{"doi":"10.1016/j.scitotenv.2023.169458","title":"Exploring applications of non-targeted analysis in the characterization of the prenatal exposome","abstract":"Capturing the breadth of chemical exposures in utero is critical in understanding their long-term health effects for mother and child. We explored methodological adaptations in a Non-Targeted Analysis (NTA) pipeline and evaluated the effects on chemical annotation and discovery for maternal and infant exposure. We focus on lesser-known/underreported chemicals in maternal and umbilical cord serum analyzed with liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOF/MS). The samples were collected from a demographically diverse cohort of 296 maternal-cord pairs (n = 592) recruited in San Francisco Bay area. We developed and evaluated two data processing pipelines, primarily differing by detection frequency cut-off, to extract chemical features from non-targeted analysis (NTA). We annotated the detected chemical features by matching with EPA CompTox Chemicals Dashboard (n = 860,000 chemicals) and Human Metabolome Database (n = 3140 chemicals) and applied a Kendrick Mass Defect filter to detect homologous series. We collected fragmentation spectra (MS/MS) on a subset of serum samples and matched to an experimental MS/MS database within the MS-Dial website and other experimental MS/MS spectra collected from standards in our lab. We annotated ~72 % of the features (total features = 32,197, levels 1-4). We confirmed 22 compounds with analytical standards, tentatively identified 88 compounds with MS/MS spectra, and annotated 4862 exogenous chemicals with an in-house developed annotation algorithm. We detected 36 chemicals that appear to not have been previously reported in human blood and 9 chemicals that were reported in less than five studies. Our findings underline the importance of NTA in the discovery of lesser-known/unreported chemicals important to characterize human exposures.","journal":"The Science of The Total Environment","year":2023,"id":368459,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":4,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.847,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":578503,"name":"Dimitri Abrahamsson","orcid":"0000-0002-3402-7565","position":1,"is_corresponding":false},{"id":512428,"name":"Miaomiao Wang","orcid":"0000-0001-5714-6420","position":2,"is_corresponding":false},{"id":906594,"name":"Marya G. Zlatnik","orcid":null,"position":3,"is_corresponding":false},{"id":232426,"name":"Rachel Morello‐Frosch","orcid":"0000-0003-1153-7287","position":4,"is_corresponding":false},{"id":298301,"name":"June-Soo Park","orcid":"0009-0005-2177-4405","position":5,"is_corresponding":false},{"id":2824,"name":"Marina Sirota","orcid":"0000-0002-7246-6083","position":6,"is_corresponding":false},{"id":298305,"name":"Tracey J. Woodruff","orcid":"0000-0003-3622-1297","position":7,"is_corresponding":false},{"id":1063541,"name":"Garret D. Bland","orcid":"0000-0001-9879-7879","position":0,"is_corresponding":true}],"reference_count":68,"raw_metadata":null,"created_at":"2026-07-19T01:15:20.453499Z","pmid":"38142008","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}