Background: Ambient fine particulate matter ≤ 2.5 µm (PM) air pollution exposure has been identified as a global health threat, the epidemiological evidence suggests that PM increased the risk of chronic kidney disease (CKD) among the diabetes mellitus (DM) patients. Despite the growing body of research on PM exposure, there has been limited investigation into its impact on the kidneys and the underlying mechanisms. Past studies have demonstrated that PM exposure can lead to lipid metabolism disorder, which has been linked to the development and progression of diabetic kidney disease (DKD).
Methods: In this study, db/db mice were exposed to different dosage PM for 8 weeks. The effect of PM exposure was analysis by assessment of renal function, pathological staining, immunohistochemical (IHC), quantitative real-time PCR (qPCR) and liquid chromatography with tandem mass spectrometry (LC-MS/MS) based metabolomic analyses.
Results: The increasing of Oil Red staining area and adipose differentiation related protein (ADRP) expression detected by IHC staining indicated more ectopic lipid accumulation in kidney after PM exposure, and the increasing of SREBP-1 and the declining of ATGL detected by IHC staining and qPCR indicated the disorder of lipid synthesisandlipolysis in DKD mice kidney after PM exposure. The expressions of high mobility group nucleosome binding protein 1 (HMGN1) and kidney injury molecule 1 (KIM-1) that are associated with kidney damage increased in kidney after PM exposure. Correlation analysis indicated that there was a relationship between HMGN1-KIM-1 and lipid metabolic markers. In addition, kidneys of mice were analyzed using LC-MS/MS based metabolomic analyses. PM exposure altered metabolic profiles in the mice kidney, including 50 metabolites. In conclusion the results of this study show that PM exposure lead to abnormal renal function and further promotes renal injury by disturbance of renal lipid metabolism and alter metabolic profiles.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10476618 | PMC |
http://dx.doi.org/10.7717/peerj.15856 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!