{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Buthmann JL"],"funding":["Christopher Hess Research Fund","Alfred E. Mann Foundation","NIMH NIH HHS","March of Dimes Foundation","Charles B. and Ann L. Johnson Endowed Fund","National Institute of Mental Health","National Institutes of Health","Bill and Melinda Gates Foundation","Tad Taube Maternal and Child Health Research Fund","NIGMS NIH HHS","NIH HHS","Stanford Maternal and Child Health Research Institute"],"pagination":["1098-1107"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11265978"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["65(8)"],"pubmed_abstract":["Background
Understanding the prenatal origins of children's psychopathology is a fundamental goal in developmental and clinical science. Recent research suggests that inflammation during pregnancy can trigger a cascade of fetal programming changes that contribute to vulnerability for the emergence of psychopathology. Most studies, however, have focused on a handful of proinflammatory cytokines and have not explored a range of prenatal biological pathways that may be involved in increasing postnatal risk for emotional and behavioral difficulties.Methods
Using extreme gradient boosted machine learning models, we explored large-scale proteomics, considering over 1,000 proteins from first trimester blood samples, to predict behavior in early childhood. Mothers reported on their"],"journal":["Journal of child psychology and psychiatry, and allied disciplines"],"pubmed_title":["Large-scale proteomics in the first trimester of pregnancy predict psychopathology and temperament in preschool children: an exploratory study."],"pmcid":["PMC11265978"],"funding_grant_id":["R35GM138353","R37MH101495","R37 MH101495","R35 GM138353"],"pubmed_authors":["Shaw GM","Wong RJ","Miller JG","Buthmann JL","Gotlib IH","Aghaeepour N","King LS","Stevenson DK"],"additional_accession":[]},"is_claimable":false,"name":"Large-scale proteomics in the first trimester of pregnancy predict psychopathology and temperament in preschool children: an exploratory study.","description":"Background
Understanding the prenatal origins of children's psychopathology is a fundamental goal in developmental and clinical science. Recent research suggests that inflammation during pregnancy can trigger a cascade of fetal programming changes that contribute to vulnerability for the emergence of psychopathology. Most studies, however, have focused on a handful of proinflammatory cytokines and have not explored a range of prenatal biological pathways that may be involved in increasing postnatal risk for emotional and behavioral difficulties.Methods
Using extreme gradient boosted machine learning models, we explored large-scale proteomics, considering over 1,000 proteins from first trimester blood samples, to predict behavior in early childhood. Mothers reported on their","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Aug","modification":"2026-03-17T15:29:55.63Z","creation":"2025-08-16T03:06:54.78Z"},"accession":"S-EPMC11265978","cross_references":{"pubmed":["38287782"],"doi":["10.1111/jcpp.13948"]}}