Soluble Urokinase Plasminogen Activator Receptor and Decline in Kidney Function in Autosomal Dominant Polycystic Kidney Disease

Significance Statement

Soluble urokinase plasminogen activator receptor (suPAR), a marker of inflammation, is also an independent marker for incidence and progression of renal diseases. Mechanistically, it has been shown to activate podocytes in glomerular diseases. In this study, the authors provide the first description linking suPAR levels with disease progression for a major genetic renal disease that mainly affects the extraglomerular compartment, autosomal dominant polycystic kidney disease (ADPKD). They found an association between suPAR levels and height-adjusted total kidney volume, independent of age, sex, race, hypertension, and eGFR. In addition, patients with suPAR levels >2.82 ng/ml had a 3.38-fold increase in risk of incident ESRD. These findings suggest that suPAR levels may be useful for early identification of patients with ADPKD at high risk of disease progression.

Visual Abstract

Abstract

Background

Levels of soluble urokinase plasminogen activator receptor (suPAR), an inflammation marker, are strongly predictive of incident kidney disease. Patients with autosomal dominant polycystic kidney disease (ADPKD) experience progressive decline in renal function, but rates of decline and outcomes vary greatly. Whether suPAR levels are predictive of declining kidney function in patients with ADPKD is unknown.

Methods

We assessed suPAR levels in 649 patients with ADPKD who underwent scheduled follow-up for at least 3 years, with repeated measurements of height-adjusted total kidney volume and creatinine-derived eGFR. We used linear mixed models for repeated measures and Cox proportional hazards to characterize associations between baseline suPAR levels and follow-up eGFR or incident ESRD.

Results

The median suPAR level was 2.47 ng/ml and median height-adjusted total kidney volume was 778, whereas mean eGFR was 84 ml/min per 1.73 m². suPAR levels were associated with height-adjusted total kidney volume (β=0.02; 95% confidence interval, 0.01 to 0.03), independent of age, sex, race, hypertension, and eGFR. Patients in the lowest suPAR tertile (<2.18 ng/ml) had a 6.8% decline in eGFR at 3 years and 22% developed CKD stage 3, whereas those in the highest tertile (suPAR>2.83 ng/ml) had a 19.4% decline in eGFR at 3 years and 68% developed CKD stage 3. suPAR levels >2.82 ng/ml had a 3.38-fold increase in the risk of incident ESRD.

Conclusions

suPAR levels were associated with progressive decline in renal function and incident ESRD in patients with ADPKD, and may aid early identification of patients at high risk of disease progression.

Autosomal dominant polycystic kidney disease (ADPKD) is the most common form of inherited kidney disease, affecting all races at a prevalence of 1:400–1:1000.¹ It is characterized by the formation of cysts in various organs, most notably the kidneys, hypertension, and progressive renal dysfunction, with the majority of the affected eventually requiring dialysis.¹ Although kidney function typically remains intact until the fourth decade of life, the onset and clinical course of clinical manifestations is highly variable, even within families, and only partially dependent on the underlying mutations (PKD1 or PKD2).¹ Although PKD is not thought of as an inflammatory disease, PKD genes regulate the expression of proinflammatory chemoattractants, and there is mounting evidence that inflammation is an important component of cyst progression early in the onset of the disease.^2,3

Recently, evidence of a novel pathway of kidney injury has emerged involving the bone marrow, immune cells, and the signaling molecule soluble urokinase plasminogen activator receptor (suPAR). suPAR is the circulating form of a glycosyl-phosphatidylinositol-anchored three-domain membrane (D_I, D_II, and D_III) protein expressed on a variety of cells, including immunologically active cells, endothelial cells, and podocytes.⁴⁻⁶ It is a marker of immune activation, and levels are elevated in various conditions associated with inflammation such as increasing age, diabetes, atherosclerosis, heart failure, sepsis, HIV, autoimmune diseases, and smoking.⁷⁻¹¹ suPAR was found to be associated with progressive decline in renal function in various populations,¹²⁻¹⁶ and has a direct pathologic effect induced by binding and activation of podocyte αvβ3 integrin that, in turn, leads to activation of the small GTPase Rac1, downstream cytoskeletal restructuring, and, subsequently, podocyte effacement.^5,17

Determining the risk of disease progression has important clinical implications, including establishing prognosis and early identification of potential donors for transplantation, and targeting patients that may benefit from specific therapies such as tolvaptan.^18,19 Current risk stratification schemes have relied on models that incorporate genotype, clinical characteristics, and imaging, but no markers of inflammation.²⁰⁻²² We sought to determine whether suPAR levels were prognostic in patients with ADPKD, and whether addition of suPAR as a marker of inflammation to currently adopted models would improve risk stratification.

Methods

Study Design

We measured suPAR levels in the plasma of 659 adult patients with APKD enrolled in two separate cohorts: Tolvaptan Efficacy and Safety in Management of Autosomal Dominant Polycystic Kidney Disease and its Outcomes (TEMPO 3:4; n=479; 33% of the cohort) and Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease (CRISP; n=180; 75% of the cohort).^23,24 Patient selection for both cohorts was on the basis of availability of plasma. Participants in both cohorts had yearly serum creatinine and magnetic resonance imaging (MRI)–derived total kidney volume (TKV) measurements, for a total follow-up time of 3 years in TEMPO 3:4 and 13 years for CRISP. Incident ESRD data were available in CRISP. We describe the association between suPAR and (1) clinical characteristics of patients with ADPKD including TKV, (2) the percent change in kidney function as estimated by creatinine-derived eGFR, and lastly, (3) incident ESRD. The institutional review board or ethics committee at each site where CRISP and TEMPO 3:4 participants were enrolled had approved the respective protocols. Written informed consent was obtained from all enrollees.

Inclusion and Exclusion Criteria

TEMPO 3:4

TEMPO 3:4 is a multicenter clinical trial that enrolled adults (18–50 years of age) with ADPKD from January 2007 through January 2009, and randomized them in a 2:1 fashion to tolvaptan versus placebo.^18,23 Patients with advanced diabetes were excluded from the trial and data on diabetic status was not collected during the trial. A TKV of ≥750 ml and an estimated creatinine clearance of ≥60 ml/min were required for inclusion. The trial was sponsored by Otsuka Pharmaceuticals (Rockville, MD). Details are provided in the original publications.^18,23 For the purpose of this study, suPAR was measured in 479 participants who were randomized to the placebo arm.

CRISP

CRISP is a National Institutes of Health sponsored, multicenter, prospective cohort whose purpose was to evaluate imaging techniques used for monitoring disease progression in patients with ADPKD.²⁴ CRISP enrolled patients aged 15–46 years with an estimated creatinine clearance >70 ml/min. Renal function as estimated by eGFR and MRI-derived TKV were measured at baseline and yearly or biannually (after the first 3 years) thereafter. suPAR was measured in a total of 180 CRISP participants with available plasma samples.

Measurement of suPAR Levels

Independent technicians blinded to the clinical data measured suPAR levels using a commercially available ELISA kit (suPARnostic kit; ViroGates, Copenhagen, Denmark) as previously described.²⁵ The intra- and interassay variability for the suPAR determinations were 2.75% and 9.17%, respectively. We and others have shown that suPAR levels in stored plasma and serum are stable and reproducible in samples stored for more than 5 years at −80°C.^4,5

Assessment of Renal Function

Renal function was estimated in both cohorts using serum creatinine–derived eGFR, calculated using the CKD Epidemiology Collaboration equation.²⁶ Participants in TEMPO 3:4 had scheduled baseline and yearly creatinine measurements up to 3 years postenrollment, whereas those in CRISP had baseline and yearly measurements for the first 3 years, and then biannually up to 14 years postenrollment.^18,24 Incident ESRD data were also available in CRISP and was defined as the initiation of chronic dialysis or kidney transplant.

Measurement of TKV

Patients underwent a standardized protocol for MRI of the abdomen. The MRI acquisition protocol included coronal T2-weighted single-shot fast spin–echo, half-Fourier acquired single-shot turbo spin–echo images; and three-dimensional spoiled gradient interpolated T1-weighted images without fat saturation. Measured TKV was referenced to height (height-adjusted total kidney volume [htTKV], ml/m). All images were acquired at 3- or 4-mm slice thickness covering the entire kidneys during breath-holds. MRI scan images were sent to the CRISP or TEMPO 3:4 central reading facilities for quality control and measurement of kidney volume using stereology in CRISP or planimetry in TEMPO 3:4. Detailed protocols have been previously published.^18,27

Statistical Analyses

We analyzed both cohorts combined, in addition to providing the results of each cohort separately in the Supplemental Material. We reported clinical characteristics using descriptive statistics such as means and SD, and medians with 25th and 75th percentiles for variables with skewed distributions (suPAR, htTKV). Between-group differences were tested using the t test for continuous variables, and chi-squared for categorical variables. For non-normally distributed variables such as suPAR, TKV, and htTKV, the Mann–Whitney U test was used to compare groups in unadjusted analyses. We correlated baseline suPAR levels with TKV and htTKV using the Spearman rank test. We used multivariable linear regression adjusting for age, sex, race, body mass index, the presence of hypertension, the use of angiotensin-converting enzyme inhibitors or angiotensin receptor blockers, eGFR, and htTKV to identify characteristics independently associated with suPAR levels, expressed as a base-2 log transformation or “per 100% increase.” For the purpose of the analysis, participants with Irazabal classification 2A were included with the 1A group, given their outcomes are reportedly similar.²²

suPAR and the Decline in Renal Kidney Function

We plotted the yearly percent change in eGFR compared with baseline stratified by suPAR tertiles and used a multivariable longitudinal linear mixed-effect model to determine whether the slope of percent change in eGFR differed across suPAR tertiles, adjusting for age, sex, presence of hypertension, use of renin-angiotensin inhibitors, and baseline htTKV. The subgroups of patients with htTKV<600 ml/m (n=205) and Irazabal classification ≤1C were examined separately to determine whether suPAR could be used to further risk stratify patients with ADPKD deemed to have a lower risk of progression to CKD. A similar analysis was performed examining the association between suPAR tertiles and the percent change in htTKV. The combined analysis was limited to 3 years of data, while the subgroup analyses examining each cohort separately used all available data within each cohort. We then computed the area under the curve and plotted the receiver operating characteristic curves for suPAR levels and the Irazabal classification in their association with CKD stage 3 (defined as an eGFR <60 ml/min) at 3-year follow-up in the subset of patients with baseline eGFR ≥60 ml/min (n=546).

suPAR and Incident ESRD

Lastly, we used proportional hazards modeling to examine the association between suPAR and incident ESRD in the CRISP cohort. The initial model 0 was unadjusted and included suPAR levels alone, expressed either as a continuous variable (log base 2, per 100% increase) or categorical (tertiles). Model 1 included the following clinical characteristics: age, gender, race, body mass index, hypertension, renin-angiotensin system inhibitors, urine albumin-to-creatinine ratio, eGFR, and htTKV. Model 2 incorporated both the clinical characteristics in addition to suPAR. To determine whether the association between suPAR and incident ESRD differed by htTKV, we also examined the interaction between suPAR as a categorical variable using the median as a cutoff, and htTKV<600 ml/m. The median instead of tertiles was used as a cutoff to allow for larger subgroup size. Participants were censored at the latest follow-up visit date, and censoring was assumed to be independent.

Two-tailed P values ≤0.05 were considered statistically significant. Analyses were performed using IBM SPSS Statistics version 24, (IBM Corp., Armonk, NY), SAS version 9.4 (SAS Institute, Cary, NC), and R version 3.2.2 (R Core Team, Vienna, Austria). Risk prediction metrics including c-statistics, continuous net reclassification indices (NRIs), and integrated discrimination indices (IDIs) were computed using R and the survC1 and survIDINRI packages.²⁸⁻³¹

Results

Cohort Characteristics

Overall, we measured suPAR levels in 659 patients with ADPKD (Supplemental Table 1, Table 1). The participants in TEMPO 3:4 (n=479) were older, had lower eGFR, and higher median suPAR levels compared with those enrolled in CRISP (Supplemental Table 1). Genotype was available for 453 (69%) of participants, of whom 83% had a PKD1 mutation, 14% had a PKD2 mutations, and 3% had no mutations detected. Seventy two percent were truncating mutations. Predicting Renal Outcomes in Polycystic Kidney Disease (PROPKD) scores were only available for 274 participants from the TEMPO 3:4 cohort (42%).

Table 1.

Demographics and clinical characteristics stratified by median suPAR levels

Variables	Entire Cohort (n=659)	suPAR <2.18 ng/ml (n=219)	suPAR 2.18–2.83 ng/ml (n=220)	suPAR ≥2.84 ng/ml (n=220)	P Value
Age, yr	37 (8)	34 (9)	38 (7)	39 (7)	<0.001
Male, n (%)	322 (49%)	135 (62%)	110 (50%)	77 (35%)	<0.001
White, n (%)	565 (86%)	179 (82%)	193 (88%)	193 (88%)	0.12
Hypertension, n (%)	497 (75%)	138 (63%)	181 (82%)	178 (81%)	<0.001
Body mass index, kg/m2	26 (5)	25 (5)	25 (5)	27 (6)	0.002
Genotypea
PKD1	378 (83%)	127 (79%)	124 (83%)	127 (88%)
PKD2	61 (14%)	27 (17%)	20 (13%)	14 (10%)
No mutation detected	14 (3%)	6 (4%)	5 (3%)	3 (2%)
ACEi or ARB use, n (%)	427 (65%)	121 (55%)	149 (68%)	157 (71%)	0.001
eGFR, ml/min per 1.73 m2	84 (23)	95 (22)	84 (22)	73 (21)	<0.001
TKV, ml	1328 [948; 1853]	1051 [832; 1597]	1384 [1010; 1939]	1574 [1115; 2049]	<0.001
htTKV, ml/m	778 [558; 1085]	606 [472; 886]	787 [591; 1105]	922 [649; 1205]	<0.001
PROPKD scoreb	6 (6)	5 (3)	5 (3)	6 (2)
Irazabal classification					0.04
1A	28 (4%)	4 (2%)	2 (1%)	3 (1%)
1B	42 (11%)	36 (16%)	20 (9%)	16 (7%)
1C	247 (38%)	80 (37%)	81 (37%)	86 (39%)
1D	198 (30%)	61 (28%)	68 (31%)	69 (31%)
1E	110 (17%)	32 (15%)	40 (18%)	38 (17%)
2A	19 (3%)	6 (3%)	9 (4%)	4 (2%)
suPAR, ng/ml	2.47 [1.98; 3.10]	1.77 [1.52; 1.98]	2.47 [2.32; 2.61]	3.38 [3.10; 4.03]	<0.001

Values are mean (SD), n (%), or median [25th; 75th percentile] as noted. P value is for the comparison between patients with suPAR<2.47 ng/ml and those with suPAR≥2.47 ng/ml. ACEi, angiotensin-converting enzyme inhibitor; ARB angiotensin receptor blocker.

^aOnly available in 453 participants.

^bOnly available in 275 participants from the TEMPO 3:4 cohort.

suPAR and Clinical Characteristics

Participants with higher suPAR levels were more likely to be older, women, hypertensive, on renin-angiotensin system antagonists, and have lower eGFR (Table 1). suPAR levels had a modest correlation with TKV (r=0.28; P<0.001) and htTKV (r=0.30; P<0.001), and the median suPAR levels for patients with ADPKD with htTKV<600 ml/m was 2.15 (IQR, 1.69–2.63), compared with 2.79 (IQR, 2.18–3.24; P<0.001) (Figure 1). In multivariable analysis, htTKV was independently associated with suPAR levels (Table 2), even after adjusting for eGFR. Otherwise, there were no significant differences in suPAR levels between patients in the various Irazabal classification, and the overall correlation between suPAR and Irazabal classification was weak at best (r=0.08; P=0.03). There was no statistically significant difference in suPAR levels between the different genotypes, and suPAR did not correlate with PROPKD scores (r=0.06; P=0.4).

Figure 1.

SuPAR levels are higher with increasing kidney volumes.

Table 2.

Characteristics associated with suPAR levels in participants with ADPKD

Variables	suPAR, per 100% Increase
	β, P Value	95% CI
Age, per 10 yr	0.06, 0.029	0.01 to 0.11
Male	−0.29, <0.001	−0.36 to −0.21
White	0.09, 0.07	−0.01 to 0.19
Body mass index, per kg/m2	0.00, 0.22	−0.00 to 0.01
Hypertension	0.00, 0.97	−0.12 to 0.13
ACEi or ARB use	0.02, 0.70	−0.09 to 0.13
eGFR, per 5 ml/min per 1.73 m2	−0.03, <0.001	−0.04 to −0.02
htTKV, per 100 ml/m	0.02, <0.001	0.01 to 0.03

Values in bold are statistically significant. ACEi, angiotensin-converting enzyme inhibitor; ARB, angiotensin receptor blocker.

suPAR and the Decline in Kidney Function

A total of 659 patients had measured eGFR, suPAR, and htTKV levels at baseline, 629 (95%) at 1 year, 542 (82%) at 2 years, and 458 (69%) at 3 years of follow-up. A significant difference in the percent eGFR decline between the highest and lowest suPAR tertiles is noted even in the first year of follow-up (−1.4%; SD 13.6) for suPAR<2.18 ng/ml versus −7.6% (SD 12.9) for suPAR>2.83 ng/ml (P<0.001). By the third year of follow-up, participants with suPAR<2.18 ng/ml had a −6.8% decline in eGFR, compared with −19.4% in those with suPAR>2.83 ng/ml (P<0.001; Figure 2A). The association between percent change in eGFR and suPAR remained significant even after adjustment for age, sex, presence of hypertension, use of renin-angiotensin inhibitors, and htTKV or Irazabal classification. When examining the low-risk subgroup defined by htTKV<600 ml/m (n=205), patients with suPAR>2.15 ng/ml (median) had an 8.8% decline in eGFR compared with −3.9% for those with suPAR<2.15 ng/ml (P<0.001; Figure 2B). Similarly, in the subgroup with Irazabal classification ≤1C (n=347), patients with suPAR≥2.44 ng/ml had a −13% decline in eGFR, compared with −6% for those with suPAR<2.44 ng/ml (P<0.001; Figure 2C). Overall, results were consistent across both cohorts when analyzed separately (Supplemental Figure 1, A and B).

Figure 2.

Patients with higher suPAR levels had a steeper decline in kidney function.

We found no statistically significant correlation between baseline suPAR levels and the change in htTKV at follow-up (Supplemental Figure 2). Adjusting for genotype (P for interaction =0.8) or PROPKD score (P=0.7) did not affect the association between suPAR and percent eGFR decline.

suPAR and Incident CKD Stage 3

Notably, by 3 years of follow-up, 68% of patients with suPAR>2.83 ng/ml developed CKD stage 3, defined as an eGFR<60 ml/min per 1.73 m², with an unadjusted 4.26-fold increase in the risk of CKD stage 3 (95% confidence interval [95% CI], 2.35 to 7.70), compared with only 22% of those with suPAR<2.18 ng/ml (Table 3). The association remained statistically significant after adjusting for clinical characteristics, but the effect size was dampened when baseline eGFR was added to the model. In subgroup analyses, the association between suPAR and incident CKD did not differ according to htTKV, baseline eGFR, or genotype.

Table 3.

suPAR and incident CKD stage 3 and ESRD in patients with ADPKD

Variable	CKD Stage 3		ESRD
	HR, P Value	95% CI	HR, P Value	95% CI
Model 0: suPAR (unadjusted)
suPAR, per 100% increase (log2)	3.11, <0.001	2.40 to 4.01	2.04, 0.02	1.15 to 3.60
suPAR, <2.176 ng/ml (ref)	-	-	-	-
2.176–2.826 ng/ml	2.26, 0.01	1.20 to 4.24	2.01, 0.13	0.82 to 4.94
≥2.827 ng/ml	4.26, <0.001	2.35 to 7.70	3.53, 0.003	1.52 to 8.20
Model 1: suPAR+clinical characteristics
suPAR, per 100% increase (log2)	3.00, <0.001	1.91 to 4.74	2.21, 0.05	1.02 to 4.79
suPAR, <2.176 ng/ml (ref)	-	-	-	-
2.176–2.826 ng/ml	1.94, 0.04	1.02 to 3.70	1.38, 0.51	0.53 to 3.58
≥2.827 ng/ml	4.08, <0.001	2.19 to 7.61	3.94, 0.009	1.41 to 10.99
Model 2: suPAR+clinical characteristics+eGFR
suPAR, per 100% increase (log2)	1.76, 0.02	1.11 to 2.81	1.90, 0.13	0.83 to 4.38
suPAR, <2.176 ng/ml (ref)	-	-	-	-
2.176–2.826 ng/ml	1.76, 0.09	0.92 to 3.36	1.26, 0.64	0.48 to 3.30
≥2.827 ng/ml	2.49, 0.005	1.31 to 4.71	3.63, 0.02	1.28 to 10.30
Model 3: suPAR+clinical characteristics+eGFR+htTKV
suPAR, per 100% increase (log2)	1.69, 0.03	1.05 to 2.72	1.72, 0.14	0.83 to 3.68
suPAR, <2.176 ng/ml (ref)	-	-	-	-
2.176–2.826 ng/ml	1.46, 0.27	0.75 to 2.84	1.27, 0.62	0.49 to 3.39
≥2.827 ng/ml	2.18, 0.02	1.15 to 4.15	3.21, 0.03	1.13 to 9.09
Interaction and subgroup analyses	P for Interaction
suPAR ≥2.827 ng/ml eGFRa	0.89		0.72
suPAR ≥2.827 ng/ml htTKV<600 ml/ma	0.93		0.26
suPAR ≥2.827 ng/ml genotypea	0.99		0.99

The association between suPAR levels and CKD stage 3 was examined in a subset of both cohorts (n=546), whereas data on incident ESRD was only available in the CRISP cohort (n=180). Model 0 reports the association of suPAR both as a continuous and a categorical variable. Model 1 includes suPAR in addition to age, sex, body mass index, hypertension, use of ACEi/ARB and urine albumin-to-creatinine ratio. Models 2 and 3 and the interaction analyses include the clinical characteristics in model 1, in addition to the listed variables. ACEi, angiotensin-converting enzyme inhibitor; ARB, angiotensin receptor blocker.

^aUrine albumin-to-creatinine ratio was only available in the CRISP cohort.

^bValues in bold were statistically significant at P<0.05.

suPAR Compared with Irazabal Classification and PROPKD Score in Predicting Incident CKD

We computed risk discrimination indices, including the c-statistic, NRI, and IDI, for the prediction of incident CKD (Table 4). The area under the curve for suPAR in its association with CKD stage 3 was 0.0.738 (95% CI, 0.68 to 0.80), compared with 0.719 (95% CI, 0.65 to 0.79) using Irazabal class alone. Most importantly, incorporating both suPAR and the Irazabal classification significantly improved the area under the curve to 0.801 (95% CI, 0.75 to 0.86) for incident CKD stage 3; a change of 0.081 (95% CI, 0.04 to 0.13).

Table 4.

Risk discrimination metrics for incident CKD stage 3

Model	Incident CKD Stage 3
	c-Statistic (95% CI)	Δc-Statistic (95%CI)	Continuous NRI (95% CI)	Relative IDI (95% CI)
Irazabal classification	0.72 (0.65 to 0.79)	—	0.35 (0.23 to 0.46)	0.13 (0.07 to 0.19)
PROPKD scorea	0.62 (0.51 to 0.74)	—	0.18 (-0.02 to 0.35)	0.03 (0.002 to 0.09)
suPAR	0.74 (0.68 to 0.80)	—	0.42 (0.27 to 0.57)	0.12 (0.06 to 0.18)
Irazabal+suPAR	0.80 (0.75 to 0.86)	0.08 (0.04 to 0.13)	0.47 (0.37 to 0.58)	0.22 (0.15 to 0.30)
PROPKD+suPARa	0.76 (0.67 to 0.85)	0.14 (0.03 to 0.24)	0.42 (0.1 to 0.54)	0.14 (0.06 to 0.22)

NRI, net reclassification index; IDI, integrated discrimination index.

^aPROPKD scores were available for only 275 participants from TEMPO 3:4.

In the subset with PROPKD scores available (n=275), the area under the curve for PROPKD was 0.624 (95% CI, 0.51 to 0.74) for the PROPKD score. Addition of suPAR to the PROPKD score significantly improved the c-statistic to 0.760 (95% CI, 0.67 to 0.85), a change of 0.136 (95% CI, 0.03 to 0.24). Addition of suPAR to Irazabal classification or PROPKD scores similarly improved the NRI and IDI (Table 4).

suPAR and Incident ESRD

We lastly examined the association between suPAR levels and incident ESRD in the CRISP cohort. Out of 180 patients, 32 (17.8%) met the end point at a median follow-up of 13.4 years (range, 2–15); 15 (46.8%) in patients with suPAR>2.82 ng/ml, compared with only seven (21.8%) in those with a baseline suPAR level of <2.18 ng/ml (P<0.001; Figure 3). In multivariable analysis, patients in the highest suPAR tertile had 3.38-fold increase in the risk of incident ESRD after extensive adjustment for clinical characteristics, including baseline eGFR, urine albumin-to-creatinine ratio and htTKV (Table 3). The association did not differ between those with a baseline htTKV <600 and >600 ml/m (Table 3). Adjusting for genotype did not affect the association between suPAR and incident ESRD (P for interaction =0.9).

Figure 3.

Patients in the highest suPAR tertile were more likely to require dialysis at long-term follow-up.

Discussion

In this study of two well characterized prospective cohorts of patients with ADPKD, we found high suPAR levels to be strongly associated with a decline in kidney function and incident ESRD, independently of htTKV; an important surrogate marker of disease progression.³²⁻³⁴ Moreover, we found that suPAR levels allowed differentiating between patients with faster and slower decline in renal function in those deemed at relatively low risk with htTKV<600 ml/m. Most importantly, incorporating suPAR with the Irazabal classification significantly improved the ability to discriminate those at high risk for progressing to CKD stage 3 by 3 years’ follow-up.

Polycystic kidney disease is the most commonly inherited cause of CKD, and the autosomal dominant form accounts for close to 10% of patients with ESRD.^35,36 Until recently, the treatment of patients with ADPKD relied on control of risk factors such as BP control, low-salt diet, and statins, which may prevent progression of disease and reduce cardiovascular mortality.^37,38 Two trials have recently provided evidence for the effectiveness of tolvaptan in slowing the progression of kidney disease in ADPKD.^18,19 Treatment with tolvaptan could extend kidney survival up to 9 years; however, it is limited by tolerability, especially in patients with poor kidney function.³⁹ Appropriate selection of patients is crucial, and the major clinical challenge is to define the patients at risk for rapid progression who may derive the most benefit from tolvaptan. The most commonly adopted classification schemes are on the basis of imaging and scores using clinical characteristics such as the Mayo and Irazabal classifications, and the PROPKD score, none of which incorporate markers of inflammation.²⁰⁻²²

This is the first study to describe an association between a novel marker of immune activation, suPAR, and progression of kidney disease in patients with ADPKD. Notably, patients deemed at low risk of progression to CKD by htTKV<600 ml/m and Irazabal class ≤1C but relatively elevated suPAR levels still exhibited a more rapid decline in eGFR compared with those with lower suPAR levels, even when accounting for differences in baseline eGFR. Although Irazabal class and htTKV are mainly on the basis of structural assessment of the kidneys, suPAR levels reflect both immune activation and, at least partly, baseline kidney function, given their modest correlation with eGFR—different but complementary aspects in assessing kidney disease. These findings suggest that suPAR could be useful for the early identification of those for whom PKD is most likely to progress. We provide evidence that incorporating imaging characteristics such as the Irazabal classification, and a marker of inflammation such as suPAR, may be the optimal risk stratification method for patients with ADPKD. These findings should not be surprising; inflammation is an initially protective physiologic response to injury or structural alterations and is likely to be present before changes in morphology noted on imaging. SuPAR, as a marker of immune activation, may be more likely than others to be an ideal inflammatory marker for early kidney injury, given its putative role in the pathogenesis of kidney injury.^5,25,40,41

However, given suPAR’s pathogenic involvement in kidney disease is reported to occur at the level of the glomerulus,^5,40,41 it is unlikely to be the main driver of injury in ADPKD, given PKD is largely a structural and tubular disorder for which pathophysiology lies in the disturbance of ciliary function. More recently, we have described a synergistic association between suPAR and other molecules involved mechanistically in kidney injury such as APOL1 or anti-CD40.⁴⁰ Thus, the findings we report likely reflect a modifying effect of suPAR in the progression of ADPKD, a marker of the underlying inflammatory process in addition to potential kidney injury, for which mechanistic underpinnings are unknown and warrant exploration. For example, suPAR’s activation of podocyte integrins in already hyperfiltrating glomeruli in ADPKD may be the trigger exacerbating kidney dysfunction.

There are two main clinical implications for our findings. First, suPAR levels could be combined with current risk stratification schemes to identify patients at high risk for progression and who might benefit from early intervention. Second, if a mechanistic role of suPAR in ADPKD can be established, novel treatments for ADPKD can be envisioned in the form of a neutralizing antibody to suPAR.

Strengths and Limitations

We have measured suPAR in two relatively larger cohorts of patients with ADPKD: TEMPO 4:3, a rigorously conducted clinical trial, and CRISP, an National Institute of Diabetes and Digestive and Kidney Diseases–funded prospective cohort. We have replicated the association between suPAR and renal dysfunction in both cohorts and combining them has allowed for subgroup analyses. Limitations to the study include the risk of selection bias given a subset of each study had samples available for measurement of suPAR levels, in addition to the incomplete long-term follow-up of patients enrolled in CRISP. Moreover, the weak association between suPAR and ESRD is likely due to the small sample size of CRISP (n=180) with few events, and the first event being 6 years after suPAR measurement. Although we did not observe an impact of genotype on the association between suPAR and incident kidney disease, genotype was available for 69% of participants. PROPKD scores were also only available in a smaller subset of patients (n=275).

In conclusion, elevated suPAR levels are associated with a decline in kidney function in patients with ADPKD, independently of htTKV. Adding suPAR to current risk stratification schemes for patients with ADPKD may identify those at high risk of disease progression that may not have manifested significant morphologic changes in imaging.

Disclosures

Dr. Reiser is a cofounder and shareholder of Trisaq, a biotechnology company that develops therapeutics to target suPAR. Dr. Wei has a pending patent on the role of suPAR in Diabetes Mellitus. Dr. Pao and Ms. Roth are both employees of Otsuka Pharmaceutical Development & Commercialization, Inc. Dr. Landsittel reports grants from University of Pittsburgh, during the conduct of the study. Dr. Yu reports other from Regulus Therapeutics, outside the submitted work. Dr. Reiser reports personal fees from Biomarin, grants from National Institutes of Health, grants from Nephcure, other from TRISAQ, grants from Thermo BCT, personal fees from Astellas, personal fees from Massachusetts General Hospital, personal fees from Genentech, personal fees from Up to Date, personal fees from Merck, personal fees from Incepetionsci, personal fees from GLG, outside the submitted work; In addition, Dr. Reiser has a patent US20110212083-Role of soluble uPAR in the Pathogenesis of Proteinuric Kidney Disease with royalties paid to TRISAQ, a patent US9867923-Reducing Soluble Urokinase Receptor in the Circulation with royalties paid to Miltenyi, a patent JP2016530510-Non-Glycoslyated suPAR Biomarkers and Uses thereof with royalties paid to TRISAQ, a patent US20160296592-Methods/Compositions for the Treatment of Proteinuric Diseases with royalties paid to TRISAQ, a patent US9144594-Dynamin Mediated Diseases with royalties paid to TRISAQ, and a patent US8809386-Dynamin Ring Stabilizers with royalties paid to TRISAQ. The remaining authors have nothing to disclose.

Supplemental Material

This article contains the following supplemental material online at http://jasn.asnjournals.org/lookup/suppl/doi:10.1681/ASN.2018121227/-/DCSupplemental.

Supplemental Table 1. Demographics and clinical characteristics stratified by cohort.

Supplemental Figure 1. Percent change in eGFR in the (A) TEMPO 3:4 (n=479) and (B) CRISP (n=180), stratified by suPAR tertiles. Error bars represent ±1 SEM.

Supplemental Figure 2. Percent change in htTKV in both cohorts, stratified by suPAR tertiles. Error bars represent ±1 SEM.