Evidence map›Paper›PMID 37046301›Full record

ArticleJournal of translational medicine2023

Identification of novel cell-free RNAs in maternal plasma as preterm biomarkers in combination with placental RNA profiles.

Heyue Jin, Yimin Zhang, Zhigang Fan, Xianyan Wang, Chen Rui, Shaozhen Xing, Hongmei Dong, Qunan Wang, Fangbiao Tao, Yumin Zhu

Open access · goldAbstract read
In one paragraph

Article in Journal of translational medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
1.5field-weighted citation impact, top 18% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 1 country.

Heyue JinDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei, Anhui, China.
Yimin ZhangDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei, Anhui, China.
Zhigang FanDepartment of Neonatology, Ma'anshan Maternal and Child Health Hospital, Ma'anshan, Anhui, China.
Xianyan WangDepartment of Toxicology, School of Public Health, Anhui Medical University, Hefei, Anhui, China.
Chen RuiDepartment of Toxicology, School of Public Health, Anhui Medical University, Hefei, Anhui, China.
Shaozhen XingMOE Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing, China.
Hongmei DongDepartment of Obstetrics, Ma'anshan Maternal and Child Health Hospital, Ma'anshan, Anhui, China.
Qunan WangDepartment of Toxicology, School of Public Health, Anhui Medical University, Hefei, Anhui, China. wqn@ahmu.edu.cn.
Fangbiao TaoDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei, Anhui, China. fbtao@ahmu.edu.cn.
Yumin ZhuDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei, Anhui, China. zhuyumin2011@163.com.
Anhui Medical University · CNMaternal and Child Health Care Hospital of Bao'an · CNHefei Institutes of Physical Science · CNTsinghua University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPreterm birth (PTB) is the main driver of newborn deaths. The identification of pregnancies at risk of PTB remains challenging, as the incomplete understanding of molecular mechanisms associated with PTB. Although several transcriptome studies have been done on the placenta and plasma from PTB women, a comprehensive description of the RNA profiles from plasma and placenta associated with PTB remains lacking.

methodsCandidate markers with consistent trends in the placenta and plasma were identified by implementing differential expression analysis using placental tissue and maternal plasma RNA-seq datasets, and then validated by RT-qPCR in an independent cohort. In combination with bioinformatics analysis tools, we set up two protein-protein interaction networks of the significant PTB-related modules. The support vector machine (SVM) model was used to verify the prediction potential of cell free RNAs (cfRNAs) in plasma for PTB and late PTB.

resultsWe identified 15 genes with consistent regulatory trends in placenta and plasma of PTB while the full term birth (FTB) acts as a control. Subsequently, we verified seven cfRNAs in an independent cohort by RT-qPCR in maternal plasma. The cfRNA ARHGEF28 showed consistence in the experimental validation and performed excellently in prediction of PTB in the model. The AUC achieved 0.990 for whole PTB and 0.986 for late PTB.

conclusionsIn a comparison of PTB versus FTB, the combined investigation of placental and plasma RNA profiles has shown a further understanding of the mechanism of PTB. Then, the cfRNA identified has the capacity of predicting whole PTB and late PTB.

Indexed as

PlacentaPremature BirthBiomarkersFemaleHumansInfant, NewbornPregnancyRNABiomarkersRNACell-free RNAPlacentaPlasmaPredictionPreterm birthTranscriptome

Identifiers

PMID37046301
PMCPMC10100253
OpenAlexW4365150064

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.