DNA methylation signal of birthweight generalizes to high-risk pregnancies and is independent of genetic, maternal, and obstetric factors: a twin study
DNA methylation is associated with individual differences in birthweight in a high-risk clinical population of MC twins, independent of shared genetic, familial, maternal, and obstetric factors.
Abstract
Background. DNA methylation patterns in cord blood are robustly associated with birthweight in the general population. However, it remains unknown whether these associations extend to clinically relevant populations, such as preterm neonates or those born small for gestational age, and whether they directly reflect birthweight or are driven indirectly by genetic, familial, maternal, and obstetric factors. Methods. We calculated a birthweight methylation profile score (MPSBW) using weights of 835 CpGs previously associated with birthweight in the general population and evaluated its association with birthweight in 67 monochorionic (MC) twin pairs including 134 neonates (97% born preterm) from the Twinlife study. MC twin pairs are identical twins sharing a single placenta, often unequally, which can result in unequal resource distribution and differential fetal growth. Results. We examined the association between within-pair differences in birthweight and MPSBW, thereby estimating the association independent of factors shared equally by co-twins. A 500-gram increase in birthweight was associated with a 0.256 SD increase in MPSBW (p<0.005) in this population of preterm neonates. Adjustment for polygenic score for birthweight (PGSBW) confirmed that the observed epigenetic associations were not driven by common genetic variation underlying birthweight. Interestingly, a similar effect size (0.226 SD per 500 g birthweight increase; p<0.05) was observed in the within-pair analysis, which controls for all shared influences within a twin pair. Conclusion DNA methylation is associated with individual differences in birthweight in a high-risk clinical population of MC twins, independent of shared genetic, familial or maternal influences.
Background/Objectives: Large-for-gestational-age (LGA) birth is associated with adverse perinatal outcomes and increased risk of metabolic disease later in life. Despite these risks, epigenetic studies of LGA remain limited, particularly those using umbilical cord blood DNA methylation (DNAm) as the tissue of interest. Methods: We conducted an epigenome-wide association study of cord blood DNAm in a nested case–control sample from the Gestational Regulators of Weight (GROW) cohort. The analysis included 28 term LGA infants and 63 term appropriate-for-gestational-age (AGA) controls. DNAm was measured using the Illumina HumanMethylation450 BeadChip. Epigenome-wide association analyses were performed with adjustment for residual principal components and estimated cord blood cell-type proportions. Results: No CpG sites reached statistical significance after false discovery rate correction. Twenty-four CpGs showed nominal associations with LGA status at p-value < 1.00 × 10−4, including five CpGs with absolute methylation differences greater than 0.05. Among annotated loci, the strongest interpretable signals included cg06750897 in PBX1 (Δβ = 0.110, p-value = 1.70 × 10−5) and two nearby CpGs in SMAD3, cg23731272 (Δβ = 0.111, p-value = 4.31 × 10−5) and cg02486855 (Δβ = 0.109, p-value = 9.45 × 10−5). These two SMAD3 CpGs showed concordant hypermethylation in LGA infants and formed a candidate regional methylation signal in exploratory targeted regional analysis. Conclusions: In this pilot study, LGA was associated with modest cord blood DNAm differences, although no CpG sites reached genome-wide significance. The strongest interpretable signals involved PBX1 and SMAD3, suggesting candidate loci for further evaluation in larger studies of fetal overgrowth.
Xiao-Yu Liang, Christopher Doumith, Dawn P. Misra et al.· Epigenomes· 0 citations
A role of DNAm at birth in mediating the association of maternal smoking, birth weight and ADHD-related genetic variants with ADHD symptoms is demonstrated, however, lack of individual site-specific findings and the observational design limit causal biological interpretations.
A. Neumann, M. Suderman, J. Felix et al.· medRxiv· 0 citations
Approximately 10% US infants are born small for gestational age (SGA), a condition linked to increased morbidity and mortality. Infants born to Black women are twice as likely to be SGA compared with those born to White women. Although maternal factors, including epigenetic modifications, likely contribute to SGA, the underlying biological mechanisms remain poorly understood. We evaluated whether epigenetic modifications in early pregnancy were associated with SGA among pregnant Black women. We analyzed data from 931 pregnant non-Hispanic Black women (6–13 weeks of gestation) enrolled in the Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-be (nuMoM2b) cohort across eight academic medical centers. We conducted an epigenome-wide association study using the Infinium MethylationEPIC assay on blood samples from women who delivered SGA infants (n = 133) and appropriate for gestational age infants (n = 798). We adjusted for maternal age, prenatal smoking, education, body mass index, and infant sex, and corrected with multiple testing. We identified 14 differentially methylated 5'-C-phosphate-G-3' (CpG) sites mapping to genes involved in placental development, vascular remodeling, and fetal growth regulation. Functional enrichment analysis highlighted the pathways involved in early embryonic development and placental function, implicating early-pregnancy maternal epigenetic alterations in SGA delivery among Black women and supporting DNA methylation profiling as a potential SGA biomarker.
Paolo Reho, Tingting Zhao, Yihong Zhao et al.· Epigenetics Insights· 0 citations
Pregnancy is a biologically complex period with profound implications for maternal and offspring health. Adverse pregnancy outcomes such as pre-eclampsia, gestational diabetes, preterm birth, and growth restriction contribute substantially to maternal and neonatal morbidity and mortality, while also increasing risks of late-onset disorders in both mothers and children. Understanding the genetic basis of these pregnancy phenotypes and birth outcomes is therefore critical for advancing maternal–child health research. Unlike most human traits, pregnancy phenotypes are shaped by both maternal and fetal genomes, which are correlated but exert distinct influences. This dual genetic contribution presents unique challenges for genetic studies and necessitates specialized statistical approaches. In this review, we highlight recent methodological advances in genomic research designed to disentangle maternal and fetal genetic effects. We first discuss single-variant genome-wide association approaches, including conditional analyses, haplotype-based methods, structural equation modeling, and weighted linear models, which enable partitioning of maternal and fetal contributions. We then examine multi-variant strategies such as polygenic scores and Mendelian randomization, which provide insights into causal relationships, shared genetic architectures, and long-term health consequences. Finally, we explore approaches to characterizing the genetic architecture of pregnancy phenotypes, including methods for partitioning maternal and fetal genetic contributions and genetic correlation analyses with other health-related traits. Together, these genomic approaches have begun to clarify the complex interplay between maternal and fetal genomes in shaping pregnancy outcomes and their links to later-life health in both mothers and offspring. By emphasizing methodological innovation rather than empirical findings, this review provides a framework for future studies aiming to unravel the genetic underpinnings of pregnancy phenotypes and their connections with long-term health.
Ge Zhang, R. Freathy, B. Jacobsson et al.· Frontiers in Genetics· 0 citations
Background. Cord blood DNA methylation profile scores (MPSs) based on genetic and pre-/perinatal risk factors for neurodevelopmental conditions (NDCs) may capture downstream biological effects and help understand how combined exposure signals contribute to NDC risk. Methods. Using data from two longitudinal birth cohorts, Generation R (N-train = 1856, N-test = 476) and ALSPAC (N-validation= 832), we developed cord blood MPSs based on genetic and pre-/perinatal NDC risk factors. We assessed individual and combined predictive performance of risk factors and MPSs for eight childhood psychiatric outcomes (four broad, four specific), measured between ages 5 and 14 years. We also evaluated if the MPSs could be combined into a composite "transmission load" MPS. Results. We validated four novel MPSs: maternal age, birthweight, and genetic liability for ADHD and schizophrenia (r range = 0.08 to 0.29) and included two previously validated MPSs: maternal smoking and gestational age (r range = 0.42 to 0.63). Jointly modeling the six MPSs with their corresponding risk factors explained on average 3.3% of variance in outcomes, higher than that explained by risk factors (1.8%) or MPSs alone (1.6%), indicating complementary sources of risk. The "transmission load" MPS did not replicate due to heterogeneous contributions of the predictors across cohorts. Conclusions. The four novel MPSs based on genetic and pre-/perinatal risk factors can serve as valuable tools for future research. Integrating genetic and prenatal risk factors with DNA methylation at birth can provide insights into their individual and joint contributions to early psychiatric risk and may improve prediction.
Elena Isaevska, Rosa H. Mulder, I. Schuurmans et al.· medRxiv· 0 citations
The Barker-consistent hypothesis-free discovery approach identified novel and known candidate genes that, with future validation, may serve as therapeutic targets, identify high-risk individuals, and support clinical trial recruitment.
John Yen Tang, N. Ng, A. S. Kwok et al.· Journal of Global Health· 0 citations
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