Evidence map›Paper›PMID 34258280›Full record

ArticleBioMed research international2021

Blood Plasma Metabolic Profile of Newborns with Hypoxic-Ischaemic Encephalopathy by GC-MS.

Yanjuan Jia, Xiaoni Jia, Hui Xu, Lan Gao, Chaojun Wei, Yonghong Li, Xia Liu, Xiaoling Gao, Li Wei

Open access · hybridAbstract read
In one paragraph

Article in BioMed research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.7field-weighted citation impact, top 10% 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

4 citing papers in PubMed, 9 citations in OpenAlex.

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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

9 authors at 3 institutions in 1 country.

Yanjuan Jia *NHC Key Laboratory of Diagnosis and Therapy of Gastrointestinal Tumor, Gansu Provincial Hospital, Lanzhou, China 730000.ORCID https://orcid.org/0000-0001-5896-3684
Xiaoni Jia *The Neonatal Department, Qingyang People's Hospital, Qingyang, China 73000.ORCID https://orcid.org/0000-0001-8475-0316
Hui XuNHC Key Laboratory of Diagnosis and Therapy of Gastrointestinal Tumor, Gansu Provincial Hospital, Lanzhou, China 730000.ORCID https://orcid.org/0000-0003-1237-7027
Lan GaoThe Department of Life Science, Lanzhou University, Lanzhou, China 730000.ORCID https://orcid.org/0000-0003-2244-7332
Chaojun WeiNHC Key Laboratory of Diagnosis and Therapy of Gastrointestinal Tumor, Gansu Provincial Hospital, Lanzhou, China 730000.ORCID https://orcid.org/0000-0002-1769-7655
Yonghong LiNHC Key Laboratory of Diagnosis and Therapy of Gastrointestinal Tumor, Gansu Provincial Hospital, Lanzhou, China 730000.ORCID https://orcid.org/0000-0002-5198-3786
Xia LiuThe Neonatal Department, Qingyang People's Hospital, Qingyang, China 73000.ORCID https://orcid.org/0000-0002-0691-6365
Xiaoling GaoNHC Key Laboratory of Diagnosis and Therapy of Gastrointestinal Tumor, Gansu Provincial Hospital, Lanzhou, China 730000.ORCID https://orcid.org/0000-0002-5466-3200
Li WeiThe Laboratory Center, Gansu Provincial Hospital, Lanzhou, China 730000.ORCID https://orcid.org/0000-0003-0830-3877
Gansu Provincial Hospital · CNQingzhou City People's Hospital · CNLanzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEarly diagnosis of hypoxic-ischaemic encephalopathy (HIE) is crucial in preventing neurodevelopmental disabilities and reducing morbidity and mortality. The study was to investigate the plasma metabolic signatures in the peripheral blood of HIE newborns and explore the potential diagnostic biomarkers.

methodIn the present study, 24 newborns with HIE and 24 healthy controls were recruited. The plasma metabolites were measured by gas chromatography-mass spectrometry (GC-MS), and the raw data was standardized by the EigenMS method. Significantly differential metabolites were identified by multivariate statistics. Pathway enrichment was performed by bioinformatics analysis. Meanwhile, the diagnostic value of candidate biomarkers was evaluated.

resultThe multivariate statistical models showed a robust capacity to distinguish the HIE cases from the controls. 52 metabolites were completely annotated. 331 significantly changed pathways were enriched based on seven databases, including 33 overlapped pathways. Most of them were related to amino acid metabolism, energy metabolism, neurotransmitter biosynthesis, pyrimidine metabolism, the regulation of HIF by oxygen, and GPCR downstream signaling. 14 candidate metabolites showed great diagnostic potential on HIE. Among them, alpha-ketoglutaric acid has the potential to assess the severity of HIE in particular.

conclusionThe blood plasma metabolic profile could comprehensively reflect the metabolic disorders of the whole body under hypoxia-ischaemic injury. Several candidate metabolites may serve as promising biomarkers for the early diagnosis of HIE. Further validation based on large clinical samples and the establishment of guidelines for the clinical application of mass spectrometry data standardization methods are imperative in the future.

Indexed as

BiomarkersCase-Control StudiesCluster AnalysisComputational BiologyDatabases, FactualFemaleGas Chromatography-Mass SpectrometryGestational AgeHumansHypoxia-Ischemia, BrainInfant, NewbornMagnetic Resonance ImagingMaleMetabolomeMultivariate AnalysisNeonatal ScreeningBiomarkers

Identifiers

PMID34258280
PMCPMC8249136
OpenAlexW3176618717

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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.