{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T15:33:11Z","timestamp":1791819191624,"version":"4.3.4"},"reference-count":31,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2020,6,2]],"date-time":"2020-06-02T00:00:00Z","timestamp":1591056000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2018A030313286"],"award-info":[{"award-number":["2018A030313286"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81871177"],"award-info":[{"award-number":["81871177"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["obgyn.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["BJOG"],"published-print":{"date-parts":[[2021,1]]},"abstract":"<jats:sec><jats:title>Objective<\/jats:title><jats:p>To predict fetal growth restriction (FGR) by whole\u2010genome promoter profiling of maternal plasma.<\/jats:p><\/jats:sec><jats:sec><jats:title>Design<\/jats:title><jats:p>Nested case\u2013control study.<\/jats:p><\/jats:sec><jats:sec><jats:title>Setting<\/jats:title><jats:p>Hospital\u2010based.<\/jats:p><\/jats:sec><jats:sec><jats:title>Population or Sample<\/jats:title><jats:p>810 pregnancies: 162 FGR cases and 648 controls.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We identified gene promoters with a nucleosome footprint that differed between FGR cases and controls based on maternal plasma cell\u2010free DNA (cfDNA) nucleosome profiling. Optimal classifiers were developed using support vector machine (SVM) and logistic regression (LR) models.<\/jats:p><\/jats:sec><jats:sec><jats:title>Main outcome measures<\/jats:title><jats:p>Genes with differential coverages in promoter regions through the low\u2010coverage whole\u2010genome sequencing data analysis among FGR cases and controls. Receiver operating characteristic (ROC) analysis (area under the curve [AUC], accuracy, sensitivity and specificity) was used to evaluate the performance of classifiers.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Through the low\u2010coverage whole\u2010genome sequencing data analysis of FGR cases and controls, genes with significantly differential DNA coverage at promoter regions (\u22121000 to +1000\u00a0bp of transcription start sites) were identified. The non\u2010invasive \u2018FGR classifier 1\u2019 (C<jats:sub>FGR<\/jats:sub>1) had the highest classification performance (AUC, 0.803; 95% CI 0.767\u20130.839; accuracy, 83.2%) was developed based on 14 genes with differential promoter coverage using a support vector machine.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>A promising FGR prediction method was successfully developed for assessing the risk of FGR at an early gestational age based on maternal plasma cfDNA nucleosome profiling.<\/jats:p><\/jats:sec><jats:sec><jats:title>Tweetable abstract<\/jats:title><jats:p>A promising FGR prediction method was successfully developed, based on maternal plasma cfDNA nucleosome profiling.<\/jats:p><\/jats:sec>","DOI":"10.1111\/1471-0528.16292","type":"journal-article","created":{"date-parts":[[2020,5,4]],"date-time":"2020-05-04T11:23:40Z","timestamp":1588591420000},"page":"458-466","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Non\u2010invasive prediction of fetal growth restriction by whole\u2010genome promoter profiling of maternal plasma DNA: a nested case\u2013control study"],"prefix":"10.1111","volume":"128","author":[{"given":"C","family":"Xu","sequence":"first","affiliation":[{"name":"The Second School of Clinical Medicine Southern Medical University Guangzhou China"},{"name":"Department of Obstetrics and Gynaecology Nanfang Hospital Southern Medical University Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Z","family":"Guo","sequence":"additional","affiliation":[{"name":"Institute of Antibody Engineering School of Laboratory Medicine and 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