Variably methylated regions in the newborn epigenome: environmental, genetic and combined influences
暂无分享,去创建一个
Fabian J Theis | Dan J Stein | H. Zar | S. London | S. Entringer | P. Wadhwa | C. Buss | J. Lahti | K. Räikkönen | E. Binder | M. Kobor | M. Meaney | K. O’Donnell | Gökçen Eraslan | E. Kajantie | S. Dalvie | D. Czamara | N. Koen | W. Nystad | R. Reynolds | K. Koenen | H. Laivuori | E. Hämäläinen | Meaghan J. Jones | S. Håberg | M. Lahti-Pulkkinen | J. MacIsaac | D. Lin | C. Page | P. Villa | N. Müller | Elika Garg | Ivan Kondofersky | E. Hämäläinen
[1] R. Fry,et al. Environmental Influences on the Epigenome: Exposure- Associated DNA Methylation in Human Populations. , 2018, Annual review of public health.
[2] A. Amstadter,et al. Maternal prenatal stress and infant DNA methylation: A systematic review , 2018, Developmental psychobiology.
[3] Kathryn Demanelis,et al. Co-occurring expression and methylation QTLs allow detection of common causal variants and shared biological mechanisms , 2018, Nature Communications.
[4] Warren W. Kretzschmar,et al. Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression , 2017, Nature Genetics.
[5] Marc D. Rudolph,et al. Maternal Systemic Interleukin-6 During Pregnancy Is Associated With Newborn Amygdala Phenotypes and Subsequent Behavior at 2 Years of Age , 2018, Biological Psychiatry.
[6] Martin Styner,et al. Intergenerational Effect of Maternal Exposure to Childhood Maltreatment on Newborn Brain Anatomy , 2018, Biological Psychiatry.
[7] Dan J Stein,et al. Maternal blood contamination of collected cord blood can be identified using DNA methylation at three CpGs , 2017, Clinical Epigenetics.
[8] Jakob Grove,et al. Discovery of the first genome-wide significant risk loci for ADHD , 2017, bioRxiv.
[9] T. Haaf,et al. DNA methylation signatures in cord blood of ICSI children , 2017, Human reproduction.
[10] Xiaoju Yang,et al. Genome-wide Methyl-Seq analysis of blood-brain targets of glucocorticoid exposure , 2017, Epigenetics.
[11] Christopher S. Poultney,et al. Meta-analysis of GWAS of over 16,000 individuals with autism spectrum disorder highlights a novel locus at 10q24.32 and a significant overlap with schizophrenia , 2017, Molecular Autism.
[12] M. O’Donovan,et al. Pleiotropic effects of trait-associated genetic variation on DNA methylation: utility for refining , 2018 .
[13] ClarLynda R. Williams-DeVane,et al. Maternal BMI at the start of pregnancy and offspring epigenome-wide DNA methylation: findings from the pregnancy and childhood epigenetics (PACE) consortium , 2017, bioRxiv.
[14] G. Johannsson,et al. Reduced DNA methylation and psychopathology following endogenous hypercortisolism – a genome-wide study , 2017, Scientific Reports.
[15] Warren A. Cheung,et al. Functional variation in allelic methylomes underscores a strong genetic contribution and reveals novel epigenetic alterations in the human epigenome , 2017, Genome Biology.
[16] Alexander M. Morin,et al. Developmental pathways to adiposity begin before birth and are influenced by genotype, prenatal environment and epigenome , 2017, BMC Medicine.
[17] S. Entringer,et al. Maternal Cortisol During Pregnancy and Infant Adiposity: A Prospective Investigation , 2016, The Journal of clinical endocrinology and metabolism.
[18] Tom R. Gaunt,et al. DNA methylation and substance-use risk: a prospective, genome-wide study spanning gestation to adolescence , 2016, Translational psychiatry.
[19] Matthew T. Maurano,et al. Genetic Drivers of Epigenetic and Transcriptional Variation in Human Immune Cells , 2016, Cell.
[20] Timothy J. Peters,et al. Critical evaluation of the Illumina MethylationEPIC BeadChip microarray for whole-genome DNA methylation profiling , 2016, Genome Biology.
[21] S. Entringer,et al. Prediction and Prevention of Preeclampsia and Intrauterine Growth Restriction (PREDO) study. , 2016 .
[22] X. Shao,et al. Genetic contribution to variation in DNA methylation at maternal smoking-sensitive loci in exposed neonates , 2016, Epigenetics.
[23] Bonnie R. Joubert,et al. Maternal Age at Delivery Is Associated with an Epigenetic Signature in Both Newborns and Adults , 2016, PloS one.
[24] A. McIntosh,et al. Identification of polymorphic and off-target probe binding sites on the Illumina Infinium MethylationEPIC BeadChip , 2016, bioRxiv.
[25] Charles Auffray,et al. DNA Methylation in Newborns and Maternal Smoking in Pregnancy: Genome-wide Consortium Meta-analysis. , 2016, American journal of human genetics.
[26] P. Magnus,et al. Cohort Profile Update: The Norwegian Mother and Child Cohort Study (MoBa). , 2016, International journal of epidemiology.
[27] Tom R. Gaunt,et al. Systematic identification of genetic influences on methylation across the human life course , 2016, Genome Biology.
[28] Shan V Andrews,et al. DNA methylation of cord blood cell types: Applications for mixed cell birth studies , 2016, Epigenetics.
[29] Roland Eils,et al. Environment‐induced epigenetic reprogramming in genomic regulatory elements in smoking mothers and their children , 2016, Molecular systems biology.
[30] J. Payton,et al. Mapping of Variable DNA Methylation Across Multiple Cell Types Defines a Dynamic Regulatory Landscape of the Human Genome , 2016, G3: Genes, Genomes, Genetics.
[31] Sarah E. Reese,et al. Maternal plasma folate impacts differential DNA methylation in an epigenome-wide meta-analysis of newborns , 2016, Nature Communications.
[32] Tom R. Gaunt,et al. An epigenome-wide association meta-analysis of prenatal maternal stress in neonates: A model approach for replication , 2016, Epigenetics.
[33] D. Stein,et al. Validation of the Self Reporting Questionnaire 20-Item (SRQ-20) for Use in a Low- and Middle-Income Country Emergency Centre Setting , 2016, International Journal of Mental Health and Addiction.
[34] Patrick F. Sullivan,et al. High density methylation QTL analysis in human blood via next-generation sequencing of the methylated genomic DNA fraction , 2015, Genome Biology.
[35] M. Esteller,et al. Validation of a DNA methylation microarray for 850,000 CpG sites of the human genome enriched in enhancer sequences , 2015, Epigenomics.
[36] A. Hofman,et al. Disease variants alter transcription factor levels and methylation of their binding sites , 2016, Nature Genetics.
[37] S. Entringer,et al. Prenatal stress, development, health and disease risk: A psychobiological perspective—2015 Curt Richter Award Paper , 2015, Psychoneuroendocrinology.
[38] Dan J Stein,et al. Investigating the psychosocial determinants of child health in Africa: The Drakenstein Child Health Study , 2015, Journal of Neuroscience Methods.
[39] O. Troyanskaya,et al. Predicting effects of noncoding variants with deep learning–based sequence model , 2015, Nature Methods.
[40] Judy H. Cho,et al. Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations , 2015, Nature Genetics.
[41] Christian Gieger,et al. Discovery and Fine-Mapping of Glycaemic and Obesity-Related Trait Loci Using High-Density Imputation , 2015, PLoS genetics.
[42] Tom R. Gaunt,et al. Maternal pre-pregnancy BMI and gestational weight gain, offspring DNA methylation and later offspring adiposity: findings from the Avon Longitudinal Study of Parents and Children , 2015, International journal of epidemiology.
[43] M. O’Hara,et al. Prenatal Stress due to a Natural Disaster Predicts Adiposity in Childhood: The Iowa Flood Study , 2015, Journal of obesity.
[44] Ting Wang,et al. Intermediate DNA methylation is a conserved signature of genome regulation , 2015, Nature Communications.
[45] P. Gluckman,et al. Brain-derived neurotrophic factor (BDNF) Val66Met polymorphism influences the association of the methylome with maternal anxiety and neonatal brain volumes , 2015, Development and Psychopathology.
[46] J. van Helden,et al. Integrative analysis of public ChIP-seq experiments reveals a complex multi-cell regulatory landscape , 2014, Nucleic acids research.
[47] Dan J Stein,et al. Investigating the early-life determinants of illness in Africa: the Drakenstein Child Health Study , 2014, Thorax.
[48] C. Spencer,et al. Biological Insights From 108 Schizophrenia-Associated Genetic Loci , 2014, Nature.
[49] P. Gluckman,et al. The effect of genotype and in utero environment on interindividual variation in neonate DNA methylomes , 2014, Genome research.
[50] Rafael A. Irizarry,et al. Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays , 2014, Bioinform..
[51] Enrique Blanco,et al. ENCODE (Encyclopedia of DNA Elements) , 2014 .
[52] K. Hansen,et al. Functional normalization of 450k methylation array data improves replication in large cancer studies , 2014, Genome Biology.
[53] Lynn M Almli,et al. Methylation quantitative trait loci (meQTLs) are consistently detected across ancestry, developmental stage, and tissue type , 2014, BMC Genomics.
[54] Mathieu Blanchette,et al. The relationship between DNA methylation, genetic and expression inter-individual variation in untransformed human fibroblasts , 2014, Genome Biology.
[55] Mei-Lyn Ong,et al. Novel region discovery method for Infinium 450K DNA methylation data reveals changes associated with aging in muscle and neuronal pathways , 2013, Aging cell.
[56] M. Szyf,et al. Effects of antenatal synthetic glucocorticoid on glucocorticoid receptor binding, DNA methylation, and genome-wide mRNA levels in the fetal male hippocampus. , 2013, Endocrinology.
[57] I. Yanai,et al. The genomic determinants of genotype × environment interactions in gene expression. , 2013, Trends in genetics : TIG.
[58] E. Dermitzakis,et al. Passive and active DNA methylation and the interplay with genetic variation in gene regulation , 2013, eLife.
[59] B. Bradley,et al. Childhood maltreatment is associated with distinct genomic and epigenetic profiles in posttraumatic stress disorder , 2013, Proceedings of the National Academy of Sciences.
[60] M. Daly,et al. Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis , 2013, The Lancet.
[61] Pau Farré,et al. Additional annotation enhances potential for biologically-relevant analysis of the Illumina Infinium HumanMethylation450 BeadChip array , 2013, Epigenetics & Chromatin.
[62] R. Weksberg,et al. Discovery of cross-reactive probes and polymorphic CpGs in the Illumina Infinium HumanMethylation450 microarray , 2013, Epigenetics.
[63] D. Hellhammer,et al. Prenatal adversity: a risk factor in borderline personality disorder? , 2012, Psychological Medicine.
[64] B. Bradley,et al. Allele-specific FKBP5 DNA demethylation mediates gene–childhood trauma interactions , 2012, Nature Neuroscience.
[65] Francesco Marabita,et al. A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data , 2012, Bioinform..
[66] D. Bentley,et al. Large-scale genome-wide association analysis of bipolar disorder identifies a new susceptibility locus near ODZ4 , 2012, Nature Genetics.
[67] Susan K. Murphy,et al. 450K Epigenome-Wide Scan Identifies Differential DNA Methylation in Newborns Related to Maternal Smoking during Pregnancy , 2012, Environmental health perspectives.
[68] Tanya M. Teslovich,et al. Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes , 2012, Nature Genetics.
[69] T. Hashimshony,et al. A genomic bias for genotype–environment interactions in C. elegans , 2012, Molecular systems biology.
[70] K. Gunderson,et al. High density DNA methylation array with single CpG site resolution. , 2011, Genomics.
[71] M. Esteller,et al. Validation of a DNA methylation microarray for 450,000 CpG sites in the human genome , 2011, Epigenetics.
[72] Luigi Ferrucci,et al. Abundant Quantitative Trait Loci Exist for DNA Methylation and Gene Expression in Human Brain , 2010, PLoS genetics.
[73] A. Feinberg,et al. Stochastic epigenetic variation as a driving force of development, evolutionary adaptation, and disease , 2010, Proceedings of the National Academy of Sciences.
[74] Kent L Thornburg,et al. Effect of in Utero and Early-life Conditions on Adult Health and Disease Epidemiol Ogic a Nd Clinic a L Observations , 2022 .
[75] Marie-Aline Charles,et al. Childhood Obesity and Metabolic Imprinting , 2007, Diabetes Care.
[76] O. Mäkitie,et al. Glucose regulation in young adults with very low birth weight. , 2007, The New England journal of medicine.
[77] H. Meltzer,et al. The biobank of the Norwegian mother and child cohort Study: A resource for the next 100 years , 2006, European Journal of Epidemiology.
[78] T. Roseboom,et al. The Dutch famine and its long-term consequences for adult health. , 2006, Early human development.
[79] T. Grange,et al. Active cytosine demethylation triggered by a nuclear receptor involves DNA strand breaks. , 2006, Proceedings of the National Academy of Sciences of the United States of America.
[80] J. Eriksson,et al. Trajectories of growth among children who have coronary events as adults. , 2005, The New England journal of medicine.
[81] Paul T. Groth,et al. The ENCODE (ENCyclopedia Of DNA Elements) Project , 2004, Science.
[82] M. Rubio‐Stipec,et al. The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST): development, reliability and feasibility. , 2002, Addiction.
[83] L. Irgens,et al. The Medical Birth Registry of Norway. Epidemiological research and surveillance throughout 30 years , 2000, Acta obstetricia et gynecologica Scandinavica.
[84] Ping Zhang,et al. Inference after variable selection in linear regression models , 1992 .
[85] L. Radloff. The CES-D Scale , 1977 .
[86] A. Beck,et al. An inventory for measuring depression. , 1961, Archives of general psychiatry.
[87] J. Lahti,et al. Maternal Depressive Symptoms During and After Pregnancy and Psychiatric Problems in Children. , 2017, Journal of the American Academy of Child and Adolescent Psychiatry.
[88] T. Bale,et al. The Placenta as a Mediator of Stress Effects on Neurodevelopmental Reprogramming , 2016, Neuropsychopharmacology.
[89] S. London,et al. Maternal folate levels in pregnancy and asthma in children at age 3 years. , 2011, Journal of Allergy and Clinical Immunology.
[90] Cheng Li,et al. Adjusting batch effects in microarray expression data using empirical Bayes methods. , 2007, Biostatistics.
[91] H. Akaike,et al. Information Theory and an Extension of the Maximum Likelihood Principle , 1973 .
[92] Andrew E. Jaffe,et al. Bioinformatics Applications Note Gene Expression the Sva Package for Removing Batch Effects and Other Unwanted Variation in High-throughput Experiments , 2022 .
[93] J. Lahti,et al. Edinburgh Research Explorer Associations between maternal risk factors of adverse pregnancy and birth outcomes and the offspring epigenetic clock of gestational age at birth , 2022 .