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To identify DKD biomarkers and explore autophagy\u2010related mechanisms to find potential therapeutic targets for DKD treatment.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>After standardizing and analyzing the GSE142025 and Merged_GSE47183_GSE32591 datasets, DKD\u2010related transcriptional changes (DEGs) were identified using computational methods, volcano plots, and heatmaps. Functional enrichment analysis of GO and KEGG pathways explored the role of autophagy\u2010related genes. Key genes were identified through a PPI network, and potential DKD biomarkers were selected using machine learning. ROC curve analysis evaluated the biomarkers\u2019 diagnostic effectiveness. qPCR and immunohistochemical staining confirmed biomarker expression in DKD mouse kidneys. snRNA\u2010seq identified cell\u2010specific transcriptional profiles and signaling networks. Pseudotemporal analysis highlighted DKD\u2010related PCT cell dynamics.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>This study showed autophagy\u2010related gene enrichment in pathways like inflammatory response and TNF\/NF\u2010\u03baB signaling. Four biomarkers (COL1A2, CSF1R, PTPRC, and TYROBP) showed diagnostic potential for DKD. Immune cell infiltration analysis revealed differences between DKD and control groups. qPCR and staining indicated significant upregulation of these biomarkers. snRNA\u2010seq identified cell clusters and DEGs, with altered signaling pathways and PCT cell communication. Network centrality analysis highlighted the differing roles of PCT in cell communication between control and DKD groups. Pseudotime trajectory analysis and BEAM revealed potential regulatory mechanisms in PCT cell differentiation and development in DKD.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This study offers new insights into DKD biomarkers and autophagy\u2010related mechanisms, suggesting potential therapeutic targets and laying the groundwork for future research and treatment strategies.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1155\/jdr\/3768039","type":"journal-article","created":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T11:01:31Z","timestamp":1775559691000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Screening Autophagy\u2010Related DKD Biomarkers Based on Bulk RNA and Single\u2010Cell Analysis and Uncovering Their Regulatory Mechanisms in DKD Renal 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