Evidence map›Paper›PMID 36088304›Full record

ArticleBMC pregnancy and childbirth2022

Performance of whole-genome promoter nucleosome profiling of maternal plasma cell-free DNA for prenatal noninvasive prediction of fetal macrosomia: a retrospective nested case-control study in mainland China.

Qianwen Lu, Zhiwei Guo, Jun Zhang, Ke Wang, Qi Tian, Siping Liu, Kun Li, Cailing Xu, Caimin Li, Zenglu Lv and 3 more

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In one paragraph

Article in BMC pregnancy and childbirth, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

13 authors.

Qianwen Lu *Department of Fetal Medicine and Prenatal Diagnosis, Zhujiang Hospital, Southern Medical University, Guangzhou, 510280, China.
Zhiwei Guo *Institute of Antibody Engineering, School of Laboratory Medical and Biotechnology, Southern Medical University, Guangzhou, 510515, China.
Jun Zhang *Department of Obstetrics and Gynecology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510630, China.
Ke WangDepartment of Obstetrics and Gynecology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Qi TianDepartment of Obstetrics and Gynecology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510630, China.
Siping LiuDepartment of Obstetrics and Gynecology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Kun LiInstitute of Antibody Engineering, School of Laboratory Medical and Biotechnology, Southern Medical University, Guangzhou, 510515, China.
Cailing XuDepartment of Fetal Medicine and Prenatal Diagnosis, Zhujiang Hospital, Southern Medical University, Guangzhou, 510280, China.
Caimin LiDepartment of Fetal Medicine and Prenatal Diagnosis, Zhujiang Hospital, Southern Medical University, Guangzhou, 510280, China.
Zenglu LvDepartment of Pathology, Cangzhou People's Hospital, Cangzhou, 061000, China.
Zhigang ZhangDepartment of Pathology, Cangzhou People's Hospital, Cangzhou, 061000, China. zhzhg001518@126.com.
Xuexi YangInstitute of Antibody Engineering, School of Laboratory Medical and Biotechnology, Southern Medical University, Guangzhou, 510515, China. yangxuexi2017@126.com.
Fang YangDepartment of Fetal Medicine and Prenatal Diagnosis, Zhujiang Hospital, Southern Medical University, Guangzhou, 510280, China. fangfangy@hotmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFetal macrosomia is common occurrence in pregnancy, which is associated with several adverse prognosis both of maternal and neonatal. While, the accuracy of prediction of fetal macrosomia is poor. The aim of this study was to develop a reliable noninvasive prediction classifier of fetal macrosomia.

methodsA total of 3600 samples of routine noninvasive prenatal testing (NIPT) data at 12

resultsAccording to the available follow-up results, 162 fetal macrosomia pregnancies and 648 matched controls were included. A total of 1086 genes with significantly differential promoter profiling were found between pregnancies with macrosomia and controls (p < 0.05). With the AUC as a reference，the classifier based on SVM (C

conclusionsOur study provides that assessing the risk of fetal macrosomia by whole-genome promoter nucleosome profiling of maternal plasma cfDNA based on low-coverage next-generation sequencing is feasible.

Indexed as

Cell-Free Nucleic AcidsFetal MacrosomiaCase-Control StudiesChinaFemaleHumansInfant, NewbornNucleosomesPregnancyRetrospective StudiesCell-Free Nucleic AcidsNucleosomesCell-free DNAClassifierFetal macrosomiaLow-coverage whole-genome promoter profilingNoninvasive prediction

Identifiers

PMID36088304
PMCPMC9463826

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