Dataset Information

Identification of MiR-223 Associated with Diagnosis in Ectopic Pregnancy.

ABSTRACT:

Background

In this study, we conducted an integrated study of the diagnostic value of MiR-223 in ectopic pregnancy (EP).

Methods

We used GSE44731 downloaded from GEO and GEO2R to identify differentially expressed miRNA. The hub genes corresponding to the differential miRNA were then identified by using the Xiantao academic tool, GO (Gene Ontology), and KEGG (Kyoto Encyclopedia of Genes and Genomes). Afterward, we used the miEAA database to perform gene set enrichment analysis (GSEA) of differential miRNA, and used Xiantao academic tools again to conduct the ceRNA network based on the target genes. Protein-protein interaction (PPI) network construction and lncRNA of hub miRNA target genes were then predicted by the starbase database. For validation, the villus tissue from intrauterine pregnancy and tubal pregnancy was collected and assayed by qPCR.

Results

In total 19 differentially expressed miRNAs were screened out, of which MiR-223 had a relatively clear diagnostic significance. Hub genes were enriched and analyzed by GO, KEGG, and GSEA, and the results showed that regulation of NF-κB and other signaling pathways are primarily enriched in ectopic pregnancy. We also obtained 215 key genes from PPI analysis. Our ceRNA analysis indicated that LRRC75A-AS1 and PITPNA-AS1 were associated with MiR-223, and the expression of MiR-223 in qPCR was significantly high in tubal pregnancy group.

Conclusion

We found that MiR-223 can be used in the diagnosis of EP. Our findings provide valuable information and direction for future research into novel targets for EP diagnosis.

SUBMITTER: Qiu J

PROVIDER: S-EPMC10314770 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Publications

Identification of MiR-223 Associated with Diagnosis in Ectopic Pregnancy.

Qiu Jiahan J Chen Jiaxun J Deng Gaopi G Yuan Shuo S

International journal of general medicine 20230627

<h4>Background</h4>In this study, we conducted an integrated study of the diagnostic value of MiR-223 in ectopic pregnancy (EP).<h4>Methods</h4>We used GSE44731 downloaded from GEO and GEO2R to identify differentially expressed miRNA. The hub genes corresponding to the differential miRNA were then identified by using the Xiantao academic tool, GO (Gene Ontology), and KEGG (Kyoto Encyclopedia of Genes and Genomes). Afterward, we used the miEAA database to perform gene set enrichment analysis (GSE ...[more]

PMID: 37398511

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Project description:BackgroundDifferentiating between a normal intrauterine pregnancy (IUP) and abnormal conditions including early pregnancy loss (EPL) or ectopic pregnancy (EP) is a major clinical challenge in early pregnancy. Currently, serial β-human chorionic gonadotropin (β-hCG) and progesterone are the most commonly used plasma biomarkers for evaluating pregnancy prognosis when ultrasound is inconclusive. However, neither biomarker can predict an EP with sufficient and reproducible accuracy. Hence, identification of new plasma biomarkers that can accurately diagnose EP would have great clinical value.MethodsPlasma was collected from a discovery cohort of 48 consenting women having an IUP, EPL, or EP. Samples were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) followed by a label-free proteomics analysis to identify significant changes between pregnancy outcomes. A panel of 14 candidate biomarkers were then verified in an independent cohort of 74 women using absolute quantitation by targeted parallel reaction monitoring mass spectrometry (PRM-MS) which provided the capacity to distinguish between closely related protein isoforms. Logistic regression and Lasso feature selection were used to evaluate the performance of individual biomarkers and panels of multiple biomarkers to predict EP.ResultsA total of 1391 proteins were identified in an unbiased plasma proteome discovery. A number of significant changes (FDR ≤ 5%) were identified when comparing EP vs. non-EP (IUP + EPL). Next, 14 candidate biomarkers (ADAM12, CGA, CGB, ISM2, NOTUM, PAEP, PAPPA, PSG1, PSG2, PSG3, PSG9, PSG11, PSG6/9, and PSG8/1) were verified as being significantly different between EP and non-EP in an independent cohort (FDR ≤ 5%). Using logistic regression models, a risk score for EP was calculated for each subject, and four multiple biomarker logistic models were identified that performed similarly and had higher AUCs than models with single predictors.ConclusionsOverall, four multivariable logistic models were identified that had significantly better prediction of having EP than those logistic models with single biomarkers. Model 4 (NOTUM, PAEP, PAPPA, ADAM12) had the highest AUC (0.987) and accuracy (96%). However, because the models are statistically similar, all markers in the four models and other highly correlated markers should be considered in further validation studies.

Dataset Information

Identification of MiR-223 Associated with Diagnosis in Ectopic Pregnancy.

Background

Methods

Results

Conclusion

Publications

Identification of MiR-223 Associated with Diagnosis in Ectopic Pregnancy.

Similar Datasets

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