Tubular Secretion and Estimated GFR Decline in the Jackson Heart Study

Kidney Outcomes and Trajectories of Tubular Injury and Function in Critically Ill Persons with and without Coronavirus-2019

Background

Coronavirus disease-2019 (COVID-19) may injure the kidney tubules via activation of inflammatory host responses and/or direct viral infiltration. Most studies of kidney injury in COVID-19 lacked contemporaneous controls or measured kidney biomarkers at a single time point. To better understand mechanisms of AKI in COVID-19, we compared kidney outcomes and trajectories of tubular injury, viability, and function in prospectively enrolled critically ill adults with and without COVID-19.

Methods

The COVID-19 Host Response and Outcomes (CHROME) study prospectively enrolled patients admitted to intensive care units in Washington state with symptoms of lower respiratory tract infection, determining COVID-19 status by nucleic acid amplification on arrival. We evaluated major adverse kidney events (MAKE) defined as a doubling of serum creatinine, kidney replacement therapy, or death, in 330 patients after inverse probability weighting. In the 181 patients with available biosamples, we determined trajectories of urine kidney injury molecule-1 (KIM-1) and epithelial growth factor (EGF), and urine:plasma ratios of endogenous markers of tubular secretory clearance.

Results

At ICU admission, mean age was 55±16 years; 45% required mechanical ventilation; and mean serum creatinine concentration was 1.1 mg/dL. COVID-19 was associated with a 70% greater incidence of MAKE (95% CI 1.05, 2.74) and a 741% greater incidence of KRT (95% CI 1.69, 32.41). The biomarker cohort had a median of three follow-up measurements. Urine EGF, secretory clearance ratios, and eGFR increased over time in the COVID-19 negative group but remained unchanged in the COVID-19 positive group. In contrast, urine KIM-1 concentrations did not significantly change over the course of the study in either group.

Conclusions

Among critically ill adults, COVID-19 is associated with a more protracted course of proximal tubular dysfunction.

Predicting complex kidney drug handling using a physiologically-based pharmacokinetic model informed by biomarker-estimated secretory clearance and blood flow

Kidney function-adjusted drug dosing is currently based solely on the estimated glomerular filtration rate (GFR), however, kidney drug handling is accomplished by a combination of filtration, tubular secretion, and re-absorption. Mechanistic physiologically-based pharmacokinetic (PBPK) models recapitulate anatomic compartments to predict elimination from estimated perfusion, filtration, secretion, and re-absorption, but clinical applications are limited by a lack of empiric individual-level measurements of these functions. We adapted and validated a PBPK model to predict drug clearance from individual biomarker-based estimates of kidney perfusion and secretory clearance. We estimated organic anion transporter-mediated secretion via kynurenic acid clearance and kidney blood flow (KBF) via isovalerylglycine clearance in human participants, incorporating these measurements with GFR into the model to predict kidney drug clearance. We compared measured and model-predicted clearances of administered tenofovir and oseltamivir, which are cleared by both filtration and secretion. There were 27 outpatients (age 55 ± 15 years, mean iohexol-GFR [iGFR] 76 ± 31 mL/min/1.73 m2 ) in this drug clearance study. The mean observed and mechanistic model-predicted tenofovir clearances were 169 ± 102 mL/min and 163 ± 80 mL/min, respectively; estimated mean error of the mechanistic model was 37.1 mL/min (95% confidence interval [CI]: 24-52.9), compared to a mean error of 41.8 mL/min (95% CI: 25-61.6) from regression model. The mean observed and model-predicted oseltamivir carboxylate clearances were 183 ± 104 mL/min and 179 ± 89 mL/min, respectively; estimated mean error of the mechanistic model was 42.9 mL/min (95% CI: 29.7-56.4), versus error of 48.1 mL/min (95% CI: 31.2-67.3) from the regression model. Individualized estimates of tubular secretion and KBF improved the accuracy of PBPK model-predicted tenofovir and oseltamivir kidney clearances, suggesting the potential for biomarker-informed measures of kidney function to refine personalized drug dosing.