Epigenome-Wide Association Study of Infant Feeding and DNA Methylation in Infancy and Childhood in a Population at Increased Risk for Type 1 Diabetes

Epigenetics as a Biomarker for Early-Life Environmental Exposure

PURPOSE OF REVIEW

There is interest in evaluating the developmental origins of health and disease (DOHaD) which emphasizes the role of prenatal and early-life environments on non-communicable health outcomes throughout the life course. The ability to rigorously assess and identify early-life risk factors for later health outcomes, including those with childhood onset, in large population samples is often limited due to measurement challenges such as impractical costs associated with prospective studies with a long follow-up duration, short half-lives for some environmental toxicants, and lack of biomarkers that capture inter-individual differences in biologic response to external environments.

RECENT FINDINGS

Epigenomic patterns, and DNA methylation in particular, have emerged as a potential objective biomarker to address some of these study design and exposure measurement challenges. In this article, we summarize the literature to date on epigenetic changes associated with specific prenatal and early-life exposure domains as well as exposure mixtures in human observational studies and their biomarker potential. Additionally, we highlight evidence for other types of epigenetic patterns to serve as exposure biomarkers. Evidence strongly supports epigenomic biomarkers of exposure that are detectable across the lifespan and across a range of exposure domains. Current and future areas of research in this field seek to expand these lines of evidence to other environmental exposures, to determine their specificity, and to develop predictive algorithms and methylation scores that can be used to evaluate early-life risk factors for health outcomes across the life span.

Association of Pediatric Buccal Epigenetic Age Acceleration With Adverse Neonatal Brain Growth and Neurodevelopmental Outcomes Among Children Born Very Preterm With a Neonatal Infection

IMPORTANCE

Very preterm neonates (24-32 weeks' gestation) remain at a higher risk of morbidity and neurodevelopmental adversity throughout their lifespan. Because the extent of prematurity alone does not fully explain the risk of adverse neonatal brain growth or neurodevelopmental outcomes, there is a need for neonatal biomarkers to help estimate these risks in this population.

OBJECTIVES

To characterize the pediatric buccal epigenetic (PedBE) clock-a recently developed tool to measure biological aging-among very preterm neonates and to assess its association with the extent of prematurity, neonatal comorbidities, neonatal brain growth, and neurodevelopmental outcomes at 18 months of age.

DESIGN, SETTING, AND PARTICIPANTS

This prospective cohort study was conducted in 2 neonatal intensive care units of 2 hospitals in Toronto, Ontario, Canada. A total of 35 very preterm neonates (24-32 weeks' gestation) were recruited in 2017 and 2018, and neuroimaging was performed and buccal swab samples were acquired at 2 time points: the first in early life (median postmenstrual age, 32.9 weeks [IQR, 32.0-35.0 weeks]) and the second at term-equivalent age (TEA) at a median postmenstrual age of 43.0 weeks (IQR, 41.0-46.0 weeks). Follow-ups for neurodevelopmental assessments were completed in 2019 and 2020. All neonates in this cohort had at least 1 infection because they were originally enrolled to assess the association of neonatal infection with neurodevelopment. Neonates with congenital malformations, genetic syndromes, or congenital TORCH (toxoplasmosis, rubella, cytomegalovirus, herpes and other agents) infection were excluded.

EXPOSURES

The extent of prematurity was measured by gestational age at birth and PedBE age difference. PedBE age was computed using DNA methylation obtained from 94 age-informative CpG (cytosine-phosphate-guanosine) sites. PedBE age difference (weeks) was calculated by subtracting PedBE age at each time point from the corresponding postmenstrual age.

MAIN OUTCOMES AND MEASURES

Total cerebral volumes and cerebral growth during the neonatal intensive care unit period were obtained from magnetic resonance imaging scans at 2 time points: approximately the first 2 weeks of life and at TEA. Bayley Scales of Infant and Toddler Development, Third Edition, were used to assess neurodevelopmental outcomes at 18 months.

RESULTS

Among 35 very preterm neonates (21 boys [60.0%]; median gestational age, 27.0 weeks [IQR, 25.9-29.9 weeks]; 23 [65.7%] born extremely preterm [<28 weeks' gestation]), extremely preterm neonates had an accelerated PedBE age compared with neonates born at a later gestational age (β = 9.0; 95% CI, 2.7-15.3; P = .01). An accelerated PedBE age was also associated with smaller cerebral volumes (β = -5356.8; 95% CI, -6899.3 to -2961.7; P = .01) and slower cerebral growth (β = -2651.5; 95% CI, -5301.2 to -1164.1; P = .04); these associations remained significant after adjusting for clinical neonatal factors. These findings were significant at TEA but not earlier in life. Similarly, an accelerated PedBE age at TEA was associated with lower cognitive (β = -0.4; 95% CI, -0.8 to -0.03; P = .04) and language (β = -0.6; 95% CI, -1.1 to -0.06; P = .02) scores at 18 months.

CONCLUSIONS AND RELEVANCE

This cohort study of very preterm neonates suggests that biological aging may be associated with impaired brain growth and neurodevelopmental outcomes. The associations between epigenetic aging and adverse neonatal brain health warrant further attention.

Breastfeeding and Allergy Effect Modified by Genetic, Environmental, Dietary, and Immunological Factors

Breastfeeding (BF) is the most natural mode of nutrition. Its beneficial effect has been revealed in terms of both the neonatal period and those of lifelong effects. However, as for protection against allergy, there is not enough data. In the current narrative review, the literature within the last five years from clinical trials and population-based studies on breastfeeding and allergy from different aspects was explored. The aim of this review was to explain how different factors could contribute to the overall effect of BF. Special consideration was given to accompanying exposure to cow milk, supplement use, the introduction of solid foods, microbiota changes, and the epigenetic function of BF. Those factors seem to be modifying the impact of BF. We also identified studies regarding BF in atopic mothers, with SCFA as a main player explaining differences according to this status. Conclusion: Based on the population-based studies, breastfeeding could be protective against some allergic phenotypes, but the results differ within different study groups. According to the new research in that matter, the effect of BF could be modified by different genetic (HMO composition), environmental (cesarean section, allergen exposure), dietary (SCFA, introduction of solid food), and immunologic factors (IgG, IgE), thus partially explaining the variance.