ArticleClinical epigenetics2018
DNA methylation as a predictor of fetal alcohol spectrum disorder.
Article in Clinical epigenetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
53 citing papers in PubMed, 2 syntheses or guidelines pooled it, 111 citations in OpenAlex.
- Contributions of Artificial Intelligence Reported in Obstetrics and Gynecology Journals: Systematic Review.Journal of medical Internet research · 2022Pooled it
- Association of prenatal alcohol exposure with offspring DNA methylation in mammals: a systematic review of the evidence.Clinical epigenetics · 2022Pooled it
- The association between prenatal alcohol exposure and protein expression in human placenta.Birth defects research · 2019Trial
- From teratogens to trajectories: Integrating teratology and Developmental Origins of Health and Disease (DOHaD) frameworks for a new take on fetal alcohol spectrum disorders (FASD).Neurobiology of stress · 2026Article
- Does a Biochemical Approach Facilitate the Diagnosis of Prenatal Alcohol Exposure and Fetal Alcohol Spectrum Disorder in Neonatal Period?International journal of molecular sciences · 2026Review
- ACSS2 mediates prenatal alcohol exposure-related morphological and behavioral phenotypes.Neurobiology of disease · 2026Article
- A robust computational framework for methylation age and disease-risk prediction based on pairwise learning.Nature computational science · 2026Article
- Prenatal Alcohol Exposure and Mental Health Outcomes: A Two-Sample Mendelian Randomization Study of DNA Methylation Signatures.medRxiv : the preprint server for health sciences · 2026Article
- Early biomarkers associated with prenatal alcohol exposure and neurodevelopmental outcomes.Frontiers in pharmacology · 2026Review
- Cross-Tissue Specificity of Pediatric DNA Methylation Associated With Cumulative Family Stress.Developmental psychobiology · 2025Article
- Epigenome-wide association study of placental co-methylated regions in newborns for prenatal opioid exposure.Environmental epigenetics · 2025Article
- Nonconceptus Mechanisms of Prenatal Alcohol Exposure That Disrupt Embryo-Fetal Development: An Integrative View.Alcohol research : current reviews · 2025Review
- Early moderate prenatal alcohol exposure and maternal diet impact offspring DNA methylation across species.eLife · 2024Article
- Genetic variation and pesticide exposure influence blood DNA methylation signatures in females with early-stage Parkinson's disease.NPJ Parkinson's disease · 2024Article
- Machine learning approaches to the identification of children affected by prenatal alcohol exposure: A narrative review.Alcohol, clinical & experimental research · 2024Review
- Article
- Predicting fetal alcohol spectrum disorders in preschool-aged children from early life factors.Alcohol, clinical & experimental research · 2024Article
- Machine learning algorithms to the early diagnosis of fetal alcohol spectrum disorders.Frontiers in neuroscience · 2024Article
- Parental scaffolding in play: A comparison of fetal alcohol spectrum disorders and autism spectrum disorder.Research in developmental disabilities · 2023Article
- Predicting Fetal Alcohol Spectrum Disorders Using Machine Learning Techniques: Multisite Retrospective Cohort Study.Journal of medical Internet research · 2023Article
Corrections and comments
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Authors and funding
9 authors at 6 institutions in 1 country.
Funding
Abstract
Background: Fetal alcohol spectrum disorder (FASD) is a developmental disorder that manifests through a range of cognitive, adaptive, physiological, and neurobiological deficits resulting from prenatal alcohol exposure. Although the North American prevalence is currently estimated at 2-5%, FASD has proven difficult to identify in the absence of the overt physical features characteristic of fetal alcohol syndrome. As interventions may have the greatest impact at an early age, accurate biomarkers are needed to identify children at risk for FASD. Building on our previous work identifying distinct DNA methylation patterns in children and adolescents with FASD, we have attempted to validate these associations in a different clinical cohort and to use our DNA methylation signature to develop a possible epigenetic predictor of FASD. Methods: Genome-wide DNA methylation patterns were analyzed using the Illumina HumanMethylation450 array in the buccal epithelial cells of a cohort of 48 individuals aged 3.5-18 (24 FASD cases, 24 controls). The DNA methylation predictor of FASD was built using a stochastic gradient boosting model on our previously published dataset FASD cases and controls (GSE80261). The predictor was tested on the current dataset and an independent dataset of 48 autism spectrum disorder cases and 48 controls (GSE50759). Results: We validated findings from our previous study that identified a DNA methylation signature of FASD, replicating the altered DNA methylation levels of 161/648 CpGs in this independent cohort, which may represent a robust signature of FASD in the epigenome. We also generated a predictive model of FASD using machine learning in a subset of our previously published cohort of 179 samples (83 FASD cases, 96 controls), which was tested in this novel cohort of 48 samples and resulted in a moderately accurate predictor of FASD status. Upon testing the algorithm in an independent cohort of individuals with autism spectrum disorder, we did not detect any bias towards autism, sex, age, or ethnicity. Conclusion: These findings further support the association of FASD with distinct DNA methylation patterns, while providing a possible entry point towards the development of epigenetic biomarkers of FASD.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.