Alterations of Proximal Tubular Secretion in Autosomal Dominant Polycystic Kidney Disease

Study Populations: The Mid-Atlantic Autosomal Dominant Polycystic Kidney Disease Cohort

The Mid-Atlantic Autosomal Dominant Polycystic Kidney Disease Cohort is a prospective study of adults with ADPKD. From 2013 to 2016, the cohort enrolled 132 participants from the Baltimore PKD Center at the University of Maryland. The diagnosis of ADPKD was confirmed on the basis of modified Pei–Ravine criteria (9). Eligibility criteria were age >18 years old and eGFR˃15 ml/min per 1.73 m². Major exclusions included prior kidney transplantation, pregnancy, and uncontrolled diabetes. Each participant provided a serum and spot urine sample after an overnight fast on the morning of their study visit. A subset of 112 study participants underwent abdominal magnetic resonance imaging (MRI) for determination of total kidney volume by a radiologist who was blinded to other study characteristics. For the purpose of this study, we excluded three participants who had missing urine albumin measurements and one participant who had a missing urine sample. We further excluded two participants with ADPKD who had implausibly high fractional excretions (>10) of any secretory solute: one participant had cinnamoylglycine fractional excretion of 14.7, and another participant had isovalerylgycine fractional excretion of 14.8, likely due to measurement error. Our final cohort consisted of 126 participants with ADPKD (Figure 1). All participants provided informed consent, and the institutional review board of the University of Maryland approved the study.

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Figure 1.

Participant inclusions and exclusions by study cohort. ADPKD, autosomal dominant polycystic kidney disease.

Control Populations

We chose two control populations on the basis of the level of eGFR (Figure 1). For patients with ADPKD who had an eGFR calculated with the Chronic Kidney Disease Epidemiology Collaboration equation (eGFR_CKD-EPI) ≥90 ml/min per 1.73 m² (n=31), we selected a control population of 30 healthy individuals, all with eGFR≥90 ml/min per 1.73 m², from a previously completed dietary trial (10,11). Trial eligibility criteria were a body mass index (BMI) =28–33 kg/m² and no prior history of cardiovascular disease, diabetes mellitus, active smoking, or alcohol abuse. During the baseline trial visit, participants provided a 24-hour urine collection and multiple blood samples during the same time period. We excluded four trial participants who had missing urine data and one participant who had evidence of an overcollected urine sample on the basis of urinary creatinine excretion (12), leaving a final cohort of 25 healthy participants for comparison. For each participant, we used the three fasting blood samples obtained at 8 a.m., 12 p.m., and 5:30 p.m.; 8 a.m. blood samples was missing for three participants.

For patients with ADPKD who had an eGFR<90 ml/min per 1.73 m² (median eGFR =110 ml/min per 1.73 m²; interquartile range, 103–120 ml/min per 1.73 m²), we selected a control population of general patients with CKD and without ADPKD from the Seattle Kidney Study (SKS), a prospective study of 691 patients with CKD recruited from outpatient nephrology clinics in Seattle, Washington. Eligibility criteria for the SKS were age >18 years old and CKD of any stage not requiring dialysis. Major exclusions were kidney transplantation or the expectation of starting RRT within 3 months. For purposes of this study, we selected 298 SKS participants who provided a timed collection of urine sample collected continuously during the night before their outpatient study visit (mean collection time =12.8±3.5 hours) and a fasting morning blood sample during morning of their study visit. We further excluded four SKS participants with a suspected clinical diagnosis of ADPKD on the basis of review of outpatient clinic notes, 19 participants with eGFR_CKD-EPI≥90 ml/min per 1.73 m², 24 participants whose timed urine samples were suspected to be under- or overcollected on the basis of urinary creatinine excretion (12), and 21 participants whose blood samples were nonfasting, leaving 230 eligible participants for matching. We then performed 1:1 matching of ADPKD cohort members to eligible SKS participants on the basis of eGFR_CKD-EPI categories (<30, 30–59, and 60–89 ml/min per 1.73 m²), age within 10 years, and when possible, race and sex, with further adjustment for these characteristics in the analyses (see below). All trial and SKS participants provided informed consent, and the University of Washington’s institutional review board approved the studies.

Measurements of Secretory Solutes

We selected 16 candidate secretory solutes on the basis of the published literature demonstrating one or more of the following characteristics: affinity for basolateral proximal tubular transporters, an increase in circulating concentrations in organic anion transporter (OAT) knockout mouse models, a high reported degree of protein binding, and/or reported kidney clearances that exceed that of creatinine or GFR (13–17). We developed a targeted liquid chromatography-tandem mass spectrometry assay for these solutes in plasma and urine using labeled internal standards and single-point calibration as previously described (18,19). Supplemental Material (Supplemental Tables 1–11) provides a detailed description of our laboratory techniques. Briefly, we extracted serum or plasma solutes from bound proteins using protein precipitation with acidified acetonitrile and solid-phase extraction through phospholipid removal. We extracted urine solutes using solid-phase extraction using either a mixed cation exchange extraction plate or a hydrophilic-lipophilic binding extraction plate (Supplemental Table 1). We reconstituted dried extracts in acetonitrile/formic acid and injected solution onto a Restek PFPP chromatographic column. The column eluate was subsequently introduced into a triple quadrupole tandem mass spectrometer (Sciex 6500) (Supplemental Tables 3–8). Limits of quantification and recoveries in different matrices are shown in Supplemental Tables 9 and 10. Lipemia and low total protein did not interfere with any analyte recoveries. We used stable isotope-labeled internal standards (Supplemental Table 2) and external calibration to purchased chemicals (Supplemental Table 1) to maximize precision. To maximize the accuracy of the calibration and minimize measurement bias, we used standard addition of purified analytes that were quantified using nuclear magnetic resonance. We performed further validation experiments to maximize precision. Inter- and intraassay coefficients of variation for individual solutes in plasma and urine range from 3.4% to 14.7% (Supplemental Table 11).

We were unable to determine the lower limits of detection for three solutes due to isobaric interference (adipic acid, suberic acid, and succinic acid), and therefore, we excluded these solutes from further analyses. We further excluded pantothenic acid from consideration on the basis of previous studies demonstrating glomerular filtration and tubular reabsorption of this compound (20,21) and 3-hydroxy hippurate due to implausibly high kidney clearance. Subsequent protein binding studies performed in our laboratory revealed that three additional solutes (isovalerylglycine, tiglylglycine, and xanthosine) had lower binding percentages than previously reported (Supplemental Table 11). However, we retained these solutes in this study, because their kidney clearances greatly exceed eGFR, suggesting tubular secretion as the major kidney pathway of elimination.

We calculated the fractional excretion of each secretory solute (FE_X) as the proportion of kidney solute clearance relative to creatinine clearance:In this equation, U_X and P_X represent urine and serum/plasma concentrations of secretory solute X, respectively, and U_Cr and P_Cr represent urine and plasma concentrations of creatinine, respectively. For healthy individuals in the dietary trial, P_X was calculated from the average of three fasting measurements of each solute; otherwise, we used spot serum solute concentrations to calculate fractional excretions.

Measurements of Covariates

ADPKD study coordinators obtained demographic and medical histories via patient interviews and review of medical records and measured serum creatinine concentrations using an isotope dilution mass spectrometry–traceable assay. The SKS participants provided self-reported demographic information, social habits, and prevalent medical conditions via study questionnaires administered during the study visits. In the dietary trial and the SKS, coordinators measured serum and urine concentrations of creatinine using the Modified Jaffe Method on a Beckman DXC Unicell clinical analyzer with calibration to isotope dilution mass spectroscopy. GFR was estimated using the 2009 Chronic Kidney Disease Epidemiology Collaboration equation for all study cohorts (22).

Statistical Analyses

We compared relative differences in solute fractional excretions across study cohorts using linear regression. Models included the log-transformed fractional excretion value as the dependent variable, the cohort of interest (ADPKD versus control) as the independent variable, and adjustment terms for eGFR_CKD-EPI, age, sex, BMI, and urine albumin-to-creatinine ratio. Exponentiated coefficients from these models can be interpreted as the fold difference in solute fractional excretion between the cohorts under comparison holding the other model covariates constant.

We controlled for multiple comparisons using the Bonferroni correction, controlling the familywise type I error rate at 5%. For each individual test, this corresponds to a two-sided P value of 0.05/11=<0.01 for declaring statistical significance. Among the ADPKD cohort, we used linear regression to determine associations of solute fractional excretions with height-adjusted kidney volume. All statistical analyses were conducted using the statistical computing environment R version 3.3.0 (R Foundation for Statistical Computing, Vienna, Austria) and STATA 11 (StataCorp, College Station, TX).