Abstract
The early environment, including maternal characteristics, provides many cues to young organisms that shape their long-term physical and mental health. Identifying the earliest molecular events that precede observable developmental outcomes could help identify children in need of support prior to the onset of physical and mental health difficulties. In this study, we examined whether mothers’ attachment insecurity, maltreatment history, and depressive symptoms were associated with alterations in DNA methylation patterns in their infants, and whether these correlates in the infant epigenome were associated with socioemotional and behavioral functioning in toddlerhood. We recruited 156 women oversampled for histories of depression, who completed psychiatric interviews and depression screening during pregnancy, then provided follow-up behavioral data on their children at 18 months. Buccal cell DNA was obtained from 32 of their infants for a large-scale analysis of methylation patterns across 5 × 106 individual CpG dinucleotides, using clustering-based significance criteria to control for multiple comparisons. We found that tens of thousands of individual infant CpGs were alternatively methylated in association with maternal attachment insecurity, maltreatment in childhood, and antenatal and postpartum depressive symptoms, including genes implicated in developmental patterning, cell-cell communication, hormonal regulation, immune function/inflammatory response, and neurotransmission. Density of DNA methylation at selected genes from the result set was also significantly associated with toddler socioemotional and behavioral problems. This is the first report to identify novel regions of the human infant genome at which DNA methylation patterns are associated longitudinally both with maternal characteristics and with offspring socioemotional and behavioral problems in toddlerhood.
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Data availability
Data are accessible at https://figshare.com/articles/dataset/1010i-CGATGT_S1_L001_R1_001_fastq_gz/17027099.
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Acknowledgements
This work was supported by a Stanford Precision Health and Integrated Diagnostics Seed Funding grant to TKR, and by NIH Grants R21-HD090493 and R21-MH111978 to IHG. AEU is a Tashia and John Morgridge Faculty Fellow of the Stanford Child Health Research Institute, is a Project-PI of the Stanford Center of Excellence in Genomics—Center for Personal Dynamic Regulomes (NIH HG007735-0, Center PI Chang), and acknowledges funding from and helpful discussions with Bruce Blackie. The sequencing data were generated on an Illumina HiSeq 4000 that was purchased with funds from NIH under award number S10OD018220. TL and YC are affiliated with Accura Science, LLC, and were financially recompensed for their expert biostatistical analysis. Code availability is at the discretion of Accura Science, by correspondence with TL. The REDCap platform services at Stanford are subsidized by (a) Stanford School of Medicine Research Office and (b) the National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health, through grant UL1 TR001085.
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TKR conceived of the study, obtained targeted funding for the project, and wrote the paper. MCR managed data collection and contributed to data analysis, writing and editing. LSK and KLH contributed to study design, data collection, data analysis, interpretation, writing, and editing. MH performed the DNA processing and sequencing. XZ contributed to the analysis plan and to data acquisition and processing. YC and TL performed the bioinformatic analysis. NLR contributed to study design and reviewed and edited the final manuscript. KTW assisted with interpretation of results and reviewed and edited the final manuscript. AEU contributed to study design, oversaw acquisition and analysis of epigenetic data, and reviewed and edited the final manuscript. IHG is PI of the parent study, provided guidance for study design, data acquisition and analysis, and reviewed and edited the manuscript for publication.
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Robakis, T.K., Roth, M.C., King, L.S. et al. Maternal attachment insecurity, maltreatment history, and depressive symptoms are associated with broad DNA methylation signatures in infants. Mol Psychiatry 27, 3306–3315 (2022). https://doi.org/10.1038/s41380-022-01592-w
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DOI: https://doi.org/10.1038/s41380-022-01592-w
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