Osteoporosis disproportionately affects older women, yet gender differences in human osteoblasts remain unexplored. Identifying mechanisms and biomarkers of osteoporosis will enable the development of preventative and therapeutic approaches. Transcriptome data of 187 osteoblast samples from men and women were compared. Differentially expressed genes (DEGs) were identified, and weighted gene co-expression network analysis (WGCNA) was used to discover co-expressed modules. Enrichment analysis was performed to annotate DEGs. Preservation analysis determined whether modules and pathways were similar between genders. Blood methylation, transcriptome data, mouse phenotype data, and drug treatment data were utilized to identify key osteoporosis genes. We identified 1460 DEGs enriched in immune response, neurogenesis, and GWAS osteoporosis-related genes. WGCNA uncovered 8 modules associated with immune response, development, collagen metabolism, mitochondrion, and amino acid synthesis. Preservation analysis indicated modules and pathways were generally similar between genders. Incorporating GWAS and mouse phenotype data revealed 9 key genes, including GMDS, SMOC2, SASH1, MMP2, AHCYL1, ARRDC2, IGHMBP2, ATP6V1A, and CTSK. These genes were differentially methylated in patient blood and differentiated high and low bone mineral density patients in pre- and postmenopausal women. Denosumab treatment in postmenopausal women down-regulated 6 key genes, up-regulated T cell proportions, and down-regulated fibroblast proportion. qRT-PCR was used to confirm the genes in postmenopausal women. We identified 9 key osteoporosis genes by comparing the transcriptome of osteoblasts in women and men. Our findings' clinical implications were confirmed by multi-omics data and qRT-PCR, and our study provides novel biomarkers and therapeutic targets for osteoporosis diagnosis and treatment.

骨质疏松症对老年女性的影响尤为严重，但人类成骨细胞的性别差异仍未得到探索。确定骨质疏松症的机制和生物标志物将有助于开发预防和治疗方法。比较了来自男性和女性的 187 份成骨细胞样本的转录组数据。鉴定差异表达基因（DEG），并使用加权基因共表达网络分析（WGCNA）来发现共表达模块。进行富集分析来注释 DEG。保存分析确定模块和途径在性别之间是否相似。利用血液甲基化、转录组数据、小鼠表型数据和药物治疗数据来识别关键的骨质疏松症基因。我们鉴定了 1460 个富含免疫反应、神经发生和 GWAS 骨质疏松相关基因的 DEG。WGCNA 发现了与免疫反应、发育、胶原代谢、线粒体和氨基酸合成相关的 8 个模块。保存分析表明，性别之间的模块和途径通常相似。结合 GWAS 和小鼠表型数据揭示了 9 个关键基因，包括 GMDS、SMOC2、SASH1、MMP2、AHCYL1、ARRDC2、IGHMBP2、ATP6V1A 和 CTSK。这些基因在患者血液中存在差异甲基化，并区分绝经前和绝经后女性的高骨密度和低骨密度患者。绝经后女性的狄诺塞麦治疗下调了 6 个关键基因，上调了 T 细胞比例，下调了成纤维细胞比例。qRT-PCR 用于确认绝经后女性的基因。我们通过比较女性和男性成骨细胞的转录组，确定了 9 个关键的骨质疏松症基因。我们的研究结果的临床意义得到了多组学数据和qRT-PCR的证实，我们的研究为骨质疏松症的诊断和治疗提供了新的生物标志物和治疗靶点。