Integrated Single-cell RNA-seq and Bulk RNA-seq Identify Diagnostic Biomarkers for Postmenopausal Osteoporosis.

IF 3.5 4区 医学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY Current medicinal chemistry Pub Date : 2024-10-03 DOI:10.2174/0109298673343344240930054414
Hanyu Wang, Chong Peng, Guangbing Hu, Wenhao Chen, Yong Hu, Honglin Pi
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Abstract

Aim: We aimed to explore diagnostic biomarkers of postmenopausal osteoporosis (PMOP).

Background: PMOP brings enormous physical and economic burden to elderly women.

Objectives: This study aims to screen new biomarkers for osteoporosis, providing insights for early diagnosis and therapeutic targets of osteoporosis.

Methods: Weighted gene co-expression network analysis (WGCNA) was applied to identify osteoporosis-related hub genes. Single-cell transcriptomic atlas of osteoporosis was depicted and the heterogeneity of monocytes was analyzed, based on which the biomarkers for osteoporosis were screened. Gene set enrichment analysis (GSEA) was conducted on the biomarkers. The diagnostic model (nomogram) was established and evaluated based on the expression levels of biomarkers. Additionally, the transcription factor (TF) regulatory network was constructed to predict the potential TF and targeted miRNA of biomarkers. The drugs with significant correlation with biomarkers were identified by Spearman correlation analysis.

Results: We obtained 30 osteoporosis-associated hub genes. 9 cell types were identified, and the monocytes were subdivided to 4 subtypes. Three biomarkers, DHX29, LSM5, and UBE2V2, were screened. DHX29 and UBE2V2 were highly expressed in non-classical monocytes, while LSM5 exhibited the highest expression in other monocytes, followed by non-classical monocytes. GSEA indicated that osteoporosis may be correlated with vascular calcification and the biomarkers may be involved in the formation of immune cells. Then, nomogram was constructed and exhibited good robustness. In addition, MYC and SETDB1 were the shared IF in three biomarkers, which may play critical regulatory roles in the progression of osteoporosis. Moreover, 41, 49, and 68 drugs appeared significant correlations with DHX29, LSM5, and UBE2V2, respectively.

Conclusion: This study provided a basis for early diagnosis and targeted treatment of osteoporosis.

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整合单细胞 RNA-seq 和大容量 RNA-seq 发现绝经后骨质疏松症的诊断生物标记物
目的:我们旨在探索绝经后骨质疏松症(PMOP)的诊断生物标志物:背景:绝经后骨质疏松症给老年妇女带来了巨大的身体和经济负担:本研究旨在筛选骨质疏松症的新生物标志物,为骨质疏松症的早期诊断和治疗目标提供见解:方法:应用加权基因共表达网络分析(WGCNA)确定骨质疏松症相关的枢纽基因。描绘了骨质疏松症的单细胞转录组图谱,分析了单细胞的异质性,并在此基础上筛选出骨质疏松症的生物标志物。对生物标志物进行了基因组富集分析(GSEA)。根据生物标志物的表达水平,建立并评估了诊断模型(提名图)。此外,还构建了转录因子(TF)调控网络,以预测生物标志物的潜在 TF 和靶向 miRNA。通过斯皮尔曼相关性分析,确定了与生物标志物有明显相关性的药物:结果:我们获得了 30 个骨质疏松症相关的枢纽基因。结果:我们获得了 30 个骨质疏松症相关枢纽基因,确定了 9 种细胞类型,并将单核细胞细分为 4 个亚型。筛选出了三个生物标志物:DHX29、LSM5 和 UBE2V2。DHX29和UBE2V2在非经典单核细胞中高表达,而LSM5在其他单核细胞中表达最高,其次是非经典单核细胞。GSEA表明,骨质疏松症可能与血管钙化有关,而这些生物标志物可能参与了免疫细胞的形成。然后,构建了提名图,并显示出良好的稳健性。此外,MYC 和 SETDB1 是三个生物标志物的共同 IF,它们可能在骨质疏松症的进展过程中起着关键的调控作用。此外,41、49 和 68 种药物分别与 DHX29、LSM5 和 UBE2V2 呈显著相关:该研究为骨质疏松症的早期诊断和针对性治疗提供了依据。
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来源期刊
Current medicinal chemistry
Current medicinal chemistry 医学-生化与分子生物学
CiteScore
8.60
自引率
2.40%
发文量
468
审稿时长
3 months
期刊介绍: Aims & Scope Current Medicinal Chemistry covers all the latest and outstanding developments in medicinal chemistry and rational drug design. Each issue contains a series of timely in-depth reviews and guest edited thematic issues written by leaders in the field covering a range of the current topics in medicinal chemistry. The journal also publishes reviews on recent patents. Current Medicinal Chemistry is an essential journal for every medicinal chemist who wishes to be kept informed and up-to-date with the latest and most important developments.
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