{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T11:38:27Z","timestamp":1784029107415,"version":"3.55.0"},"reference-count":72,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2024,5,14]],"date-time":"2024-05-14T00:00:00Z","timestamp":1715644800000},"content-version":"vor","delay-in-days":134,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Diabetes Research"],"published-print":{"date-parts":[[2024,1]]},"abstract":"<jats:p><jats:bold>Objective:<\/jats:bold> This study is aimed at investigating diagnostic biomarkers associated with lipotoxicity and the molecular mechanisms underlying diabetic nephropathy (DN).<\/jats:p><jats:p><jats:bold>Methods:<\/jats:bold> The GSE96804 dataset from the Gene Expression Omnibus (GEO) database was utilized to identify differentially expressed genes (DEGs) in DN patients. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted using the DEGs. A protein\u2013protein interaction (PPI) network was established to identify key genes linked to lipotoxicity in DN. Immune infiltration analysis was employed to identify immune cells with differential expression in DN and to assess the correlation between these immune cells and lipotoxicity\u2010related hub genes. The findings were validated using the external dataset GSE104954. ROC analysis was performed to assess the diagnostic performance of the hub genes. The Gene set enrichment analysis (GSEA) enrichment method was utilized to analyze the key genes associated with lipotoxicity as mentioned above.<\/jats:p><jats:p><jats:bold>Result:<\/jats:bold> In this study, a total of 544 DEGs were identified. Among them, extracellular matrix (ECM), fatty acid metabolism, AGE\u2010RAGE, and PI3K\u2010Akt signaling pathways were significantly enriched. Combining the PPI network and lipotoxicity\u2010related genes (LRGS), LUM and ALB were identified as lipotoxicity\u2010related diagnostic biomarkers for DN. ROC analysis showed that the AUC values for LUM and ALB were 0.882 and 0.885, respectively. The AUC values for LUM and ALB validated in external datasets were 0.98 and 0.82, respectively. Immune infiltration analysis revealed significant changes in various immune cells during disease progression. Macrophages M2, mast cells activated, and neutrophils were significantly associated with all lipotoxicity\u2010related hub genes. These key genes were enriched in fatty acid metabolism and extracellular matrix\u2010related pathways.<\/jats:p><jats:p><jats:bold>Conclusion:<\/jats:bold> The identified lipotoxicity\u2010related hub genes provide a deeper understanding of the development mechanisms of DN, potentially offering new theoretical foundations for the development of diagnostic biomarkers and therapeutic targets related to lipotoxicity in DN.<\/jats:p>","DOI":"10.1155\/2024\/5550812","type":"journal-article","created":{"date-parts":[[2024,5,15]],"date-time":"2024-05-15T00:05:07Z","timestamp":1715731507000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Identification of Lipotoxicity\u2010Related Biomarkers in Diabetic Nephropathy Based on Bioinformatic 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