Comprehensive bioinformatic analysis reveals novel potential diagnostic biomarkers associated with monocytes in osteoporosis
Xianyun QiniD, Bo WeniD, Pan HeiD, Zetong Chen, Shengyun Tan, Zhiyou MaoiD
Abstract
Osteoporosis affects millions of women globally. In this study, we applied bioinformatics methods to screen for novel diagnostic biomarkers of osteoporosis in women using the GSE62402 and GSE56814 datasets. PCSK5, ZNF225, and H1FX were used to construct a diagnostic model. ROC, calibration, and decision curve analyses were performed to assess the diagnostic performance on the training (GSE56814) and external (GSE56815) datasets. The expression level of model genes was validated in GEO datasets. Furthermore, five transcription factors (ETS1, NOTCH1, MAZ, ERG, and FLI1) were identified as common upstream regulators of model genes. PCSK5, ZNF225, and H1FX serve as novel diagnostic biomarkers, providing new insights into the pathogenesis of and treatment strategies for osteoporosis in women.
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