Evidence map›Paper›PMID 33886611›Full record

ArticlePloS one2021

Investigating gene methylation signatures for fetal intolerance prediction.

Yu-Hang Zhang, Zhandong Li, Tao Zeng, Lei Chen, Hao Li, Margarita Gamarra, Romany F Mansour, José Escorcia-Gutierrez, Tao Huang, Yu-Dong Cai

Abstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

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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

2 citing papers in PubMed.

  1. Article
  2. Episignature analysis of moderate effects and mosaics.European journal of human genetics : EJHG · 2023
    Article
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.

Yu-Hang ZhangSchool of Life Sciences, Shanghai University, Shanghai, China.
Zhandong LiCollege of Food Engineering, Jilin Engineering Normal University, Changchun, China.
Tao ZengBio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
Lei ChenCollege of Information Engineering, Shanghai Maritime University, Shanghai, China.
Hao LiCollege of Food Engineering, Jilin Engineering Normal University, Changchun, China.
Margarita GamarraDepartment of Computational Science and Electronic, Universidad de la Costa, CUC, Barranquilla, Colombia.ORCID 0000-0003-1834-2984
Romany F MansourDepartment of Mathematics, Faculty of Science, New Valley University, El-Kharga, Egypt.ORCID 0000-0001-5857-8495
José Escorcia-GutierrezElectronic and Telecommunicacions Program, Universidad Autónoma del Caribe, Barranquilla, Colombia.ORCID 0000-0003-0518-3187
Tao HuangBio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.ORCID 0000-0003-1975-9693
Yu-Dong CaiSchool of Life Sciences, Shanghai University, Shanghai, China.ORCID 0000-0001-5664-7979

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pregnancy is a complicated and long procedure during one or more offspring development inside a woman. A short period of oxygen shortage after birth is quite normal for most babies and does not threaten their health. However, if babies have to suffer from a long period of oxygen shortage, then this condition is an indication of pathological fetal intolerance, which probably causes their death. The identification of the pathological fetal intolerance from the physical oxygen shortage is one of the important clinical problems in obstetrics for a long time. The clinical syndromes typically manifest five symptoms that indicate that the baby may suffer from fetal intolerance. At present, liquid biopsy combined with high-throughput sequencing or mass spectrum techniques provides a quick approach to detect real-time alteration in the peripheral blood at multiple levels with the rapid development of molecule sequencing technologies. Gene methylation is functionally correlated with gene expression; thus, the combination of gene methylation and expression information would help in screening out the key regulators for the pathogenesis of fetal intolerance. We combined gene methylation and expression features together and screened out the optimal features, including gene expression or methylation signatures, for fetal intolerance prediction for the first time. In addition, we applied various computational methods to construct a comprehensive computational pipeline to identify the potential biomarkers for fetal intolerance dependent on the liquid biopsy samples. We set up qualitative and quantitative computational models for the prediction for fetal intolerance during pregnancy. Moreover, we provided a new prospective for the detailed pathological mechanism of fetal intolerance. This work can provide a solid foundation for further experimental research and contribute to the application of liquid biopsy in antenatal care.

Indexed as

DNA MethylationDatabases, FactualFemaleHumansHypoxiaPregnancyPrenatal CareRisk Factors

Identifiers

PMID33886611
PMCPMC8062050

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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.