{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T05:01:11Z","timestamp":1780290071708,"version":"3.54.0"},"reference-count":74,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Endocrinol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Postmenopausal osteoporosis (PMO) is a prevalent metabolic bone disease wherein immune dysregulation and autophagy are critically involved. This study aimed to identify key genes linking immune cells and autophagy in PMO and construct a diagnostic model.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Autophagy-immune-related differentially expressed genes (DEGs) were identified by integrating limma analysis, WGCNA module genes, and autophagy-related genes (ARGs). Hub genes were screened via protein-protein interaction (PPI) network and statistical tests. A diagnostic model was built and validated. Functional enrichment (GSEA) and immune infiltration analysis (GSVA) were performed. Regulatory networks involving transcription factors (TFs) and microRNAs (miRNAs) were constructed. Drug prediction and single-cell RNA sequencing (scRNA-seq) analyses were conducted. An ovariectomized (OVX) mouse model was established to assess bone mineral density, serum biomarkers, and hub gene expression via RT-qPCR.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Three hub genes (CDK2, DDIT3, MAPK8) were identified. The diagnostic model exhibited high predictive accuracy (AUC\u00a0=\u00a00.91). GSEA indicated CDK2 and DDIT3 were associated with ligand-receptor interaction pathways. Hub genes correlated significantly with altered immune cell infiltration. Regulatory networks included multiple TFs and miRNAs. Drug prediction identified potential therapeutics targeting each hub gene. scRNA-seq highlighted bone marrow mesenchymal stem cells (BM MSCs) as a key site, with pseudotemporal analysis revealing dynamic hub gene expression during differentiation.\n                      <jats:italic>In vivo<\/jats:italic>\n                      , OVX mice showed reduced bone density, estradiol, and osteocalcin, elevated CTX-1, and increased MAPK8 and DDIT3 expression.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>An immune-autophagy-related diagnostic model based on DDIT3 and MAPK8 was developed and validated, offering new insights into PMO evaluation and therapeutic strategy.<\/jats:p>\n                  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