Key Points
Question
What is the association among preterm risk factors, epigenetic aging, and neurodevelopmental outcomes in children born preterm?
Findings
In this cohort study with 102 children, epigenetic aging, higher maternal education level, extreme prematurity, and severe brain injury were associated with neurodevelopmental outcomes. The association between epigenetic aging and motor outcomes was modified by severe brain injury.
Meaning
The findings suggests that the association between epigenetic aging and neurodevelopment among children born preterm is context dependent and can vary based on the presence of preterm risk factors.
Abstract
Importance
Studies examining biological factors associated with neurodevelopment in the preterm population are limited. It was previously demonstrated that epigenetic age acceleration was associated with better neurodevelopmental outcomes among children born preterm. It is unclear whether this association is modified by clinical and environmental preterm risk factors.
Objective
To examine whether the association between epigenetic aging and neurodevelopmental outcomes is modified by preterm brain injury and socioeconomic status.
Design, Setting, and Participants
This was a prospective cohort study of children born at 24 to 32 weeks’ gestation, recruited from 2 neonatal intensive care units from 2015 to 2019 and followed up to January 2026. The cohort was well characterized with clinical data, brain magnetic resonance imaging, and neurodevelopmental assessments (Bayley-III cognitive and motor domains) at 3 years. Participants with buccal epithelial cell DNA collected at 3 years were included.
Exposure
Epigenetic age (in weeks) at 3 years was determined using the pediatric buccal epigenetic clock and corrected for chronological age to give epigenetic age difference.
Main Outcomes and Measures
Primary analyses used linear regression to examine the association between epigenetic age difference, preterm risk factors (any brain injury, severe brain injury, maternal educational level), and cognitive and motor outcomes at 3 years. Secondary analyses examined whether brain injury and maternal education level modified the associations between epigenetic age difference and cognitive and motor outcomes at 3 years.
Results
A total of 102 study participants (median gestational age, 27.0 weeks [IQR, 25.6-28.9 weeks]; 54 female [53%]) were included. Higher maternal educational level (β = 11.65; 95% CI, 3.55-19.76; P = .005) and epigenetic age acceleration (β = 0.07; 95% CI, 0.01-0.14; P = .04) were associated with higher cognitive scores. Epigenetic age acceleration was also associated with higher motor scores (β = 0.16; 95% CI, 0.06-0.27; P = .003), while extreme prematurity (β = –5.66; 95% CI, −10.85 to −0.46; P = .03) and severe brain injury (β = –10.99; 95% CI, −21.32 to −0.66; P = .04) were associated with lower motor scores. Severe brain injury modified the association between epigenetic aging and motor outcomes (β = 0.41; 95% CI, 0.08-0.74; P = .02), and children with epigenetic age acceleration in the presence of severe brain injury had higher motor scores.
Conclusions and Relevance
In this prospective preterm cohort study, epigenetic aging, severe brain injury, and socioeconomic status were associated with neurodevelopmental outcomes. Children with severe brain injury along with epigenetic age acceleration had higher motor scores. These findings suggest the association between epigenetic aging and neurodevelopment is context dependent and can vary based on the presence of preterm risk factors.
This cohort study examines the association between preterm risk factors, epigenetic aging, and cognitive and motor outcomes among children born preterm.
Introduction
Children born preterm are at increased risk for developmental delay and cognitive, language, and motor impairments.1,2,3 Previous studies have identified clinical factors that are associated with differences in neurodevelopmental outcomes, including sex, neonatal morbidities (infection, bronchopulmonary dysplasia, retinopathy of prematurity), and brain injury.4,5,6,7,8,9 Environmental or home factors, including socioeconomic status and parenting style, are also known to influence neurodevelopmental outcomes.10,11,12,13,14 Biological factors, including genetics and epigenetics, likely contribute to differences in neurodevelopmental outcomes in the preterm population; however these studies are limited.1,15,16,17 Neurodevelopmental trajectories after preterm birth are shaped by complex interactions between biological, clinical, and environmental factors. Previous studies have examined preterm risk factors in isolation, and how these factors interact with underlying biological factors to influence neurodevelopment remains unclear.
Epigenetic mechanisms reflect gene-environment interactions and play an important part in neurodevelopment, aging, and disease states.18,19,20,21,22 Environmental factors can alter gene expression through epigenetic mechanisms (without changing the underlying DNA), leading to differences in a biological pathway or clinical phenotype. There are several epigenetic mechanisms, including chromatin remodeling, histone modification, and DNA methylation. In DNA methylation, the presence of a methyl group on cytosine phosphate guanine (CpG) sites can influence gene transcription, resulting in the gene being activated or silenced.20 These DNA methylation patterns are not fixed and can change over time based on the presence of environmental stressors. In epigenetic studies, DNA methylation is examined using epigenome-wide association studies or epigenetic clocks. Epigenome-wide association studies examine DNA methylation across multiple CpG sites to identify sites associated with the phenotype of interest. In contrast, epigenetic clocks provide a single measure of biological aging or epigenetic age, based on a weighted combination of age-predictive CpG sites. Differences between epigenetic age and chronological age is classified as epigenetic age acceleration (higher epigenetic age relative to chronological age) or deceleration (lower epigenetic age relative to chronological age). Epigenetic age can be easily compared across clinical populations or study groups23 and is well suited to examine biological aging patterns in association with health outcomes. The pediatric buccal epigenetic (PedBE) clock was developed for pediatric populations and has been shown to be highly correlated with chronological age.16,24
Preterm birth is a form of early-life adversity associated with environmental stressors such as procedural pain, medical interventions, and separation from parents. These environmental stressors of prematurity may be associated with epigenetic differences that influence health outcomes and neurodevelopment. Previous studies have found epigenetic differences in the preterm population using epigenome-wide DNA methylation studies and, more recently, using epigenetic clocks.15,16,17,19,25,26 The developmental implications of epigenetic age acceleration and deceleration are not well understood in pediatric or preterm populations. The PedBE clock was recently validated in a pediatric population of children born preterm, and an association was found between epigenetic age and chronological age.16 That study also demonstrated that epigenetic age acceleration was associated with higher cognitive and motor scores among children born preterm. However, the presence of neonatal morbidities was associated with epigenetic age deceleration, suggesting that systemic complications of prematurity may be associated with epigenetic aging patterns. Other studies using epigenetic clocks in the preterm population have also found differences in epigenetic aging in the presence of neonatal morbidities, such as bronchopulmonary dysplasia and postnatal infection.15,17 These prior studies demonstrated an association between epigenetic aging and preterm risk factors, particularly neonatal morbidities. It remains unclear whether other clinical and environmental preterm risk factors are associated with differences in epigenetic aging, and whether these factors interact to influence neurodevelopmental outcomes.
In this prospective preterm cohort study, we examined associations among epigenetic aging, brain injury, and socioeconomic status and neurodevelopmental outcomes. We hypothesized that the direction of the association between epigenetic aging and neurodevelopmental outcome would differ across levels of brain injury and maternal education.
Methods
Study Participants
A prospective cohort of 195 infants born preterm between 24 and 32 weeks’ gestational age was recruited from the neonatal intensive care units of 2 hospitals in Canada (The Hospital for Sick Children and Mount Sinai Hospital) from 2015 to 2019, and followed up longitudinally to January 2026. Exclusion criteria included the presence of congenital brain malformations or congenital infections. A total of 102 participants with epigenetic data were included in the present study, and no participants were lost to follow-up. Of the 102 study participants, 82 (80%) were singletons and 20 (20%) comprised 10 twin pairs. The study was approved by the institutional research ethics boards of The Hospital for Sick Children and Mount Sinai Hospital, and written and informed consent was obtained from parents. This study is reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cohort studies.
Clinical Data
Clinical and demographic data were collected from medical record review from the neonatal intensive care unit admission and updated at each study visit. The following data were collected for each study participant: sex, gestational age, postnatal infection, bronchopulmonary dysplasia, retinopathy of prematurity, any brain injury, severe brain injury, maternal educational level (used as a marker of socioeconomic status), age at brain magnetic resonance imaging (MRI), age at developmental assessment, and age at buccal epithelial cell DNA collection. Bronchopulmonary dysplasia was defined based on the requirement of supplemental oxygen at 36 weeks’ postmenstrual age. Infection was defined as a culture-positive infection. Maternal and prenatal data included maternal medical comorbidities (diabetes, hypertension), maternal substance use (alcohol, smoking, recreational drugs), and administration of prenatal corticosteroids and magnesium sulfate.
Neurodevelopmental Assessments
Study participants were assessed using the Bayley Scales of Infant and Toddler Development, 3rd edition (Bayley-III), at 3 years of age. The Bayley-III cognitive and motor composite scores were used for analyses. All developmental assessments were performed by an experienced psychometrist who was part of the neonatal neurodevelopmental follow-up clinic. Cognitive outcomes were not available for 4 participants and motor outcomes were not available for 10 participants.
Neuroimaging
All study participants underwent 2 brain MRIs, which were performed on a Siemens 3T MRI scanner, without pharmacologic sedation. The first MRI was the early-life scan, which occurred soon after birth, and the second MRI was a term-equivalent scan at 38 to 42 weeks’ postmenstrual age. All MRI scans were reviewed by a pediatric neuroradiologist (H.B.) to assess for the presence and severity of brain injury. Brain injury was classified as per prior studies4,16,27 as white matter injury (mild, moderate, severe) and intraventricular hemorrhage (grades 1-3, periventricular hemorrhagic infarct). Severe brain injury was defined as the presence of white matter injury that was moderate or severe, intraventricular hemorrhage grade 3, or periventricular hemorrhagic infarct.
Epigenetic Data
Buccal epithelial cell samples were processed to obtain DNA methylation data as previously described.16 Epigenetic age was calculated using the PedBE clock24 and is presented in weeks. The applicability of the PedBE clock in early childhood has been previously demonstrated in this cohort with a correlation between epigenetic age and chronological age at 3 years of age (r = 0.40; mean absolute error = 49.8 weeks; P < .001).16 Epigenetic age difference was calculated by subtracting chronological age from epigenetic age. A higher epigenetic age difference was termed epigenetic age acceleration, and a lower epigenetic age difference was termed epigenetic age deceleration. We used absolute age difference as the most suitable measure of epigenetic age acceleration, as it is more appropriate in single-group datasets compared with residual-based age acceleration, which is preferred for case-control study designs.28
Statistical Analysis
All statistical tests were conducted using Stata, version 18 (Stata Corp). Full data were available for most variables; some participants did not have data for certain variables, including retinopathy of prematurity (n = 12), maternal educational level (n = 1), buccal cell proportion (n = 10), cognitive scores at 3 years (n = 4), and motor scores at 3 years (n = 10). Primary analyses examined associations among (1) preterm risk factors (any brain injury, severe brain injury, maternal educational level) and epigenetic age difference at 3 years and (2) epigenetic age difference, preterm risk factors (any brain injury, severe brain injury, maternal educational level), and cognitive and motor outcomes at 3 years. Secondary exploratory analyses examined whether associations between epigenetic age difference and cognitive and motor outcomes were modified by preterm risk factors (any brain injury, severe brain injury, maternal educational level). Interaction (cross-product) terms were created for epigenetic age difference × any brain injury, epigenetic age difference × severe brain injury, and epigenetic age difference × maternal educational level. Supplemental analyses were performed to examine associations between maternal and prenatal factors and epigenetic age difference. Regression models examining associations with epigenetic age difference were adjusted for chronological age and buccal epithelial cell proportion. Regression models examining associations with neurodevelopmental outcomes were adjusted for male sex and extreme prematurity. β Coefficients represent adjusted differences in Bayley-III scores or epigenetic age difference for main effects and differences in slopes for interaction effects. All P values were from 2-sided tests and results were deemed statistically significant at P < .05.
Results
The final study sample included 102 children born preterm with buccal epithelial cell DNA methylation data at 3 years of age (Table 1). The sample included 48 males (47%) and 54 females (53%), and the median gestational age was 27.2 weeks (IQR, 25.6-28.9 weeks). Descriptive data on prenatal exposures, neonatal morbidities, epigenetic age difference, and neurodevelopmental outcomes data are presented in Table 1.
Table 1. Clinical Characteristics of the Study Cohort.
| Characteristic | Participants, No. (%) (N = 102) |
|---|---|
| Gestational age, median (IQR), wk | 27.0 (25.6-28.9) |
| Sex | |
| Male | 48 (47) |
| Female | 54 (53) |
| Twins | 20 (20) |
| Maternal diabetes | 12 (12) |
| Maternal hypertension | 19 (19) |
| Maternal alcohol use | 6 (7) |
| Maternal smoking | 10 (11) |
| Maternal recreational drug use | 3 (3) |
| Antenatal corticosteroids | 82 (81) |
| Antenatal magnesium sulfate | 77 (79) |
| Infection | 35 (34) |
| Retinopathy of prematurity (n = 90) | 45 (44) |
| Grade 1 | 39 (38) |
| Grade 2 | 35 (34) |
| Grade 3 | 18 (18) |
| Immature | 2 (2) |
| Bronchopulmonary dysplasia | 32 (31) |
| Any brain injury | 69 (68) |
| Severe brain injury (moderate or severe WMI, IVH grade 3, or PVHI) | 16 (16) |
| Maternal educational level (n = 101) | |
| Primary or secondary | 24 (24) |
| Postsecondary | 62 (61) |
| Graduate | 15 (15) |
| Chronological age at 3 y, median (IQR), wk | 158.6 (156.6-162.9) |
| Epigenetic age at 3 y, median (IQR), wk | 212.9 (193.4-228.1) |
| Epigenetic age difference at 3 y, median (IQR), wk | 52.7 (34.7-62.9) |
| Buccal cell proportion at 3 y, median (IQR) (n = 92) | 96.5 (91.7-97.7) |
| Bayley-III cognitive composite score at 3 y, median (IQR) (n = 98) | 95.0 (90.0-100.0) |
| Bayley-III motor composite score at 3 y, median (IQR) (n = 92) | 94.0 (82.5-100.0) |
Abbreviations: Bayley-III, Bayley Scales of Infant and Toddler Development, 3rd edition; IVH, intraventricular hemorrhage; PVHI, periventricular hemorrhagic infarction; WMI, white matter injury.
The association between preterm risk factors and epigenetic age difference was examined using regression models (Table 2). Any brain injury (β, −3.60; 95% CI, −14.09 to 6.90), severe brain injury (β, −12.11; 95% CI, −26.3 to 2.10), and maternal educational level (postsecondary: β, 3.11; 95% CI, −8.56 to 14.78) did not show significant associations with epigenetic age difference.
Table 2. Regression Models Examining the Association Between Preterm Risk Factors and Epigenetic Age Difference at 3 Years.
| Epigenetic age difference at 3 y | β (95% CI) | P value |
|---|---|---|
| Model 1 | ||
| Any brain injury | −3.60 (−14.09 to 6.90) | .50 |
| Buccal cell proportion at 3 y | −1.35 (−1.86 to −0.85) | <.001 |
| Age at 3 y | 0.53 (−0.02 to 1.07) | .05 |
| Model 2 | ||
| Severe brain injury | −12.11 (−26.3X to 2.10) | .09 |
| Buccal cell proportion at 3 y | −1.44 (−1.93 to −0.94) | <.001 |
| Age at 3 y | 0.51 (−0.005 to 1.02) | .05 |
| Model 3 | ||
| Maternal educational level | ||
| Postsecondary | 3.11 (−8.56 to 14.78) | .60 |
| Graduate | 0.08 (−14.12 to 14.29) | .99 |
| Buccal cell proportion at 3 y | −1.33 (−1.79 to −0.87) | <.001 |
| Age at 3 y | 0.55 (−0.02 to 1.11) | .05 |
Regression models showed significant associations among epigenetic age difference, preterm risk factors, and neurodevelopmental outcomes (Table 3). Higher maternal educational level (β = 11.65; 95% CI, 3.55-19.76; P = .005) and greater epigenetic age difference or epigenetic age acceleration (β = 0.07; 95% CI, 0.01-0.14; P = .04) were associated with higher cognitive scores. Greater epigenetic age difference or epigenetic age acceleration was also associated with higher motor scores (β = 0.16; 95% CI, 0.06-0.27; P = .003), while extreme prematurity (β = –5.66; 95% CI, −10.85 to −0.46; P = .03) and severe brain injury (β = –10.99; 95% CI, −21.32 to −0.66; P = .04) were associated with lower motor scores.
Table 3. Regression Models Examining the Associations Among Epigenetic Age Difference, Preterm Risk Factors, and Neurodevelopmental Outcomes at 3 Years (Main Effects).
| Outcome | β (95% CI) | P value |
|---|---|---|
| Cognitive outcomes at 3 y | ||
| Model 1 | ||
| Epigenetic age difference at 3 y | 0.09 (0.03 to 0.16) | .007 |
| Any brain injury | −2.72 (−6.76 to 1.31) | .18 |
| Male sex | −2.94 (−6.78 to 0.91) | .13 |
| Extremely preterm | −2.48 (−6.29 to 1.33) | .20 |
| Model 2 | ||
| Epigenetic age difference at 3 y | 0.10 (0.03 to 0.17) | .005 |
| Severe brain injury | 0.49 (−7.99 to 8.97) | .91 |
| Male sex | −2.85 (−6.76 to 1.06) | .15 |
| Extremely preterm | −2.74 (−6.54 to 1.06) | .16 |
| Model 3 | ||
| Epigenetic age difference at 3 y | 0.07 (0.01 to 0.14) | .04 |
| Maternal educational level | ||
| Postsecondary | 4.84 (−0.19 to 9.87) | .06 |
| Graduate | 11.65 (3.55 to 19.76) | .005 |
| Male sex | −3.63 (−7.53 to 0.27) | .07 |
| Extremely preterm | −3.13 (−6.41 to 0.15) | .06 |
| Motor outcomes at 3 y | ||
| Model 1 | ||
| Epigenetic age difference at 3 y | 0.18 (0.08 to 0.29) | .001 |
| Any brain injury | −2.05 (−7.11 to 3.01) | .42 |
| Male sex | −4.79 (−9.99 to 0.42) | .07 |
| Extremely preterm | −5.85 (−11.27 to −0.43) | .04 |
| Model 2 | ||
| Epigenetic age difference at 3 y | 0.16 (0.06 to 0.27) | .003 |
| Severe brain injury | −10.99 (−21.32 to −0.66) | .04 |
| Male sex | −4.61 (−9.69 to 0.48) | .08 |
| Extremely preterm | −5.66 (−10.85 to −0.46) | .03 |
| Model 3 | ||
| Epigenetic age difference at 3 y | 0.19 (0.07 to 0.31) | .002 |
| Maternal educational level | ||
| Postsecondary | 1.48 (−5.40 to 8.37) | .67 |
| Graduate | 1.15 (−7.77 to 10.07) | .80 |
| Male sex | −4.88 (−10.18 to 0.42) | .07 |
| Extremely preterm | −6.27 (−11.67 to −0.88) | .02 |
We performed secondary analyses examining whether the association between epigenetic age difference and neurodevelopmental outcomes was modified by brain injury and maternal educational level (Table 4). Severe brain injury modified the association between epigenetic age difference and motor outcomes (β = 0.41; 95% CI, 0.08-0.74; P = .02). Children with severe brain injury and greater epigenetic age acceleration had higher motor scores (Figure). There were no significant interaction effects between epigenetic age difference and any brain injury, or between epigenetic age difference and maternal educational level.
Table 4. Regression Models Examining the Association Between Epigenetic Age Difference, Preterm Risk Factors, and Neurodevelopmental Outcomes at 3 Years (Interaction Effects).
| Outcome | β (95% CI) | P value |
|---|---|---|
| Cognitive outcomes at 3 y | ||
| Model 1 | ||
| Epigenetic age difference at 3 y | 0.16 (0.02 to 0.30) | .02 |
| Any brain injury | 2.36 (−6.37 to 11.09) | .59 |
| Male sex | −3.08 (−6.88 to 0.73) | .11 |
| Extremely preterm | −2.82 (−6.62 to 0.99) | .15 |
| Epigenetic age difference × any brain injury interaction | −0.09 (−0.25 to 0.06) | .22 |
| Model 2 | ||
| Epigenetic age difference at 3 y | 0.10 (0.02 to 0.18) | .01 |
| Severe brain injury | −0.17 (−8.36 to 8.02) | .97 |
| Male sex | −2.85 (−6.79 to 1.09) | .15 |
| Extremely preterm | −2.70 (−6.35 to 0.95) | .15 |
| Epigenetic age difference × severe brain injury interaction | 0.02 (−0.19 to 0.22) | .88 |
| Model 3 | ||
| Epigenetic age difference at 3 y | 0.04 (−0.12 to 0.20) | .59 |
| Maternal educational level | ||
| Postsecondary | 0.03 (−0.14 to 0.20) | .71 |
| Graduate | 0.08 (−0.21 to 0.37) | .61 |
| Male sex | −3.54 (−7.49 to 0.42) | .07 |
| Extremely preterm | −3.11 (−6.39 to 0.15) | .06 |
| Epigenetic age difference × postsecondary maternal educational level interaction | 0.02 (−0.20 to 0.62) | .90 |
| Epigenetic age difference × graduate maternal educational level interaction | 0.21 (−0.20 to 0.62) | .31 |
| Motor outcomes at 3 y | ||
| Model 1 | ||
| Epigenetic age difference at 3 y | 0.16 (0.05 to 0.28) | .007 |
| Any brain injury | −3.56 (−15.94 to 8.81) | .56 |
| Male sex | −4.75 (−9.92 to 0.43) | .07 |
| Extremely preterm | −5.75 (−11.28 to −0.23) | .04 |
| Epigenetic age difference × any brain injury interaction | 0.03 (−0.16 to 0.22) | .77 |
| Model 2 | ||
| Epigenetic age difference at 3 y | 0.11 (0.01 to 0.21) | .03 |
| Severe brain injury | −26.65 (−39.88 to −13.42) | <.001 |
| Male sex | −5.16 (−10.00 to −0.31) | .04 |
| Extremely preterm | −5.13 (−10.00 to −0.25) | .04 |
| Epigenetic age difference × severe brain injury interaction | 0.41 (0.08 to 0.74) | .02 |
| Model 3 | ||
| Epigenetic age difference 3 y | 0.15 (−0.04 to 0.34) | .11 |
| Maternal educational level | ||
| Postsecondary | 0.93 (−11.73 to 13.60) | .89 |
| Graduate | −9.47 (−31.67 to 12.74) | .40 |
| Male sex | −4.62 (−10.11 to 0.86) | .10 |
| Extremely preterm | −6.19 (−11.43 to −0.94) | .02 |
| Epigenetic age difference × postsecondary maternal educational level interaction | 0.02 (−0.20 to 0.62) | .90 |
| Epigenetic age difference × graduate maternal educational level interaction | 0.21 (−0.20 to 0.62) | .31 |
Figure. Scatterplot of Motor Score and Epigenetic Age Difference by Severe Brain Injury.
Epigenetic age acceleration was associated with higher motor scores in children with severe brain injury. Dots indicate observed values for children with no severe brain injury (n = 86). Triangles indicate observed values for children with severe brain injury (n = 16). Shaded areas indicate 95% CIs, while the dashed and solid lines indicate adjusted fit.
eTable 1 in Supplement 1 shows regression models examining associations between prenatal factors and epigenetic age difference and eTable 2 in Supplement 1 shows regression models examining associations among prenatal factors, epigenetic age difference, and neurodevelopmental outcomes. Maternal diabetes and hypertension were not associated with epigenetic age difference or cognitive and motor outcomes. Maternal recreational drug use was associated with lower motor scores (β = –17.98; 95% CI, –31.47 to –4.49; P = .01), although there were only 3 participants with maternal recreational drug use. Antenatal corticosteroids and magnesium sulfate were not associated with epigenetic age difference or cognitive and motor outcomes.
Discussion
In this prospective preterm cohort study, we found that epigenetic aging, severe brain injury, and socioeconomic status were associated with differences in neurodevelopmental outcomes. For the cognitive domain, epigenetic age acceleration and higher maternal educational level were associated with higher cognitive scores. For the motor domain, epigenetic age acceleration was associated with higher motor scores, while severe brain injury was associated with lower motor scores. We also found that the association between epigenetic aging and neurodevelopment was context dependent and can vary based on the presence of preterm risk factors. More specifically, we found that the association between epigenetic aging and motor outcomes was modified by severe brain injury, and that children with severe brain injury and epigenetic age acceleration had higher motor scores. Our results suggest that epigenetic aging is a biological factor associated with differences in neurodevelopmental outcomes among children born preterm. Furthermore, epigenetic responses may differ based on the child’s clinical context and presence of preterm risk factors, highlighting the complex interplay of biological and clinical risk factors in shaping outcomes in the preterm population. Differences in epigenetic aging may reflect biological responses or adaptations to clinical stressors (eg, severe brain injury) among children born preterm.
Our results are consistent with previous studies that have also demonstrated epigenetic differences among children born preterm, including PedBE-focused studies and epigenome-wide association studies.15,16,17,19,25,26 The environmental stressors of prematurity are profound, and epigenetic mechanisms may reflect biological responses to this early-life adversity. Epigenetic responses may vary over the life course, and concordance and discordance between epigenetic age and chronological age is reflective of underlying health and aging.20 Among pediatric populations, DNA methylation increases rapidly from birth to childhood, and epigenetic age acceleration has been found to be associated with both favorable and adverse health outcomes.15,16,22,29,30 In the adult literature, epigenetic age acceleration has been more consistently associated with poor health outcomes.20 A recent study validated the PedBE epigenetic clock for children born preterm, demonstrating an association between epigenetic age and chronological age, as well as an association between epigenetic age acceleration and neurodevelopmental outcomes.16 The study also found an association between epigenetic aging and the presence of a neonatal morbidity (eg, infection, bronchopulmonary dysplasia). We expanded on this work to understand whether other clinical and environmental preterm risk factors were associated with epigenetic aging, and whether these factors interact to influence outcomes among children born preterm. The present study specifically examined brain injury and socioeconomic status, as these are key preterm risk factors that have been found to be associated with differences in neurodevelopmental outcome among children born preterm.7,11,27 We found that brain injury, socioeconomic status, and epigenetic aging were all associated with cognitive and motor outcomes among children born preterm. However, brain injury and socioeconomic status were not associated with differences in epigenetic aging. These findings, along with previous work, suggest that the association betweem preterm risk factors and epigenetic aging may be linked more strongly with neonatal morbidities involving systemic illness or inflammation rather than brain injury and socioeconomic status.15,16,17,19,26 A previous study found that infection and retinopathy of prematurity were both associated with a 12-week lower epigenetic age difference.16 Similarly, differences in epigenetic age and DNA methylation have been found in the presence of infection, retinopathy of prematurity, bronchopulmonary dysplasia, and neonatal pain in children born preterm.15,19,26,31
In clinical practice, neurodevelopmental outcomes of children born preterm can be highly variable. Established clinical and environmental preterm risk factors (eg, gestational age, sex, neonatal morbidities, socioeconomic status) and neuroimaging findings do not fully account for the variability in outcomes. Our results add to the growing body of literature indicating that epigenetic aging is an important biological factor associated with neurodevelopmental outcomes in the preterm population and may help explain the variability in outcomes. Epigenetic aging was associated with both cognitive and motor outcomes, while other preterm risk factors were associated with domain-specific outcomes. Maternal educational level was associated with cognitive outcomes, while severe brain injury was associated with motor outcomes. Motor outcomes may be more strongly associated with the presence of preterm brain injury, which can disrupt key motor pathways, while cognitive outcomes may be shaped by the home environment and socioeconomic status. Our findings, along with other studies, demonstrate the importance of brain injury in motor outcomes and the influence of the home and socioeconomic status in cognitive outcomes.7,11,12,27,32,33
In contrast, epigenetic aging was not domain specific and was associated with both cognitive and motor outcomes. Epigenetic aging is an important biological factor associated with neurodevelopment among children born preterm that may help explain the variability in outcomes. Epigenetic aging should be considered a preterm risk factor, in the context of established clinical, neuroimaging, and environmental preterm risk factors. Future studies should focus on the utility of epigenetic-based measures in clinical settings, in particular with respect to neurodevelopmental prognostication. Additional longitudinal studies are also needed to understand epigenetic aging trajectories over time and their associations with neurodevelopmental outcomes in children born preterm.
Strengths and Limitations
Strengths of this study include the prospective preterm cohort with well-defined clinical, neuroimaging, epigenetic, and developmental data collection from birth to early childhood, as well as the use of a validated pediatric epigenetic clock. Limitations of this study include the lack of serial epigenetic measures to examine epigenetic aging patterns over time. We examined epigenetic aging and neurodevelopmental outcomes at the same time point, and a temporal association could not be established. For our subgroup analyses there was a small number of participants in the severe brain injury subgroup. We did, however, examine participants with any brain injury, which included a larger number of participants. The PedBE clock used in this study had previously demonstrated moderate agreement with chronological age. This finding may reflect the narrow age range at sample collection or relate to the clock being developed in children born at term rather than preterm. We could not fully control for maternal factors, parental age, genetic variants, and environmental exposures that may have contributed to epigenetic and neurodevelopmental differences. Finally, this study examined epigenetic differences associated with cognitive and motor outcomes, and the inclusion of other developmental domains may have been informative (eg, language, behavioral outcomes, and neurosensory impairments).
Conclusions
In this prospective preterm cohort study, we found that epigenetic aging was associated with neurodevelopmental outcomes and that this association was context dependent. Epigenetic aging, severe brain injury, and maternal educational level were associated with cognitive and motor outcomes in children born preterm. The association between epigenetic aging and motor outcomes was modified by severe brain injury, and children with severe brain injury who had epigenetic age acceleration had higher motor scores. These findings suggest that the association between epigenetic aging and neurodevelopmental outcomes can vary based on the presence of preterm risk factors.
eTable 1. Regression Models Examining Association Between Perinatal Factors and Epigenetic Age Difference at 3 Years
eTable 2. Regression Models Examining the Association Between Perinatal Factors, Epigenetic Age Difference and Neurodevelopmental Outcomes at 3 Years
Data Sharing Statement
References
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
eTable 1. Regression Models Examining Association Between Perinatal Factors and Epigenetic Age Difference at 3 Years
eTable 2. Regression Models Examining the Association Between Perinatal Factors, Epigenetic Age Difference and Neurodevelopmental Outcomes at 3 Years
Data Sharing Statement
