Eicosanoids and Related Metabolites Associated with ESKD in a Community-Based Cohort

• Published in: Kidney360 Vol. 5; no. 1; pp. 57 - 64
• Main Authors: Surapaneni, Aditya L, Schlosser, Pascal, Rhee, Eugene P, Cheng, Susan, Jain, Mohit, Alotaiabi, Mona, Coresh, Josef, Grams, Morgan E
• Format: Journal Article
• Language: English
• Published: United States American Society of Nephrology 01.01.2024
• Subjects: Chronic Kidney Disease; Eicosanoids; Humans; Kidney Failure, Chronic; Original Investigation; Renal Insufficiency, Chronic
• ISSN: 2641-7650; 2641-7650
• DOI: 10.34067/KID.0000000000000334

Key Points High-throughput eicosanoid profiling can identify metabolites that may play a protective role in the development of kidney disease. In contrast to many other nonlipid metabolites, eicosanoid levels are minimally related with kidney filtration cross-sectionally. Background Eicosanoids are derivatives of polyunsaturated fatty acids and participate in the inflammatory response and the maintenance of endothelial function. Specific eicosanoids have been linked to various diseases, including hypertension and asthma, and may also reduce renal blood flow. A systematic investigation of eicosanoid-related metabolites and adverse kidney outcomes could identify key mediators of kidney disease and inform ongoing work in drug development. Methods Profiling of eicosanoid-related metabolites was performed in 9650 participants in the Atherosclerosis Risk in Communities Study (visit 2; mean age, 57 years). The associations between metabolite levels and the development of ESKD was investigated using Cox proportional hazards regression ( n =256 events; median follow-up, 25.5 years). Metabolites with statistically significant associations with ESKD were evaluated for a potential causal role using bidirectional Mendelian randomization techniques, linking genetic instruments for eicosanoid levels to genomewide association study summary statistics of eGFR. Results The 223 eicosanoid-related metabolites that were profiled and passed quality control (QC) were generally uncorrelated with eGFR in cross-sectional analyses (median Spearman correlation, −0.03; IQR, −0.05 to 0.002). In models adjusted for multiple covariates, including baseline eGFR, three metabolites had statistically significant associations with ESKD ( P value < 0.05/223). These included a hydroxyoctadecenoic acid, a dihydroxydocosapentaenoic acid, and arachidonic acid, with higher levels of the former two protective against ESKD and higher levels of arachidonic acid having a positive association with risk of ESKD. Mendelian randomization analyses suggested a causal role for the hydroxyoctadecenoic and arachidonic acid in determining eGFR. Spectral analysis identified the former metabolite as either 11-hydroxy-9-octadecenoic acid or 10-hydroxy-11-octadecenoic acid. Conclusions High-throughput eicosanoid profiling can identify metabolites that may play a protective role in the development of kidney disease.