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BMC Medical Genetics logoLink to BMC Medical Genetics
. 2015 Jul 23;16:52. doi: 10.1186/s12881-015-0194-x

Sequence variation in telomerase reverse transcriptase (TERT) as a determinant of risk of cardiovascular disease: the Atherosclerosis Risk in Communities (ARIC) study

Jan Bressler 1, Nora Franceschini 2, Ellen W Demerath 3, Thomas H Mosley 4, Aaron R Folsom 3, Eric Boerwinkle 1,5,
PMCID: PMC4557920  PMID: 26201603

Abstract

Background

Telomerase reverse transcriptase (TERT) maintains telomere ends during DNA replication by catalyzing the addition of short telomere repeats. The expression of telomerase is normally repressed in somatic cells leading to a gradual shortening of telomeres and cellular senescence with aging. Interindividual variation in leukocyte telomere length has been previously associated with susceptibility to cardiovascular disease. The aim of the present study was to determine whether six variants in the TERT gene are associated with risk of incident coronary heart disease, incident ischemic stroke, and mortality in participants in the biracial population-based Atherosclerosis Risk in Communities (ARIC) study, including rs2736100 that was found to influence mean telomere length in a genome-wide analysis.

Methods

ARIC is a prospective study of the etiology and natural history of atherosclerosis in 15,792 individuals aged 45 to 64 years at baseline in 1987–1989. Haplotype tagging SNPs in TERT were genotyped using a custom array containing nearly 49,000 SNPs in 2,100 genes associated with cardiovascular and metabolic phenotypes. Cox proportional hazards models were used to assess the association between the TERT polymorphisms and incident cardiovascular disease and mortality over a 20-year follow-up period in 8,907 whites and 3,022 African-Americans with no history of disease at the baseline examination, while individuals with prevalent cardiovascular disease were not excluded from the analyses of mortality.

Results

After adjustment for age and gender, and assuming an additive genetic model, rs2736122 and rs2853668 were nominally associated with incident coronary heart disease (hazards rate ratio = 1.20, p = 0.02, 95 % confidence interval = 1.03– 1.40) and stroke (hazards rate ratio = 1.17, p = 0.05, 95 % confidence interval = 1.00 - 1.38), respectively, in African-Americans. None of the variants was significantly associated with cardiovascular disease in white study participants or with mortality in either racial group.

Conclusions

Replication in additional population-based samples combined with genotyping of polymorphisms in other genes involved in maintenance of telomere length may help to determine whether genetic variants associated with telomere homeostasis influence the risk of cardiovascular disease in middle-aged adults.

Keywords: Genetic epidemiology, Myocardial infarction, Cerebrovascular stroke, Telomere homeostasis, Cell senescence, Cellular aging

Background

Telomeres are DNA-protein complexes that protect the ends of chromosomes. Telomerase maintains telomere ends during DNA replication by catalyzing the addition of short telomere repeats (TTAGGG). The enzyme is comprised of a protein with reverse transcriptase activity that is encoded by the telomerase reverse transcriptase (TERT) gene, and a telomerase RNA component (TERC) which serves as a template for the telomere repeat after recognition of a single stranded G-rich primer [1]. Expression of telomerase is normally repressed in somatic cells leading to a gradual shortening of telomeres and cellular senescence with aging [2, 3]. Heritability of telomere length in humans has been reported to range from 36 % - 90 % [4, 5].

Leukocyte telomere length has been reported to be associated with susceptibility to cardiovascular disease [6]. When mean telomere length was measured in 10 patients with severe coronary artery disease and compared to that observed for 20 controls, the size was significantly reduced and equivalent to that found in individuals without heart disease who were 9 years older [7]. Significantly shorter telomeres were also detected in leukocyte DNA from 203 subjects who had had a myocardial infarction (MI) before the age of 50 [8], from 620 chronic heart failure patients [9], and from 150 stroke patients [10] when compared to controls. Shorter telomere length has also been reported to be associated with a higher prevalence of both atherothrombotic and hemorrhagic stroke in a Chinese case–control study [11]. Finally, in four prospective studies that evaluated disease incidence, there was an increased risk of coronary artery disease [12], MI [1315], and stroke [13] associated with shorter telomere length, while no association was found with ischemic stroke in either the Nurses’ Health Study or the Physicians’ Health Study [16, 17]. Taken together, these results suggest that variation in telomere length may play a role in the risk and progression of cardiovascular disease. An association between survival and leukocyte telomere length has also been observed in several previous epidemiological studies [1820].

Recently, a single nucleotide polymorphism (SNP) (rs2736100) located within an intron of TERT was significantly associated with mean leukocyte telomere length in a genome-wide association (GWA) study in which 37,684 individuals from fifteen cohorts were included in the discovery set. The estimated per-allele effect of addition of the A allele was 94.2 base pairs, equivalent to 3.14 years of age-related telomere shortening [21]. The aim of the present study was to determine whether six haplotype tagging SNPs located within the TERT gene or the 5’ promoter region including rs2736100 were associated with risk of incident coronary heart disease (CHD), ischemic stroke, and all-cause mortality in participants in the large biracial population-based ARIC cohort. To date, there have been few previous investigations of the role of telomerase variants in cardiovascular disease and its risk factors that have included individuals of African ancestry [22].

Methods

Atherosclerosis Risk in Communities (ARIC) Study

The ARIC study was designed to study the development of atherosclerosis in 15,792 individuals aged 45–64 years. At the time of recruitment in 1987–1989, the participants resided in Forsyth County, North Carolina; Jackson, Mississippi (African-Americans only); northwestern suburbs of Minneapolis, Minnesota; or Washington County, Maryland and were selected by probability sampling. Incident cardiovascular events were ascertained by annual telephone contact, and surveillance of local hospital discharge lists and death records from state vital statistics offices. CHD cases were defined as either fatal CHD or a definite or probable MI. Definite and probable stroke were defined as a rapid focal neurological deficit lasting 24 hours or until death; validation of stroke hospitalization has been described elsewhere [23]. In brief, records for eligible hospitalizations were abstracted by a single trained nurse and classified by a standardized computer algorithm, and were also reviewed by a trained physician. Any disagreements between the computer diagnosis and that of the reviewing physician were adjudicated by a second physician. Incident CHD, ischemic stroke, and death in this study included events from 1987 through December 31, 2011. Individuals were excluded from all of the analyses if they were neither African-American nor white (n = 48); if they were African-Americans from the Minnesota or Maryland field centers (n = 55) due to the small numbers recruited from these sites; or if they did not consent to use or storage of their DNA (n = 44). Participants with prevalent CHD, stroke, or transient ischemic attack were excluded from the analyses of incident CHD and ischemic stroke (n = 1,430) as were those with missing genotype data for all sequence variants (n = 2,206). The final study sample at risk of cardiovascular disease consisted of 8,987 white and 3,022 African-American study participants. Subjects with prevalent CHD or stroke were not excluded from the analyses of all-cause mortality. The study design and methods were approved by the institutional review boards at the collaborating medical centers: University of Mississippi Medical Center Institutional Review Board (Jackson Field Center); Wake Forest University Health Sciences Institutional Review Board (Forsyth County Field Center); University of Minnesota Institutional Review Board (Minnesota Field Center); and the Johns Hopkins School of Public Health Institutional Review Board (Washington County Field Center). Informed consent was provided in writing. A detailed description of the ARIC study has been published previously [24].

TERT polymorphisms and genotyping

Six SNPs either within the TERT gene or the 5-kb proximal promoter region were genotyped as previously described [25]. The TERT SNPs were among a panel of nearly 49,000 SNPs in 2,100 genes associated with cardiovascular and metabolic phenotypes selected for inclusion on the custom Illumina IBC (ITMAT-Broad-CARe) array as part of the shared Candidate Gene Association Resource (CARe) funded by the National Heart, Lung, and Blood Institute [26]. Systematic searching of the PubMed citation database (http://www.ncbi.nlm.nih.gov/pubmed), pathway-based bioinformatics tools, and advance access to the results of findings from GWA studies of diabetes, hypertension, and coronary artery disease were used to develop an initial list of genes that were then prioritized by investigators from the nine cohorts participating in the CARe Consortium. Genes and pathways implicated in cardiovascular disease as well as lipid metabolism, thrombogenesis, insulin resistance, metabolism, inflammation, oxidative stress, and apoptosis were of particular interest in the selection process. For most of the genes on the array including TERT (n = 1,784), haplotype tagging SNPs were selected to capture genetic variation represented in the four HapMap populations [27] and SeattleSNPs [28] resequencing project. Three TERT variants present on the array were excluded from further analysis either because they were monomorphic or did not meet Hardy-Weinberg equilibrium expectations in both whites and African-Americans.

Clinical and laboratory measurements

The clinical and laboratory measurements used for this study were assessed during the first clinical examination in 1987–1989 and have been described previously [29, 30]. Plasma total cholesterol and triglycerides were measured by enzymatic methods and low density lipoprotein (LDL) cholesterol was calculated [31]. High density lipoprotein (HDL) cholesterol was measured after dextran-magnesium precipitation of non-HDL [32]. Blood pressure was measured three times while seated using a random-zero sphygmomanometer and the last two measurements were averaged for analysis. Individuals with diastolic blood pressure ≥ 90 mm Hg, systolic blood pressure ≥140 mm Hg, or who used antihypertensive medication were defined as having hypertension. Fasting serum glucose was measured by a standard hexokinase method on a Coulter DACOS chemistry analyzer (Coulter Instruments, Fullerton, CA). The case definition for diabetes was a fasting glucose level > 7.0 mmol/L, a nonfasting glucose level >11.1 mmol/L, and/or self-reported physician diagnosis or treatment for diabetes. Body weight and other anthropometric variables were measured by trained technicians according to standardized protocols. Body mass index (BMI) was calculated as weight in kilograms/(height in meters)2. Information on cigarette smoking and alcohol consumption was obtained using an interviewer-administered questionnaire, and both smoking and drinking status was classified as current, former, or never.

Statistical analysis

Hardy-Weinberg equilibrium was tested for each SNP separately by race using a χ2 goodness-of-fit test prior to the application of any exclusion criteria. Linkage disequilibrium (LD) was estimated using Haploview version 4.2 [33]. Proportions, mean values, and standard deviations were calculated for clinical and demographic variables relevant to cardiovascular disease. Comparisons between groups were performed using chi square tests for categorical variables and t-tests for continuous variables. Cox proportional hazards models were used to estimate hazard rate ratios (HRR) for incident CHD and ischemic stroke, and for death from all causes for each addition of the minor allele for each SNP. The genotypes for rs2736100 were coded in both races with respect to the allele previously shown to be associated with shorter telomere length [21]. Analyses of rs6863494 were only carried out for African-American study participants since this variant was monomorphic in whites. Regression models were adjusted for either age and gender (model 1), or for age, gender, and a panel of established cardiovascular risk factors including BMI, current smoking, diabetes, hypertension, and HDL and LDL cholesterol (model 2). The proportional hazards assumption was met for all of the TERT SNPs tested individually by race with the exception of rs2736122 (model 1) and rs4246742 (models 1 and 2) when analyzed in whites for association with incident CHD, and rs2853668 (model 1) in the analyses of mortality in whites [34]. In the analyses of CHD and ischemic stroke, follow-up time was calculated from the date of the baseline visit to the date of the first event. For the non-cases, follow-up continued through the date of last contact, or the date of death if the date of last contact had occurred within one year. In the analyses of all-cause mortality, follow-up continued through either the date of death or December 31, 2011. A two-sided p-value of 0.05 was considered statistically significant, and the Bonferroni correction was used to adjust for multiple comparisons. The results are presented separately by self-reported racial group. Power calculations were performed using the Cox regression module of the Power Analysis and Sample Size computer program [35]. Using the observed incidence of CHD and ischemic stroke in each racial group, the allele frequency for each TERT polymorphism in African-Americans and whites, and a Bonferroni corrected p-value of 0.002 (0.05/6 variants x 2 phenotypes x 2 races), there was greater than 90 % statistical power to detect a HRR of ≥ 1.1 for each TERT variant. All of the statistical analyses were performed using Stata version 9.0 (Stata Corporation, College Station, TX).

Results

The allele and genotype frequencies for six TERT polymorphisms evaluated in this study (Table 1) were in accordance with Hardy-Weinberg expectations for both white and African-American study subjects (all p > 0.05). When LD was estimated for these variants, the SNPs were not highly correlated for either white or African-American study participants (all r2 < 0.15) (Table 2). A description of the study sample at the first clinical visit stratified by race is shown in Table 3. There were 403 incident CHD cases (13.3 %) and 287 ischemic stroke cases (9.5 %) ascertained in African-American subjects during an average follow-up period of 20.0 years, and 933 CHD cases (10.4 %) and 452 stroke cases (5.0 %) identified in whites during an average follow-up period of 20.4 years. All of the clinical and demographic characteristics differed significantly between white and African-American participants with the exception of the levels of total and LDL cholesterol.

Table 1.

TERT genotype and allele frequencies stratified by race. ARIC study (1987–1989)

African-American MAF White MAF p
dbSNP ID N % N %
rs2736122
GG 1,857 56.1 0.25 5,283 53.8 0.27 0.04
AG 1,246 37.7 3,835 39.1
AA 205 6.2 698 7.1
rs4246742
TT 1,444 43.5 0.35 7,037 71.6 0.15 <0.01
AT 1,453 43.8 2,549 25.9
AA 421 12.7 241 2.5
rs6863494
TT 2,950 90.3 0.05 9,823 100..0 0.00 <0.01
CT 305 9.3 2 0.0
CC 13 0.4 0 0.0
rs4975605
CC 1,012 30.6 0.45 2,742 27.9 0.47 <0.01
AC 1,619 48.9 4,861 49.5
AA 679 20.5 2,218 22.6
rs2736100*
CC 683 20.6 0.54 2,533 25.8 0.49 <0.01
CA 1,661 50.0 4,932 50.2
AA 975 29.4 2,361 24.0
rs2853668
GG 841 25.3 0.50 5,432 55.3 0.26 <0.01
TG 1,647 49.6 3,707 37.7
TT 831 25.1 688 7.0

dbSNP, The National Center for Biotechnology Information’s SNP database; SNP, single nucleotide polymorphism; ID, identification; N, number; MAF, minor allele frequency; p, p-value for difference in genotype frequencies between racial groups evaluated by Pearson’s chi-squared test; *A allele previously associated with shorter telomere length [21]

Table 2.

Linkage disequilibrium between TERT single nucleotide polymorphisms

LD TERT SNP
r2, White rs2736122 rs4246742 rs6863494* rs4975605 rs2736100 rs2853668
rs2736122 x 0.053 --- 0.062 0.058 0.021
rs4246742 0.053 x --- 0.09 0.005 0.006
rs6863494 x
rs4975605 0.062 0.09 --- x 0.04 0.034
rs2736100 0.058 0.005 --- 0.04 x 0.13
rs2853668 0.021 0.006 --- 0.034 0.13 x
r2, African-American rs2736122 rs4246742 rs6863494 rs4975605 rs2736100 rs2853668
rs2736122 x 0.001 0.011 0.052 0.001 0.016
rs4246742 0.001 x 0.097 0.047 0.015 0.001
rs6863494 0.011 0.097 x 0.032 0.024 0.004
rs4975605 0.052 0.047 0.032 x 0.021 0.011
rs2736100 0.001 0.015 0.024 0.021 x 0.023
rs2853668 0.016 0.001 0.004 0.011 0.023 x

LD, linkage disequilibrium; SNP, single nucleotide polymorphism; *rs6863494 is monomorphic in whites

Table 3.

Race-specific clinical and demographic characteristics. ARIC participants free of CVD (1987 – 1989)

N AA N White p
(N = 3,022) (N = 8,987)
N (%) N (%)
Male 3,022 1,081 (35.8) 8,987 4,030 (44.8) <0.001
Current smokers 3,020 857 (28.4) 8,984 2,145 (23.9) <0.001
Current alcohol 2,994 951 (31.8) 8,975 5,909 (65.8) <0.001
Hypertension 3,009 1,613 (53.6) 8,953 2,250 (25.1) <0.001
Diabetes 2,953 532 (18.0) 8,972 715 (8.0) <0.001
Incident MI/Fatal CHD 3,022 403 (13.3) 8,987 933 (10.4) <0.001
Incident ischemic stroke 3,022 287 (9.5) 8,987 452 (5.0) <0.001
Mean (SD) Mean (SD)
Age (years) 3,022 53.1 (5.7) 8,987 54.1 (5.7) <0.001
DBP, mm Hg 3,022 79.6 (11.8) 8,983 71.6 (10.0) <0.001
SBP, mm Hg 3,022 127.8 (20.3) 8,984 118.2 (16.9) <0.001
Glucose (mmol/L) 2,941 6.4 (3.0) 8,980 5.8 (1.6) <0.001
Insulin (pmol/L) 2,941 138.0 (291.4) 8,979 81.4 (94.9) <0.001
BMI (kg/m2) 3,019 29.7 (6.1) 8,980 26.9 (4.8) <0.001
Total cholesterol, mmol/L 2,895 5.6 (1.2) 8,971 5.5 (1.0) 0.503
LDL cholesterol, mmol/L 2,870 3.6 (1.1) 8,832 3.5 (1.0) 0.281
HDL cholesterol, mmol/L 2,895 1.4 (0.4) 8,973 1.3 (0.4) <0.001
Triglycerides, mmol/L 2,896 1.3 (0.9) 8,973 1.5 (1.0) <0.001

CVD, cardiovascular disease; N, number; AA, African-American; p, p-value for tests of differences of group means determined by t-tests or of categorical values evaluated by Pearson’s chi-squared test between racial groups; MI, myocardial infarction; CHD, coronary heart disease; DBP, diastolic blood pressure; SBP, systolic blood pressure; BMI, body mass index; LDL, low density lipoprotein; HDL, high density lipoprotein

The results of the analysis of the association between the TERT sequence variants and incident CHD and ischemic stroke are displayed in Tables 4 and 5, respectively. SNP rs2736122 was nominally associated with incident CHD in African-Americans both in the minimally adjusted Cox regression model (HRR = 1.20, p = 0.02, 95 % confidence interval (CI) = 1.03 – 1.40) and in a second model that was further adjusted for a panel of established cardiovascular risk factors (HRR = 1.18, p = 0.04, 95 % CI = 1.01 – 1.39). Similarly, one of the genetic variants was nominally associated with incident ischemic stroke (rs2853668) in African-Americans in a model adjusted for age and gender (HRR = 1.17, p = 0.05, 95 % CI = 1.00 – 1.38), but this relationship was attenuated after BMI, current smoking, and diabetes and hypertension case status were added to the regression models. There were also 1,203 (36.2 %) and 2,875 deaths (29.3 %) among African-American and white participants, respectively, during the mean 20.5-year follow-up period. All-cause mortality was assessed but no association with any of the TERT sequence variants was found for either racial group (all p > 0.15) (Table 6). None of the associations described above remained significant after correction for multiple comparisons.

Table 4.

TERT sequence variation and incident coronary heart disease. ARIC study (1987 – 2011)

African-American (N = 3,022) (MI/Fatal CHD = 403) White (N = 8,987) (MI/Fatal CHD =933)
Model 1 Model 2 Model 1 Model 2
dbSNP ID HRR 95 % CI p HRR 95 % CI p HRR 95 % CI p HRR 95 % CI p
rs2736122*
CHD 1.20 1.03, 1.40 0.02 1.18 1.01, 1.39 0.04 0.95 0.86, 1.06 0.38 0.94 0.85, 1.05 0.29
rs4246742*
CHD 1.00 0.87, 1.15 0.97 0.98 0.85, 1.14 0.83 0.96 0.85, 1.09 0.56 0.99 0.87, 1.13 0.88
rs6863494
CHD 0.93 0.67,1.29 0.66 0.95 0.68, 1.32 0.77 -- --
rs4975605
CHD 1.04 0.91, 1.19 0.55 1.05 0.91, 1.20 0.52 1.02 0.94, 1.12 0.61 1.02 0.93, 1.11 0.74
rs2736100
CHD 0.99 0.86, 1.14 0.89 1.00 0.86, 1.15 0.97 0.97 0.88, 1.06 0.48 0.98 0.89, 1.07 0.60
rs2853668
CHD 0.93 0.81, 1.07 0.32 0.98 0.84, 1.13 0.73 1.05 0.95, 1.16 0.35 1.07 0.97, 1.19 0.19

dbSNP, The National Center for Biotechnology Information’s SNP database; SNP, single nucleotide polymorphism; ID, identification; N, number; HRR, hazard rate ratio; CI, confidence interval; p, p-value for hazard rate ratios from Cox regression models; MI, myocardial infarction; CHD, coronary heart disease; Model 1, adjusted for age and gender; Model 2, adjusted for age, gender, BMI, current smoking, diabetes, hypertension, HDL cholesterol, and LDL cholesterol; *not consistent with proportional hazards assumptions in whites for rs2736122 (Model 1) and rs4246742 (Models 1 and 2)

Table 5.

TERT sequence variation and incident ischemic stroke. ARIC study (1987 – 2011)

African-American (N = 3,022) (Ischemic Stroke = 287) White (N = 8,987 ) (Ischemic Stroke = 452)
Model 1 Model 2 Model 1 Model 2
dbSNP ID HRR 95 % CI p HRR 95 % CI p HRR 95 % CI p HRR 95 % CI p
rs2736122
Isch. stroke 0.89 0.73, 1.08 0.24 0.90 0.74, 1.10 0.32 1.01 0.87, 1.17 0.89 1.02 0.87, 1.18 0.82
rs4246742
Isch. stroke 0.94 0.79, 1.11 0.47 0.96 0.80, 1.15 0.67 0.99 0.82, 1.18 0.89 1.00 0.83, 1.21 0.99
rs6863494
Isch. stroke 0.90 0.61, 1.33 0.59 0.96 0.65, 1.42 0.84 -- --
rs4975605
Isch. stroke 0.94 0.80, 1.11 0.48 0.88 0.74, 1.04 0.14 1.00 0.88, 1.14 0.97 1.00 0.87, 1.14 0.98
rs2736100
Isch. stroke 1.07 0.91, 1.27 0.41 1.03 0.86, 1.22 0.75 0.93 0.82, 1.06 0.31 0.93 0.81, 1.06 0.27
rs2853668
Isch. stroke 1.17 1.00, 1.38 0.05 1.08 0.91, 1.28 0.36 1.02 0.88, 1.18 0.76 1.03 0.89, 1.20 0.71

dbSNP, The National Center for Biotechnology Information’s SNP database; SNP, single nucleotide polymorphism; ID, identification; N, number; HRR, hazard rate ratio; CI, confidence interval; p, p-value for hazard rate ratios from Cox regression models; Model 1, adjusted for age and gender; Model 2, adjusted for age, gender, BMI, current smoking, diabetes, hypertension, HDL cholesterol, LDL cholesterol; Isch., ischemic

Table 6.

TERT sequence variation and all-cause mortality. ARIC study (1987 – 2011)

African-American (N = 3,319) (Deaths = 1,203) White (N = 9,827) (Deaths = 2,875)
Model 1 Model 2 Model 1 Model 2
dbSNP ID HRR 95 % CI p HRR 95 % CI p HRR 95 % CI p HRR 95 % CI p
rs2736122
Mortality 1.05 0.95, 1.15 0.36 1.04 0.94, 1.14 0.47 1.04 0.98, 1.10 0.22 1.03 0.97, 1.10 0.27
rs4246742
Mortality 0.99 0.91, 1.08 0.85 0.99 0.90, 1.08 0.76 1.01 0.94, 1.08 0.80 1.02 0.95, 1.09 0.63
rs6863494
Mortality 1.00 0.84, 1.20 0.96 1.00 0.84, 1.20 0.96 -- --
rs4975605
Mortality 0.96 0.89, 1.04 0.37 0.94 0.87, 1.02 0.16 1.00 0.95, 1.05 0.96 0.99 0.94, 1.04 0.74
rs2736100
Mortality 1.00 0.92, 1.09 0.93 0.98 0.90, 1.07 0.73 1.03 0.98, 1.09 0.21 1.03 0.97, 1.08 0.32
rs2853668*
Mortality 1.00 0.92, 1.09 0.94 0.97 0.89, 1.05 0.44 0.99 0.93, 1.05 0.73 1.02 0.96, 1.08 0.62

dbSNP, The National Center for Biotechnology Information’s SNP database; SNP, single nucleotide polymorphism; ID, identification; N, number; HRR, hazard rate ratio; CI, confidence interval; p, p-value for hazard rate ratios from Cox regression models; Model 1, adjusted for age and gender; Model 2, adjusted for age, gender, BMI, current smoking, diabetes, hypertension, HDL cholesterol, LDL cholesterol; * not consistent with proportional hazards assumptions in whites for rs2853668 (Model 1)

Discussion

A functional role for telomerase in the maintenance of telomere length has been established both in vitro and in vivo, including in the heart [36]. In an early test of the proposed causal relationship between telomere attrition and cellular senescence, retinal pigment epithelial cells and foreskin fibroblasts that do not normally express telomerase were transfected with the enzyme’s catalytic subunit. The telomerase positive clones exhibited elongated telomeres and exceeded their normal life span by more than 20 cell divisions [37]. Similarly, restoration of telomerase activity in Terc-deficient mice resulted in longer telomeres and absence of premature aging [38], and alleviated the tissue degeneration and activation of DNA damage signaling that are characteristic consequences of telomere loss [39]. Forced expression of TERT in cardiac muscle in mice promoted cell proliferation and cardiac myocyte survival, suggesting a possible strategy for organ regeneration after injury [40].

Leukocyte telomere length has been shown to be associated with cardiovascular disease risk in some but not all studies [717]. In the current study, a nominal association between rs2736122 and incident CHD in the fully adjusted model (HRR = 1.18, p = 0.04, 95 % CI = 1.01– 1.39), and rs2853668 and incident ischemic stroke in a regression model adjusted only for age and gender (HRR = 1.17, p = 0.05, 95 % CI = 1.00 – 1.38) was detected in African-American ARIC study participants. These observations are in accordance with an earlier report that 5 TERT SNPs including rs2736100 and rs4975605, and 2 variants including rs2853668 were associated with risk of incident nonfatal MI and ischemic stroke, respectively, in 23,294 individuals of European ancestry enrolled in the Women’s Genome Health Study (WGHS) [41]. However, rs2853668 was associated with a reduced susceptibility to ischemic stroke in the WGHS (HRR (stroke) = 0.81, p = 0.03, 95 % CI = 0.66 – 0.98) after adjustment for age, BMI, smoking, diabetes, hypertension, and hormone use while the same variant increased risk in the ARIC study. Although there was adequate power to detect the same HRR observed by Zee et al., none of the three polymorphisms found to be associated with cardiovascular disease in the WGHS that were also genotyped in the ARIC study (rs2736100, rs4975605, rs2853668) [41] were associated with stroke or CHD in white study participants. Other reasons for the discordant findings could be associations that were found by chance in either or both cohorts, as well as differences in ascertainment since WGHS included only nonfatal MI cases in the analyses while the ARIC study case definition encompassed both MI and fatal CHD.

Although the observed associations between the TERT variants and both CHD and stroke were modest in African Americans and were no longer significant after correction for multiple testing, differences in LD could contribute to the absence of an association in whites if a true causative variant was only correlated with rs2736122 or rs285366 in African-Americans. Inspection of the LD plots generated at the TERT locus for the Utah residents with Northern and European ancestry (CEU) and African ancestry in Southwest USA (ASW) populations included in the International HapMap Project reveals that the race-specific LD patterns are not identical, with the caveat that this region has not been densely genotyped (HapMap3 Genome Browser release #2, chromosome 5: positions 1,306,287 – 1,348,162) [27]. Similarly, variation in linkage disequilibrium structure between whites and African-Americans could also explain the reversal in the direction of association of rs2853668 with incident ischemic stroke seen in the ARIC study when compared with the WGHS. Assuming that rs2853668 may not be the causal variant in either cohort, correlation between the polymorphism and a protective allele at another locus in WGHS participants, and with a risk allele in ARIC participants could lead to the observed results [42]. Other reasons for the discrepancy could include chance, differences in allele frequency for the rs2853668 T allele in the two racial groups, and variation in other genetic or environmental factors that may contribute to cerebrovascular disease risk in the two study populations. The TERT rs2736100 variant was not associated with incident CHD or stroke in either racial group. In the GWA study of telomere length in which rs2736100 was identified, there was also no relationship between this variant and prevalent coronary artery disease in a meta-analysis that combined the results for 22,233 cases and 64,762 controls of European ancestry who were enrolled in the CARDIoGRAM consortium but did not include individuals of African descent [21, 43].

The relationship between telomere length and aging and longevity has also been assessed. A negative correlation between telomere length and age has been consistently observed when examined in multiple tissues [3, 4447]. More recently, telomere length was positively correlated with increased lifespan in the Amish Family Osteoporosis Study [18], and Fitzpatrick et al. reported that individuals in the shortest quartile of leukocyte telomere length in the Cardiovascular Health Study were more likely to die than those in the longest quartile during a 6.1-year follow-up period [20]. In contrast, Bischoff et al. found no correlation between telomere length and survival in a sample of 812 individuals from 3 different Danish study populations [48]. Similar results were reported in the Scottish Lothian Birth Cohort [49], and in a study of 3,075 participants in the population-based Health ABC Study aged 70–79 years in which neither overall survival or death from cardiovascular disease was associated with telomere length [50]. While an association between two polymorphisms in oligonucleotide/oligosaccharide-binding fold containing 1(OBFC1), a gene related to telomere length [51], and decreased risk of cardiovascular death was demonstrated in women in the Cardiovascular Health Study [52], none of the TERT sequence variants examined here had a discernible effect on the time to death in ARIC study participants.

For all of the statistical analyses described above, it is possible that, although there was only a marginal effect on the risk of developing cardiovascular disease when the TERT polymorphisms were considered individually, the polymorphisms may play a role in combination with other loci associated with variation in telomere length as demonstrated by Codd et al. in a genetic risk score analysis for coronary artery disease [21]. In addition, since the association between the TERT polymorphisms and telomere length could not be evaluated in the ARIC study, a link between increased risk of cardiovascular disease and the possible functional impact of the gene could not be explored further. It should also be noted that since several risk factors for cardiovascular disease including obesity and smoking have been shown to be associated with telomere length in leukocytes [53], differences in the distribution of these covariates between populations or racial and ethnic groups could result in inconsistencies in the reported relationship between TERT and a given disease outcome. Further investigation of sequence variation in TERC [54] as well as other genes such as OBFC1, CTS telomere maintenance complex component 1 (CTC1), and zinc finger protein 676 (ZNF676) that have been identified and replicated in large-scale GWA studies of telomere length [51, 55] but were not present on the genotyping array may also prove to be informative in the ARIC cohort.

Conclusions

The association between six TERT polymorphisms that tag the variation in this gene and development of MI and ischemic stroke over a 20-year follow-up period was examined in white and African-American ARIC study participants with no prior history of disease. After adjustment for age and gender, rs2736122 and rs2853668 were nominally associated with incident CHD and stroke, respectively, in African-Americans but not in whites. The results suggest that interindividual variation in a gene implicated in cellular aging may be associated with cardiovascular disease, and that replication in other population-based cohort studies is warranted.

Acknowledgements

The Atherosclerosis Risk in Communities Study is carried out as a collaborative study supported by National Heart, Lung, and Blood Institute contracts (HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, and HHSN268201100012C), and the National Genome Research Institute contract U01-HG-004402, and National Institutes of Health contract HHSN268200625226C. The authors thank the staff and participants of the ARIC study for their important contributions. Infrastructure was partly supported by Grant Number UL1RR025005, a component of the National Institutes of Health and NIH Roadmap for Medical Research.

Abbreviations

ARIC

Atherosclerosis Risk in Communities

BMI

Body mass index

CARe

Candidate Gene Association Resource

CHD

Coronary heart disease

GWA

Genome-wide association

HDL

High density lipoprotein

HRR

Hazard rate ratio

IBC

ITMAT-Broad-CARe

LD

Linkage disequilibrium

LDL

Low density lipoprotein

MI

Myocardial infarction

OBFC1

Oligonucleotide/oligosaccharide-binding fold containing 1

SNP

Single nucleotide polymorphism

TERC

Telomerase RNA component

TERT

Telomerase reverse transcriptase

WGHS

Women’s Genome Health Study

Footnotes

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

JB performed the statistical analysis, participated in study design, and drafted the manuscript. NF participated in study design and data interpretation, and helped draft the manuscript. EWD participated in study design and data interpretation, and helped draft the manuscript. THM participated in study design and data interpretation, and helped draft the manuscript. ARF participated in study design and data interpretation, and helped draft the manuscript. EB conceived of the study, participated in study design and data interpretation, and helped draft the manuscript. All authors read and approved the final manuscript.

Contributor Information

Jan Bressler, Email: Jan.Bressler@uth.tmc.edu.

Nora Franceschini, Email: noraf@unc.edu.

Ellen W. Demerath, Email: ewd@umn.edu

Thomas H. Mosley, Email: tmosley@umc.edu

Aaron R. Folsom, Email: folsom@epi.umn.edu

Eric Boerwinkle, Phone: (713) 500-9816, Email: Eric.Boerwinkle@uth.tmc.edu.

References

  • 1.Morin GB. The human telomere terminal transferase enzyme is a ribonucleoprotein that synthesizes TTAGGG repeats. Cell. 1989;59(3):521–529. doi: 10.1016/0092-8674(89)90035-4. [DOI] [PubMed] [Google Scholar]
  • 2.Harley CB, Futcher AB, Greider CW. Telomeres shorten during ageing of human fibroblasts. Nature. 1990;345(6274):458–460. doi: 10.1038/345458a0. [DOI] [PubMed] [Google Scholar]
  • 3.Hastie ND, Dempster M, Dunlop MG, Thompson AM, Green DK, Allshire RC. Telomere reduction in human colorectal carcinoma and with ageing. Nature. 1990;346(6287):866–868. doi: 10.1038/346866a0. [DOI] [PubMed] [Google Scholar]
  • 4.Vasa-Nicotera M, Brouilette S, Mangino M, Thompson JR, Braund P, Clemitson JR, et al. Mapping of a major locus that determines telomere length in humans. Am J Hum Genet. 2005;76(1):147–151. doi: 10.1086/426734. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Andrew T, Aviv A, Falchi M, Surdulescu GL, Gardner JP, Lu X, et al. Mapping genetic loci that determine leukocyte telomere length in a large sample of unselected female sibling pairs. Am J Hum Genet. 2006;78(3):480–486. doi: 10.1086/500052. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Serrano AL, Andres V. Telomeres and cardiovascular disease: does size matter? Circ Res. 2004;94(5):575–584. doi: 10.1161/01.RES.0000122141.18795.9C. [DOI] [PubMed] [Google Scholar]
  • 7.Samani NJ, Boultby R, Butler R, Thompson JR, Goodall AH. Telomere shortening in atherosclerosis. Lancet. 2001;358(9280):472–473. doi: 10.1016/S0140-6736(01)05633-1. [DOI] [PubMed] [Google Scholar]
  • 8.Brouilette S, Singh RK, Thompson JR, Goodall AH, Samani NJ. White cell telomere length and risk of premature myocardial infarction. Arterioscler, Thromb, Vasc Biol. 2003;23(5):842–846. doi: 10.1161/01.ATV.0000067426.96344.32. [DOI] [PubMed] [Google Scholar]
  • 9.van der Harst P, van der Steege G, de Boer RA, Voors AA, Hall AS, Mulder MJ, et al. Telomere length of circulating leukocytes is decreased in patients with chronic heart failure. J Am Coll Cardiol. 2007;49(13):1459–1464. doi: 10.1016/j.jacc.2007.01.027. [DOI] [PubMed] [Google Scholar]
  • 10.Jiang X, Dong M, Cheng J, Huang S, He Y, Ma K, et al. Decreased leukocyte telomere length (LTL) is associated with stroke but unlikely to be causative. PLoS One. 2013;8(7):e68254. doi: 10.1371/journal.pone.0068254. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Zhang W, Chen Y, Wang Y, Liu P, Zhang M, Zhang C, et al. Short telomere length in blood leucocytes contributes to the presence of atherothrombotic stroke and haemorrhagic stroke and risk of post-stroke death. Clin Sci. 2013;125(1):27–36. doi: 10.1042/CS20120691. [DOI] [PubMed] [Google Scholar]
  • 12.Brouilette SW, Moore JS, McMahon AD, Thompson JR, Ford I, Shepherd J, et al. Telomere length, risk of coronary heart disease, and statin treatment in the West of Scotland Primary Prevention Study: a nested case–control study. Lancet. 2007;369(9556):107–114. doi: 10.1016/S0140-6736(07)60071-3. [DOI] [PubMed] [Google Scholar]
  • 13.Fitzpatrick AL, Kronmal RA, Gardner JP, Psaty BM, Jenny NS, Tracy RP, et al. Leukocyte telomere length and cardiovascular disease in the cardiovascular health study. Am J Epidemiol. 2007;165(1):14–21. doi: 10.1093/aje/kwj346. [DOI] [PubMed] [Google Scholar]
  • 14.Zee RY, Michaud SE, Germer S, Ridker PM. Association of shorter mean telomere length with risk of incident myocardial infarction: a prospective, nested case–control approach. Clinica chimica acta; international journal of clinical chemistry. 2009;403(1–2):139–141. doi: 10.1016/j.cca.2009.02.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Weischer M, Bojesen SE, Cawthon RM, Freiberg JJ, Tybjaerg-Hansen A, Nordestgaard BG. Short telomere length, myocardial infarction, ischemic heart disease, and early death. Arterioscler, Thromb, Vasc Biol. 2012;32(3):822–829. doi: 10.1161/ATVBAHA.111.237271. [DOI] [PubMed] [Google Scholar]
  • 16.Schurks M, Prescott J, Dushkes R, De Vivo I, Rexrode KM. Telomere length and ischaemic stroke in women: a nested case–control study. European journal of neurology : the official journal of the European Federation of Neurological Societies. 2013;20(7):1068–1074. doi: 10.1111/ene.12135. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Zee RY, Castonguay AJ, Barton NS, Ridker PM. Relative leukocyte telomere length and risk of incident ischemic stroke in men: a prospective, nested case–control approach. Rejuvenation Res. 2010;13(4):411–414. doi: 10.1089/rej.2009.0975. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Njajou OT, Cawthon RM, Damcott CM, Wu SH, Ott S, Garant MJ, et al. Telomere length is paternally inherited and is associated with parental lifespan. Proc Natl Acad Sci U S A. 2007;104(29):12135–12139. doi: 10.1073/pnas.0702703104. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Cawthon RM, Smith KR, O’Brien E, Sivatchenko A, Kerber RA. Association between telomere length in blood and mortality in people aged 60 years or older. Lancet. 2003;361(9355):393–395. doi: 10.1016/S0140-6736(03)12384-7. [DOI] [PubMed] [Google Scholar]
  • 20.Fitzpatrick AL, Kronmal RA, Kimura M, Gardner JP, Psaty BM, Jenny NS, et al. Leukocyte telomere length and mortality in the Cardiovascular Health Study. J Gerontol A Biol Sci Med Sci. 2011;66(4):421–429. doi: 10.1093/gerona/glq224. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Codd V, Nelson CP, Albrecht E, Mangino M, Deelen J, Buxton JL, et al. Identification of seven loci affecting mean telomere length and their association with disease. Nat Genet. 2013;45(4):422–427. doi: 10.1038/ng.2528. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Roberts JD, Dewland TA, Longoria J, Fitzpatrick AL, Ziv E, Hu D, et al. Telomere length and the risk of atrial fibrillation: insights into the role of biological versus chronological aging. Circ Arrhythm Electrophysiol. 2014;7(6):1026–1032. doi: 10.1161/CIRCEP.114.001781. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Rosamond WD, Folsom AR, Chambless LE, Wang CH, McGovern PG, Howard G, et al. Stroke incidence and survival among middle-aged adults: 9-year follow-up of the Atherosclerosis Risk in Communities (ARIC) cohort. Stroke; a journal of cerebral circulation. 1999;30(4):736–743. doi: 10.1161/01.STR.30.4.736. [DOI] [PubMed] [Google Scholar]
  • 24.The ARIC investigators. The Atherosclerosis Risk in Communities (ARIC) Study: design and objectives. American journal of epidemiology 1989, 129(4):687–702. [PubMed]
  • 25.Musunuru K, Lettre G, Young T, Farlow DN, Pirruccello JP, Ejebe KG, et al. Candidate gene association resource (CARe): design, methods, and proof of concept. Circ Cardiovasc Genet. 2010;3(3):267–275. doi: 10.1161/CIRCGENETICS.109.882696. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Keating BJ, Tischfield S, Murray SS, Bhangale T, Price TS, Glessner JT, et al. Concept, design and implementation of a cardiovascular gene-centric 50 k SNP array for large-scale genomic association studies. PLoS One. 2008;3(10):e3583. doi: 10.1371/journal.pone.0003583. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.International HapMap C, Frazer KA, Ballinger DG, Cox DR, Hinds DA, Stuve LL, et al. A second generation human haplotype map of over 3.1 million SNPs. Nature. 2007;449(7164):851–861. doi: 10.1038/nature06258. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Crawford DC, Carlson CS, Rieder MJ, Carrington DP, Yi Q, Smith JD, et al. Haplotype diversity across 100 candidate genes for inflammation, lipid metabolism, and blood pressure regulation in two populations. Am J Hum Genet. 2004;74(4):610–622. doi: 10.1086/382227. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Bressler J, Kao WH, Pankow JS, Boerwinkle E. Risk of type 2 diabetes and obesity is differentially associated with variation in FTO in whites and African-Americans in the ARIC study. PLoS One. 2010;5(5):e10521. doi: 10.1371/journal.pone.0010521. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Morrison AC, Bray MS, Folsom AR, Boerwinkle E. ADD1 460 W allele associated with cardiovascular disease in hypertensive individuals. Hypertension. 2002;39(6):1053–1057. doi: 10.1161/01.HYP.0000019128.94483.3A. [DOI] [PubMed] [Google Scholar]
  • 31.Siedel J, Hagele EO, Ziegenhorn J, Wahlefeld AW. Reagent for the enzymatic determination of serum total cholesterol with improved lipolytic efficiency. Clin Chem. 1983;29(6):1075–1080. [PubMed] [Google Scholar]
  • 32.Warnick GR, Benderson J, Albers JJ. Dextran sulfate-Mg2+ precipitation procedure for quantitation of high-density-lipoprotein cholesterol. Clin Chem. 1982;28(6):1379–1388. [PubMed] [Google Scholar]
  • 33.Barrett JC, Fry B, Maller J, Daly MJ. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics. 2005;21(2):263–265. doi: 10.1093/bioinformatics/bth457. [DOI] [PubMed] [Google Scholar]
  • 34.Grambsch PM, Therneau TM. Proportional hazards tests and diagnostics based on weighted residuals. Biometrika. 1994;81(3):515–526. doi: 10.1093/biomet/81.3.515. [DOI] [Google Scholar]
  • 35.Hintze J. Power Analysis and Sample Size (PASS) 11. Kaysville UT: NCSS, LLC; 2011. [Google Scholar]
  • 36.Moslehi J, DePinho RA, Sahin E. Telomeres and mitochondria in the aging heart. Circ Res. 2012;110(9):1226–1237. doi: 10.1161/CIRCRESAHA.111.246868. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Bodnar AG, Ouellette M, Frolkis M, Holt SE, Chiu CP, Morin GB, et al. Extension of life-span by introduction of telomerase into normal human cells. Science. 1998;279(5349):349–352. doi: 10.1126/science.279.5349.349. [DOI] [PubMed] [Google Scholar]
  • 38.Samper E, Flores JM, Blasco MA. Restoration of telomerase activity rescues chromosomal instability and premature aging in Terc−/− mice with short telomeres. EMBO Rep. 2001;2(9):800–807. doi: 10.1093/embo-reports/kve174. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Jaskelioff M, Muller FL, Paik JH, Thomas E, Jiang S, Adams AC, et al. Telomerase reactivation reverses tissue degeneration in aged telomerase-deficient mice. Nature. 2011;469(7328):102–106. doi: 10.1038/nature09603. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Oh H, Taffet GE, Youker KA, Entman ML, Overbeek PA, Michael LH, et al. Telomerase reverse transcriptase promotes cardiac muscle cell proliferation, hypertrophy, and survival. Proc Natl Acad Sci U S A. 2001;98(18):10308–10313. doi: 10.1073/pnas.191169098. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Zee RY, Ridker PM, Chasman DI. Genetic variants in eleven telomere-associated genes and the risk of incident cardio/cerebrovascular disease: The Women’s Genome Health Study. Clinica chimica acta; international journal of clinical chemistry. 2011;412(1–2):199–202. doi: 10.1016/j.cca.2010.10.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Lin PI, Vance JM, Pericak-Vance MA, Martin ER. No gene is an island: the flip-flop phenomenon. Am J Hum Genet. 2007;80(3):531–538. doi: 10.1086/512133. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Preuss M, Konig IR, Thompson JR, Erdmann J, Absher D, Assimes TL, et al. Design of the Coronary ARtery DIsease Genome-Wide Replication And Meta-Analysis (CARDIoGRAM) Study: A Genome-wide association meta-analysis involving more than 22 000 cases and 60 000 controls. Circ Cardiovasc Genet. 2010;3(5):475–483. doi: 10.1161/CIRCGENETICS.109.899443. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Frenck RW, Jr, Blackburn EH, Shannon KM. The rate of telomere sequence loss in human leukocytes varies with age. Proc Natl Acad Sci U S A. 1998;95(10):5607–5610. doi: 10.1073/pnas.95.10.5607. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Melk A, Ramassar V, Helms LM, Moore R, Rayner D, Solez K, et al. Telomere shortening in kidneys with age. Journal of the American Society of Nephrology : JASN. 2000;11(3):444–453. doi: 10.1681/ASN.V113444. [DOI] [PubMed] [Google Scholar]
  • 46.Benetos A, Okuda K, Lajemi M, Kimura M, Thomas F, Skurnick J, et al. Telomere length as an indicator of biological aging: the gender effect and relation with pulse pressure and pulse wave velocity. Hypertension. 2001;37(2 Pt 2):381–385. doi: 10.1161/01.HYP.37.2.381. [DOI] [PubMed] [Google Scholar]
  • 47.Ishii A, Nakamura K, Kishimoto H, Honma N, Aida J, Sawabe M, et al. Telomere shortening with aging in the human pancreas. Exp Gerontol. 2006;41(9):882–886. doi: 10.1016/j.exger.2006.06.036. [DOI] [PubMed] [Google Scholar]
  • 48.Bischoff C, Petersen HC, Graakjaer J, Andersen-Ranberg K, Vaupel JW, Bohr VA, et al. No association between telomere length and survival among the elderly and oldest old. Epidemiology. 2006;17(2):190–194. doi: 10.1097/01.ede.0000199436.55248.10. [DOI] [PubMed] [Google Scholar]
  • 49.Harris SE, Deary IJ, MacIntyre A, Lamb KJ, Radhakrishnan K, Starr JM, et al. The association between telomere length, physical health, cognitive ageing, and mortality in non-demented older people. Neurosci Lett. 2006;406(3):260–264. doi: 10.1016/j.neulet.2006.07.055. [DOI] [PubMed] [Google Scholar]
  • 50.Njajou OT, Hsueh WC, Blackburn EH, Newman AB, Wu SH, Li R, et al. Association between telomere length, specific causes of death, and years of healthy life in health, aging, and body composition, a population-based cohort study. J Gerontol A Biol Sci Med Sci. 2009;64(8):860–864. doi: 10.1093/gerona/glp061. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.Levy D, Neuhausen SL, Hunt SC, Kimura M, Hwang SJ, Chen W, et al. Genome-wide association identifies OBFC1 as a locus involved in human leukocyte telomere biology. Proc Natl Acad Sci U S A. 2010;107(20):9293–9298. doi: 10.1073/pnas.0911494107. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52.Burnett-Hartman AN, Fitzpatrick AL, Kronmal RA, Psaty BM, Jenny NS, Bis JC, et al. Telomere-associated polymorphisms correlate with cardiovascular disease mortality in Caucasian women: the Cardiovascular Health Study. Mech Ageing Dev. 2012;133(5):275–281. doi: 10.1016/j.mad.2012.03.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.Valdes AM, Andrew T, Gardner JP, Kimura M, Oelsner E, Cherkas LF, et al. Obesity, cigarette smoking, and telomere length in women. Lancet. 2005;366(9486):662–664. doi: 10.1016/S0140-6736(05)66630-5. [DOI] [PubMed] [Google Scholar]
  • 54.Codd V, Mangino M, van der Harst P, Braund PS, Kaiser M, Beveridge AJ, et al. Common variants near TERC are associated with mean telomere length. Nat Genet. 2010;42(3):197–199. doi: 10.1038/ng.532. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55.Mangino M, Hwang SJ, Spector TD, Hunt SC, Kimura M, Fitzpatrick AL, et al. Genome-wide meta-analysis points to CTC1 and ZNF676 as genes regulating telomere homeostasis in humans. Hum Mol Genet. 2012;21(24):5385–5394. doi: 10.1093/hmg/dds382. [DOI] [PMC free article] [PubMed] [Google Scholar]

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