- Research article
- Open access
- Published:
Sub-optimal maternal gestational gain is associated with shorter leukocyte telomere length at birth in a predominantly Latinx cohort of newborns
Maternal Health, Neonatology and Perinatology volume 9, Article number: 14 (2023)
Abstract
Objective
To assess in utero exposures associated with leukocyte telomere length (LTL) at birth and maternal LTL in a primarily Latinx birth cohort.
Study design
Mothers and newborns were recruited postnatally before 24 h of life. Newborn LTL was collected via heelstick at birth and maternal LTL was collected postnatally. LTL was determined by quantitative PCR. Using a longitudinal design, we evaluated associations between neonatal and maternal LTL and appropriate maternal gestational gain as indicated by the American College of Obstetrics and Gynecology (ACOG).
Result
Mean infant LTL was 2.02 ± 0.30 T/S (n = 386) and maternal LTL was 1.54 ± 0.26 T/S (n = 58). Independent risk factors for shorter LTL at birth included longer gestational duration (Coeff:-0.03, 95%CI: -0.05—0.01;p < 0.01) and maternal gestational weight gain below ACOG recommendations (Coeff:-0.10, 95%CI: -0.18 – -0.02; p = 0.01).
Conclusion
Gestational weight gain below ACOG recommendations may adversely impact neonatal health in Latinx infants as indicated by shorter LTL at birth.
Background
Telomeres, a biomarker of mitotic replicative history in somatic cells [45], shorten in tandem with the biological age of an organism [7]. Rate of attrition is dependent upon the presence of risk factors [53], with some studies noting the negative effects of lower socioeconomic status [11, 18], mental illness [59], smoking [63], and toxic environmental exposures [70] on leukocyte telomere length (LTL). Shorter LTL is a known risk factor for disease, including certain types of cancer [7, 41] and chronic metabolic disease include type 2 diabetes mellitus and cardiovascular disease [17, 27, 66].
There is significant LTL variability at birth [53]. Most studies have found female LTL to be longer than in males, including some of our own [39, 53, 69]. Other factors that are associated with shorter LTL at birth include more advanced parental age [12, 71] exposures to oxidative stress, including maternal smoking or secondhand smoke exposure in utero [48, 63] and the presence of maternal mental illness or stress during pregnancy [23, 64].
Previous studies have found race/ethnicity to be a significant factor impacting LTL at birth [20, 34, 39]. Most studies, however, only assess differences between participants of white or black racial background [34, 55], or only assess LTL later in childhood in diverse cohorts [49, 50]. Few studies have addressed relationships between race or ethnicity and LTL at birth or included Latinx children apart from our previous publications [10, 69]. Latinx families are one of the fastest growing [28], historically and contemporarily marginalized [2] population groups in the United States. Close to 50% of new births in the state of California are Latinx and Latinx newborns represent the largest population demographic of young children [54].
As shorter LTL at birth is associated with long-term adverse health outcomes [14, 43, 51], elucidating in utero factors that impact LTL could have major public health implications for this important population group. In this study, we evaluated the role of maternal weight gain in pregnancy on newborn LTL as excessive or inadequate weight gain in pregnancy can have short and long-term consequences including obesity and metabolic disease [9, 22].
Methods
Cohort and inclusion, exclusion criteria
Data were collected from the Telomere at Birth (TAB) cohort, a longitudinal study of mothers and babies recruited postnatally at UCSF Benioff and Zuckerberg San Francisco General Hospitals to assess how intrauterine exposures impact LTL. Eligibility criteria for maternal enrollment included English or Spanish speaking, no history of active illicit drug use and plans to stay in the San Francisco Bay Area for the foreseeable future. Eligibility criteria for infant enrollment included > 32 weeks gestational age, no contraindications for breastfeeding, in the newborn or intensive care nursery without any imminent surgery or chronic disease condition including possibility of HIV infection or COVID-19. All study procedures were approved by the Institutional Review Board (IRB) at the University of California, San Francisco (UCSF) and all patients signed informed consent for their and their children’s participation. There were no financial competing interests associated with this research. All methods were carried out in accordance with relevant guidelines and regulations (Declaration of Helsinki).
Study procedures
Eligible study participants were screened via electronic medical record review in both hospitals and subsequently approached prior to 24-h postpartum when the California Genetic Newborn Screen is routinely conducted. Bilingual research coordinators explained all study procedures to potential participants. Participants were subsequently interviewed using a one-page questionnaire to collect information on exposures in pregnancy including dietary ones (specifically sugar sweetened beverage (SSB), defined as all sodas, fruit juices and sweetened teas, and 100% fruit juice intake during pregnancy), smoking/second hand smoke exposure and weight gain in pregnancy. Demographic and household information was also collected including race/ethnicity, marital status, smoking history and exposure to secondhand smoke. Self-reported medical conditions and health history were also collected including diagnoses in pregnancy such as gestational diabetes mellitus and hypertension, age of menarche and the medical record was used to confirm all diagnoses. Centers for Disease and Control (CDC) growth curves were used to calculate newborn percentiles and Z scores [36]. All data was uploaded into RedCap and analyzed using Stata 15.0 and 16.0 (StataCorp, College Station, TX, USA). and Python 3.
Leukocyte telomere length analysis
DNA was extracted from the dried blood spots (DBS) on Whatmann 903 cards with the QIAamp DNA Investigator kit (QIAGEN cat# 56,504) and eluted in 50 ml ATE buffer. The DBS were collected between August 2016 to March 2020, stored at -80ºC and batch-extracted in November 2020. The DNA yields from DBS are too low to be accurately measured by OD260/OD280. Instead, based on our experience, we used 8 ul of extracted DNA. The values from the single-copy genes were within the standard curve, confirming that we had used the proper amount of input DNA.
DNA was stored at -80ºC and LTL assays were performed between November to December of 2020. The telomere qPCR primers were tel1b [5'-CGGTTT(GTTTGG)5GTT-3'], used at a final concentration of 100 nM, and tel2b [5'-GGCTTG(CCTTAC)5CCT-3'], used at a final concentration of 900 nM. The single-copy gene (human beta-globin) qPCR primers were hbg1 [5'-GCTTCTGACACAACTGTGTTCACTAGC-3'], used at a final concentration of 300 nM, and hbg2 [5'-CACCAACTTCATCCACGTTCACC-3'], used at a final concentration of 700 nM. The final reaction mix consisted of the following: 20 mM Tris-hydrochloride, pH 8.4; 50 mM potassium chloride; 200 μM each deoxyribonucleotide triphosphate; 1% dimethyl sulfoxide; 0.4 × SYBR green I; 22 ng Escherichia coli DNA; 0.4 Units of platinum Taq DNA polymerase (Invitrogen Inc., Carlsbad, CA), and approximately 6.6 ng of genomic DNA per 11 µl reaction. A threefold serial dilution of a commercial human genomic DNA (Sigma-Aldrich, cat#11,691,112,001) containing 26, 8.75, 2.9, 0.97, 0.324 and 0.108 ng of DNA was included in each PCR run as the reference standard. The quantity of targeted templates in each sample was determined relative to the reference DNA sample by the maximum second derivative method in the Roche LC480 program. The reaction was carried out in a Roche LightCycler 480 in 384-well plates, with triplicate wells for each sample. Dixon Q test was used to exclude outliners from the triplicates. The average of the T and S triplicate wells after outliner removal was used to calculate the T/S ratio for each sample. The same reference DNA was used for all PCR runs. The PCR efficiencies of the T and S reactions were 88.4% ± 4.1% and 91.4% ± 3.9% respectively.
The thermal profile for telomere (T) consisted of denaturing at 96ºC for 1 min followed by 30 cycles of denaturing at 96ºC for 1 s and annealing or extension at 54ºC for 60 s with fluorescence data collection. The thermal profile for a single copy gene (S) consisted of denaturing at 96ºC for 1 min followed by 8 cycles of denaturing at 95ºC for 15 s, annealing at 58ºC for 1 s, and extension at 72ºC for 20 s, followed by 35 cycles of denaturing at 96ºC for 1 s, annealing at 58ºC for 1 s, extension at 72ºC for 20 s, and holding at 83ºC for 5 s with data collection. We adapted the assay from the Cawthon 2002 study [15, 38]. The average inter-assay coefficient of variation (CV) for this study was 2.3 ± 1.5%. Intra-class correlation (ICC) of repeat extractions of 46 dried blood spot samples from this study was 0.883 (CI [0.766–0.942]).
Statistical analysis
Maternal/parental characteristics
We evaluated whether the LTL data was normally distributed using a QQ plot graphical plot which confirmed LTL normal distribution. We conducted bivariate analyses using t-tests to evaluate the association between maternal and child LTL and dichotomous parental characteristics such as maternal high school education, Latinx parental ethnicity, paternal age (≤ 35 years and > 35 years), maternal smoking (yes/no), maternal mental illness pre-gestation or during pregnancy, maternal pre-existing or gestational hypertension, age of menstruation onset (≤ 12 years and > 12 years), and weight gain during pregnancy (≤ 40 lbs and > 40 lbs).
Parental categorical variables that were assessed in relation to child or maternal LTL included maternal education, marital status, parental race, maternal age (< 20, 20–25, 25–30, 30–35, 35–40, and > 40), maternal diabetes (preexisting diabetes, gestational diabetes, no diabetes), sugar-sweetened beverage (SSB) consumption (no SSB consumption, some (0–4/week) SSB consumption, high (> 4/week) SSB consumption), pre-pregnancy maternal body mass index (BMI) (underweight/normal, overweight, and obese), American College of Obstetrics and Gynecology (ACOG) [3] weight gain during pregnancy recommendations per pre-pregnancy BMI (under range [< 28 lbs (divide by 2.205 for kilograms) for < 18.5 BMI, < 25 lbs for 18.5–24.9 BMI, < 15 lbs for 25–29.9 BMI, and < 11 lbs for >=30 BMI], normal range [28–40 lbs for < 18.5 BMI, 25–35 lbs for 18.5–24.9 BMI, 15–25 lbs for 25–29.9 BMI, 11–20 lbs for >=30 BMI], and over range [> 40 lbs for < 18.5 BMI, > 35 lbs for 18.5–24.9 BMI, > 25 lbs for 25–29.9 BMI, and > 20 lbs for >=30 BMI]) [3], parity (1, 2/3, and > 3). Categorical variables were assessed for significance with maternal and child LTL using one-way analysis of variance tests. We also evaluated the relationship between weight gain within or outside ACOG limits and possible interaction with infant sex to determine infant LTL using linear regression models.
Child characteristics
Dichotomous child variables included gender (M/F), Apgar at 5 min (< 9, ≥ 9), birth type (vaginal, C-section), child birth weight Z-score (< 0, ≥ 0), child birth length Z-score (< 0, ≥ 0), and head circumference (≤ 34.5 cm, > 34.5 cm). Student t-tests were used to ascertain child and maternal LTL in relation to dichotomous variables. Similarly, categorical child characteristics such as gestational age (< 35 weeks, ≥ 35 and < 37 weeks, and ≥ 37 weeks), Apgar at 1 min (< 7, ≥ 7 and < 9, and ≥ 9), and child birth weight (all birth weights, low birth weight (<2500 grams), macrosomic (>4000 grams)) were assessed using one-way analysis of variance tests.
Continuous variables
Maternal characteristics
Linear regression and Pearson’s correlation coefficient was used to assess the relationship between continuous variables such maternal LTL and the following continuous variables: maternal age, SSB intake, pre-pregnancy BMI, weight gain in pregnancy (lbs), age of menstruation onset, parity, gestational age, child birth weight (grams), birth weight Z-score, birth length Z-score, Apgar score at 1 min, Apgar score at 5 min, and head circumference (cm).
Child characteristics
Regressions and Pearson’s correlation coefficient was also performed to assess the association between child LTL and the variables mentioned above.
Multivariable linear regression
Multivariable linear regression models were used to assess independent predictors of maternal LTL and child LTL. Variables with statistical significance of p < 0.10 in bivariate analyses or potential biological plausibility were included in multivariable models.
We constructed two multivariable models of child LTL. One larger model (n = 351) included birthweight Z score, SSB weekly consumption, maternal Latina ethnicity, maternal age at menarche, gestational age, pre-existing or gestational mental illness and ACOG weight gain during pregnancy (within, above or below guidelines) and maternal pre-pregnancy BMI. A smaller model (n = 151) included paternal Latino ethnicity in addition to the aforementioned variables (excluding maternal pre-pregnancy and BMI to maximize sample size). The second model was significantly smaller as there was a sizable percentage of missing data for the second model as fewer families provided ethnicity information on fathers. We decided to run this smaller model to evaluate the potential role of paternal ethnicity on infant LTL.
In the maternal LTL model (n = 54), we included the continuous variables parity, SSB consumption per week, maternal age, maternal pre-pregnancy BMI, gestational weight gain in pregnancy and the dichotomous variable maternal high school education (high school diploma/no high school diploma).
Results
Predictors of child leukocyte telomere length
A total of 389 infants had a mean LTL of 2.02 ± 0.30 T/S (Table 1). We did not find any significant maternal or paternal level characteristics including maternal or paternal racial background, ethnicity or age or associated with newborn LTL (Table 1). However, fathers with Mexican/Central American ethnicity had shorter LTL (1.99 ± 0.25) than those with South American/Caribbean/Spain/Portuguese background (2.12 ± 0.40 T/S) (P = 0.02; Table 1).
Mothers with a history of mental illness had shorter infant LTL (1.96 ± 0.28 T/S) than mothers with no history (2.03 ± 0.30 T/S), although this relationship was not statistically significant (P = 0.086). Similarly, mothers who gained less than the ACOG recommended weight gain for pregnancy had infants with shorter LTL (1.95 ± 0.24 T/S) compared with mothers who gained the recommended or above the recommended amount (2.04 ± 0.34 T/S and 2.03 ± 0.27 T/S respectively; P = 0.08) although the difference did not meet statistical significance (Table 1). There was an overall trend of mothers who gained more weight having infants with longer LTL but the results were not statistically significant (> = 40 lbs versus < 40 lbs, 2.09 ± 0.03 T/S versus 2.01 +/-0.30) and neared statistical significance (p < 0.05).
We found few child level variables that were associated with longer LTL at birth (Table 1). Female infants had longer LTL than male infants (2.06 ± 0.29 T/S vs 1.99 + /0.30 T/S; P = 0.04) (Table 1) as did newborns with shorter gestational duration compared with newborns with longer gestation (r = -0.12, P = 0.02). Larger head circumference was associated with longer newborn LTL but the results trended towards statistical significance(r = -0.09, P = 0.09).
Predictors of maternal leukocyte telomere length
For the 58 mothers with leukocyte telomere length (LTL) measured postnatally, mean LTL was 1.54 ± 0.26 T/S (Table 2). Older mothers tended to have shorter LTL than younger mothers (r = -0.30, P = 0.02) (Table 2). We did not find any association between other maternal or child variables and LTL including maternal demographics, health history and child anthropometrics at birth including infant LTL (Table 2).
Multivariable predictors of newborn leukocyte telomere length
In multivariable model (N = 359) of newborn LTL including maternal Latina ethnicity, maternal mental illness during pregnancy, age of menarche, maternal pre-pregnancy BMI, weight gain in pregnancy based on ACOG recommendations, maternal diabetes mellitus (pre-existing or gestational), newborn sex, gestational age, birth weight Z-score, and maternal SSB consumption per week, three variables were associated with newborn LTL (Table 3). Female sex was associated with significantly longer newborn LTL compared with male (ß-coefficient = 0.08, 95%CI 0.02–0.14; p = 0.01). Longer gestational duration compared with shorter gestation was associated with shorter LTL (ß-coefficient = -0.03, -0.06-(-)0.01; p < 0.01). Mothers with weight gain below the ACOG recommendation also had newborns with shorter LTL (ß-coefficient = -0.10, (95%CI -0.18–0.02; p = 0.02). (Table 3; Figs. 1 and 2). We evaluated the possible role of interaction between gestational weight gain per ACOG recommendations and infant sex in relation to infant LTL not finding any significant statistical effect for the interaction term.
In a smaller model of newborn LTL including paternal Latino ethnicity categories (Mexican/Central American versus South American/Caribbean/Spain/Portuguese), maternal age, parity, maternal education, weight gain within, below or above ACOG recommendations and pre-pregnancy BMI with a sample size (N = 156), two variables were associated with shorter newborn LTL. Increased gestational age was associated with shorter LTL (ß = coefficient = -0.04, -0.07-(-)0.01; p < 0.01) and mothers with weight gain below the ACOG recommendation similarly were associated with shorter newborn LTL (ß-coefficient = -0.15,95%CI -0.26-(-)0.04; p < 0.01) (results not shown). Paternal Latino ethnicity of South American/Caribbean/Spanish/Portuguese origin was associated with longer LTL in newborns but the results trended to statistical significance (ß-coefficient = 0.11, 95%CI -0.001–0.23; p = 0.07) (results not shown). Similar to the above larger model of newborn LTL, male sex was associated with shorter LTL compared with female newborns although the results trended towards statistical significance (Coeff -0.08, 95%CI -0.17–0.008, P = 0.07).
Multivariable predictors of maternal leukocyte telomere length
In a model of maternal LTL (n = 54) including maternal parity, SSB weekly consumption (servings), maternal age, education level and pre-pregnancy BMI, increasing maternal age was associated with a decreased maternal postnatal LTL (ß-coefficient = -0.02, 95%CI -0.03—0.005) (Table 4). No high school diploma was associated with shorter maternal LTL compared with having a high school diploma (ß- coefficient = 0.18, 95%CI 0.003–0.36; p = 0.046) (Table 4).
Discussion
Inadequate gestational gain and shorter LTL
Our data from a primarily Latina cohort indicate that sub-optimal maternal weight gain during pregnancy (using definitions from ACOG) is associated with a reduction in newborn infant LTL. We found the longest infant LTL to be from the normal weight gain category, providing evidence at the cellular level of the integrity of these ACOG recommendations. Our studies confirm findings from another group that found shorter fetal LTL with inadequate gestational weight gain earlier in gestation [46]. Maugeri and colleagues similarly utilized a longitudinal birth cohort design, but assessed fetal LTL in cell-free DNA from amniotic fluid at a mean of 16 weeks, in a European Italian population. Another European study (Belgian cohort) however did not find any association between weight gain in pregnancy, similarly using the adequate/insufficient or excessive weight gain based on ACOG categories [42]. This study, however, had a much lower percentage of women with pre-pregnancy overweight or obesity compared with ours (34.3% in the European cohort (10.7% obese) versus 44.85% in our cohort including 21.45% obese). We also had a relatively high percentage of women who had insufficient gain in pregnancy (25%), and it is not clear how many women in the Belgian cohort did not have adequate gain. It is possible that demographic and health characteristics differences between studies explain disparate findings.
In addition to our observations of negative LTL effects from inadequate gestational weight gain, other adverse maternal and neonatal outcomes are related to high and low gestational weight gain [29], and appear to follow a U-shaped curve [67]. Although not statistically significant, there was a trend in our data also of shorter LTL with excessive gestational gain. Among Latina mothers, in particular, disparate gestational weight gain and aforementioned outcomes exist, and are closely associated with pre-pregnancy BMI [19], so future steps, such as nutrition counselling, are essential in reducing adverse infant outcomes. Previous studies have found that inadequate and excessive gestational gain are associated with epigenetic changes including DNA methylation in the placental and umbilical cord tissues [35, 44]. The temporal relationship between maternal phenotypic traits such as diet or weight gain in pregnancy, DNA methylation patterns and infant LTL are not clear although one study has suggested that epigenetic changes may mediate the relationship between maternal phenotypes and infant LTL [6].
Maternal education level and maternal/child LTL
Maternal educational disparities often track with health outcomes (both for mothers and children), as education level is a good proxy of overall socioeconomic status [56]. In our sample, we found that high school education was significantly associated with longer maternal LTL, which aligns closely with past findings [1, 4, 40]. When stratifying our high school educated mothers further, however, we did not find any significant differences between college educated vs high school educated mothers compared to those who had education less than high school, similar to recent findings [4]. This adds to growing literature that educational attainment is an important determinant of LTL in adult life, potentially due to the role that educational attainment plays in buffering against stress and as a correlate of socioeconomic status [60, 62]. We did not find, however, any association between maternal education level and infant LTL in contrast with our previous findings [69].
Infant sex and LTL
Similar to previous findings in Latinx newborns [69], in this larger cohort of primarily Latinx newborns, we found significantly longer newborn LTL in females compared to males, a finding that has been explored in recent studies (Bosquet [23, 24, 26, 33] but not replicated. One other study reported a greater difference between males and females [16] than our findings. We had a 3.40% difference between male and female LTL T/S ratios compared with a 4.39% difference in a large study of Chinese, Malay and Indian infants in a Singaporean cohort [16]. Our previous finding in cord blood in a smaller sample (n = 54) had a 5.1% difference between male and female newborns [69]. Other US based studies have not found statistically significant differences between male and female LTL at birth [23, 53] or a smaller difference than our finding (1.46%) [25] and a study of infants at 3 months of age from the Netherlands also did not find any difference between girls and boys [26]. It is possible that there is interaction between racial/ethnic and sex differences in determining newborn LTL at birth as some studies with white and black newborns have found [20] more pronounced differences between certain racial/ethnic groups.
Parental demographics and infant LTL
Previous studies have demonstrated significant differences in racial background and LTL in infants [20, 25, 49]. In particular, populations with African/black origin have longer LTL than other population groups [30, 32, 40, 52].
As Latinx ethnicity comprises heterogeneous population groups with different racial backgrounds, we sought to further categorize place of origin within our diverse cohort of Latinx families. We found longer LTL of infants from fathers with Caribbean, South American, Spanish or Portuguese backgrounds although the results only trended to statistical significance. It is possible that this group reflects the African ancestry of the Caribbean origin fathers, who comprised about 20% of our Latinx fathers. Black African and African-Americans have longer LTL than non-Hispanic whites in many other studies in adults [49, 57, 65], as well as infants [13, 20, 25]. This is the first study to report on differences in infant LTL within a Latinx cohort on the basis of geographic origin. Interestingly, this study is also one of the few studies to delineate differences in LTL on the basis of paternal geographic origin. As our sample that included data on paternal ethnicity and race was smaller, future studies should evaluate the role of maternal and paternal ethnic and racial background on infant LTL.
Negative findings
Overall, our study did not replicate the association between adverse maternal health exposures in pregnancy and shorter LTL in neonates, possibly due to the relative homogeneity of our sample in terms of socio-demographics and the absence of common chronic health conditions.
Other studies have found that maternal stress during pregnancy is associated with decreased maternal LTL [47] and infant LTL [58]. We did find that pre-existing or gestational mental illness had a negative impact on child LTL in univariate analysis, although results did not meet statistical significance in multivariable models, which may have been the result of a small sample size of patients with recorded mental illness and a lack of data on severity or duration. We had approximately 14% of mothers report mental health issues in pregnancy and we did not differentiate between incident diagnosis or pre-existing conditions. We also did not collect data on treatment or remission and it is possible that untreated mental illness may have more adverse impacts on neonatal LTL. Previous studies have found that maternal stress in pregnancy is associated with shorter LTL [58]. Alternatively, the impact on child LTL may be delayed and exposure to maternal mental illness in utero may only impact child health at later timepoints as other studies have indicated with school age children [61].
We also did not find any association with SSB consumption in pregnancy and child or maternal LTL. From previous studies, including some of our own, sugar-sweetened beverage (SSB) consumption has been shown to be associated with shorter LTL in early childhood, adolescence, and adulthood [10, 37, 68] however few studies have been conducted with pregnant women. A previous study with longitudinal LTL measurements found that pregnant women with reduced SSB consumption had decreased LTL attrition over time but did not find any association between LTL and overall SSB consumption. Our sample size of LTL in postpartum women in this study was small and it is possible that impacts on children may also be delayed and further follow-up is warranted.
We also did not find any association between parental age and infant LTL. Other studies have shown positive associations between paternal age and children’s LTL [8, 12, 16, 31, 71], and slight negative correlations with advancing maternal age [21]. However, our paternal and maternal age distribution was narrow. In the case of our fathers, the majority were under the age of 35, where advanced paternal age has been shown to correlate with increased infant LTL in previous studies [16, 31].
Future directions
Future studies could evaluate the role of maternal gestational gain on telomere length in other tissue types such as placental and umbilical cord that could better elucidate pathways between maternal health in pregnancy and neonatal outcomes. Longitudinal measurements of placental LTL could help elucidate whether gestational gain at certain time periods in pregnancy were of particular significance. Other studies have suggested that DNA methylations patterns may mediate the relationship between parental phenotypes and infant LTL and as such future infant LTL studies could also include evaluation of DNA methylation [5]. In this study, we did not collect paternal LTL data, which may have been helpful in substantiating some of the associations we found between paternal variables and child LTL. Our study was also limited by sample size in the analysis of health variables that had a low frequency in our population, including smoking during pregnancy, pre-existing diabetes mellitus and hypertension.
Availability of data and material
Data is available by email request and review from the principal investigator of the study (Wojcicki).
References
Adler N, Pantell MS, O’Donovan A, Blackburn E, Cawthon R, Koster A, Opresko P, Newman A, Harris TB, Epel E. Educational attainment and late life telomere length in the Health, Aging and Body Composition Study. Brain Behav Immun. 2013;27:15–21. https://doi.org/10.1016/j.bbi.2012.08.014.
Akee, R., Jones, M. R., & Porter, S. R. (2019). Race Matters: Income Shares, Income Inequality, and Income Mobility for All U.S. Races. Demography, 56(3), 999–1021. https://doi.org/10.1007/s13524-019-00773-7.
American College of Obstetricians and Gynecologists (2013). ACOG Committee opinion no. 548: weight gain during pregnancy. Obstetrics and gynecology, 121(1), 210–212. https://doi.org/10.1097/01.aog.0000425668.87506.4c
Amin V, Fletcher JM, Sun Z, Lu Q. Higher educational attainment is associated with longer telomeres in midlife: Evidence from sibling comparisons in the UK Biobank. SSM Popul Health. 2022;17:101018. https://doi.org/10.1016/j.ssmph.2021.101018.
Andreu-Sánchez S, Aubert G, Ripoll-Cladellas A, Henkelman S, Zhernakova DV, Sinha T, Kurilshikov A, Cenit MC, Jan Bonder M, Franke L, Wijmenga C, Fu J, van der Wijst MGP, Melé M, Lansdorp P, Zhernakova A. Genetic, parental and lifestyle factors influence telomere length. Commun Biol. 2022;5(1):565. https://doi.org/10.1038/s42003-022-03521-7.
Andreu-Sánchez S, Aubert G, Ripoll-Cladellas A, Henkelman S, Zhernakova DV, Sinha T, Kurilshikov A, Cenit MC, Jan Bonder M, Franke L, Wijmenga C, Fu J, van der Wijst MGP, Melé M, Lansdorp P, Zhernakova A. Genetic, parental and lifestyle factors influence telomere length. Commun Biol. 2022;5(1):565. https://doi.org/10.1038/s42003-022-03521-7.PMID:35681050;PMCID:PMC9184499.
Aubert G, Lansdorp PM. Telomeres and Aging. Physiol Rev. 2008;88(2):557–79. https://doi.org/10.1152/physrev.00026.2007.
Aviv A, Susser E. Leukocyte Telomere Length and the Father’s Age Enigma: Implications for Population Health and for Life Course. Int J Epidemiol. 2013;42(2):457–62. https://doi.org/10.1093/ije/dys236.
Baran J, Weres A, Czenczek-Lewandowska E, Leszczak J, Kalandyk-Osinko K, Łuszczki E, Sobek G, Mazur A. Excessive Gestational Weight Gain: Long-Term Consequences for the Child. J Clin Med. 2020;9(12):3795. https://doi.org/10.3390/jcm9123795.PMID:33255248;PMCID:PMC7761026.
Baskind MJ, Hawkins J, Heyman MB, Wojcicki JM. Obesity at Age 6 Months Is Associated with Shorter Preschool Leukocyte Telomere Length Independent of Parental Telomere Length. J Pediatr. 2021;233:141–9. https://doi.org/10.1016/j.jpeds.2020.11.025.
Batty GD, Wang Y, Brouilette SW, Shiels P, Packard C, Moore J, Samani NJ, Ford I. Socioeconomic status and telomere length: The West of Scotland Coronary Prevention Study. J Epidemiol Community Health. 2009;63(10):839–41. https://doi.org/10.1136/jech.2009.088427.
Broer L, Codd V, Nyholt DR, Deelen J, Mangino M, Willemsen G, et al. Meta-analysis of telomere length in 19 713 subjects reveals high heritability, stronger maternal inheritance and a paternal age effect. Eur J Hum Genet. 2013;21(10):1163–8. https://doi.org/10.1038/ejhg.2012.303.
Brown L, Needham B, Ailshire J. Telomere length among older U.S. adults: differences by race/ethnicity, gender, and age. J Aging Health. 2017;29(8):1350–66. https://doi.org/10.1177/0898264316661390.
Casavant SG, Cong X, Moore J, Starkweather A. Associations between preterm infant stress, epigenetic alteration, telomere length and neurodevelopmental outcomes: A systematic review. Early Human Dev. 2019;131:63–74. https://doi.org/10.1016/j.earlhumdev.2019.03.003.
Cawthon RM. Telomere measurement by quantitative PCR. Nucleic Acids Res. 2002;30(10):e47. https://doi.org/10.1093/nar/30.10.e47.
Chen L, Tan KML, Gong M, Chong MFF, Tan KH, Chong YS, Meaney MJ, Gluckman PD, Eriksson JG, Karnani N. Variability in newborn telomere length is explained by inheritance and intrauterine environment. BMC Med. 2022;20(1):20. https://doi.org/10.1186/s12916-021-02217-9.
Cheng F, Luk AO, Shi M, Huang C, Jiang G, Yang A, et al. Shortened leukocyte telomere length is associated with glycemic progression in type 2 diabetes: a prospective and mendelian randomization analysis. Diabetes Care. 2022;45(3):701–9. https://doi.org/10.2337/dc21-1609.
Cherkas LF, Aviv A, Valdes AM, Hunkin JL, Gardner JP, Surdulescu GL, Kimura M, Spector TD. The effects of social status on biological aging as measured by white-blood-cell telomere length. Aging Cell. 2006;5(5):361–5. https://doi.org/10.1111/j.1474-9726.2006.00222.x.
Dolin CD, Gross RS, Deierlein AL, Berube LT, Katzow M, Yaghoubian Y, Brubaker SG, Messito MJ. Predictors of Gestational Weight Gain in a Low-Income Hispanic Population: Sociodemographic Characteristics, Health Behaviors, and Psychosocial Stressors. Int J Environ Res Public Health. 2020;17(1):352. https://doi.org/10.3390/ijerph17010352.
Drury SS, Esteves K, Hatch V, Woodbury M, Borne S, Adamski A, Theall KP. Setting the Trajectory: Racial Disparities in Newborn Telomere Length. J Pediatr. 2015;166(5):1181–6. https://doi.org/10.1016/j.jpeds.2015.01.003.
Eisenberg DTA, Kuzawa CW. The paternal age at conception effect on offspring telomere length: Mechanistic, comparative and adaptive perspectives. Philos Trans R Soc Lond B Biol Sci. 2018;373(1741):20160442. https://doi.org/10.1098/rstb.2016.0442.
Elwan D, Olveda R, Medrano R, Wojcicki JM. Excess pregnancy weight gain in latinas: Impact on infant’s adiposity and growth hormones at birth. Prev Med Rep. 2021;22:101341. https://doi.org/10.1016/j.pmedr.2021.101341.
Enlow MB, Bollati V, Sideridis G, Flom JD, Hoxha M, Hacker M, Wright RJ. Sex differences in effects of maternal risk and protective factors in childhood and pregnancy on newborn telomere length. Psychoneuroendocrinology. 2018;95:74–85. https://doi.org/10.1016/j.psyneuen.2018.05.025.
Enlow MB, Sideridis G, Bollati V, Hoxha M, Hacker MR, Wright RJ. Maternal cortisol output in pregnancy and newborn telomere length: Evidence for sex-specific effects. Psychoneuroendocrinology. 2019;102:225–35. https://doi.org/10.1016/j.psyneuen.2018.12.222.
Factor-Litvak P, Susser E, Kezios K, McKeague I, Kark JD, Hoffman M, Kimura M, Wapner R, Aviv A. Leukocyte Telomere Length in Newborns: Implications for the Role of Telomeres in Human Disease. Pediatrics. 2016;137(4):e20153927. https://doi.org/10.1542/peds.2015-3927.
de Fluiter KS, Codd V, Denniff M, Kerkhof GF, van Beijsterveldt IALP, Breij LM, Samani NJ, Abrahamse-Berkeveld M, Hokken-Koelega ACS. Longitudinal telomere length and body composition in healthy term-born infants during the first two years of life. PLoS ONE. 2021;16(2):e0246400. https://doi.org/10.1371/journal.pone.0246400.
Fok WC, Batista LFZ. Stressed ends: Telomere attrition in chronic diseases. Rev Bras Hematol Hemoter. 2017;39(2):98–9. https://doi.org/10.1016/j.bjhh.2017.03.004.
Frey, W. H. (2020). The nation is diversifying even faster than predicted, according to new census data. Brookings. https://www.brookings.edu/research/new-census-data-shows-the-nation-is-diversifying-even-faster-than-predicted/
Goldstein RF, Abell SK, Ranasinha S, Misso ML, Boyle JA, Harrison CL, Black MH, Li N, Hu G, Corrado F, Hegaard H, Kim YJ, Haugen M, Song WO, Kim MH, Bogaerts A, Devlieger R, Chung JH, Teede HJ. Gestational weight gain across continents and ethnicity: Systematic review and meta-analysis of maternal and infant outcomes in more than one million women. BMC Med. 2018;16(1):153. https://doi.org/10.1186/s12916-018-1128-1.
Hansen MEB, Hunt SC, Stone RC, Horvath K, Herbig U, Ranciaro A, Hirbo J, Beggs W, Reiner AP, Wilson JG, Kimura M, De Vivo I, Chen MM, Kark JD, Levy D, Nyambo T, Tishkoff SA, Aviv A. Shorter telomere length in Europeans than in Africans due to polygenetic adaptation. Hum Mol Genet. 2016;25(11):2324–30. https://doi.org/10.1093/hmg/ddw070.
Horvath K, Eisenberg D, Stone R, Anderson J, Kark J, Aviv A. Paternal Age and Transgenerational Telomere Length Maintenance: A Simulation Model. Sci Rep. 2019;9(1):20. https://doi.org/10.1038/s41598-018-36923-x.
Hunt SC, Chen W, Gardner JP, Kimura M, Srinivasan SR, Eckfeldt JH, Berenson GS, Aviv A. 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. 2008;7(4):451–8. https://doi.org/10.1111/j.1474-9726.2008.00397.x.
Izano MA, Cushing LJ, Lin J, Eick SM, Goin DE, Epel E, Woodruff TJ, Morello-Frosch R. The association of maternal psychosocial stress with newborn telomere length. PLoS ONE. 2020;15(12):e0242064. https://doi.org/10.1371/journal.pone.0242064.
Jones CW, Gambala C, Esteves KC, Wallace M, Schlesinger R, O’Quinn M, Kidd L, Theall KP, Drury SS. Differences in placental telomere length suggest a link between racial disparities in birth outcomes and cellular aging. Am J Obstet Gynecol. 2017;216(3):294.e1–294.e8. https://doi.org/10.1016/j.ajog.2016.11.1027.
Kawai T, Yamada T, Abe K, et al. Increased epigenetic alterations at the promoters of transcriptional regulators following inadequate maternal gestational weight gain. Sci Rep. 2015;5:14224. https://doi.org/10.1038/srep14224.
Kuczmarski RJ, Ogden CL, Grummer-Strawn LM, Flegal KM, Guo SS, Wei R, Mei Z, Curtin LR, Roche AF, Johnson CL. CDC growth charts: United States. Adv Data. 2000;314:1–27 (PMID: 11183293).
Leung CW, Laraia BA, Coleman-Phox K, Bush NR, Lin J, Blackburn EH, Adler NE, Epel ES. Sugary beverage and food consumption, and leukocyte telomere length maintenance in pregnant women. Eur J Clin Nutr. 2016;70(9):1086–8. https://doi.org/10.1038/ejcn.2016.93.
Lin J, Epel E, Cheon J, et al. Analyses and comparisons of telomerase activity and telomere length in human T and B cells: insights for epidemiology of telomere maintenance. J Immunol Methods. 2010;352(1–2):71–80. https://doi.org/10.1016/j.jim.2009.09.012.
Ly K, Walker C, Berry S, Snell R, Marks E, Thayer Z, Atatoa-Carr P, Morton S. Telomere length in early childhood is associated with sex and ethnicity. Sci Rep. 2019;9(1):10359. https://doi.org/10.1038/s41598-019-46338-x.
Lynch SM, Peek MK, Mitra N, Ravichandran K, Branas C, Spangler E, Zhou W, Paskett ED, Gehlert S, DeGraffinreid C, Rebbeck TR, Riethman H. Race, Ethnicity, Psychosocial Factors, and Telomere Length in a Multicenter Setting. PLoS ONE. 2016;11(1):e0146723. https://doi.org/10.1371/journal.pone.0146723.
Ma H, Zhou Z, Wei S, Liu Z, Pooley KA, Dunning AM, Svenson U, Roos G, Hosgood HD, Shen M, Wei Q. Shortened telomere length is associated with increased risk of cancer: A meta-analysis. PLoS ONE. 2011;6(6):e20466. https://doi.org/10.1371/journal.pone.0020466.
Martens DS, Plusquin M, Gyselaers W, De Vivo I, Nawrot TS. Maternal pre-pregnancy body mass index and newborn telomere length. BMC Med. 2016;14(1):148. https://doi.org/10.1186/s12916-016-0689-0.PMID:27751173;PMCID:PMC5067896.
Martens DS, Van Der Stukken C, Derom C, Thiery E, Bijnens EM, Nawrot TS. Newborn telomere length predicts later life telomere length: Tracking telomere length from birth to child- and adulthood. EBioMedicine. 2021;63:103164. https://doi.org/10.1016/j.ebiom.2020.103164.
Mas-Parés B, Xargay-Torrent S, Gómez-Vilarrubla A, Carreras-Badosa G, Prats-Puig A, De Zegher F, Ibáñez L, Bassols J, López-Bermejo A. Gestational Weight Gain Relates to DNA Methylation in Umbilical Cord, Which, In Turn, Associates with Offspring Obesity-Related Parameters. Nutrients. 2023;15(14):3175. https://doi.org/10.3390/nu15143175. PMID:37513594;PMCID:PMC10386148.
Mather KA, Jorm AF, Parslow RA, Christensen H. Is Telomere Length a Biomarker of Aging? A Review. J Gerontol A Biol Sci Med Sci. 2011;66A(2):202–13. https://doi.org/10.1093/gerona/glq180.
Maugeri, A., Magnano San Lio, R., La Rosa, M. C., Giunta, G., Panella, M., Cianci, A., Caruso, M. A. T., Agodi, A., & Barchitta, M. (2021). The Relationship between Telomere Length and Gestational Weight Gain: Findings from the Mamma & Bambino Cohort. Biomedicines, 10(1), 67https://doi.org/10.3390/biomedicines10010067
Merced-Nieves, F. M., Dzwilewski, K. L. C., Aguiar, A., Lin, J., & Schantz, S. L. (2021). Associations of prenatal maternal stress with measures of cognition in 7.5-month-old infants. Developmental Psychobiology, 63(5), 960–972. https://doi.org/10.1002/dev.22059
Mirzakhani H, De Vivo I, Leeder JS, Gaedigk R, Vyhlidal CA, Weiss ST, Tantisira K. Early pregnancy intrauterine fetal exposure to maternal smoking and impact on fetal telomere length. Eur J Obstet Gynecol Reprod Biol. 2017;218:27–32. https://doi.org/10.1016/j.ejogrb.2017.09.013.
Needham BL, Salerno S, Roberts E, Boss J, Allgood KL, Mukherjee B. Do Black/White Differences in Telomere Length Depend on Socioeconomic Status? Biodemography Soc Biol. 2019;65(4):287–312. https://doi.org/10.1080/19485565.2020.1765734.
Niño, M. D. (2021). Poverty, Material Hardship, and Telomere Length Among Latina/o Children. Journal of Racial and Ethnic Health Disparities, 1–10. https://doi.org/10.1007/s40615-021-01072-x
Niu Z, Wen X, Buka SL, Wang M, Tian L, Loucks EB, Kubzansky LD, Mu L. Associations of telomere length at birth with predicted atherosclerotic lesions and cardiovascular disease risk factors in midlife: A 40-year longitudinal study. Atherosclerosis. 2021;333:67–74. https://doi.org/10.1016/j.atherosclerosis.2021.08.013.
Nsereko E, Uwase A, Muvunyi CM, Rulisa S, Ntirushwa D, Moreland P, Corwin EJ, Santos N, Lin J, Chen JL, Nzayirambaho M, Wojcicki JM. Association between micronutrients and maternal leukocyte telomere length in early pregnancy in Rwanda. BMC Pregnancy Childbirth. 2020;20(1):692. https://doi.org/10.1186/s12884-020-03330-y.
Okuda K, Bardeguez A, Gardner JP, Rodriguez P, Ganesh V, Kimura M, Skurnick J, Awad G, Aviv A. Telomere Length in the Newborn. Pediatr Res. 2002;52(3):377–81. https://doi.org/10.1203/00006450-200209000-00012.
Osterman, M., Hamilton, B., Martin, J., Driscoll, A., & Valenzuela, C. (2021). Births: Final Data for 2020. National Center for Health Statistics (U.S.). https://doi.org/10.15620/cdc:112078
Pantesco EJ, Leibel DK, Ashe JJ, Waldstein SR, Katzel LI, Liu HB, Weng N, Evans MK, Zonderman AB, Beatty Moody DL. Multiple Forms of Discrimination, Social Status, and Telomere Length: Interactions within Race. Psychoneuroendocrinology. 2018;98:119–26. https://doi.org/10.1016/j.psyneuen.2018.08.012.
Phelan JC, Link BG, Tehranifar P. Social Conditions as Fundamental Causes of Health Inequalities: Theory, Evidence, and Policy Implications. J Health Soc Behav. 2010;51(1_suppl):S28–S40. https://doi.org/10.1177/0022146510383498.
Rewak M, Buka S, Prescott J, De Vivo I, Loucks EB, Kawachi I, Non AL, Kubzansky LD. Race-Related Health Disparities and Biological Aging: Does Rate of Telomere Shortening Differ Across Blacks and Whites? Biol Psychol. 2014;99:92–9. https://doi.org/10.1016/j.biopsycho.2014.03.007.
Send TS, Gilles M, Codd V, Wolf I, Bardtke S, Streit F, Strohmaier J, Frank J, Schendel D, Sütterlin MW, Denniff M, Laucht M, Samani NJ, Deuschle M, Rietschel M, Witt SH. Telomere Length in Newborns is Related to Maternal Stress During Pregnancy. Neuropsychopharmacology. 2017;42(12):2407–13. https://doi.org/10.1038/npp.2017.73.
Simon, N. M., Smoller, J. W., McNamara, K. L., Maser, R. S., Zalta, A. K., Pollack, M. H., Nierenberg, A. A., Fava, M., & Wong, K.-K. (n.d.). Telomere Shortening and Mood Disorders: Preliminary Support for a Chronic Stress Model of Accelerated Aging. 4.
Steptoe A, Hamer M, Butcher L, Lin J, Brydon L, Kivimäki M, Marmot M, Blackburn E, Erusalimsky JD. Educational attainment but not measures of current socioeconomic circumstances are associated with leukocyte telomere length in healthy older men and women. Brain Behav Immun. 2011;25(7):1292–8. https://doi.org/10.1016/j.bbi.2011.04.010.
Stout-Oswald SA, Glynn LM, Bisoffi M, Demers CH, Davis EP. Prenatal exposure to maternal psychological distress and telomere length in childhood. Dev Psychobiol. 2022;64(1):e22238. https://doi.org/10.1002/dev.22238.
Thomas MD, Sohail S, Mendez RM, Márquez-Magaña L, Allen AM. Racial Discrimination and Telomere Length in Midlife African American Women: Interactions of Educational Attainment and Employment Status. Ann Behav Med. 2021;55(7):601–11. https://doi.org/10.1093/abm/kaaa104.
Valdes AM, Andrew T, Gardner JP, Kimura M, Oelsner E, Cherkas LF, Aviv A, Spector TD. Obesity, cigarette smoking, and telomere length in women. Lancet (London, England). 2005;366(9486):662–4. https://doi.org/10.1016/S0140-6736(05)66630-5.
Verner G, Epel E, Lahti-Pulkkinen M, Kajantie E, Buss C, Lin J, Blackburn E, Räikkönen K, Wadhwa PD, Entringer S. Maternal Psychological Resilience During Pregnancy and Newborn Telomere Length: A Prospective Study. Am J Psychiatry. 2021;178(2):183–92. https://doi.org/10.1176/appi.ajp.2020.19101003.
Walton RT, Mudway IS, Dundas I, Marlin N, Koh LC, Aitlhadj L, Vulliamy T, Jamaludin JB, Wood HE, Barratt BM, Beevers S, Dajnak D, Sheikh A, Kelly FJ, Griffiths CJ, Grigg J. Air pollution, ethnicity and telomere length in east London schoolchildren: An observational study. Environ Int. 2016;96:41–7. https://doi.org/10.1016/j.envint.2016.08.021.
Wang J, Dong X, Cao L, Sun Y, Qiu Y, Zhang Y, Cao R, Covasa M, Zhong L. Association between telomere length and diabetes mellitus: A meta-analysis. J Int Med Res. 2016;44(6):1156–73. https://doi.org/10.1177/0300060516667132.
Wang L, Zhang X, Chen T, Tao J, Gao Y, Cai L, Chen H, Yu C. Association of Gestational Weight Gain With Infant Morbidity and Mortality in the United States. JAMA Netw Open. 2021;4(12):e2141498. https://doi.org/10.1001/jamanetworkopen.2021.41498.
Wojcicki JM, Medrano R, Lin J, Epel E. Increased Cellular Aging by 3 Years of Age in Latino, Preschool Children Who Consume More Sugar-Sweetened Beverages: A Pilot Study. Child Obes. 2018;14(3):149–57. https://doi.org/10.1089/chi.2017.0159.
Wojcicki JM, Olveda R, Heyman MB, Elwan D, Lin J, Blackburn E, Epel E. Cord blood telomere length in Latino infants: Relation with maternal education and infant sex. J Perinatol. 2016;36(3):235–41. https://doi.org/10.1038/jp.2015.178.
Woo J, Tang N, Suen E, Leung J, Wong M. Green space, psychological restoration, and telomere length. The Lancet. 2009;373(9660):299–300. https://doi.org/10.1016/S0140-6736(09)60094-5.
Wulaningsih W, Hardy R, Wong A, Kuh D. Parental age and offspring leukocyte telomere length and attrition in midlife: Evidence from the 1946 British birth cohort. Exp Gerontol. 2018;112:92–6. https://doi.org/10.1016/j.exger.2018.09.008.
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Thanks to the participants for their engagement in this study.
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The authors received funding from the UCSF Preterm Birth Initiative, Marc and Lynn Benioff and the Little Giraffe Foundation.
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JW, LJP, KCP and LR conceived of the study. AP and JW collected the data. JW and AP conducted data analyses. JL did telomere analysis. JW, LJP, KCP, LR, AP and JW analyzed the data.
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Prasad, A., Lin, J., Jelliffe-Pawlowski, L. et al. Sub-optimal maternal gestational gain is associated with shorter leukocyte telomere length at birth in a predominantly Latinx cohort of newborns. matern health, neonatol and perinatol 9, 14 (2023). https://doi.org/10.1186/s40748-023-00167-z
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DOI: https://doi.org/10.1186/s40748-023-00167-z