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. 2019 Jul 17;15(4):e12857. doi: 10.1111/mcn.12857

Association of birth outcomes and postnatal growth with adult leukocyte telomere length: Data from New Delhi Birth Cohort

Mohamad Tarik 1, Lakshmy Ramakrishnan 1,✉, Sikha Sinha 2, Harsh Pal Singh Sachdev 2, Nikhil Tandon 3, Ambuj Roy 4, Santosh Kumar Bhargava 5
PMCID: PMC6859967  PMID: 31216382

Abstract

Born small for gestational age due to undernutrition in utero and subsequent catch‐up growth is associated with risk of developing chronic diseases in adulthood. Telomere length has been shown to be a predictor of these age‐related diseases and may be a link between birth size, a surrogate for foetal undernutrition, and adult chronic diseases. We assessed the relationship of leukocyte telomere length in adult life with birth outcomes and serial change in body mass index (BMI) from birth to adulthood. Leukocyte relative telomere length (RTL) was measured by MMqPCR in 1,309 subjects from New Delhi Birth Cohort who participated in two phases of the study between 2006–2009 (Phase 6) and 2012–2015 (Phase 7) at a mean age of 39.08 (±3.29), and its association with birth outcomes and conditional BMI gain at 2, 11, and 29 years was assessed in a mixed regression model. We did not find any significant association of RTL with body size at birth including birthweight, birth length, and birth BMI. Gestational age was positively associated with RTL (P = .017, multivariate model: P = .039). Conditional BMI gain at 2 and 11 years was not associated with RTL. BMI gain at 29 year was negatively associated with RTL in multivariate model (P = .015). Born small for gestational age was not associated with RTL in adulthood. Leukocyte telomere attrition was observed in those born before 37 weeks of gestational age as well as in those who gained weight as adults, which may predispose to chronic diseases.

Keywords: Barker hypothesis, birth cohort, cardiovascular disease, child growth, childhood obesity, chronic disease

Key massages.

  • Gestational age is associated with shorter telomere in adult life in the NDBC cohort.

  • Small for gestational age (SGA) is not associated with leukocyte's telomere attrition at the mean age of 39.08 (±3.29) years.

  • Conditional BMI gain at 2 and 11 years is not associated with telomere attrition in adult life, although BMI gain at 29 years was associated with shorter telomere.

1. INTRODUCTION

The prevalence of noncommunicable disease is rising in India (WHO, 2018). Barker et al. reported an association between low birthweight (LBW) or small for gestational age (SGA; birthweight < 2,500 gm), a surrogate of intrauterine growth, and mortality due to cardiac disease (Barker et al., 1993; Barker, Winter, Osmond, Margetts, & Simmonds, 1989). Subsequent research has demonstrated correlation between variations in birthweight and blood pressure (Barker, Osmond, Golding, Kuh, & Wadsworth, 1989; Curhan et al., 1996), cholesterol concentration (Barker, Martyn, Osmond, Hales, & Fall, 1993), carotid atherosclerosis (Martyn, Gale, Jespersen, & Sherriff, 1998), fibrinogen (Martyn, Meade, Stirling, & Barker, 1995), obesity (Stettler, Kumanyika, Katz, Zemel, & Stallings, 2003; Stettler & Stallings, 2002), and metabolic syndrome (Curhan et al., 1996; Hofman et al., 1997) in adulthood. Approximately 27% of babies born in India are low birthweight, with nearly half of them being full term babies (Radha et al., 2015), a consequence of inadequate nutrient intake by mothers during pregnancy, and this may be contributing to the rising trend of chronic diseases in this part of the world. Several plausible mechanisms have been proposed to explain the in utero origin of adult diseases (Edwards, Coulter, Symonds, & McMillen, 2001; McTernan et al., 2001; Seckl, Cleasby, & Nyirenda, 2000), but the underlying mechanism is yet not completely elucidated. Telomere length has been linked to adult chronic diseases, and it is likely that adverse nutritional conditions during foetal growth increases oxidative stress, which in turn may affect the telomeres. Animal studies have shown that LBW due to intrauterine growth restriction during gestation and subsequent catch‐up growth results in shorter telomere length (Jennings, Ozanne, Dorling, & Hales, 1999; Tarry‐Adkins et al., 2009; Tarry‐Adkins, Martin‐Gronert, Chen, Cripps, & Ozanne, 2008). Studies in humans have been equivocal with some studies showing an association between telomere length and birthweight (Entringer et al., 2011; Raqib et al., 2007), whereas others have shown no effect of birthweight on telomere length in young adults (Kajantie et al., 2012; Smeets, Codd, Samani, & Hokken‐Koelega, 2015). Earlier reports have not even addressed the issue of postnatal catch‐up growth subsequent to being born SGA on telomere length. Retarded growth during intrauterine phase as well as during infancy, childhood, and adolescence has been reported to increase risk of coronary heart disease irrespective of size at birth (Eriksson, Forsén, Tuomilehto, Osmond, & Barker, 2001). Studies have also shown ill effects of catch‐up growth during infancy and childhood on risk of development of chronic diseases later in life in children born SGA.

The New Delhi Birth Cohort (NDBC) in which the present study is carried out has information on birthweight and six monthly changes in height and weight till 21 years (Bhargava et al., 2004) in a cohort of more than 1,000 subjects. Frequent anthropometric measurements of the cohort during infancy, childhood, adolescence, and adulthood provided a unique opportunity to study the relative importance of prenatal and postnatal growth on RTL in adulthood. The association of birth outcomes (birth size and gestational age) and body mass index (BMI) gain at 2, 11, and 29 years was studied with RTL at adulthood.

2. METHODS

The present study is carried out in the subjects of NDBC, which was established in 1969 to study pregnancy outcomes and child growth. Details of the cohort are given in our previous publication (Bhargava et al., 2004). Briefly, newborn offspring's weight and length were recorded within 72 hr and six monthly intervals (±15 days) until 21 years of age in the first four phases during 1969–1990. After a break of 8 years, in 1998 (Phase 5), the subjects who were by now around 29 years of age were retraced to assess metabolic and cardiovascular risk factors. Data on socio‐economic status, education, family history of diseases, tobacco and alcohol consumption, diet, and physical activity were collected using standard questionnaires from 1,583 retraced subjects. Anthropometry, blood pressure, and ECG were recorded. Blood was taken for analysis of plasma glucose, insulin lipids, and proinflammatory markers. In Phase 6 (2006–2009), 1,100 subjects participated, all the measurements except proinflammatory markers were repeated, and in addition, cIMT, brachial artery endothelial function, and body composition using dual X‐ray absorptiometry were performed. In Phase 7 conducted between 2012 and 2015, all anthropometric, clinical, and biochemical measurements (except proinflammatory markers) as mentioned for Phase 5 were repeated (Figure 1).

Figure 1.

Figure 1

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Description of the various phases of the New Delhi Birth Cohort study

2.1. Current study

In the present study, 1,353 subjects were included, whose blood samples were collected in Phases 6 and 7 of the NDBC. Of the 1,353 subjects, 44 subjects were excluded due to poor DNA quality, leaving 1,309. Therefore, the current study was carried out in stored blood available from 655 subjects from Phase 6 from which good quality DNA could be extracted as well as from freshly collected blood samples from 654 subjects recruited in Phase 7 of the study. The mean age of the participants from Phase 6 who were included in the present study was 35.98 (±1.03) years and that of participants recruited in Phase 7 and included in the present study was 42.19 (±1.13) years and the mean age of total subjects (1,309) was 39.08 (±3.29) years. The first adult follow‐up phase (1998–2002) was conducted on 1,526 participants. In comparison with the original cohort of 8,181 subjects, these participants had 7% more male subjects, the rate of maternal literacy was 6% higher, the mean birthweight was 32 g higher, and the mean birth length was 2 mm longer. The height, weight, and BMI in childhood and adolescence were approximately 0.1 SD lower than in the original cohort (Bhargava et al., 2004). In the subsequent adult phases during which this study was conducted, in comparison with the original cohort, the participants were comparable for birthweight, and paternal education and occupation but there were marginal or small differences in mean birth length (1 mm higher), maternal literacy (6% higher), nuclear families (7% higher), household income, type of housing, utilization of health services, water supply, and sanitation. Ethical clearance was obtained from institution ethical committee, and informed consent was obtained from all subjects. In both the phases, 10 ml of blood was obtained from subjects after an overnight fast. Plasma (fluoride and EDTA) and serum samples were separated, and plasma glucose (by glucose oxidase method on Beckman autoanalyser) and serum lipids (total cholesterol and triglycerides by enzymatic method and HDL by immune‐inhibition method) were measured. The rest of the plasma and serum were aliquoted and preserved at −70°C till further analysis. High sensitive C‐reactive protein (hs‐CRP) was determined in serum by solid phase ELISA method using commercially available kit (catalogue number: 11190; Biochek, USA) in only in fresh serum samples collected in Phase 7. RTL was determined by qPCR after extracting DNA from stored samples from Phase 6 and freshly collected samples from Phase 7. To validate the qPCR method, absolute telomere length (aTL) was measured by Southern blot assay in a subset of 94 samples as previously described (Tarik et al., 2018).

2.2. Measurement of telomere length by qPCR

DNA was isolated from whole blood using Dneasy blood and tissue kit (Qiagen, Germany). Leukocyte telomere length was measured by monochrome multiplex quantitative PCR (MMqPCR) method described by Cawthon (2009) with minor modifications. Reference DNA at concentrations 120, 40, 13.33, 4.44, and 1.48 ng μl−1 were prepared from standard genomic DNA. Duplicate samples of 2 μl of reference DNA and DNA extracted from blood samples (~20 ng μl−1) were taken in 1× master mix consisting of 0.5× SYBR Green I, 10 mM Tris–HCl, 50 mMKCl, 3 mM MgCl2, 0.2 mM each dNTP, 1 mM DTT, 1 M betaine, and 0.625 U AmpliTaq Gold DNA polymerase and nuclease free water in a final volume of 25 μl and added into reaction wells of 96‐well PCR plate (Axygen, USA) compatible with real‐time PCR detection system (IQ5 software, Bio‐Rad) and amplified. One nontemplate control (NTC) and two positive controls were also amplified in duplicates in each run. For the multiplex qPCR, the telomere primers (forward: ACACTAAGGGTTTGGGTTTGGGTTAGTGT and reverse: TGTTAGGTATCCTCATCCCTATCCCTATCCCTATCCCTAACA, final concentration of 900 nM) and single copy gene, albumin primers (forward: GGCGGCGGGCGCGGGCTGGGCGGAAATGCTGCACAGAATCCTTG and reverse: GCCCGGCCCGCCGCGCCCGTCCCGCCGGAAAAGCATGGTCGCCTG, final concentration 500 nM) were added in each reaction, and product was amplified using real‐time PCR (Bio‐Rad iQ5 software 2.0 version). After the run was completed, the Ct values of telomere and albumin gene was transferred to spreadsheet separately and the ratio of the copy number of telomere (T), and the single copy gene (S) was determined, which is predicted as the proportional to the average telomere length (i.e., the T/S ratio) per cell.

2.3. Statistical analysis

Data were checked for normality, and variables with skewed distributions were log transformed. Mean and SD was computed for describing the characteristics of study subjects. Univariate and multivariate regression models were used for analysing the relationship between RTL and anthropometric variable from birth to adulthood and biochemical variables. We used all recorded data from the NDBC (not just those for subjects recruited for this study) to derive SD scores for height, weight, and BMI for each subject at age 6 months and at birthdays from age 1 to 21 years as previously described (Bhargava et al., 2004). We also examined the associations of RTL with growth (conditional BMI gain) during infancy (birth to 2 years), childhood (2–11 years), and adolescence and adulthood (11–29 years). To measure growth during a time interval (e.g., between the ages of 2 and 11 years), we regressed the value at the end of the interval (age 11 years) on the value at the beginning of the interval (age 2 years) and at earlier time points (birth) and expressed the residual as an SD score (Adair et al., 2009). The conditional BMI gain is useful in assessment of association with growth during specific time period as this method overcomes the highly correlated measurements of height and weight in an individual. Age 29 was the age at which first retracing and follow up happened in the cohort. BMI gain as adult was taken as the conditional BMI gain from adolescence age (11 years) to age 29.

3. RESULTS

Of the 1,353 samples available for the study, genomic DNA of good integrity on 0.8% agarose gel could be obtained from 1,309 samples, and these were used for telomere length analysis. The mean age of the total participants was 39.08 (±3.29) year. A total of 655 subjects with mean age of 35.98 (±1.03) years were taken from Phase 6 and 654 subjects with mean age of 42.19 (±1.13) years from Phase 7. Leukocyte RTL ranged from 0.401 to 2.344 with mean values of 0.984 (±0.29) in 1,309 subjects, 0.95 (±0.31) in 655 subjects during Phase 6, and 1.02 (±0.32) in 654 subjects from Phase 7.

Mean RTL was comparable between males and females in Phase 6, whereas in Phase 7, females had significantly higher RTL as compared with males. The characteristics of the study subjects included in Phases 6 and 7 are depicted in Table 1. Birth measurements were comparable between males and females in Phase 6, whereas males were heavier and taller at birth as compared with females in Phase 7. As adults, females were shorter and weighed less as compared with males in both the phases. As compared with males, waist circumference was lower in females in both phases, but BMI was higher in Phase 7.

Table 1.

Body measurements at birth and as adults

Variable Phase 6 Phase 7
Males Females P valuea Males Females P valuea
N Mean (SD) N Mean (SD) N Mean (SD) N Mean (SD)
Birth
Birthweight (kg) 352 2.88 (0.43) 237 2.82 (0.37) .059 385 2.89 (0.45) 233 2.79 (0.38) .005
Birth length (cm) 336 48.79 (2.03) 236 48.55 (1.86) .147 375 48.72 (2.03) 232 48.30 (1.91) .013
Birth BMI 336 12.04 (1.25) 236 11.93 (1.17) .273 375 12.11 (1.27) 232 11.92 (1.22) .079
Gestational age (weeks) 340 38.69 (2.69) 247 39.06 (2.39) .087 389 38.78 (2.58) 233 39.04 (2.64) .226
Adult
Age (years) 388 35.95 (1.01) 269 36.03 (1.07) .324 434 42.14 (1.14) 262 42.17 (1.10) .770
Height (cm) 387 170.07 (6.30) 268 155.46 (5.52) <.001 428 170.11 (6.16) 259 155.04 (5.79) <.001
Weight (kg) 388 76.03 (14.46) 269 64.96 (14.06) <.001 428 78.81 (13.26) 260 70.74 (14.14) <.001
BMI (kg m−2) 387 26.26 (4.47) 268 26.81 (5.34) .155 428 27.20 (4.15) 259 29.42 (5.51) <.001
Waist circumference (cm) 388 95.0 (11.8) 268 86.0 (12.4) <.001 429 98.2 (11.1) 259 94.4 (11.5) <.001
Telomere length (relative)a 387 0.95 (0.31) 268 0.95 (0.31) .910 407 1.00 (0.31) 247 1.05 (0.34) .028
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Geometric mean after natural log transformation.

a

P value for gender difference.

Bold values indicate statistical significance at the p ≤ 0.05 level).

3.1. Association of telomere length with anthropometric variables from birth to adulthood in New Delhi Cohort subjects

The data from Phases 6 and 7 of the study were analysed together in mixed univariate and multivariate regression models (Table 2). In the univariate model, birthweight and birth BMI were not associated with RTL at the age of ~39 years. There was a significant positive association of gestational age with telomere length (P = .017), and association remained significant after adjusting for confounding factors in multivariate regression Model 2 (P = .039) and in Model 3 (P = .05). Conditional BMI gain at 2 and 11 year was not significantly associated with telomere length. Conditional BMI gain at adulthood (29 years) was negatively associated with RTL after adjusting for confounders in Model 2 (P = .015) and Model 3 (P = .044). Additionally, we have assessed the association of telomere length with conditional BMI gain from 29 to current age, but the association was not significant in univariate and multivariate regression model (B = −0.026, 95% CI [−0.128, 0.076]; P = .612). There was no significant association of RTL with birthweight, gestational age, birth BMI, BMI gain at 2, 11, and adulthood in univariate and multivariate regression analysis when males and females were separately analysed. Hs‐CRP was inversely associated with RTL in univariate regression model (regression coefficient B = −0.007, P = .021) adjusted for age and gender.

Table 2.

Association of telomere length with birth outcome and conditional BMI gain from birth to adulthood in New Delhi Cohort subjects

Variable Univariate regression Multivariate regression
Model 1 Model 2 Model 3
N Coefficients (P value)[Link] Coefficients (P value) N = 822 Coefficients (P value)a N = 819
Birthweight (kg) 1,166 0.029 (.178)
Birth length (cm) 1,139 0.003 (.503)
Birth BMI (kg m−2) 1,139 0.010 (.155) 0.002 (.854) 0.003 (.678)
Gestational age (weeks) 1,168 0.008 (.017) 0.009 (.039) 0.008 (.050)
BMI gain at 2 years 1,140 −0.003 (.693) −0.009 (.445) −0.005 (.633)
BMI gain at 11 years 1,089 0.0102 (.538) −0.021 (.175) −0.012 (.423)
BMI gain at 29 year 1,014 −0.018 (.072) −0.042 (.015) −0.036 (.044)
Age (years) 1,309 −0.126 (.106) 0.001 (.891) 0.003 (.711)
Gender 1,309 0.023 (.169) 0.061 (.062) 0.044 (.094)
Adult body weight (kg) 1,303 −0.0005 (.399)
Adult body height (cm) 1,300 −0.0009 (.484)
Adult BMI (kg m−2) 1,300 −0.001 (.330)
Hs‐CRPb 580 −0.007 (.021)
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a

Appropriate adjustment for age, gender, and phase.

b

Adjusted for age, gender, phase, birth BMI, BMI gain at 2, 11, and adulthood, tobacco use, alcohol intake, gestational age, current BMI, systolic blood pressure, triglyceride, and occupational status.

Adjusted for age, gender, phase, birth BMI, BMI gain at 2, 11, and adulthood, tobacco use, alcohol intake, gestational age, current BMI, and socio‐economic status score.

Appropriate adjustment for age and gender (hs‐CRP measured in Phase 7 only).

p ≤ 0.05 are reported in bold.

We have also assessed the association of birth outcomes with aTL measured in 94 subjects by Southern blot. The mean aTL was 7,391.12 ± 892.79 bp (ranged: 5,588.76–10,050.00 bp). aTL was not associated with birthweight (n = 76, B = 0.132; 95% CI [−0.372, 0.635]; P = .604), birth BMI (n = 69; B = 99.28; 95% CI [−109.87, 308.42]; P = .347) and gestational age (n = 72, B = 6.855, 95% CI [−76.62, 62.91]; P = .845). Conditional BMI gain at 2, 11, and 29 years (n = 45) was also not associated with aTL.

4. DISCUSSION

4.1. Telomere length and birth outcomes

The study did not find any significant association between birthweight, birth length, and birth BMI and RTL in adult life at the mean age of 39.08 (±3.29) years. Evidence of the association of telomere length with birthweight is inconsistent. aTL measured by Southern blot in a subset of samples (n = 76) also did not show association with birth parameters. Similar to our study, Kajantie et al. (2012) and Song et al. (2015) as well as Dutch famine birth cohort study (de Rooij et al., 2015) did not find any association between telomere length and birthweight. Kajantie et al. (2012) used data from three cohorts to study the association of telomere length with birthweight: The Helsinki Birth Cohort (HSBC) of 1,894 subjects aged 56–69, the Helsinki study of the very low birthweight adult of 164 subjects aged 18–27, and the FinnTwin16 cohort aged 23–31 years. The authors did not find any association between telomere length and birthweight in any of the three cohorts and the findings are similar to that of our study. In the Newcastle Thousand Family Study, 318 individual born in Newcastle in 1947 were followed up at age 49–51 for measurement of telomere length. This study also found no association between birthweight and later telomere length corroborating our results (Pearce et al., 2012). Song et al. studied leukocyte telomere length in 62‐year‐old women to assess Type 2 diabetes risk factors between low birthweight and normal birthweight women. The authors did not observe any significant difference in telomere length between low birthweight subjects and normal birthweight subjects. Although, low birthweight (SGA) was significantly associated with increased risk of Type 2 diabetes in later life, leukocyte telomere length did not appear to mediate significant proportion of the total effect of LBW on Type 2 diabetes in this cohort of women (Song et al., 2015). In a Dutch famine birth cohort study of 131 subjects, de Rooij et al. observed that leukocyte telomere length at the age of 68 years did not differ between those who were exposed compared with those who were unexposed to famine during gestation. The leukocyte telomere length was not associated with birthweight in this Dutch cohort (de Rooij et al., 2015).

As against the abovementioned studies, Strohmaier et al. (2015) reported association of telomere length with birthweight in 16‐year‐old monozygotic twins but not seen in dizygotic twins. Raqib et al. (2007) reported significantly shorter lymphocyte TL in 5 years old preschool children (n = 132) born with low birthweight compared with normal birthweight and suggested that this may be due to persistent immune activation because of high infection rate leading to higher T cell turnover. Entringer et al. (2011) reported that LBW due to severe maternal stress during gestation (n = 45) is associated with significantly shorter telomere length. All the three studies showing significant association of birthweight with telomere length have been conducted in children, adolescence, or young adults. The positive association seen in young subjects as compared with no association seen in older age groups indicates that the association may change throughout life. This could be due to changing telomere dynamics with relatively rapid loss of telomere during early childhood and subsequently a slow linear decline in adulthood (Frenck, Blackburn, & Shannon, 1998).

Laganović et al. (2014) paradoxically reported longer telomere in young men (age 21) born SGA as compared with those born appropriate for gestational age. The authors suggest that slower telomere attrition due to a decline in stem cell turnover in IUGR/preterm may be the reason for the longer telomere length in SGA.

The results of our study do not support the hypothesis that telomere length may be a marker linking foetal adverse exposure with adult diseases and does not corroborate findings of animal studies where intrauterine growth restriction during the foetal period was found to associate with shorter telomeres in cells of specific organs such as kidney (Jennings et al., 1999), aortic cells (Tarry‐Adkins et al., 2008), and pancreatic islets cells (Tarry‐Adkins et al., 2009). In the present study, the telomere length was measured in leukocytes unlike in animal studies where telomere length was measured in specific tissues. There is disagreement on whether leukocyte telomere would be a reflection of telomere length in tissues with recent studies reporting that leukocyte telomere length does not strongly correlate with telomere length in other organs (Daniali et al., 2013; Dlouha, Maluskova, Kralova Lesna, Lanska, & Hubacek, 2014). Rate of telomere attrition differ between tissues (Ulaner, Hu, Vu, Giudice, & Hoffman, 2001) due to differences in the rate of cell division as well as differences in susceptibility to oxidative stress.

4.2. Impact of gestational age on leukocyte telomere length at adult life

A significant positive association of RTL with gestational age was observed in the present study after adjusting for age and gender and the association remained significant after adjusting with all possible confounding factors in multivariate regression models, which suggests that gestational age has independent effect on leukocyte telomere length. aTL measured by Southern blot in subset of samples (n = 72) did not show an association with gestational age possibly due to small sample size. The association of telomere length with gestational age has been studied earlier and the reports are contradictory. A recent study by Smeets et al. (2015) reported a positive association of gestational age with leukocyte telomere length at 21 years of age, a finding similar to that in our study. Kajantie et al. (2012) on the other hand reported no association between gestational age and leukocyte telomere length in three cohorts with different age ranges. An inverse association was reported by Pearce et al. in the Newcastle birth cohort between gestational age and telomere length possibly a chance finding due to number of confounding variables (Pearce et al., 2012).

This effect of gestational age on telomere length can be ascribed to stress in utero. Babies born prior to 37 weeks of gestation is often associated with stressful exposure, which is likely to increase oxidative stress burden and thereby telomere shortening. Oxidative stress risk factors including malnutrition, antioxidant deficient diets, physiological and psychological stressors, behavioural factors (cigarette smoking, alcohol intake, and drug use), obesity, environmental pollutants, and genotoxic agents are well‐studied risk factors of preterm birth (Goldenberg, Culhane, Iams, & Romero, 2008; Romero et al., 2006), and these stressors induce foetal cell senescence signals, which is likely to trigger premature labour (Menon, 2014). Another reason for a shorter telomere in subjects born prior to 37 weeks of gestation could be catch‐up growth seen in preterm babies. Most preterm babies would undergo an accelerated growth near term and this can result in replicative stress.

4.3. Conditional BMI gain and telomere length

Conditional BMI gain at 2 and 11 years was not significantly associated with RTL, but conditional BMI gain at 29 year was significantly associated with shorter telomere. We came across only one study, which has studied the association between BMI z‐score change from childhood to adulthood and telomere length. Buxton et al. (2014) reported an inverse association of BMI changes from age at adiposity rebound (which was around 5 years) to 31 years with telomere length in female subjects from the Northern Finland Birth Cohort. A one unit z‐score increase in BMI score change was associated with 3.08% decrease in telomere length in the study.

The mechanism responsible for the association of change in BMI with telomere length has not been elucidated. It can be speculated that increased adiposity due to larger gain in weight would lead to increased oxidative stress (Sankhla et al., 2012; Savini, Catani, Evangelista, Gasperi, & Avigliano, 2013) and inflammation (Kiecolt‐Glaser et al., 2003), which may accelerate telomere attrition (Goldenberg et al., 2008). A significant inverse association was observed between hs‐CRP and telomere length by us (P = .05), which suggests that low‐grade inflammation may be accelerating leukocyte telomere attrition.

We observed a shorter telomere length in participants from Phase 6 at a mean age of 36 years compared with participants from Phase 7 at a mean age of 42. This is contrary to the negative association between age and telomere length reported in literature. This could be attributed to various reasons. First, the samples from Phase 6 were stored upto 3–6 years prior to extraction of DNA for telomere length analysis and the MMqPCR method used to assess RTL is known to be sensitive to differences in DNA quality (Dlouha et al., 2014). To minimize this effect, we only used good quality DNA for RTL analysis. Second, diet, stress, physical activity, and lifestyle changes can also influence telomere length via improving telomerase activation (Boccardi, Paolisso, & Mecocci, 2016; Cassidy et al., 2010). We however did not assess these factors in our study. In a study, Weischer et al. (2014) reported that 44% individuals during 10 years follow up showed an elongation in telomere length, possible explanation given by the authors is underestimated regenerative capacity of nonstem cells.

One weakness of our study is that, we measured RTL by RT‐PCR and not aTL by Southern blotting, which is the gold standard but difficult to perform in large number of samples. We did carry out a comparative analysis of RTL by RT‐PCR and Southern blot in around 100 samples to validate our measurement and found a good agreement between the two methods (Tarik et al., 2018). Our study had several strengths. Trained personnel collected anthropometric data at several times from birth till adulthood providing us with unique opportunity to study association of adiposity and weight gain at different phases of life with telomere length.

In conclusion, our finding suggests that birth size is not associated with leukocyte telomere length. Leukocyte telomere attrition was observed in those born prior to 37 weeks of gestational age possibly predisposing to chronic diseases.

CONFLICTS OF INTEREST

The authors declare that they have no conflicts of interest.

CONTRIBUTIONS

MT and LR was involved in the design of experiment, data analysis, and the writing of the manuscript. SKB contributed towards recruitment of the participants for the study. SS helped in statistical analysis. HPSS, NT, and AR contributed in the designing of the study and evaluation of manuscript.

ACKNOWLEDGMENT

We acknowledge Bhaskar Singh and Rajeshwari Verma for maintaining liaison with the cohort and NDBC team for recruitment of participant. The current study was funded by Department of Biotechnology, Ministry of science and technology, India.

Tarik M, Ramakrishnan L, Sinha S, et al. Association of birth outcomes and postnatal growth with adult leukocyte telomere length. Matern Child Nutr. 2019;15:e12857 10.1111/mcn.12857

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