Urinary 20-HETE: A prospective Non-Invasive prognostic and diagnostic marker for diabetic kidney disease.

Introduction: The identification and validation of a non-invasive prognostic marker for early detection of diabetic kidney disease (DKD) can lead to substantial improvement in therapeutic decision-making.
Objectives: The main objective of this study is to assess the potential role of the arachidonic acid (AA) metabolite 20-hydroxyeicosatetraenoic (20-HETE) in predicting the incidence and progression of DKD.
Methods: Healthy patients and patients with diabetes were recruited from the Hamad General Hospital in Qatar, and urinary 20-HETE levels were measured. Data analysis was done using the Statistical Package for Social Sciences (SPSS).
Results: Our results show that urinary 20-HETE-to-creatinine (20-HETE/Cr) ratios were significantly elevated in patients with DKD when compared to patients with diabetes who did not exhibit clinical signs of kidney injury (p < 0.001). This correlation was preserved in the multivariate linear regression accounting for age, diabetes, family history of kidney disease, hypertension, dyslipidemia, stroke and metabolic syndrome. Urinary 20-HETE/Cr ratios were also positively correlated with the severity of kidney injury as indicated by albuminuria levels (p < 0.001). A urinary 20-HETE/Cr ratio of 4.6 pmol/mg discriminated between the presence and absence of kidney disease with a sensitivity of 82.2 % and a specificity of 67.1%. More importantly, a 10-unit increase in urinary 20-HETE/Cr ratio was tied to a 10-fold increase in the risk of developing DKD, suggesting a 20-HETE prognostic efficiency.
Conclusion: Taken together, our results suggest that urinary 20-HETE levels can potentially be used as non-invasive diagnostic and prognostic markers for DKD.
Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2022. Production and hosting by Elsevier B.V.)