Non-invasive Prediction of Fetal Growth Restriction by Whole-genome Promoter Profiling of Maternal Plasma DNA: a Nested Case-control Study

Overview

Journal BJOG

Specialty Gynecology & Obstetrics

Date 2020 May 5

PMID 32364311

Citations 9

Authors

C Xu

Z Guo

J Zhang

Q Lu

Q Tian

S Liu

K Li

K Wang

Z Tao

C Li

Z Lv

Z Zhang

X Yang

F Yang

Affiliations

Soon will be listed here.

Abstract

Objective: To predict fetal growth restriction (FGR) by whole-genome promoter profiling of maternal plasma.

Design: Nested case-control study.

Setting: Hospital-based.

Population Or Sample: 810 pregnancies: 162 FGR cases and 648 controls.

Methods: We identified gene promoters with a nucleosome footprint that differed between FGR cases and controls based on maternal plasma cell-free DNA (cfDNA) nucleosome profiling. Optimal classifiers were developed using support vector machine (SVM) and logistic regression (LR) models.

Main Outcome Measures: Genes with differential coverages in promoter regions through the low-coverage whole-genome 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.

Results: Through the low-coverage whole-genome sequencing data analysis of FGR cases and controls, genes with significantly differential DNA coverage at promoter regions (-1000 to +1000 bp of transcription start sites) were identified. The non-invasive 'FGR classifier 1' (C 1) had the highest classification performance (AUC, 0.803; 95% CI 0.767-0.839; accuracy, 83.2%) was developed based on 14 genes with differential promoter coverage using a support vector machine.

Conclusions: 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.

Tweetable Abstract: A promising FGR prediction method was successfully developed, based on maternal plasma cfDNA nucleosome profiling.

Citing Articles

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Non-invasive prediction of preeclampsia using the maternal plasma cell-free DNA profile and clinical risk factors.

Yu Y, Xu W, Zhang S, Feng S, Feng F, Dai J Front Med (Lausanne). 2024; 11:1254467.

PMID: 38695016 PMC: 11061442. DOI: 10.3389/fmed.2024.1254467.

Prediction Models for Intrauterine Growth Restriction Using Artificial Intelligence and Machine Learning: A Systematic Review and Meta-Analysis.

Rescinito R, Ratti M, Payedimarri A, Panella M Healthcare (Basel). 2023; 11(11).

PMID: 37297757 PMC: 10252230. DOI: 10.3390/healthcare11111617.

Integrative analyses of maternal plasma cell-free DNA nucleosome footprint differences reveal chromosomal aneuploidy fetuses gene expression profile.

Zhang M, Li K, Qu S, Guo Z, Wang Y, Yang X J Transl Med. 2022; 20(1):536.

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Hypertensive disorders of pregnancy share common cfDNA methylation profiles.

Spinelli M, Zdanowicz J, Keller I, Nicholson P, Raio L, Amylidi-Mohr S Sci Rep. 2022; 12(1):19837.

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