Evidence map›Paper›PMID 37496029›Full record

ArticleJournal of orthopaedic surgery and research2023

Identification and evaluation of circulating exosomal miRNAs for the diagnosis of postmenopausal osteoporosis.

Zhibang Sun, Junjie Shi, Chenyang Yang, Xukun Chen, Jiaqi Chu, Jing Chen, Yuan Wang, Chenxin Zhu, Jinze Xu, Guozhen Tang and 1 more

Open access · goldAbstract read
In one paragraph

Article in Journal of orthopaedic surgery and research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.5field-weighted citation impact, top 17% 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

10 citing papers in PubMed, 10 citations in OpenAlex.

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  10. The MicroRNAs in the Pathophysiology of Osteoporosis.International journal of molecular sciences · 2024
    Review
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

11 authors at 2 institutions in 1 country.

Zhibang Sun *Department of Orthopedics, The Lu'an Affiliated Hospital of Anhui Medical University, Lu'an, People's Republic of China.
Junjie Shi *Department of Orthopedics, The Lu'an Affiliated Hospital of Anhui Medical University, Lu'an, People's Republic of China.
Chenyang Yang *Department of Orthopedics, The Lu'an Affiliated Hospital of Anhui Medical University, Lu'an, People's Republic of China.
Xukun ChenDepartment of Orthopedics, The Lu'an Affiliated Hospital of Anhui Medical University, Lu'an, People's Republic of China.
Jiaqi ChuDepartment of Orthopedics, The Lu'an Affiliated Hospital of Anhui Medical University, Lu'an, People's Republic of China.
Jing ChenDepartment of R&D, Echo Biotech Co., Ltd, Beijing, People's Republic of China.
Yuan WangDepartment of R&D, Echo Biotech Co., Ltd, Beijing, People's Republic of China.
Chenxin ZhuDepartment of Orthopedics, The Lu'an Affiliated Hospital of Anhui Medical University, Lu'an, People's Republic of China.
Jinze XuDepartment of Orthopedics, The Lu'an Affiliated Hospital of Anhui Medical University, Lu'an, People's Republic of China.
Guozhen TangDepartment of Orthopedics, The Lu'an Affiliated Hospital of Anhui Medical University, Lu'an, People's Republic of China.
Song ShaoDepartment of Orthopedics, The Lu'an Affiliated Hospital of Anhui Medical University, Lu'an, People's Republic of China. 1255319122@qq.com.
Anhui Medical University · CNSinovac Biotech · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPostmenopausal osteoporosis (PMOP) is a common condition that leads to a loss of bone density and an increased risk of fractures in women. Recent evidence suggests that exosomal miRNAs are involved in regulating bone development and osteogenesis. However, exosomal miRNAs as biomarkers for PMOP diagnosis have not been systematically evaluated. In this study, we aim to identify PMOP-associated circulating exosomal miRNAs and evaluate their diagnostic performance.

methodsWe performed next-generation sequencing and bioinformatics analysis of plasma exosomal miRNAs from 12 PMOP patients and 12 non-osteoporosis controls to identify PMOP-associated exosomal miRNAs, and then validated them in an independent natural community cohort with 26 PMOP patients and 21 non-osteoporosis controls. Exosomes were isolated with the size exclusion chromatography method from the plasma of elder postmenopausal women. The plasma exosomal miRNA profiles were characterized in PMOP paired with controls with next-generation sequencing. Potential plasma exosomal miRNAs were validated by qRT-PCR in the validation cohort, and their performance in diagnosing PMOP was systematically evaluated with the receiver operating characteristic curve.

resultsTwenty-seven miRNAs were identified as differentially expressed in PMOP versus controls in sequencing data, of which six exosomal miRNAs (miR-196-5p, miR-224-5p, miR320d, miR-34a-5p, miR-9-5p, and miR-98-5p) were confirmed to be differentially expressed in PMOP patients by qRT-PCR in the validation cohort. The three miRNAs combination (miR-34a-5p + miR-9-5p + miR-98-5p) demonstrated the best diagnostic performance, with an AUC = 0.734. In addition, the number of pregnancies was found to be an independent risk factor that can improve the performance of exosomal miRNAs in diagnosing PMOP.

conclusionsThese results suggested that the plasma exosomal miRNAs had the potential to serve as noninvasive diagnostic biomarkers for PMOP.

Indexed as

ExosomesMicroRNAsOsteoporosis, PostmenopausalAgedBiomarkersFemaleHumansOsteogenesisBiomarkersMicroRNAsMIRN224 microRNA, humanMIRN98 microRNA, humanDiagnostic efficacyMiRNANumber of pregnanciesPlasma exosomesPostmenopausal osteoporosis

Identifiers

PMID37496029
PMCPMC10373377
OpenAlexW4385268701

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.