69
:
2896
901
.
33.
Shao
L
,
Wood
CG
,
Zhang
D
,
Tannir
NM
,
Matin
S
,
Dinney
CP
, et al
Telomere dysfunction in peripheral lymphocytes as a potential predisposition factor for renal cancer
.
J Urol
2007
;
178
:
1492
6
.
34.
Lan
Q
,
Cawthon
R
,
Shen
M
,
Weinstein
SJ
,
Virtamo
J
,
Lim
U
, et al
A prospective study of telomere length measured by monochrome multiplex quantitative PCR and risk of non-Hodgkin lymphoma
.
Clin Cancer Res
2009
;
15
:
7429
33
.
35.
Widmann
TA
,
Herrman
M
,
Taha
N
,
Konig
J
,
Pfreundschuh
M
. 
Short telomeres in aggressive non-Hodgkin's lymphoma as a risk factor in lymphomagenesis
.
Exp Hematol
2007
;
35
:
939
46
.