Objective: We aimed to reveal a spatial proteomic and immune signature of kidney function regions in lupus nephritis (LN).
Material And Methods: The laser capture microdissection (LCM) was used to isolate the glomerulus, tubules, and interstitial of the kidney from paraffin samples. The data-independent acquisition (DIA) method was used to collect proteomics data. The bioinformatic analysis was performed.
Results: A total of 49,658 peptides and 4056 proteins were quantitated. Our results first showed that a high proportion of activated NK cells, naive B cells, and neutrophils in the glomerulus, activated NK cells in interstitial, and resting NK cells were accumulated in tubules in LN. The immune-related function analysis of differential expression proteins in different regions indicated that the glomerulus and interstitial were major sites of immune disturbance and regulation connected with immune response activation. Furthermore, we identified 7, 8, and 9 hub genes in LN's glomerulus, renal interstitial, and tubules. These hub genes were significantly correlated with the infiltration of immune cell subsets. We screened out ALB, CTSB, LCN2, A2M, CDC42, VIM, LTF, and CD14, which show higher performance as candidate biomarkers after correlation analysis with clinical indexes. The function within three regions of the kidney was analyzed. The differential expression proteins (DEGs) between interstitial and glomerulus were significantly enriched in the immune-related biological processes, and myeloid leukocyte-mediated immunity and cellular response to hormone stimulus. The DEGs between tubules and glomerulus were significantly enriched in cell activation and leukocyte-mediated immunity. While the DEGs between tubules and interstitial were enriched in response to lipid, antigen processing, and presentation of peptide antigen response to oxygen-containing compound, the results indicated a different function within kidney regions.
Conclusions: Collectively, we revealed spatial proteomics and immune signature of LN kidney regions by combined using LCM and DIA.
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| http://dx.doi.org/10.1007/s00011-023-01767-3 | DOI Listing |
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