Evidence map›Paper›PMID 38307924›Full record

ArticleScientific reports2024

Determination of biomarker candidates for the placenta accreta spectrum by plasma proteomic analysis.

Rauf Melekoglu, Seyma Yasar, Cemil Colak, Murat Kasap, Umran Karabulut Dogan, Saim Yologlu, Ercan Yilmaz, Sherif Shazly

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
11.1field-weighted citation impact, top 2% 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

7 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Placenta accreta spectrum.Nature reviews. Disease primers · 2025
    Review
  5. Serum Markers of Abnormal Placental Attachment in Pregnant Women.Bulletin of experimental biology and medicine · 2025
    Article
  6. Review
  7. 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

8 authors at 4 institutions in 2 countries.

Rauf MelekogluDepartment of Obstetrics and Gynecology, Faculty of Medicine, Inonu University, 44280, Malatya, Turkey. rmelekoglu@gmail.com.ORCID 0000-0001-7113-6691
Seyma YasarDepartment of Biostatistics and Medical Informatics, Faculty of Medicine, Inonu University, 44280, Malatya, Turkey.ORCID 0000-0003-1300-3393
Cemil ColakDepartment of Biostatistics and Medical Informatics, Faculty of Medicine, Inonu University, 44280, Malatya, Turkey.ORCID 0000-0001-5406-098X
Murat KasapDepartment of Medical Biology, Faculty of Medicine, Kocaeli University, Kocaeli, Turkey.ORCID 0000-0001-8527-2096
Umran Karabulut DoganClinic of Obstetrics and Gynecology, Malatya Education and Research Hospital, Malatya, Turkey.ORCID 0000-0002-1935-3696
Saim YologluDepartment of Biostatistics and Medical Informatics, Faculty of Medicine, Inonu University, 44280, Malatya, Turkey.ORCID 0000-0002-9619-3462
Ercan YilmazDepartment of Obstetrics and Gynecology, Faculty of Medicine, Inonu University, 44280, Malatya, Turkey.ORCID 0000-0003-3821-4621
Sherif ShazlyDepartment of Obstetrics and Gynecology, Leeds Teaching Hospitals NHS Trust, Leeds, UK.ORCID 0000-0003-1062-9227
Inonu University · TRKocaeli Üniversitesi · TRLeeds Teaching Hospitals NHS Trust · GBMalatya Devlet Hastanesi · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Placenta accreta spectrum (PAS) presents a significant obstetric challenge, associated with considerable maternal and fetal-neonatal morbidity and mortality. Nevertheless, it is imperative to acknowledge that a noteworthy subset of PAS cases remains undetected until the time of delivery, thereby contributing to an augmented incidence of morbidity among the affected individuals. The delayed identification of PAS not only hinders timely intervention but also exacerbates the associated health risks for both the maternal and fetal outcomes. This underscores the urgency to innovate strategies for early PAS diagnosis. In this study, we aimed to explore plasma proteins as potential diagnostic biomarkers for PAS. Integrated transcriptome and proteomic analyses were conducted to establish a novel diagnostic approach. A cohort of 15 pregnant women diagnosed with PAS and delivering at Inonu University Faculty of Medicine between 01/04/2021 and 01/01/2023, along with a matched control group of 15 pregnant women without PAS complications, were enrolled. Plasma protein identification utilized enzymatic digestion and liquid chromatography-tandem mass spectrometry techniques. Proteomic analysis identified 228 plasma proteins, of which 85 showed significant differences (P < 0.001) between PAS and control cases. We refined this to a set of 20 proteins for model construction, resulting in a highly accurate classification model (96.9% accuracy). Notable associations were observed for proteins encoded by P01859 (Immunoglobulin heavy constant gamma 2), P02538 (Keratin type II cytoskeletal 6A), P29622 [Kallistatin (also known as Serpin A4)], P17900 (Ganglioside GM2 activator Calmodulin-like protein 5), and P01619 (Immunoglobulin kappa variable 3-20), with fold changes indicating their relevance in distinguishing PAS from control groups. In conclusion, our study has identified novel plasma proteins that could serve as potential biomarkers for early diagnosis of PAS in pregnant women. Further research and validation in larger PAS cohorts are necessary to determine the clinical utility and reliability of these proteomic biomarkers for diagnosing PAS.

Indexed as

Placenta AccretaBiomarkersBlood ProteinsFemaleHumansImmunoglobulinsInfant, NewbornPlacentaPregnancyProteomicsReproducibility of ResultsRetrospective StudiesBiomarkersBlood ProteinsImmunoglobulins

Identifiers

PMID38307924
PMCPMC10837117
OpenAlexW4391470560

What OpenQuestion holds

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LicenceCC BY
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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.