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Identification of Long Non‐Coding RNA as Potential Biomarkers for the Diagnosis of Postmenopausal Osteoporosis

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Objective: To explore the feasibility and clinical application value of differentially expressed lncRNA in human peripheral blood mononuclear cell (PBMC) as a potential biomarker for postmenopausal osteoporosis (PMOP).Methods: In this study, a case‐control trial was conducted to collect a total of 10 samples of PBMC from PMOP and postmenopausal‐without‐osteoporosis (n‐PMOP) patients. RNA sequencing was performed to profile lncRNA and mRNA expression, identifying differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) based on the criteria of fold change (FC) ≥ 2 and p value < 0.05; GO and KEGG enrichment analyses were carried out for differentially expressed genes (DEGs); 10 DElncRNAs and 20 DEmRNAs were selected for lncRNA–mRNA correlation analysis and Circos plot to screen out the lncRNAs that could be used as potential biomarkers. Then, ROC curve analysis was used to evaluate the diagnostic and therapeutic value of DElncRNAs as clinical potential diagnostic markers for PMOP. Afterward, 20 PMOP and 20 n‐PMOP patients were reincluded and quantitative real‐time PCR (qRT‐PCR) was performed to externally validate the screening of lncRNAs.Result: (1) Compared with n‐PMOP, there were 1978 DElncRNAs and 1024 DEmRNAs in PMOP patients. (2) Bioinformatics technology was used to analyze the DEGs, and the GO analysis showed that the activities of the gene products were mainly related to the protein binding, membrane, plasma membrane, and extracellular region. The results of KEGG enrichment analysis showed that it was mainly enriched in PI3K‐Akt signaling pathway, metabolic pathways, and pathways in cancer and focal adhesion. (3) The correlation network and Circos plot further indicated the implication of DElncRNA expression profiles in PMOP via interactions with DEmRNAs. Among them, lncRNA RAB37, lncRNA BEGAIN, and lncRNA ZNF529 had the highest number of nodes, totaling 19, possibly potential diagnostic markers for PMOP. (4) The diagnostic efficacy of the screened lncRNAs was analyzed by ROC curve. The results showed an the area under the ROC curve (AUC) of 0.960 for lncRNA RAB37, 1.000 for lncRNA ZNF529, 1.000 for lncRNA BEGAIN. (5) The qPCR results showed that lncRNA RAB37, lncRNA ZNF529, and lncRNA BEGAIN were all significantly correlated with the occurrence of PMOP (p < 0.05). However, the significant difference of lncRNA ZNF529 was superior to that of other lncRNAs.Conclusion: The lncRNA ZNF529 is significantly overexpressed in PBMC in PMOP, and bioinformatics analysis and validation experiments indicate that it is closely associated with PMOP; thus, it is expected to be a potential diagnostic marker for PMOP.
Title: Identification of Long Non‐Coding RNA as Potential Biomarkers for the Diagnosis of Postmenopausal Osteoporosis
Description:
Objective: To explore the feasibility and clinical application value of differentially expressed lncRNA in human peripheral blood mononuclear cell (PBMC) as a potential biomarker for postmenopausal osteoporosis (PMOP).
Methods: In this study, a case‐control trial was conducted to collect a total of 10 samples of PBMC from PMOP and postmenopausal‐without‐osteoporosis (n‐PMOP) patients.
RNA sequencing was performed to profile lncRNA and mRNA expression, identifying differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) based on the criteria of fold change (FC) ≥ 2 and p value < 0.
05; GO and KEGG enrichment analyses were carried out for differentially expressed genes (DEGs); 10 DElncRNAs and 20 DEmRNAs were selected for lncRNA–mRNA correlation analysis and Circos plot to screen out the lncRNAs that could be used as potential biomarkers.
Then, ROC curve analysis was used to evaluate the diagnostic and therapeutic value of DElncRNAs as clinical potential diagnostic markers for PMOP.
Afterward, 20 PMOP and 20 n‐PMOP patients were reincluded and quantitative real‐time PCR (qRT‐PCR) was performed to externally validate the screening of lncRNAs.
Result: (1) Compared with n‐PMOP, there were 1978 DElncRNAs and 1024 DEmRNAs in PMOP patients.
(2) Bioinformatics technology was used to analyze the DEGs, and the GO analysis showed that the activities of the gene products were mainly related to the protein binding, membrane, plasma membrane, and extracellular region.
The results of KEGG enrichment analysis showed that it was mainly enriched in PI3K‐Akt signaling pathway, metabolic pathways, and pathways in cancer and focal adhesion.
(3) The correlation network and Circos plot further indicated the implication of DElncRNA expression profiles in PMOP via interactions with DEmRNAs.
Among them, lncRNA RAB37, lncRNA BEGAIN, and lncRNA ZNF529 had the highest number of nodes, totaling 19, possibly potential diagnostic markers for PMOP.
(4) The diagnostic efficacy of the screened lncRNAs was analyzed by ROC curve.
The results showed an the area under the ROC curve (AUC) of 0.
960 for lncRNA RAB37, 1.
000 for lncRNA ZNF529, 1.
000 for lncRNA BEGAIN.
(5) The qPCR results showed that lncRNA RAB37, lncRNA ZNF529, and lncRNA BEGAIN were all significantly correlated with the occurrence of PMOP (p < 0.
05).
However, the significant difference of lncRNA ZNF529 was superior to that of other lncRNAs.
Conclusion: The lncRNA ZNF529 is significantly overexpressed in PBMC in PMOP, and bioinformatics analysis and validation experiments indicate that it is closely associated with PMOP; thus, it is expected to be a potential diagnostic marker for PMOP.

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