In Diabetes ; h5-index 94.0
Diabetic kidney disease (DKD) is the leading cause of end-stage kidney disease (ESKD). Prognostic biomarkers reflective of underlying molecular mechanisms are critically needed for effective management of DKD. A three-marker panel was derived from a proteomics analysis of plasma samples by an unbiased machine learning approach from participants (N = 58) in the Clinical Phenotyping and Resource Biobank study. In combination with standard clinical parameters, this panel improved prediction of the composite outcome of ESKD or a 40% decline in glomerular filtration rate. The panel was validated in an independent group (N = 68), who also had kidney transcriptomic profiles. One marker, plasma angiopoietin 2 (ANGPT2), was significantly associated with outcomes in cohorts from the Cardiovascular Health Study (N = 3,183) and the Chinese Cohort Study of Chronic Kidney Disease (N = 210). Glomerular transcriptional angiopoietin/Tie (ANG-TIE) pathway scores, derived from the expression of 154 ANG-TIE signaling mediators, correlated positively with plasma ANGPT2 levels and kidney outcomes. Higher receptor expression in glomeruli and higher ANG-TIE pathway scores in endothelial cells corroborated potential functional effects in the kidney from elevated plasma ANGPT2 levels. Our work suggests that ANGPT2 is a promising prognostic endothelial biomarker with likely functional impact on glomerular pathogenesis in DKD.
Liu Jiahao, Nair Viji, Zhao Yi-Yang, Chang Dong-Yuan, Limonte Christine, Bansal Nisha, Fermin Damian, Eichinger Felix, Tanner Emily C, Bellovich Keith A, Steigerwalt Susan, Bhat Zeenat, Hawkins Jennifer J, Subramanian Lalita, Rosas Sylvia E, Sedor John R, Vasquez Miguel A, Waikar Sushrut S, Bitzer Markus, Pennathur Subramaniam, Brosius Frank C, De Boer Ian, Chen Min, Kretzler Matthias, Ju Wenjun
2022-Nov-04
