Identification of Spatial Specific Lipid Metabolic Signatures in Long-Standing Diabetic Kidney Disease

<b>Background:</b> Diabetic kidney disease (DKD) is a major complication of diabetes leading to kidney failure. <b>Methods:</b> This study investigates lipid metabolism profiles of long-standing DKD (LDKD, diabetes duration > 10 years) by integrative analysis of available single-cell RNA sequencing and spatial multi-omics data (focusing on spatial continuity samples) from the Kidney Precision Medicine Project. <b>Results:</b> Two injured cell types, an injured thick ascending limb (iTAL) and an injured proximal tubule (iPT), were identified and significantly elevated in LDKD samples. Both iTAL and iPT exhibit increased lipid metabolic and biosynthetic activities and decreased lipid and fatty acid oxidative processes compared to TAL/PT cells. Notably, compared to PT, iPT shows significant upregulation of specific injury and fibrosis-related genes, including <i>FSHR</i> and <i>BMP7</i>. Meanwhile, comparing iTAL to TAL, inflammatory-related genes such as <i>ANXA3</i> and <i>IGFBP2</i> are significantly upregulated. Furthermore, spatial metabolomics analysis reveals regionally distributed clusters in the kidney and notably differentially expressed lipid metabolites, such as triglycerides, glycerophospholipids, and sphingolipids, particularly pronounced in the inner medullary regions. <b>Conclusions:</b> These findings provide an integrative description of the lipid metabolism landscape in LDKD, highlighting injury-associated cellular processes and potential molecular mechanisms.