Comprehensive Analysis of Fatty Acid Metabolism in Diabetic Nephropathy from the Perspective of Immune Landscapes, Diagnosis and Precise Therapy

Enyi Zhu; Ming Zhong; Tiantian Liang; Yu Liu; Keping Wu; Zhijuan Zhang; Shuping Zhao; Hui Guan; Jiasi Chen; Li-Zhen Zhang; Yimin Zhang

doi:10.2147/JIR.S440374

Comprehensive Analysis of Fatty Acid Metabolism in Diabetic Nephropathy from the Perspective of Immune Landscapes, Diagnosis and Precise Therapy

J Inflamm Res. 2024 Feb 3:17:693-710. doi: 10.2147/JIR.S440374. eCollection 2024.

Authors

Enyi Zhu^#^{1

2}, Ming Zhong^#³, Tiantian Liang^#⁴, Yu Liu^#³, Keping Wu^{1

2}, Zhijuan Zhang^{1

2}, Shuping Zhao^{1

2}, Hui Guan⁵, Jiasi Chen⁶, Li-Zhen Zhang⁷, Yimin Zhang^{1

2}

Affiliations

¹ The Division of Nephrology, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangzhou, Guangdong, 510000, People's Republic of China.
² Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangzhou, Guangdong, 510000, People's Republic of China.
³ Department of Nephrology, Center of Kidney and Urology, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, Guangdong, 517108, People's Republic of China.
⁴ Nephrology Division, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, 510630, People's Republic of China.
⁵ Department of Radiation Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450000, People's Republic of China.
⁶ Department of Nephrology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, 510030, People's Republic of China.
⁷ Department of Urology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, 510080, People's Republic of China.

^# Contributed equally.

Abstract

Objective: Diabetic nephropathy (DN) represents the principal cause of end-stage renal diseases worldwide, lacking effective therapies. Fatty acid (FA) serves as the primary energy source in the kidney and its dysregulation is frequently observed in DN. Nevertheless, the roles of FA metabolism in the occurrence and progression of DN have not been fully elucidated.

Methods: Three DN datasets (GSE96804/GSE30528/GSE104948) were obtained and combined. Differentially expressed FA metabolism-related genes were identified and subjected to DN classification using "ConsensusClusterPlus". DN subtypes-associated modules were discovered by "WGCNA", and module genes underwent functional enrichment analysis. The immune landscapes and potential drugs were analyzed using "CIBERSORT" and "CMAP", respectively. Candidate diagnostic biomarkers of DN were screened using machine learning algorithms. A prediction model was constructed, and the performance was assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). The online tool "Nephroseq v5" was conducted to reveal the clinical significance of the candidate diagnostic biomarkers in patients with DN. A DN mouse model was established to verify the biomarkers' expression.

Results: According to 39 dysregulated FA metabolism-related genes, DN samples were divided into two molecular subtypes. Patients in Cluster B exhibited worse outcomes with a different immune landscape compared with those in Cluster A. Ten potential small-molecular drugs were predicted to treat DN in Cluster B. The diagnostic model based on PRKAR2B/ANXA1 was created with ideal predictive values in early and advanced stages of DN. The correlation analysis revealed significant association between PRKAR2B/ANXA1 and clinical characteristics. The DN mouse model validated the expression patterns of PRKAR2B/ANXA1.

Conclusion: Our study provides new insights into the role of FA metabolism in the classification, immunological pathogenesis, early diagnosis, and precise therapy of DN.

Keywords: diabetic nephropathy; diagnostic model; fatty acid metabolism; immune landscape; molecular subtypes; pharmacotherapy.

Grants and funding

This study was supported by grants from Guangdong Basic and Applied Basic Research Foundation (2020A1515111077) and China Postdoctoral Science Foundation Funded Project (2021M693672).