Combined Use of Serum Uromodulin and eGFR to Estimate Mortality Risk - Yazdani, Babak; Delgado, Graciela E.; Scharnagl, Hubert; Krämer, Bernhard K.; Drexel, Heinz; März, Winfried; Scherberich, Jürgen E.; Leiherer, Andreas; Kleber, Marcus E. (Frontiers in Medicine, 2021)
Serum uromodulin (sUmod) shows a strong direct correlation with eGFR in patients with impaired kidney function and an inverse association with mortality. However, there are patients in whom only one of both markers is decreased. Therefore, we aimed to investigate the effect of marker discordance on mortality risk. sUmod and eGFR were available in 3057 participants of the Ludwigshafen Risk and Cardiovascular Health study and 529 participants of the VIVIT study. Both studies are monocentric prospective studies of patients that had been referred for coronary angiography. Participants were categorized into four groups according to the median values of sUmod (LURIC: 146 ng/ml, VIVIT: 156) and eGFR (LURIC: 84 ml/min/1.73m2, VIVIT: 87). In 945 LURIC participants both markers were high (UHGH), in 935 both were low (ULGL), in 589 only eGFR (UHGL), and in 582 only sUmod (ULGH) was low. After balancing the groups for cardiovascular risk factors, hazard ratios (95%CI) for all-cause mortality as compared to UHGH were 2.03 (1.63-2.52), 1.43 (1.13-1.81) and 1.32 (1.03-1.69 for ULGL, UHGL and ULGH, respectively. In VIVIT, HRs were 3.12 (1.38-7.08), 2.38 (1.01-5.61), and 2.06 (0.81-5.22). Adding uromodulin to risk prediction models that already included eGFR as a covariate slightly increased the Harrell’s C and significantly improved the AUC in LURIC. In UHGL patients, hypertension, heart failure and upregulation of the renin-angiotensin-aldosterone-system seem to be the driving forces of disease development, whereas in ULGH patients metabolic disturbances might be key drivers of increased mortality. In conclusion, SUmod/eGFR subgroups mirror distinct metabolic and clinical patterns. Assessing sUmod additionally to creatinine or cystatin C has the potential to allow a more precise risk modeling and might improve risk stratification.