Telomere length is emerging as a potential factor in the pathogenesis of cardiovascular disease. We investigated whether birth weight, infant growth, childhood cognition and adult height, as well as a range of lifestyle, socio-economic and educational factors, were associated with white blood cell telomere length at age 49–51 years.
The study included 318 members of the Newcastle Thousand Families Study, a prospectively followed birth cohort which includes all individuals born in Newcastle, England in May and June 1947, who attended for clinical examination at age 49–51 years, and had telomere length successfully measured using real-time PCR analyses of DNA extracted from peripheral blood mononuclear cells.
No association was found between birth weight and later telomere length. However, associations were seen with other factors from early life. Education level was the only predictor in males, while telomere length in females was associated with gestational age at birth, childhood growth and childhood IQ.
While these findings may be due to chance, in particular where differing associations were seen between males and females, they do provide evidence of early life associations with telomere length much later in life. Our findings of sex differences in the education association may reflect the sex differences in achieved education levels in this generation where few women went to university regardless of their intelligence. Our findings do not support the concept of telomere length being on the pathway between very early growth and later disease risk.
Citation: Pearce MS, Mann KD, Martin-Ruiz C, Parker L, White M, et al. (2012) Childhood Growth, IQ and Education as Predictors of White Blood Cell Telomere Length at Age 49–51 Years: The Newcastle Thousand Families Study. PLoS ONE 7(7): e40116. doi:10.1371/journal.pone.0040116
Editor: Frédérique Magdinier, INSERM UMR S_910, France
Received: February 7, 2012; Accepted: June 1, 2012; Published: July 6, 2012
Copyright: © 2012 Pearce et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This study was partly supported by funding from the Faculty of Public Health Medicine/BUPA research fellowship (2001–4) awarded to JA and by a Research into Aging programme grant awarded to TvZ. JA is funded in full and MW in part by Fuse - the Centre for Translational Research in Public Health, a UK Clinical Research Collaboration (UKCRC) Public Health Research Centre of Excellence. Funding for Fuse is provided by the British Heart Foundation, Cancer Research UK, Economic and Social Research Council, Medical Research Council, and National Institute of Health Research. The views expressed in this paper do not necessarily represent those of the funders or UKCRC. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Telomere length has been reported to be associated with longevity and risk of a number of age-related diseases, including associations with cardiovascular disease –, type 2 diabetes mellitus , vascular  and Alzheimer’s dementia – and solid tissue tumours . However, it has been suggested that the associations with morbidity and mortality are not apparent in very old age .
Risk of adverse health in middle age has been proposed to be ‘programmed’ by impaired development in utero . Early growth has also been linked to physical functioning on older age . Telomere length is known to vary at birth  and has been suggested to be a biological marker on the pathway between early growth and later health . Further, it has been associated with age-related mortality and morbidity . Low birth weight children may have shorter telomeres in childhood , although very low birth weight newborns were found to have longer telomeres in cord blood than low birth weight newborns . However, when comparing small-for-gestational-age newborns to appropriately grown controls, telomere lengths were shown to be similar . Associations between early growth and telomere length in later life do not appear to have been studied previously.
A recent study has suggested a link between education and telomere length in adulthood . However, in addition to studying whether early growth or education are associated with a later outcome such as telomere length, it is also important to address whether factors later in life such as smoking, diet, physical activity and alcohol consumption, may have a more important role in influencing telomere length. It is only by studying detailed longitudinal birth cohort data in an appropriate manner, that questions regarding relative contributions and mediating pathways can be addressed.
The Newcastle Thousand Families birth cohort  provides such an opportunity to investigate the determinants of telomere length at age 49–51 years from across the life course and their relative contribution to explaining variation in telomere length. A previous investigation of the telomere data for this cohort found that telomere length was longer in men than in women , but did not find associations with socio-economic status or a number of lifestyle factors. The current study investigated the potential associations and interactions between sex and a number of markers of body size at different stages of life, including achieved adult height, childhood cognition, education and further adult lifestyle factors and peripheral blood telomere length at age 49–51 years in members of the Newcastle Thousand Families birth cohort.
The study received ethical approval from the South Durham Lead Research Ethics Committee and the Joint Newcastle Health Authority/University of Newcastle upon Tyne Ethics Committee, and all study members gave their written informed consent.
The Newcastle Thousand Families study began as a prospective study of all 1142 children born in May and June 1947 to mothers resident in Newcastle upon Tyne, UK . The health, growth and development of the cohort were followed in great detail up to age 15. Throughout the first years of the children’s lives, all families were visited both on a routine (up to every six weeks during infancy and at least quarterly until age five years) and on an ad hoc basis by the study team, which consisted of health visitors (nurses who visited families at home) and paediatricians.
The cohort underwent a major follow-up at age 49–51 years . Participants were members of the cohort who were either traced through the National Health Service Central Register or contacted the study team in response to media publicity. Between October 1996 and December 1998, health and lifestyle questionnaires were sent out for completion and return and study members were invited to attend for clinical examination which took place over the same time period.
Between October 1996 and December 1998, when study members were aged between 49 and 51 years, height, weight and other markers of size were measured. Waist and hip circumferences were measured according to the protocol of the World Health Organisation Monitoring Trends and Determinants in Cardiovascular Disease project . Percent body fat was estimated from impedance measured using a Holtain body composition analyser (Holtain Ltd, Crymych, Wales, UK).
Telomere length in peripheral blood mononuclear cells was measured using real-time polymerase chain reaction (PCR) analysis  on DNA extracted from blood donated at age 49–51 years with the following modifications: Measurements were performed in quadruplicate. All PCRs were carried out on an Applied Biosystems 7900HT Fast Real Time PCR machine with 384-well plate capacity. For T/S ratios, the coefficients of variation (CV) were 4.5% (intra-assay) and 6.2% (inter-assay), respectively. In addition, four internal control DNA samples were run within each plate to correct for plate–to-plate variation. This enabled the calculation of absolute telomere length (in kb) from the T/S ratios and further reduced the inter-assay CV to below 5%. The reproducibility of the whole technique including DNA isolation had also been tested in the same laboratory using parallel but independent blood samples , resulting in a CV of 2%.
Measurement of Size and Growth in Early Life
Birth weights, as recorded by the midwife, were standardised for gestational age (as recorded in ante-natal records) and sex . Growth in early childhood was defined as the standard deviation (z) score for height at age nine years, the age in childhood for which the most complete data were available, less the z-score for weight at birth. Childhood BMI, also measured at this age was also included in analyses. Liaison with schools enabled the prospective collection of information on educational performance. In 1958, study members took the 11-plus examination, consisting of written papers involving tests of verbal reasoning (Moray House tests 57 and 58) and two standardized tests of English and arithmetical ability. The total IQ score was derived as the average of the four test results. At that time in England, the 11-plus examination was a standard test used in educational establishments at the age of 11 years, often to determine the type of secondary school at which a child was to continue their education. Results of 11-plus examinations were not available for those children who had moved away from the study area.
Measurement of Adult Lifestyle
The number of pack-years of cigarettes smoked, current smoking status, physical activity, alcohol consumption and achieved education level were derived from the responses to the self-completion questionnaire data at age 49–51 years . Four categories of alcohol consumption were derived: No drinking; light drinking (up to ten units/week of alcohol for males, 5 units for females); moderate drinking (11–28 units for males, 6–21 units for females) and heavy drinking (>28 units for males, >21 units for females). In the UK, one unit is 10 ml or 8 g of pure alcohol. The number of pack-years of cigarettes smoked (one pack-year = one pack of cigarettes smoked per day for one year) was estimated from the study members’ smoking habits at ages 15, 25, 35 and 50, as ascertained at age 49–51 years. Current smoking status (at the time of questionnaire completion) was also derived (never, ex-smoker, current smoker). Physical activity assessment at age 49–51 years was based on that used for the Medical Research Council’s National Survey of Health and Development with four categories (inactive and light, moderate and heavy activity). Achieved education level was classified by the highest achieved qualifications (no qualifications, O-Level (school exit examinations at age 16 years), A-level (school exit examinations at age 18 years), and University degree level and above).
As the distribution of telomere length was skewed, it was log transformed prior to analyses. Linear regression was used to assess potential associations between log transformed telomere length and potential predictors, and relevant assumptions were tested. Regression coefficients (in log base pairs per unit) and corresponding 95% confidence intervals (95% CI) are reported. Sex-specific analyses and tests for interaction between sex and other potential explanatory variables were done within the linear regression framework. The statistical software package Stata, version 10.0, (StataCorp, College Station: TX) was used for all statistical analyses.
Of the original 1142 study members, 832 (86% of the surviving sample of 967 children whose families remained in Newcastle for at least the first year of the study) were traced at age 49–51 years 12. Of these, 574 completed the health and lifestyle questionnaire and telomere length was measured in 318 study members with available DNA samples (120 men, 198 women). There were no differences in early life factors between the study sample and the remainder of the birth cohort, other than for sex, with more women than men included.
Descriptive statistics for all variables are given in table 1. Mean telomere length was greater in men than in women (p<0.001). Univariate analyses showed strong associations between telomere length and achieved adult height, waist:hip ratio and achieved education at age 49–51 years (table 2). There was little evidence of an association between any early life factors including standardised or crude birth weight and telomere length (p = 0.92 and 0.66 respectively).
After adjusting for sex, neither achieved adult height or waist:hip ratio remained associated with telomere length (p = 0.28 and 0.53 respectively). However, the negative association between achieved education level and telomere length remained (p = 0.01). In sex-specific analyses, there were associations between telomere length and gestational age (p = 0.03), childhood growth (p = 0.05) and childhood IQ (p = 0.02) in women. Achieved education level at age 49–51 years in men was associated with telomere length (p<0.01). When compared to the reference category of no qualifications, lesser telomere lengths were seen for those with O and A-levels, but slightly longer telomeres were seen in those with university qualifications. Interactions were seen between sex and both gestational age (p = 0.026) and achieved education level (p = 0.05) on telomere length. Increasing male gestational age was associated with increased telomere length in contrast to an association between decreased length and increasing female gestation. There were decreasing telomere lengths for higher educational achievement in females, but with the longest telomere lengths in the highest achieving males. There was no evidence of interactions between sex and any of the other explanatory variables on telomere length.
Of the associations observed, the highest explanation of variation in the data was seen for sex (r2 = 0.12). Within sex-specific analyses, male achieved education level and female childhood IQ and gestational age accounted for 11%, 4% and 2.4%, respectively, of the variation in log transformed telomere length. After adjustment for sex, the resulting model including education and interactions was found to explain 15% of the variation in log transformed telomere length.
While associations were seen between telomere length and both achieved adult height and contemporary waist:hip ratio, neither association was independent of sex. This is likely to be due to men being both taller and having greater waist:hip ratios and having longer telomeres in this cohort. An association was seen between achieved education level and telomere length, with an interaction with sex. Achieved education level was the only association with telomere length in men, while gestational age, childhood IQ and childhood growth (from birth to age nine years) were associated in women.
Strengths and Potential Weaknesses
The main strength of this study is the ability to analyse prospectively collected data from different stages of life simultaneously. Of 1142 men and women recruited at birth in 1947, 28% participated in the current study. Except for sex, the study sample attending for clinical examination has been shown to be comparable for a wide range of explanatory variables in early life 23. In addition, inclusion of cohort members who had moved out of the study region (18% of those who attended for clinical examination were resident outside the Northern Region of England) increased the representativeness of the population studied. However, the potential for participation bias in terms of later factors remains a possibility and the study may have been underpowered for some variables, particularly for the sex-specific analyses. Despite the small numbers in these analyses, though, a number of associations and interactions were identified and the final model accounted for 15% of the variation in telomere length.
Telomere length is known to vary with age. All cohort members were born within a two-month period and assessed when aged between 49 and 51 years, reducing the potential for bias. Furthermore, they were all born to mothers resident within the city of Newcastle upon Tyne in the north east of England, so should have less genetic and environmental heterogeneity than would be found in a study incorporating a larger geographical area, or one with ethnic diversity .
Comparisons with Other Studies
We have previously reported that the men in this cohort had, on average, longer telomeres than the women at age 49–51 years . This is contrast to the majority of other studies reporting longer telomeres in women or no difference between men and women –However, a recent study of Scottish 70-year-olds also found longer telomeres in males when compared to females .We are not aware of any cohort-specific behavioural patterns or environmental exposures that could explain this observation, although in the older Scottish cohort it is possible that factors such as the selective survival of men with longer telomeres may play a role.
There were associations between both achieved adult height and contemporary waist:hip ratio and telomere length at age 49–51years in unadjusted analyses, but neither association remained after adjustment for sex or in sex-specific analyses. For waist:hip ratio, this is likely to reflect the larger waist:hip ratio in men compared to women.
Although telomere length is suggested to vary between men and women, such a difference is not apparent at birth, despite the variability in telomere length among newborns . Very low birth weight newborns have been found to have longer telomeres in cord blood than low birth weight newborns , while fetal growth restriction has been associated with reduced telomere length . Low birth weight children have been found to have shorter telomeres in childhood , but do not appear to have been studied in terms of telomere length later in life. Telomere length at age 49–51 years and both crude and standardised birth weight were slightly greater in males than in females, though not to the extent that they could be included in the adjusted model. Gestational age was inversely associated with telomere length in women. This, to our knowledge, has not previously been reported and requires replication in other cohorts to rule out the possibility of it being a chance finding, particularly given the number of potential predictor variables included in this analysis.
Our finding of an association between childhood growth and telomere length at age 49–51 years was restricted to women, with a higher change in z-score between birth and height at age nine years associated with longer telomeres. Obesity in childhood has been reported to be associated with shorter telomere length, again measured in childhood , but does not appear to have been studied in relation to telomere length later in life.
Childhood IQ (in females) and achieved education level (in males) were both associated with telomere length. The association with educational attainment for men, in that the longest telomeres were seen in those with the highest achieved education level, is consistent with recent evidence reporting that the associations with telomere length were dependent on educational attainment rather than contemporary socio-economic circumstances , . Also consistent with this is our previous finding of no association with socio-economic status . Telomere length has been inconsistently associated with contemporary cognitive function , –, although not with cognitive decline . That education was the significant factor in men while it was childhood IQ in women may be explained by the social values of the time, where education was not considered as important for women. Members of this cohort were teenagers in the 1960 s when only a small percentage of the population went to university and there were still high levels of inequality between the sexes, with less opportunity for women to achieve a high education level even with a relatively high IQ . However, the lack of consistent results in the expected directions for both males and females may also suggest that some of the significant findings in the sex-specific analyses may be due to chance or due to residual confounding.
Our findings suggest that, while achieved adult height and waist:hip ratio at age 49–51 years appear to be associated with telomere length at the same age, this is likely to reflect the differences in these measures between men and women and thus be due to confounding. No association was found between birth weight and later telomere length. However, significant associations were seen with other factors from early life. Education level was the only predictor in males, possibly reflecting the higher education levels in males in this generation, while telomere length in females was associated with gestational age, childhood growth and childhood IQ. While these findings may be due to chance, in particular where differing associations were seen between males and females, they do provide evidence of early life associations with telomere length much later in life. However, they do not support the concept of telomere length being on the pathway between very early growth and later disease risk.
We thank all study members for taking part in this study and the study teams and funders past and present.
Conceived and designed the experiments: LP MW TVZ JA. Performed the experiments: CMR. Analyzed the data: MSP KDM. Wrote the paper: MSP. Critically reviewed the manuscript and approved the final version: MSP KDM CMR LP MW TVZ JA.
- 1. Bekaert S, De Meyer T, Rietzschel ER, De Buyzere ML, De Bacquer D, et al. (2007) Telomere length and cardiovascular risk factors in a middle-aged population free of overt cardiovascular disease. Aging Cell 6: 639–647.
- 2. Fuster JJ, Diez J, Andres V (2007) Telomere dysfunction in hypertension. J Hypertens 25: 2185–2192.
- 3. Fyhrquist F, Silventoinen K, Saijonmaa O, Kontula K, Devereux RB, et al. (2011) Telomere length and cardiovascular risk in hypertensive patients with left ventricular hypertrophy: the LIFE study. J Hum Hypertens 25: 711–718.
- 4. Zee RY, Castonquay AJ, Barton NS, Germer S, Martin M (2010) Mean leukocyte telomere length shortening and type 2 diabetes mellitus: a case-control study. Transl Res 155; 166–169.
- 5. Von Zglinicki T, Serra V, Lorenz M, Saretzki G, Lenzen-Grossimlighaus R, et al. (2000) Short telomeres in patients with vascular dementia: an indication of low antioxidative capacity and a possible risk factor. Lab Invest 80: 1739–1747.
- 6. Panossian LA, Porter VR, Valenzuala HF, Zhu X, Reback E, et al. (2003) Telomere shortening in T cells correlates with Alzheimer’s disease status. Neurobiol Aging 24: 77–84.
- 7. Thomas P, O’Callaghan NJ, Fenech M (2008) Telomere length in white blood cells, buccal cells and brain tissue and its variation with ageing and Alzheimer’s disease. Mech Ageing Dev 129: 183–190.
- 8. Ma H, Zhou Z, Wei S, Liu Z, Pooley KA, et al. (2011) Shortened telomere length is associated with increased risk of cancer: a meta-analysis. PLoS One 6: e20466.
- 9. Martin-Ruiz CM, Gussekloo J, van Heemst D, von Zglinicki T, Westendorp RGJ (2005) Telomere length in white blood cells is not associated with morbidity or mortality in the oldest old: a population-based study. Aging Cell 4: 287–290.
- 10. Barker DJP (2003) The developmental origins of adult disease. Eur J Epidemiol 18: 733–736.
- 11. von Bonsdorff MB, Rantanen T, Sipilä S, Salonen MK, Kajantie E, et al. (2011) Birth size and childhood growth as determinants of physical functioning in older age: the Helsinki birth cohort study. Am J Epidemiol 174: 1336–1344.
- 12. Okuda K, Bardeguez A, Gardner JP, Rodriguez P, Ganesh V, et al. (2002) Telomere length in the newborn. Pediatr Res 52: 377–381.
- 13. Barnes SK, Ozanne SE (2011) Pathways linking the early environment to long-term health and lifespan. Prog Biophys Mol Biol 106: 232–336.
- 14. Raqib R, Alam DS, Sarker P, Ahmad SM, Ara G, et al. (2007) Low birth weight is associated with altered immune function in rural Bangladeshi children: a birth cohort study. Am J Clin Nutr 85: 845–852.
- 15. Friedrich U, Schwab M, Griese EU, Fritz P, Klotz U (2001) Telomeres in neonates: new insights in fetal hematopoiesis. Pediatr Res 49: 252–256.
- 16. Akkad A, Hastings R, Konje JC, Bell SC, Thurston H, et al. (2006) Telomere length in small-for-gestational-age babies. BJOG 113: 318–323.
- 17. Steptoe A, Hamer M, Butcher L, Lin J, Brydon L, et al. (2011) Educational attainment but not measures of current socioeconomic circumstances are associated with leukocyte telomere length in healthy older men and women. Brain Behav Immun 25: 1292–1298.
- 18. Pearce MS, Unwin NC, Parker L, Craft AW (2009) Cohort Profile: The Newcastle Thousand Families 1947 Birth Cohort. Int J Epidemiol 38: 932–937.
- 19. Adams J, Martin-Ruiz C, Pearce MS, White M, Parker L, et al. (2007) No association between socio-economic status and white blood cell telomere length. Aging Cell6: 125–128.
- 20. World Health Organisation (1990) Organisation. Monitoring trends and determinants in cardiovascular disease project. MONICA manual, part III. Geneva: World Health Organisation.
- 21. Cawthon R (2002) Telomere measurement by quantitative PCR. Nucleic Acids Res 30: e47.
- 22. Freeman JV, Cole TJ, Chinn S, Jones PR, White EM, et al. (1990) Cross sectional stature and weight reference curves for the UK, 1990. Arch Dis Child 73: 17–24.
- 23. Mann KD, Tennant PW, Parker L, Unwin NC, Pearce MS (2011) The relatively small contribution of birth weight to blood pressure at age 49–51 years in the Newcastle Thousand Families Study. J Hypertens 29: 1077–1084.
- 24. Hunt SC, Chen W, Gardner JP, Kimura M, Srinivasan SR, et al. (2008) Leukocyte telomeres are longer in African Americans than in whites: the National Heart, Lung, and Blood Institute Family Heart Study and the Bogalusa Heart Study. Aging Cell 7: 451–458.
- 25. Benetos A, Gardner JP, Zureik M, Labat C, Xiaobin L, et al. (2004) Short telomeres are associated with increased carotid atherosclerosis in hypertensive subjects. Hypertension 43: 182–185.
- 26. Valdes AM, Andrew T, Gardner JP, Kimura M, Oelsner E, et al. (2005) Obesity, cigarette smoking, and telomere length in women. Lancet 366: 662–664.
- 27. Mayer S, Bruderlein S, Perner S, Waibel I, Holdenried A, et al. (2006) Sex-specific telomere length profiles and age-dependent erosion dynamics of individual chromosome arms in humans. Cytogen Genome Res 112: 194–201.
- 28. Wu X, Amos CI, Zhu Y, Zhao H, Grossman BH, et al. (2003) Telomere dysfunction: a potential cancer predisposition factor. J Natl Cancer Inst 95: 1211–1218.
- 29. Harris SE, Martin-Ruiz C, von Zglinicki T, Starr JM, Deary IJ (2012) Telomere length and aging biomarkers in 70-year-olds: the Lothian Birth Cohort 1936. Neurobiol Aging 33: 1486–1468.
- 30. Davy P, Nagata M, Bullard P, Fogelson NS, Allsopp R (2009) Fetal growth restriction is associated with accelerated telomere shortening and increased expression of cell senescence markers in the placenta. Placenta 30: 539–542.
- 31. Buxton JL, Walters RG, Visvikis-Siest S, Meyre D, Froguel P, et al. (2011) Childhood obesity is associated with shorter leukocyte telomere length. J Clin Endocrinol Metab 96: 1500–1505.
- 32. Surtees PG, Wainwright NW, Pooley KA, Luben RN, Khaw KT, et al. (2012) Educational attainment and mean leukocyte telomere length in women in the European Prospective Investigation into Cancer (EPIC)-Norfolk population study. Brain Behav Immun 26: 414–418.
- 33. Devore EE, Prescott J, De Vivo I, Grodstein F (2011) Relative telomere length and cognitive decline in the Nurses’ Health Study. Neurosci Lett 492: 15–18.
- 34. Yaffe K, Lindquist K, Kluse M, Cawthon R, Harris T, et al. (2011) Telomere length and cognitive function in community-dwelling elders: Findings from the Health ABC Study. Neurobiol Aging 32: 2055–2060.
- 35. Valdes AM, Deary IJ, Gardner J, Kimura M, Lu X, et al. (2010) Leukocyte telomere length is associated with cognitive performance in healthy women. Neurobiol Aging 31: 986–992.
- 36. Forrest LF, Hodgson S, Parker L, Pearce MS (2011) The influence of childhood IQ and education on social mobility in the Newcastle Thousand Families birth cohort. BMC Public Health 11: 895.