Abstract
Background
Telomere length in blood or buccal cell DNA has been associated with risk of various cancers. Glioma can be a highly malignant brain tumor and has few known risk factors. Genetic variants in or near RTEL1 and TERT, key components of telomere biology, are associated with glioma risk. Therefore, we evaluated the association between relative telomere length (RTL) and glioma in a prospective study.
Materials and Methods
We performed a nested case-control study within the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. RTL was determined by quantitative PCR on blood or buccal cell DNA obtained at least two years prior to diagnosis from 101 individuals with glioma cases. Healthy controls (n=198) were matched to cases (2:1) on age, gender, smoking status, calendar year, and DNA source. Conditional logistic regression was used to investigate the association between RTL and glioma.
Results
As expected, RTL declined with increasing age in both cases and controls. There was no statistically significant association between RTL and glioma overall. An analysis stratified by gender suggested that short RTL (1st tertile) in males was associated with glioma (odds ratio, [OR] = 2.29, 95% confidence interval [CI] 1.02-5.11); this association was not observed for females (OR=0.41, 95% CI 0.14-1.17).
Conclusions
This prospective study did not identify significant associations between RTL and glioma risk, but there may be gender-specific differences. Larger, prospective studies are needed to evaluate these findings.
Keywords: Telomere length, glioma, epidemiology, cancer risk
1. INTRODUCTION
Telomere length in surrogate tissues (e.g., blood or buccal cells) has been associated with cancer risk in several studies[1, 2]. Telomeres are specialized nucleoprotein structures at chromosome ends that are critical for chromosomal stability. They shorten with each cell division and when critically short length is attained, cellular senescence or apoptosis is triggered[3]. Cancer cells continue to divide in the presence of short telomeres by up-regulating key pathways, such as telomerase (TERT) or alternative lengthening of telomeres (ALT)[3].
Gliomas account for approximately 69% of malignant brain tumors in the United States [4]. The five-year survival rate for all subtypes of glioma in the U.S. from 2001-2008 was approximately 45%. High grade gliomas, such as glioblastoma multiforme, have a much worse outcome with a five-year survival rate of approximately 2.9%[5]. Gliomas are more common in males than in females[4, 6]. Confirmed risk factors for glioma include moderate-to-high doses of ionizing radiation, certain inherited cancer predisposition syndromes, and a family history of glioma[7].
Genome-wide association studies (GWAS) of glioma have identified common susceptibility variants at seven loci, including two telomere biology genes, TERT and RTEL1[7-10]. Further, a recent study found increasing numbers of risk alleles in TERT and RTEL1 genes were associated with increased risk of glioma in older patients, while increasing numbers of risk alleles in CCDC26 and PHLDB1genes was associated with younger age of diagnosis of glioma [11]. The association between telomere length and SNPs in TERT or RTEL1 is not clear; some studies have found associations whereas others have not [12, 13].
There is a growing connection between changes in telomere biology in somatic glioma tissues, including TERT promoter mutations in 83% of glioblastoma multiforme [14]. Telomere length heterogeneity appears to be present in brain tumors. Some brain tumors appear to up-regulate telomerase whereas others maintain telomere length through the alternative lengthening of telomere pathway (ALT) [15-20]. The ALT pathway may play a role in specific subsets of glioma with mutations in Alpha Thalassemia/Mental Retardation X-linked (ATRX) and/or isocitrate dehydrogenase genes (IDH1) [18].
In order to better understand the connection between germline telomere biology and glioma, we conducted a nested case-control study within the Prostate, Lung, Colorectal, and Ovarian Cancer (PLCO) Screening Trial.
2. METHODS
2.1 Study Design
Our case-control study was nested within the prospective PLCO Screening Trial [21]. All study participants were of European ancestry, cancer-free at enrollment, aged between 55-75 years, enrolled between 1993 and 2001, and followed until at least 2010. For our study, cases were individuals who developed glioma as a first cancer between 1995-2010. Controls were cancer-free at time of case diagnosis. Cases and controls (two per case) were matched on: trial randomization arm (control arm or intervention arm), gender, age at baseline in 4 categories (55-59, 60-64, 65-69, 70+), calendar year of randomization, cigarette smoking status (never, current, former), and calendar year of blood draw. In addition, cases and controls were fully matched on DNA source except for 17 cases where matching was for only one control. In order to minimize the possibility of reverse causality association, only biological specimens that were collected two or more years prior to diagnosis/selection were considered.
2.2 Laboratory Methods
DNA was extracted by standard methods (phenol:chloroform or Qiagen kits) from blood, buffy coat, or buccal cells. The average relative telomere length (RTL) was determined using qPCR as described previously[22, 23]. RTL was calculated as the telomere repeat copy number/single-gene (36B4) copy number (T/S) exponentiated ratio. Laboratory technicians were blinded to the case-control status. All assays were performed in triplicate on 5 ng of genomic DNA. Forty blinded, randomly selected, quality control samples were interspersed throughout the dataset in order to assess inter-plate and intra-plate variability. The coefficient of variation (CV) for triplicate of the telomere copy (inter-assay) was 0.9% and for the single-copy gene was 0.8%. The CV for duplicate quality control samples (intra-assay) was 3.92% with a range of 0.42%-7.82%.
2.3 Statistical Analysis
Spearman's rank correlation was used to assess correlations between RTL and age for cases and controls. We used Wilcoxon-rank test to compare median RTL in cases and controls overall, and by subgroup. Conditional logistic regression was used to examine the association between age-adjusted RTL and glioma. Stratified analyses by gender were performed to assess the interaction of gender and RTL on glioma risk. In all analyses, RTL was assessed as a continuous variable and in tertiles (based on the distribution in the controls). The final analysis included 198 controls and 101 cases (RTL data were not available on 12 controls and 4 cases due to qPCR assay failures). All analyses were performed using SPSS version 19. All tests were two-sided.
3. RESULTS
Per study design, the glioma cases and controls were similar in regard to age distribution, gender, and smoking status (Table 1). There were more males than females with glioma (male:female ratio 3:2). RTL was inversely correlated with age in the controls (r = −0.14, p = 0.04). The RTL-age correlation in the cases was not statistically significant (r = 0.10, p = 0.34). The median RTL in glioma cases and controls was not significantly different (median RTL in cases = 0.74 and in controls = 0.77, p = 0.84). In the regression model, the evaluation of risk of glioma and RTL as both a continuous variable and in tertiles of RTL in controls revealed no statistically significant associations between RTL and overall risk of glioma (Table 2). Since RTL varies between tissues but is highly correlated within individuals we evaluated whether DNA sources affected our results [24-26]. Sensitivity analyses adding DNA source to the conditional logistic regression model made no difference (data not shown).
Table 1.
Descriptive Characteristics and Median Telomere Length of Study Participants
| Cases N=102 (%) | Controls N=199 (%) | P value | |
|---|---|---|---|
| Age | |||
| 55-59 | 27 (26) | 50 (25) | |
| 60-64 | 31 (31) | 61 (31) | 0.90 |
| 65-69 | 31 (31) | 60 (30) | |
| 70+ | 13 (13) | 28 (14) | |
| Gender | |||
| Males | 62 (61) | 122 (62) | 0.90 |
| Females | 40 (40) | 77 (39) | |
| Smoking status | |||
| Never | 54 (51) | 105 (53) | |
| Former | 6 (6) | 11 (6) | 0.99 |
| Current | 42 (42) | 83 (42) | |
| Median Relative Telomere Length (Range) | Median Relative Telomere Length (Range) | ||
| All | 0.74 (0.20-4.77) | 0.77§ (0.14-3.72) | 0.84 |
| Males | 0.63 (0.22-2.15) | 0.77§ (0.14-3.72) | 0.12 |
| Females | 0.91§§ (0.20-4.77) | 0.77§ (0.16-3.56) | 0.10 |
| Male glioma cases vs. female glioma cases | 0.02 | ||
Table 2.
Age-adjusted association between relative telomere length and glioma
| All participants | |||||
|---|---|---|---|---|---|
| Cases N (%) | Controls N (%) | OR* | CI (95%) | P value | |
| RTL (continuous) | 102 | 193 | 0.84 | 0.55-1.27 | 0.84 |
| RTL (median) | 102 | 192 | 1.17 | 0.73-1.88 | 0.52§ |
| Tertiles of RTL | |||||
| Short (1st tertile) | 36 (36) | 65 (33) | 1.26 | 0.69-2.29 | 0.46 |
| Medium (2nd tertile) | 32 (32) | 67 (34) | 1.06 | 0.55-2.04 | 0.86 |
| Long (3rd tertile) | 33 (33) | 66 (33) | 1.00 | REF | |
| Males only | |||||
| Continuous RTL | 62 | 116 | 0.48 | 0.23-0.99 | 0.05 |
| RTL (median) | 62 | 116 | 1.74 | 0.93-3.24 | 0.081 |
| Tertiles of RTL | |||||
| Short (1st tertile) | 29 (46) | 38 (31) | 2.29 | 1.02-5.11 | 0.04 |
| Medium (2nd tertile) | 18 (30) | 47 (38) | 1.17 | 0.47-2.87 | 0.74 |
| Long (3rd tertile) | 14 (22) | 37 (30) | 1.00 | REF | |
| P trend = 0.06 | |||||
| Females only | |||||
| Continuous RTL | 40 | 77 | 1.25 | 0.74-2.12 | 0.41 |
| RTL (median) | 40 | 76 | 0.64 | 0.30-1.37 | 0.25 |
| Tertiles of RTL | |||||
| Short (1st tertile) | 7 (17) | 27 (35) | 0.41 | 0.14-1.17 | 0.09 |
| Medium (2nd tertile) | 14 (35) | 20 (26) | 1.21 | 0.45-3.28 | 0.70 |
| Long (3rd tertile) | 19 (47) | 29 (38) | 1.00 | REF | |
| P trend = 0.15 | |||||
Conditional logistic regression with matching on age, gender, and smoking status
DNA source added to conditional logistic regression model, OR= 1.52, 95% CI = 0.91-2.54, p=0.11
Abbreviations: RTL, relative telomere length; OR, odds ratio; CI, 95% confidence interval; N, number; REF, reference
Case-case comparison of RTL showed that males with glioma had shorter telomeres than females with glioma (male cases median RTL = 0.63, female cases median RTL = 0.91, p = 0.02) (Table 1). This relationship between RTL and gender was not observed in controls. However, gender-specific analyses suggested an association between RTL and glioma in males (continuous RTL p = 0.05 and shortest RTL tertile/longest OR = 2.29, 95% CI 1.02-5.11).
4. Discussion
The etiology of glioma is not well understood, although genetic factors, high levels of exposure to ionizing radiation, and male gender appear to be risk factors[7]. We conducted a case-control study of RTL in glioma because there is a growing body of evidence suggesting that aberrant telomere biology may be associated with glioma. Common germline variants in key telomere biology genes, RTEL1 and TERT, are associated with glioma risk [7-10]. Several studies have found a connection between telomerase levels, telomere heterogeneity, TERT promoter mutations and ALT in somatic glioma tissues and provide further evidence for a biological connection [14] [15-20]. A growing number of studies suggest that short germline RTL is a risk factor for certain cancers, including bladder, esophageal, gastric, head and neck, ovarian, renal and overall incident cancer[1]. However, many of these studies were limited by sample size and by their retrospective case-control nature. Recent prospective studies suggest that germline RTL may not be strongly associated with cancer risk but, instead, may be associated with early mortality [27, 28].
Evaluations of “brain and nervous tissue cancer” and RTL were included, to a limited degree, in a large prospective study of leukocyte RTL in 3,142 individuals with cancer from a cohort of 47,102 participants in two Danish cohorts [27]. That study included 65 individuals with brain and nervous tissue cancer. There were no statistically significant associations between RTL and risk of brain and nervous tissue cancer. However, the risk of early death after brain and nervous tissue cancer was increased in individuals with shorter telomeres (hazard ratio 1.52, 95% CI 1.00-2.31) [27].
Our study is the first to specifically evaluate RTL in prospectively collected buccal or leukocyte samples from glioma cases and controls. We did not find an association between overall glioma risk and germline RTL. However, our data suggest that males with short telomeres may be at increased risk of glioma compared with age-matched, cancer-free males. A larger sample size is required before drawing any firm conclusions.
A limitation of our study is that we were underpowered to stratify by tumor subtype. While subtypes of glioma may have different mechanisms of telomere maintenance, it is unclear if that would be reflected in a germline RTL study. Given the nature of glioma case and control sample availability in PLCO, our study is also limited because it included RTL measurements on blood and buccal cell DNA. We used sample source as a matching factor in the study design and performed sensitivity analyses that showed there was no difference in results based on sample source.
The strengths of our study include the well-characterized PLCO cohort, and its prospective nature with biologic samples collected at least two years prior to glioma diagnosis. In summary, our study suggests that germline RTL is not associated with overall glioma risk, but RTL may be associated with glioma in males. Larger studies of telomere biology and specific glioma subtypes are warranted to better understand its etiology and risk factors.
Acknowledgments
We are grateful to the PLCO study participants for their valuable contributions. The PLCO Screening Trial was supported by individual contracts from the NCI to the University of Colorado Denver NO1-CN-25514, Georgetown University NO1-CN-25522, Pacific Health Research Institute NO1-CN-25515, Henry Ford Health System NO1-CN-25512, University of Minnesota, NO1-CN-25513, Washington University NO1-CN-25516, University of Pittsburgh NO1-CN-25511, University of Utah NO1-CN-25524, Marshfield Clinic Research Foundation NO1-CN-25518, University of Alabama at Birmingham NO1-CN-75022, Westat, Inc. NO1-CN-25476, University of California, Los Angeles NO1-CN-25404.
Financial support
This study was supported by the intramural research program of the Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health.
Abbreviations
- RTL
relative telomere length
- PLCO
Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial
- OR
odds ratio
- CI
95% confidence interval
- qPCR
quantitative PCR
Footnotes
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Conflicts of interest
The authors have no potential conflicts of interest.
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