Johnson S, Marlow N. Preterm birth and childhood psychiatric disorders. Pediatr Res. 2011;69:22–8.
Article
Google Scholar
Stephens BE, Vohr BR. Neurodevelopmental outcome of the premature infant. Pediatr Clin North Am. 2009;56:631–46.
Article
PubMed
Google Scholar
Chung EH, Chou J, Brown KA. Neurodevelopmental outcomes of preterm infants: a recent literature review. Transl Pediatr. 2020;9:S3-8.
Article
Google Scholar
Johnson S, Marlow N. Early and long-term outcome of infants born extremely preterm. Arch Dis Child. 2017;102:97–102.
Article
PubMed
Google Scholar
Aarnoudse-Moens CSH, Weisglas-Kuperus N, van Goudoever JB, Oosterlaan J. Meta-analysis of neurobehavioral outcomes in very preterm and/or very low birth weight children. Pediatrics. 2009;124:717–28.
Article
PubMed
Google Scholar
Aylward GP. Neurodevelopmental outcomes of infants born prematurely. J Dev Behav Pediatr. 2014;35:394–407.
Article
PubMed
Google Scholar
Rysavy MA, Colaizy TT, Bann CM, DeMauro SB, Duncan AF, Brumbaugh JE, et al. The relationship of neurodevelopmental impairment to concurrent early childhood outcomes of extremely preterm infants. J Perinatol. 2021;23:1–9. https://doi.org/10.1038/s41372-021-00999-7.
Article
CAS
Google Scholar
Cserjesi R, Van Braeckel KNJA, Timmerman M, Butcher PR, Kerstjens JM, Reijneveld SA, et al. Patterns of functioning and predictive factors in children born moderately preterm or at term. Dev Med Child Neurol. 2012;54:710–5.
Article
PubMed
Google Scholar
Heeren T, Joseph RM, Allred EN, O’Shea TM, Leviton A, Kuban KCK. Cognitive functioning at the age of 10 years among children born extremely preterm: a latent profile approach. Pediatr Res. 2017;82:614–9. https://doi.org/10.1038/pr.2017.82.
Article
PubMed
PubMed Central
Google Scholar
Burnett AC, Youssef G, Anderson PJ, Duff J, Doyle LW, Cheong JLY. Exploring the “preterm behavioral phenotype” in children born extremely preterm. J Dev Behav Pediatr. 2019;40:200–7.
Article
PubMed
Google Scholar
Hofheimer JA, Smith LM, McGowan EC, O’Shea TM, Carter BS, Neal CR, et al. Psychosocial and medical adversity associated with neonatal neurobehavior in infants born before 30 weeks gestation. Pediatr Res. 2020;87:721–9. https://doi.org/10.1038/s41390-019-0607-1.
Article
PubMed
Google Scholar
Liu J, Bann C, Lester B, Tronick E, Das A, Lagasse L, et al. Neonatal neurobehavior predicts medical and behavioral outcome. Pediatrics. 2010;125:e90–8.
Article
PubMed
Google Scholar
McGowan EC, Hofheimer JA, O’Shea TM, Carter BS, Helderman J, Neal CR, et al. Sociodemographic and medical influences on neurobehavioral patterns in preterm infants: a multi-center study. Early Hum Dev. 2020;142: 104954. https://doi.org/10.1016/j.earlhumdev.2020.104954.
Article
CAS
PubMed
PubMed Central
Google Scholar
Conradt E, Adkins DE, Crowell SE, Raby KL, Diamond LM, Ellis B. Incorporating epigenetic mechanisms to advance fetal programming theories. Dev Psychopathol. 2018;30:807–24.
Article
PubMed
PubMed Central
Google Scholar
Oberlander TF, Weinberg J, Papsdorf M, Grunau R, Misri S, Devlin AM. Prenatal exposure to maternal depression, neonatal methylation of human glucocorticoid receptor gene (NR3C1) and infant cortisol stress responses. Epigenetics. 2008;3:97–106.
Article
PubMed
Google Scholar
Conradt E, Hawes K, Guerin D, Armstrong DA, Marsit CJ, Tronick E, et al. The contributions of maternal sensitivity and maternal depressive symptoms to epigenetic processes and neuroendocrine functioning. Child Dev. 2016;87:73–85.
Article
PubMed
PubMed Central
Google Scholar
Lester BM, Conradt E, LaGasse LL, Tronick EZ, Padbury JF, Marsit CJ. Epigenetic programming by maternal behavior in the human infant. Pediatrics. 2018;142: e20171890. https://doi.org/10.1542/peds.2017-1890.
Article
PubMed
Google Scholar
Lester BM, Conradt E, Marsit C. Introduction to the special section on epigenetics. Child Dev. 2016;87:29–37. https://doi.org/10.1111/cdev.12489.
Article
PubMed
PubMed Central
Google Scholar
Monk C, Spicer J, Champagne FA. Linking prenatal maternal adversity to developmental outcomes in infants: the role of epigenetic pathways. Dev Psychopathol. 2012;24:1361–76.
Article
PubMed
PubMed Central
Google Scholar
Gartstein MA, Skinner MK. Prenatal influences on temperament development: the role of environmental epigenetics. Dev Psychopathol. 2018;30:1269–303.
Article
PubMed
Google Scholar
Robinson R, Lahti-Pulkkinen M, Heinonen K, Reynolds RM, Räikkönen K. Fetal programming of neuropsychiatric disorders by maternal pregnancy depression: a systematic mini review. Pediatr Res. 2019;85:134–45. https://doi.org/10.1038/s41390-018-0173-y.
Article
PubMed
Google Scholar
Ryan J, Mansell T, Fransquet P, Saffery R. Does maternal mental well-being in pregnancy impact the early human epigenome? Epigenomics. 2017;9:313–32. https://doi.org/10.2217/epi-2016-0118.
Article
CAS
PubMed
Google Scholar
Nowak AL, Anderson CM, Mackos AR, Neiman E, Gillespie SL. Stress during pregnancy and epigenetic modifications to offspring DNA. J Perinat Neonatal Nurs. 2020;34:134–45. https://doi.org/10.1097/JPN.0000000000000471.
Article
PubMed
PubMed Central
Google Scholar
Rijlaarsdam J, Pappa I, Walton E, Bakermans-Kranenburg MJ, Mileva-Seitz VR, Rippe RCA, et al. An epigenome-wide association meta-analysis of prenatal maternal stress in neonates: a model approach for replication. Epigenetics. 2016;11:140–9. https://doi.org/10.1080/15592294.2016.1145329.
Article
PubMed
PubMed Central
Google Scholar
Rodney NC, Mulligan CJ. A biocultural study of the effects of maternal stress on mother and newborn health in the Democratic Republic of Congo. Am J Phys Anthropol. 2014;155:200–9. https://doi.org/10.1002/ajpa.22568.
Article
PubMed
Google Scholar
Cardenas A, Faleschini S, Cortes Hidalgo A, Rifas-Shiman SL, Baccarelli AA, DeMeo DL, et al. Prenatal maternal antidepressants, anxiety, and depression and offspring DNA methylation: epigenome-wide associations at birth and persistence into early childhood. Clin Epigenetics. 2019;11:56. https://doi.org/10.1186/s13148-019-0653-x.
Article
CAS
PubMed
PubMed Central
Google Scholar
Gurnot C, Martin-Subero I, Mah SM, Weikum W, Goodman SJ, Brain U, et al. Prenatal antidepressant exposure associated with CYP2E1 DNA methylation change in neonates. Epigenetics. 2015;10:361–72. https://doi.org/10.1080/15592294.2015.1026031.
Article
PubMed
PubMed Central
Google Scholar
Non AL, Binder AM, Kubzansky LD, Michels KB. Genome-wide DNA methylation in neonates exposed to maternal depression, anxiety, or SSRI medication during pregnancy. Epigenetics. 2014;9:964–72. https://doi.org/10.4161/epi.28853.
Article
PubMed
PubMed Central
Google Scholar
Schroeder JW, Smith AK, Brennan PA, Conneely KN, Kilaru V, Knight BT, et al. DNA methylation in neonates born to women receiving psychiatric care. Epigenetics. 2012;7:409–14. https://doi.org/10.4161/epi.19551.
Article
CAS
PubMed
PubMed Central
Google Scholar
Vangeel EB, Pishva E, Hompes T, van den Hove D, Lambrechts D, Allegaert K, et al. Newborn genome-wide DNA methylation in association with pregnancy anxiety reveals a potential role for GABBR1. Clin Epigenetics. 2017;9:107. https://doi.org/10.1186/s13148-017-0408-5.
Article
CAS
PubMed
PubMed Central
Google Scholar
Viuff AC, Sharp GC, Rai D, Henriksen TB, Pedersen LH, Kyng KJ, et al. Maternal depression during pregnancy and cord blood DNA methylation: findings from the Avon Longitudinal Study of Parents and Children. Transl Psychiatry. 2018;8:244. https://doi.org/10.1038/s41398-018-0286-4.
Article
CAS
PubMed
PubMed Central
Google Scholar
Sharp GC, Salas LA, Monnereau C, Allard C, Yousefi P, Everson TM, et al. Maternal BMI at the start of pregnancy and offspring epigenome-wide DNA methylation: findings from the pregnancy and childhood epigenetics (PACE) consortium. Hum Mol Genet. 2017;26:4067–85.
Article
CAS
PubMed
PubMed Central
Google Scholar
Walden RV, Taylor SC, Hansen NI, Poole WK, Stoll BJ, Abuelo D, et al. Major congenital anomalies place extremely low birth weight infants at higher risk for poor growth and developmental outcomes. Pediatrics. 2007;120:e1512–9.
Article
PubMed
Google Scholar
Hollingshead AB. Four factor index of social status. New Haven: Yale University; 1975.
Google Scholar
Rasmussen KM, Yaktine AK. Weight gain during pregnancy: reexamining the guidelines. Washington DC: National Academy Press; 2009.
Google Scholar
Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001;16:606–13.
Article
CAS
PubMed
PubMed Central
Google Scholar
Everson TM, O’Shea TM, Burt A, Hermetz K, Carter BS, Helderman J, et al. Serious neonatal morbidities are associated with differences in DNA methylation among very preterm infants. Clin Epigenetics. 2020;12:1–15. https://doi.org/10.1186/s13148-020-00942-1.
Article
CAS
Google Scholar
Liu J, Siegmund KD. An evaluation of processing methods for humanmethylation450 BeadChip data. BMC Genom. 2016;17:469. https://doi.org/10.1186/s12864-016-2819-7.
Article
CAS
Google Scholar
Aryee MJ, Jaffe AE, Corrada-Bravo H, Ladd-Acosta C, Feinberg AP, Hansen KD, et al. Minfi: a flexible and comprehensive bioconductor package for the analysis of Infinium DNA methylation microarrays. Bioinformatics. 2014;30:1363–9. https://doi.org/10.1093/bioinformatics/btu049.
Article
CAS
PubMed
PubMed Central
Google Scholar
Pidsley R, Zotenko E, Peters TJ, Lawrence MG, Risbridger GP, Molloy P, et al. Critical evaluation of the Illumina MethylationEPIC BeadChip microarray for whole-genome DNA methylation profiling. Genome Biol. 2016;17:208. https://doi.org/10.1186/s13059-016-1066-1.
Article
CAS
PubMed
PubMed Central
Google Scholar
Pidsley R, Wong CC, Volta M, Lunnon K, Mill J, Schalkwyk LC. A data-driven approach to preprocessing Illumina 450K methylation array data. BMC Genom. 2013;14:293. https://doi.org/10.1186/1471-2164-14-293.
Article
CAS
Google Scholar
Teschendorff AE, Marabita F, Lechner M, Bartlett T, Tegner J, Gomez-Cabrero D, et al. A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data. Bioinformatics. 2013;29:189–96. https://doi.org/10.1093/bioinformatics/bts680.
Article
CAS
PubMed
Google Scholar
Jaffe AE, Irizarry RA. Accounting for cellular heterogeneity is critical in epigenome-wide association studies. Genome Biol. 2014;15:R31.
Article
PubMed
PubMed Central
Google Scholar
Zheng SC, Webster AP, Dong D, Feber A, Graham DG, Sullivan R, et al. A novel cell-type deconvolution algorithm reveals substantial contamination by immune cells in saliva, buccal and cervix. Epigenomics. 2018;10:925–40. https://doi.org/10.2217/epi-2018-0037.
Article
CAS
PubMed
Google Scholar
Everson TM, Marsit CJ, Michael O’Shea T, Burt A, Hermetz K, Carter BS, et al. Epigenome-wide analysis identifies genes and pathways linked to neurobehavioral variation in preterm infants. Sci Rep. 2019;9:1–13.
Article
CAS
Google Scholar
Braun PR, Han S, Hing B, Nagahama Y, Gaul LN, Heinzman JT, et al. Genome-wide DNA methylation comparison between live human brain and peripheral tissues within individuals. Transl Psychiatry. 2019;9:47.
Article
PubMed
PubMed Central
Google Scholar
Phipson B, Maksimovic J, Oshlack A. missMethyl: an R package for analyzing data from Illumina’s HumanMethylation450 platform. Bioinformatics. 2016;32:286–8.
Article
CAS
PubMed
Google Scholar
MacArthur J, Bowler E, Cerezo M, Gil L, Hall P, Hastings E, et al. The new NHGRI-EBI catalog of published genome-wide association studies (GWAS Catalog). Nucleic Acids Res. 2017;45:D896-901. https://doi.org/10.1093/nar/gkw1133.
Article
CAS
PubMed
Google Scholar
Zhang W, Spector TD, Deloukas P, Bell JT, Engelhardt BE. Predicting genome-wide DNA methylation using methylation marks, genomic position, and DNA regulatory elements. Genome Biol. 2015;16:14. https://doi.org/10.1186/s13059-015-0581-9.
Article
PubMed
PubMed Central
Google Scholar
Suderman M, Staley JR, French R, Arathimos R, Simpkin A, Tilling K. Dmrff: identifying differentially methylated regions efficiently with power and control. bioRxiv. 2018;508556:1–26.
Google Scholar
Nemoda Z, Massart R, Suderman M, Hallett M, Li T, Coote M, et al. Maternal depression is associated with DNA methylation changes in cord blood T lymphocytes and adult hippocampi. Transl Psychiatry. 2015;5:e545.
Article
CAS
PubMed
PubMed Central
Google Scholar
Walsh K, McCormack CA, Webster R, Pinto A, Lee S, Feng T, et al. Maternal prenatal stress phenotypes associate with fetal neurodevelopment and birth outcomes. Proc Natl Acad Sci. 2019;116:23996–4005. https://doi.org/10.1073/pnas.1905890116.
Article
CAS
PubMed
PubMed Central
Google Scholar
Simino J, Sung YJ, Kume R, Schwander K, Rao DC. Gene-alcohol interactions identify several novel blood pressure loci including a promising locus near SLC16A9. Front Genet. 2013;4:277.
Article
PubMed
PubMed Central
Google Scholar
Zhu Z, Guo Y, Shi H, Liu C-L, Panganiban RA, Chung W, et al. Shared genetic and experimental links between obesity-related traits and asthma subtypes in UK Biobank. J Allergy Clin Immunol. 2020;145:537–49.
Article
CAS
PubMed
Google Scholar
Domínguez-Cruz MG, Muñoz ML, Totomoch-Serra A, García-Escalante MG, Burgueño J, Valadez-González N, et al. Pilot genome-wide association study identifying novel risk loci for type 2 diabetes in a Maya population. Gene. 2018;677:324–31.
Article
PubMed
Google Scholar
Fanous AH, Zhou B, Aggen SH, Bergen SE, Amdur RL, Duan J, et al. Genome-wide association study of clinical dimensions of schizophrenia: polygenic effect on disorganized symptoms. Am J Psychiatry. 2012;169:1309–17.
Article
PubMed
PubMed Central
Google Scholar
Myung W, Kim J, Lim S-W, Shim S, Won H-H, Kim S, et al. A genome-wide association study of antidepressant response in Koreans. Transl Psychiatry. 2015;5:e633.
Article
CAS
PubMed
PubMed Central
Google Scholar
Goes FS, Hamshere ML, Seifuddin F, Pirooznia M, Belmonte-Mahon P, Breuer R, et al. Genome-wide association of mood-incongruent psychotic bipolar disorder. Transl Psychiatry. 2012;2:e180.
Article
CAS
PubMed
PubMed Central
Google Scholar
van der Meer D, Frei O, Kaufmann T, Shadrin AA, Devor A, Smeland OB, et al. Understanding the genetic determinants of the brain with MOSTest. Nat Commun. 2020;11:3512.
Article
PubMed
PubMed Central
Google Scholar
Davies G, Lam M, Harris SE, Trampush JW, Luciano M, Hill WD, et al. Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function. Nat Commun. 2018;9:2098.
Article
PubMed
PubMed Central
Google Scholar
Hayashi R, Goto Y, Ikeda R, Yokoyama KK, Yoshida K. CDCA4 Is an E2F transcription factor family-induced nuclear factor that regulates E2F-dependent transcriptional activation and cell proliferation. J Biol Chem. 2006;281:35633–48. https://doi.org/10.1074/jbc.M603800200.
Article
CAS
PubMed
Google Scholar
Li C, Stoma S, Lotta LA, Warner S, Albrecht E, Allione A, et al. Genome-wide association analysis in humans links nucleotide metabolism to leukocyte telomere length. Am J Hum Genet. 2020;106:389–404.
Article
CAS
PubMed
PubMed Central
Google Scholar
Lee JJ, Wedow R, Okbay A, Kong E, Maghzian O, Zacher M, et al. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nat Genet. 2018;50:1112–21.
Article
CAS
PubMed
PubMed Central
Google Scholar
Eme R. Developmental psychopathology: a primer for clinical pediatrics. World J Psychiatry. 2017;7:159–62.
Article
PubMed
PubMed Central
Google Scholar
Bas-Hoogendam JM, van Steenbergen H, Tissier RLM, Houwing-Duistermaat JJ, Westenberg PM, van der Wee NJA. Subcortical brain volumes, cortical thickness and cortical surface area in families genetically enriched for social anxiety disorder—a multiplex multigenerational neuroimaging study. EBioMedicine. 2018;36:410–28. https://doi.org/10.1016/j.ebiom.2018.08.048.
Article
PubMed
PubMed Central
Google Scholar
Evans GW, Li D, Whipple SS. Cumulative risk and child development. Psychol Bull. 2013;139:1342–96. https://doi.org/10.1037/a0031808.supp.
Article
PubMed
Google Scholar
Burchinal MR, Roberts JE, Hooper S, Zeisel SA. Cumulative risk and early cognitive development: a comparison of statistical risk models. Dev Psychol. 2000;36:793–807.
Article
CAS
PubMed
Google Scholar
Lawn RB, Anderson EL, Suderman M, Simpkin AJ, Gaunt TR, Teschendorff AE, et al. Psychosocial adversity and socioeconomic position during childhood and epigenetic age: analysis of two prospective cohort studies. Hum Mol Genet. 2018;27:1301–8.
Article
CAS
PubMed
PubMed Central
Google Scholar
Lanza ST, Rhoades BL, Greenberg MT, Cox M. Modeling multiple risks during infancy to predict quality of the caregiving environment: contributions of a person-centered approach. Infant Behav Dev. 2011;34:390–406. https://doi.org/10.1016/j.infbeh.2011.02.002.
Article
PubMed
PubMed Central
Google Scholar
Joubert BR, Håberg SE, Nilsen RM, Wang X, Vollset SE, Murphy SK, et al. 450K epigenome-wide scan identifies differential DNA methylation in newborns related to maternal smoking during pregnancy. Environ Health Perspect. 2012;120:1425–31.
Article
CAS
PubMed
PubMed Central
Google Scholar
Breton CV, Marsit CJ, Faustman E, Nadeau K, Goodrich JM, Dolinoy DC, et al. Small-magnitude effect sizes in epigenetic end points are important in children’s environmental health studies: The Children’s Environmental Health and Disease Prevention Research Center’s Epigenetics Working Group. Environ Health Perspect. 2017;125:511–26.
Article
CAS
PubMed
PubMed Central
Google Scholar