ADPKD
Messchendorp, Annemarie Lianne
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2019
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Messchendorp, A. L. (2019). ADPKD: Risk Prediction for Treatment Selection. Rijksuniversiteit Groningen.
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6
Kidney Function Reserve Capacity in early
and later stage autosomal dominant
polycystic kidney disease
A. Lianne Messchendorp Marco van Londen Jacob M. Taylor Martin H. de Borst Gerjan Navis Niek F. Casteleijn Carlo A.J.M. Gaillard Stephan J.L. Bakker Ron T. Gansevoort on behalf of the DIPAK Consortium.
ABSTRACT
BackgroundIt is assumed that in Autosomal Dominant Polycystic Kidney Disease (ADPKD), kidney function remains in the normal range for several decades due to hyperfiltration of remnant nephrons. In this study, we investigate the extent to which ADPKD patients hyperfilter.
Methods
In this cross-sectional study, we measured glomerular filtration rate (GFR) as urinary clearance using continuous infusion of 125I-Iothalamate. Kidney function reserve
capacity was determined as increase in measured GFR after adding a dopamine infusion of 4.4-6 mg/hr. Potential kidney donors were used as healthy controls and matched by age and sex to ADPKD patients for comparisons across age groups and CKD stages. Hyperfiltration was defined by a loss of kidney function reserve capacity compared to healthy controls.
Results
A total of 300 subjects were studied. In the youngest age group (18-29 years), measured GFR was not different between ADPKD patients and healthy controls (103±21 vs. 111±9 ml/min/1.73m2, p=0.14). Importantly, in this age group kidney function reserve
capacity was not lower, but slightly higher compared to healthy controls (11.1±8.3 vs. 5.3±6.5 %, p=0.04). Moreover, kidney function reserve capacity was similar to healthy controls in ADPKD patients with early stage disease (eGFR≥60 ml/min/1.73m2), either
overall or when divided into fast or slow progressors according to their Mayo htTKV class. In ADPKD patients, lower measured GFR was, however, associated with lower kidney function reserve capacity (β=1.0 [0.5,1.5] % per 10 ml/min/1.73m2, p<0.001).
Kidney function reserve capacity was therefore lower compared to healthy controls at older age and later CKD stages.
Conclusions
Patients with early stage ADPKD, either classified as having rapidly or slowly progressive disease, are still able to increase their GFR in response to dopamine. Hyperfiltration, defined by a loss of kidney function reserve capacity, may therefore not be an early phenomenon in ADPKD.
INTRODUCTION
ADPKD is characterized by the formation and growth of cysts in both kidneys, which results in a decline in glomerular filtration rate (GFR). Ultimately, most subjects with ADPKD require kidney replacement therapy. It is assumed that the decline in GFR only occurs after several decades, whereas cyst formation and growth already starts in utero. This makes GFR a less sensitive measure for disease severity and prognosis, especially in the early stages of the disease1.It has been suggested that this preservation
of GFR in early stage disease is caused by a compensatory mechanism in remnant nephrons, that are yet not lost due to disease progression. This phenomenon is called glomerular hyperfiltration2.
Glomerular hyperfiltration cannot be directly measured in humans. Several measures are therefore used as surrogate. Glomerular hyperfiltration is sometimes defined as an increased filtration fraction3. However, measurement of filtration fraction by
infusion of exogenous tracers such as iothalamate and hippuran may be inaccurate. It may lead to overestimation of filtration fraction, especially when tubular function is compromised, as in ADPKD4. Glomerular hyperfiltration is therefore more commonly
defined as the loss of kidney function reserve capacity, i.e. the impairment of the kidney to increase GFR in response to stimuli such as dopamine5, 6.
If patients with ADPKD hyperfilter in early stages of their disease, a loss of kidney function reserve capacity is expected to occur before a decline in GFR is detected. Therefore loss of kidney function reserve capacity might be one of the earliest markers of severe disease. Although this is widely assumed, it has never been formally investigated. In this study we therefore investigated, first, whether individuals hyperfilter across the full spectrum of ADPKD by measuring kidney function reserve capacity. Second, we studied which factors are associated with kidney function reserve capacity. Lastly, we analyzed whether similar results are obtained when hyperfiltration is defined as elevated filtration fraction.
MATERIAL AND METHODS
Setting and subjectsAll adult ADPKD patients visiting the University Medical Center Groningen from October 2014 until May 2017 were asked to participate in this observational study. The diagnosis of ADPKD was made based upon the revised Ravine criteria7. Subjects were
considered ineligible, among others, if they received kidney replacement therapy, had other systemic diseases or treatments potentially affecting kidney function. Patients with a wide range of kidney function were included to allow comparisons across early and later stage ADPKD. For this study, potential kidney donors were used as healthy controls and underwent kidney function measurement with iothalamate and hippuran. Only potential kidney donors without a history of cardiovascular or kidney disease and without abnormalities on a routine investigation of blood hematology, chemistry, and urinalysis, were included. These healthy controls were matched for age and sex to ADPKD patients in a 1:1 ratio. The study was performed in adherence to the Declaration of Helsinki and all participants gave written informed consent. Clinical and biochemical measurements
All subjects were scheduled for a one day clinical evaluation at our outpatient clinic. ADPKD patients collected a 24-hour urine sample one day prior and a fasting spot urine on the day of this visit. Blood samples were drawn for the measurement of creatinine with an enzymatic assay (Modular, Roche Diagnostics). GFR was estimated (eGFR) using the 2009 CKD-EPI (Chronic Kidney Disease EPIdemiology) equation8.
Protein intake (g/day) was calculated as 24-hour urinary urea excretion * 0.18 + 15 according to the Maroni formula9, and sodium intake was estimated using 24-hour
urinary sodium excretion.
MR imaging was performed to assess total kidney volume in ADPKD patients only, using a standardized abdominal magnetic resonance imaging protocol, without the use of intravenous contrast. Scanning was performed with a 1.5 or 3.0 Tesla magnetic resonance scanner (Magnetom Avento; Siemens, and Intera; Philips). Total kidney volume was measured on T2-weighted coronal images by an artificial multi-observer deep neural network model for fully automated segmentation10 and adjusted for height.
PKD mutation analysis was performed with DNA isolation using PUREGENETM nucleic
sequencing of amplified coding exons directly (exon 34-46), or on long-range PCR products (exon 1-33)11.
Kidney function measurements and Kidney Function Reserve Capacity
GFR and effective kidney plasma flow were measured as urinary clearance of
125I-Iothalamate and 131I-hippuran, respectively, applying a constant infusion method as
described previously12. Kidney function reserve capacity was determined as increase
in measured GFR after adding a dopamine infusion. A more detailed description of this measurement and the physiological changes of the kidney during dopamine infusion is added to the Supplementary Material. Kidney function reserve capacity was calculated as percentage increase in measured GFR during dopamine infusion [(measured GFRdopamine-measured GFR)/measured GFR)*100%] and as absolute increase in measured GFR (ml/min/1.73m2) (measured GFR
dopamine-measured GFR). A loss of
kidney function reserve capacity compared to healthy controls is used as a surrogate for hyperfiltration6. Filtration fraction was expressed as percentage and calculated as
measured GFR/effective kidney plasma flow*100%. Kidney blood flow (ml/min/1.73m2)
was calculated as effective kidney plasma flow/(1- serum hematocrit). Kidney vascular resistance (dynes/s/m5) was calculated as (mean arterial pressure/kidney blood
flow)*80000. Statistical analyses
Normally distributed data are expressed as means ± standard deviation (SD), whereas non-normally distributed data are expressed as median with interquartile range (IQR). Patients and healthy controls were first divided into age groups 18-29, 30-39, 40-49, 50-59 and ≥60 years to compare ADPKD patients in different stages of the disease with healthy controls. Differences between ADPKD patients and healthy controls were tested using a two-sample t test when normally distributed or a Mann-Whitney U test when not normally distributed. A chi-squared test was used for categorical data. Differences in results of kidney function measurement before and during dopamine infusion were calculated using a paired-sample t test. A p for trend was calculated for baseline characteristics and results of the kidney function measurement across age groups in both ADPKD patients and healthy controls. Therefore, a one-way ANOVA was used in case of normal distribution, a Kruskal-Wallis H test in case of non-normal distribution, and a linear chi-squared test for categorical data. Second, we divided
subjects according to CKD stage and compared healthy controls with ADPKD patients in CKD stages 1-4 with a one-way ANOVA analysis using a post-hoc Bonferroni correction. Univariable and multivariable linear regression analyses were used to investigate possible determinants of kidney function reserve capacity and filtration fraction in ADPKD patients and healthy controls separately (sex, measured GFR, PKD mutation, height adjusted total kidney volume, RAAS-inhibitor use, BMI, protein intake and sodium intake).
Next, we compared kidney function reserve capacity and filtration fraction between the various risk classes of the Mayo htTKV classification14 and between different PKD
mutations with a one-way ANOVA with post-hoc Bonferroni correction. Lastly, as a sensitivity analysis we selected patients with CKD stage 1 and 2 (i.e. eGFR ≥ 60 ml/ min/1.73m2) and divided these patients in fast progressors (Mayo htTKV class 1C-E)
or slow progressors (Mayo htTKV class 1A-B). We subsequently tested if there were differences in kidney function reserve capacity or filtration fraction between healthy controls, fast progressors and slow progressors with a one-way ANOVA with a post-hoc Bonferroni correction.
Analyses were performed with SPSS version 23.0 (SPSS Inc., Chicago, IL). A two sided p<0.05 was considered statistically significant.
RESULTS
Subject characteristics
We included 150 ADPKD patients, 59% being female, with a mean age of 46 ± 12 (range 18 - 75) years. Patients were matched by age and sex with 150 healthy controls. ADPKD patients had a similar blood pressure, but were more likely to use antihypertensive medication. As expected, ADPKD patients had lower eGFR (Table 1). For further analyses, ADPKD patients and healthy controls were subdivided into five age categories (18-29, 30-39, 40-49, 50-59 and ≥60 years). Table S1 shows the baseline characteristics according to these age groups.
Table 1. Clinical characteristics of ADPKD patients and matched healthy controls.
ADPKD Healthy controls
N N Female, n (%) 150 88 (59) 150 80 (53) Age (years) 150 46 ± 12 150 46 ± 11 Weight (kg) 150 83 ± 18 150 81 ± 13 Height (cm) 150 176 ± 10 150 176 ± 9 BMI (kg/m2) 150 26.6 ± 4.8 150 26.2 ± 3.2
Systolic blood pressure (mmHg) 149 127 ± 13 150 123 ± 11 Diastolic blood pressure (mmHg) 149 78 ± 9 150 74 ± 8 Antihypertensive use, n (%) 150 114 (76) 150 12 (8) RAAS-inhibitor use, n (%) 150 104 (69) 150 2 (1)
Protein intake (g/24hr) 147 86 ± 23 141 90 ± 29
Sodium intake (mmol/24hr) 147 157 ± 60 142 193 ± 76
eGFR (ml/min/1.73m2) 150 63 ± 31 150 92 ± 15 CKD stage, n (%) 150 - -- 1 27 (18) -- 2 52 (35) -- 3A 22 (15) -- 3B 23 (15) -- 4 23 (15) -- 5 3 (2) -htTKV (ml/m) 143 785 (489-1282) - -Mayo htTKV class, n (%) 143 -- 1A 9 (6) -- 1B 31 (21) -- 1C 50 (33) -- 1D 30 (20) -- 1E 16 (11) -- 2 7 (5) -PKD mutation, n (%) 130 -- PKD1 truncating 53 (35) -- PKD1 non--truncating 44 (29) -- PKD2 27 (18) -- No mutation detected 6 (4)
-Variables are presented as mean ± SD, or as median (IQR) in case of non-normal distribution.
Abbreviations are: ADPKD, autosomal dominant polycystic kidney disease; BMI, body mass index; eGFR,
estimated glomerular filtration rate; CKD stage, chronic kidney disease stage; htTKV, height adjusted total kidney volume; PKD, polycystic kidney disease.
Kidney function according to age
Overall, estimated and measured GFR were, respectively, 63 ± 31 and 66 ± 29 ml/ min/1.73m2 in ADPKD patients and 92 ± 15 and 102 ± 15 ml/min/1.73m2 in healthy controls.
Estimated and measured GFR were lower in ADPKD patients and healthy controls in older age groups (Table 2). However, in the youngest age group (18-29 years), both eGFR
and measured GFR were not different between ADPKD patients and healthy controls (110 ± 22 vs. 113 ± 11 ml/min/1.73m2, p=0.64 and 103 ± 21 vs 111 ± 9 ml/min/1.73m2,
p=0.14 respectively). Estimated as well as measured GFR were lower in ADPKD patients compared to healthy controls in all other age groups (30 years and older) (Figure 1).
Figure 1. Estimated GFR (upper panel) and measured GFR (lower panel) in ADPKD patients and
healthy controls according to age group. Data are expressed as Tukey boxplots with median, IQR, and minimum and maximum within 1.5 IQR and outliers. **p<0.001. Abbreviations are: ADPKD,
Ta bl e 2 . K id ne y f un ct io n m ea su re m en t a cc or di ng t o a ge g ro up . A ge (y ear s) 18 -2 9 30 -39 40 -49 50 -59 ≥6 0 P f or t re n d Var iab le s A D PK D Con tro l A D PK D Con tro l A D PK D Con tro l A D PK D Con tro l A D PK D Con tro l AD PKD Con tro l N 17 17 26 26 41 41 50 50 16 16 -eG FR (m l/ mi n/ 1. 73 m 2) 11 0± 22 11 3± 11 85 ±2 0 ** 98 ±1 3 58± 25 ** 91 ±1 0 50 ±21 ** 86 ±1 2 35 ±21 ** 83 ±1 3 <0 .0 01 <0 .0 01 M ea su re d G FR (m l/ mi n/ 1. 73 m 2) 10 3± 21 11 1± 9 90 ±1 8 ** 10 9± 10 62 ±2 5 ** 10 4±1 5 53 ±21 ** 97 ±1 4 38 ±1 9 ** 89 ±1 9 <0 .0 01 <0 .0 01 Eff ec ti ve ki dn ey p la sma flo w ( m l/ mi n/ 1. 73 m 2) 317 ±7 8 346 ±4 2 26 0± 44 ** 34 6± 58 19 2± 76 ** 32 6± 51 16 9± 66 ** 29 9± 46 12 3± 49 ** 28 2± 57 <0 .0 01 <0 .0 01 Ki dn ey b lood flo w ( m l/ mi n/ 1. 73 m 2) 54 8±1 39 62 6± 74 45 5± 83 ** 62 3± 94 31 1± 12 4 ** 57 7±1 03 28 5± 11 1 ** 532 ±8 7 22 8± 10 4 ** 51 1± 11 2 <0 .0 01 <0 .0 01 Ki dn ey v as cu la r re si st an ce (d yne s/ s/ cm 5) 11 29 1 * (1 017 4-16 07 7) 10 07 0 (9 23 8-11 09 2) 13 37 7 ** (12 41 9-15 777 ) 96 17 (8 87 4-11 10 0) 216 59 ** (17 13 4-28 20 0) 11 34 4 (9 57 4-12 65 7) 24 72 3 ** (18 214 -32 332 ) 12 37 8 (1 10 16 -14 53 0) 27 45 4 ** (2 09 70 -50 89 9) 13 54 7 (1 16 58 -16 42 4) <0 .0 01 <0 .0 01 Ki dn ey fu nc tio n rese rv e cap ac it y (% ) 11 .1 ±8 .3 * 5. 3± 6. 5 3. 8± 5.6 ** 9.9 ±8 .2 4. 3± 9. 2 ** 11 .8 ±7. 6 2. 6± 11 .4 ** 9. 4± 10 .2 -0 .1 ±8 .8 ** 9. 8± 6. 3 0. 00 1 0.1 8 Fil tr at io n fr ac tio n ( %) 33. 5±4 .4 32 .7 ±4 .9 34 .5 ±4 .1 *32 .2 ±4 .2 32 .2 ±4 .2 32 .2 ±3 .6 31 .1 ±3 .8 * 32 .8 ±3 .8 29 .6 ±4 .1 31. 9± 3. 8 <0 .0 01 0.7 5 Va ri ab le s ar e pr es en te d as m ea n ± SD or a s m ed ia n (IQ R) in ca se of no n-no rm al di st ri bu tio n. P va lu es ar e ob ta in ed us in g on e-w ay A N O VA in ca se of no rm al di st ri bu tio n an d Kr us ka l-W al lis te st in c as e of n on -n or m al di st ri bu tio n . A bbr ev ia tio ns a re : N , n um be r; A D PK D , a ut os om al d om in an t po ly cy st ic ki dn ey d is ea se ; e G FR , e st im at ed glom er ul ar fi lt ra tion r at e. * p< 0. 05 c om pa re d t o h ea lt hy c on tr ol s am e a ge g ro up **p< 0. 00 1 c om pa re d t o h ea lt hy c on tr ol s am e a ge g ro up
6
Kidney function reserve capacity
Results of the kidney function measurement before and during dopamine infusion are given in Table 3. In healthy controls, infusion of dopamine caused an increase in effective kidney plasma flow and consequently an increase in measured GFR in all age groups. However, in ADPKD patients, although effective kidney plasma flow increased in all age groups, measured GFR did not increase in patients 50-59 and ≥60 years of age.
Overall, kidney function reserve capacity was 3.9 ± 9.7% in ADPKD patients and 9.7 ± 8.6% in healthy controls (p<0.001). Kidney function reserve capacity was lower in older age groups in ADPKD patients, but not in healthy controls (Table 2). Surprisingly, in the youngest age group kidney function reserve capacity was higher in ADPKD patients compared to healthy controls (p=0.04). As expected, in the older age groups kidney function reserve capacity was lower compared to healthy controls (Figure 2 upper panel). Results with absolute kidney function reserve capacity were similar (Figure S1). In ADPKD patients, kidney function reserve capacity was lower at higher CKD stages, and was similar to healthy controls in early CKD stages (1-3A) (Figure 2 lower panel). We proceeded with testing whether there were determinants of kidney function reserve capacity which could explain the differences we observed in age groups between ADPKD patients and healthy controls. In ADPKD patients, measured GFR and height adjusted total kidney volume were univariable associated with kidney function reserve capacity (β=1.0 [0.5, 1.5] % per 10 ml/min/1.73m2, p<0.001 and β=-2.4 [-3.9,
-0.8] % per doubling, p=0.003 respectively). Only measured GFR remained associated in multivariable regression analysis, with higher measured GFR being associated with higher kidney function reserve capacity (β=0.8 [0.05, 1.6] % per 10 ml/min/1.73m2,
p=0.04). In healthy controls, measured GFR was also associated with kidney function reserve capacity, but in the opposite direction of what was observed in ADPKD patients (univariable β=-1.5 [-2.3, -0.6] % per 10 ml/min/1.73m2, p=0.001 and multivariable
Ta bl e 3 . K id ne y f un ct io n m ea su re m en t b ef or e a nd d ur in g d op am in e i nf us io n ( pr e d op am in e a nd d op am in e r es pe ct iv el y) a cc or di ng t o a ge g ro up . A ge (y ear s) 18 -2 9 30 -39 40 -49 50 -59 ≥6 0 Var iab le s Pr e do pamin e D op ami ne Pr e do pamin e D op am in e Pr e do pamin e D op amin e Pr e do pamin e D op ami ne Pr e do pamin e D op amin e A D PK D N 17 26 41 50 16 M ea su re d G FR ( m l/ mi n/ 1. 73 m 2) 10 3± 21 11 4± 25 ** 90 ±1 8 93 ±1 9 * 62 ±2 5 66± 28 ** 53 ±21 54 ±23 38 ±1 9 38 ±2 0 Eff ec ti ve k id ne y pl as m a fl ow ( m l/ mi n/ 1. 73 m 2) 317 ±7 8 36 3±9 6 ** 26 0± 44 28 4± 53 ** 19 2± 76 22 0± 95 ** 16 9± 66 18 7± 80 ** 12 3± 49 13 1± 57 * Fil tr at io n f ra ct io n ( % ) 33. 5±4 .4 32 .5 ±4 .6 * 34. 5± 4. 1 33. 1±4 .3 * 32 .2 ±4 .2 30 .7 ±4 .1 ** 31 .1 ±3 .8 29 .3± 4. 2 ** 29 .6 ±4 .1 28. 6± 4. 7 * H ea lt hy c on tro ls N 17 26 41 50 16 M ea su re d G FR ( m l/ mi n/ 1. 73 m 2) 11 1± 9 11 7± 8 * 10 9± 10 12 0±1 3 ** 10 4±1 5 116 ±18 ** 97 ±1 4 10 5±1 6 ** 89 ±1 8 97 ±1 6 ** Eff ec ti ve k id ne y pl as m a fl ow ( m l/ mi n/ 1. 73 m 2) 34 7± 42 38 7± 57 ** 34 6± 58 40 3±7 2 ** 32 6± 51 37 9± 69 ** 29 9± 46 34 3± 59 ** 28 2± 57 31 9± 56 ** Fil tr at io n f ra ct io n ( % ) 32 .7 ±4 .9 31 .1 ±5 .1 * 32 .2 ±4 .2 30 .0 ±4 .3 * 32 .2 ±3 .6 31 .1 ±4 .1 * 32 .8 ±3 .8 31. 2± 3. 8 ** 31. 9± 3. 8 30 .9± 3. 7 * Va ri ab le s ar e pr es en te d as m ea n ± SD . D iff er en ce s w er e te st ed w it h a pa ir ed t t es t . Ab br ev ia tion s a re : N , n um be r; A D PK D , a ut os om al d om in an t p ol yc ys ti c k id ne y di se as e; G FR , g lo m er ul ar fi lt ra tio n r at e. * p< 0. 05 b et w ee n p re d op am in e a nd d op am in e **p< 0. 00 1 b et w ee n pr e d op am in e a nd d op am in e
6
Figure 2. Kidney function reserve capacity (as percentage) in ADPKD patients and healthy
controls according to age group (upper panel) and CKD stage (lower panel). Data are expressed as Tukey boxplots with median, IQR, and minimum and maximum within 1.5 IQR and outliers.
*p<0.05 **p<0.001. Abbreviations are: ADPKD, autosomal dominant polycystic kidney disease;
Table 4. Possible determinants of kidney function reserve capacity and filtration fraction in
ADPKD patients (upper panel) and healthy controls (lower panel).
Kidney function reserve capacity (%) Filtration fraction (%) Univariable Multivariable Univariable Multivariable N β [CI] p-value β [CI] p-value β [CI] p-value β [CI] p-value ADPKD Male vs. female 150 [-4.7,1.7]-1.5 0.34 [-4.6,3.1]-0.8 0.70 [-2.1,0.7]-0.7 0.31 [-2.7,0.5]-1.1 0.17 Measured GFR (per 10 ml/ min/1.73m2) 150 [0.5,1.5] <0.0011.0 [0.05,1.6]0.8 0.04 [0.4,0.9] <0.0010.6 [0.3,0.9] <0.0010.6 PKD2 vs. PKD1 mutation 124 [-4.6,3.7]-0.4 0.84 [-4.8,4.0]-0.4 0.86 [-1.8,2.0]0.1 0.95 [-2.0,1.6]-0.2 0.85 htTKV (per doubling) 143 [-3.9,-0.8] 0.003-2.4 [-3.8,0.6]-1.6 0.15 [-1.1,0.3]-0.4 0.25 [-0.3,1.5]0.6 0.18 RAAS-inhibitor
use (yes vs. no) 150 [-5.3,1.5]-1.9 0.26 [-3.3,5.0]0.9 0.68 [-3.9,-1.0] 0.001-2.4 [-3.0,0.4]-1.3 0.12 BMI (per kg/m2) 150 0.1 [-0.3,0.4] 0.72 [-0.2,0.6]0.2 0.25 [-0.1,0.2]0.1 0.47 [-0.1,0.2]0.0 0.42 Protein intake (per 10 g/24hr) 147 [-0.6,0.8]0.1 0.74 [-0.7,1.1]0.2 0.63 [-0.1,0.5]0.2 0.30 [-0.4,0.3]-0.0 0.81 Sodium intake (per 10 mmol/24hr) 147 0.1 [-0.2,0.3] 0.71 [-0.4,0.3]-0.1 0.73 [0.1,0.3] <0.0010.2 [0.0,0.3]0.1 0.05 Healthy controls Male vs. female 150 [-2.9,2.7]-0.1 0.96 [-3.2,2.8]-0.2 0.89 [-1.1,1.4]0.1 0.83 [-1.3,1.5]0.1 0.91 Measured GFR (per 10 ml/ min/1.73m2) 150 [-2.3,-0.6] 0.001-1.5 [-2.4,-0.6] 0.002-1.5 [0.1,0.9]0.5 0.02 [0.1,0.9]0.5 0.03 RAAS-inhibitor
use (yes vs. no) 150 [-20.7,3.2]-8.8 0.15 [-20.0,4.5]-7.8 0.21 [-6.0,5.1]-0.4 0.88 [-7.1,4.3]-1.4 0.63 BMI (per kg/m2) 150 0.2 [-0.3,0.6] 0.47 [-0.4,0.5]0.03 0.91 [-0.2,0.2]0.0 0.84 [-0.1,0.3]0.1 0.42 Protein intake (per 10 g/24hr) 141 [-0.4,0.6]0.1 0.63 [-0.6,0.6]0.02 0.95 [-0.4,0.1]-0.2 0.17 [-0.5,0.0]-0.2 0.07 Sodium intake (per 10 mmol/24hr) 142 0.1 [-0.1,0.3] 0.53 [-0.1,0.3]0.1 0.31 [-0.1,0.1]0.0 0.75 [-0.1,0.1]0.0 0.50 Beta’s with confidence intervals and p-values were calculated using linear regression analysis with pairwise exclusion of missing data. Dependent variable is kidney function reserve capacity or filtration fraction, independent variables are sex, measured GFR, PKD mutation, htTKV, use of RAAS-inhibitors, BMI, protein intake and sodium intake. Abbreviations are: CI, 95% confidence interval; ADPKD, autosomal dominant polycystic kidney disease; GFR, glomerular filtration rate; PKD, polycystic kidney disease; htTKV, height adjusted total kidney volume; BMI, body mass index.
We investigated kidney function reserve capacity across the various Mayo height adjusted total kidney volume risk classes and across different PKD mutations. Although we found differences in kidney function reserve capacity between ADPKD patients and healthy controls, we found no differences in kidney function reserve capacity across these risk classes and mutation types in ADPKD patients (Figure S2).
When including only patients with a preserved kidney function (CKD stage 1 and 2, i.e. eGFR ≥60 ml/min/1.73m2, n=72) we also found no differences in kidney function
reserve capacity between fast progressors (Mayo height adjusted total kidney volume class 1C-E, n=47), slow progressors (Mayo height adjusted total kidney volume class 1A-B, n=25) and healthy controls (Figure 4).
Effective kidney plasma flow and filtration fraction
We repeated the analyses with our secondary measure of glomerular hyperfiltration; filtration fraction, defined as measured GFR/effective kidney plasma flow. Overall, effective kidney plasma flow was 203 ± 86 ml/min/1.73m2 in ADPKD patients and 318
± 55 ml/min/1.73m2 in healthy controls (p<0.001). Filtration fraction was comparable
between ADPKD patients and healthy controls (32.1 ± 4.3 versus 32.4 ± 3.9 % p=0.51). In older age groups, effective kidney plasma flow was lower in ADPKD patients and healthy controls, but in ADPKD patients the decrease in effective kidney plasma flow was more considerable. In ADPKD patients, we observed a lower filtration fraction at older age, whereas filtration fraction was similar at older age in healthy controls (Table 2). In the youngest age group and in CKD stage 1, effective kidney plasma flow was similar in ADPKD patients compared to healthy controls (Figure S3). Results with kidney blood flow and kidney vascular resistance were similar (Figure S4 and S5). Because measured GFR was also similar compared to healthy controls in the youngest age group, there was no difference in filtration fraction (33.5 ± 4.4 vs. 32.7 ± 4.9 %, p=0.62). In the other age groups, filtration fraction in ADPKD patients was also similar to healthy controls, with the age group 30-39 year filtration fraction being slightly higher, and in the age group 50-59 years filtration fraction being slightly lower than in healthy controls (Figure 3 upper panel). Filtration fraction decreased in ADPKD patients at higher CKD stages (Figure 3 lower panel).
Figure 3. Filtration fraction in ADPKD patients and healthy controls according to age group
(upper panel) and CKD stage (lower panel). Data are expressed as Tukey boxplots with median,
IQR, and minimum and maximum within 1.5 IQR and outliers. *p<0.05 **p<0.001. Abbreviations
are: ADPKD, autosomal dominant polycystic kidney disease; CKD, chronic kidney disease.
In ADPKD patients, measured GFR, use of RAAS-inhibitors and sodium intake were univariable associated with filtration fraction (β=0.6 [0.4, 0.9] % per 10 ml/min/1.73m2,
p<0.001, β=-2.4 [-3.9, -1.0] %, p=0.001 and β=0.2 [0.1, 0.3] % per 10 mmol/24hr, p<0.001 respectively). In the multivariable regression analysis measured GFR remained significantly associated with filtration fraction and the association of sodium intake with filtration fraction was borderline significant (β=0.6 [0.3, 0.9] % per 10 ml/min/1.73m2,
p<0.001 and β=0.1 [0.0, 0.3] % per 10 mmol/24hr, p=0.05, respectively) (Table 4). In the healthy controls only measured GFR was associated with filtration fraction in the univariable (β=0.5 [0.1, 0.9] % per 10 ml/min/1.73m2, p=0.02) as well as the multivariable
regression analysis (β=0.5 [0.1, 0.9] % per 10 ml/min/1.73m2, p=0.03) (Table 4).
As with kidney function reserve capacity, we found no differences in filtration fraction across risk classes of the Mayo height adjusted total kidney volume classification and across PKD mutations in ADPKD patients. In addition, filtration fraction was not different between healthy controls and ADPKD patients according to Mayo height adjusted total kidney volume class or PKD mutation (Figure S6).
When including only patients with a preserved kidney function (CKD stage 1 and 2, i.e. eGFR ≥60 ml/min/1.73m2, n=72) we also found no differences in filtration fraction
between fast progressors (Mayo height adjusted total kidney volume class 1C-E, n=47), slow progressors (Mayo height adjusted total kidney volume class 1A-B, n=25) and healthy controls (Figure 4, lower panel).
Figure 4. Kidney function reserve capacity (upper panel) and filtration fraction (lower panel)
in fast progressors (Mayo height adjusted total kidney volume class 1C-E) and slow progres-sors (Mayo height adjusted total kidney volume class 1A-B) in patients with CKD stage 1 and 2 (i.e. eGFR≥60ml/min/1.73m2). Data are expressed as Tukey boxplots with median, IQR, and
minimum and maximum within 1.5 IQR and outliers. Abbreviations are: htTKV, height adjusted total kidney volume; ADPKD, autosomal dominant polycystic kidney disease.
DISCUSSION
This study showed that ADPKD patients at a young age, despite having enlarged kidneys, have a GFR that is comparable to that of healthy controls at similar age. Remarkably, ADPKD patients in this age group had a normal level of kidney function reserve capacity as well as patients in early CKD stages. In older age groups and at later CKD stages, kidney function reserve capacity was lower compared to healthy controls. These results indicate that loss of kidney function reserve capacity is not an early phenomenon in ADPKD.
Franz et al., were the first to observe in a small group of subjects with ADPKD (n=44) that kidney function remains stable for decades before it deteriorates1. Later, Grantham
et al. hypothesized that this phenomenon is caused by compensatory hyperfiltration of the kidneys2. There are, however, few studies that sought to confirm or deny this
hypothesis. To date, these studies have been small and used an unstimulated elevated GFR above a certain value as definition for hyperfiltration in ADPKD patients. This is a definition used in patients with a healthy kidney function3, 15, 16. Whether this definition
can be used in patients with kidney disease is debatable. It is assumed that such patients hyperfilter to compensate for the loss of nephrons. In that case one would not expect GFR to become higher than in healthy controls. In addition, this definition makes it impossible to study hyperfiltration in later stages of the disease. A seminal study, performed in 180 children with ADPKD, found that hyperfiltration (defined as a creatinine clearance of ≥ 140 ml/min/1.73m2), present in 20% of children, was
associated with higher rates of growth in height adjusted total kidney volume and decline in creatinine clearance17. In this study kidney function was estimated using
creatinine clearance, which entails glomerular filtration as well as tubular secretion of creatinine. It has previously been shown that the tubular secretion of creatinine is higher in patients with ADPKD compared to healthy controls, especially in patients in the normal GFR range18. Therefore it cannot be excluded that the elevated creatinine
clearance in these children represents tubular dysfunction rather than glomerular hyperfiltration.
We used a gold standard technique with continuous infusion of 125I-iothalamate, to
measure GFR, and infused dopamine to determine kidney function reserve capacity19.
Several studies have shown a loss of kidney function reserve capacity, measured using infusion of a low dose of dopamine, in conditions where hyperfiltration is expected, such as in diabetes mellitus20 and after unilateral nephrectomy21. Loss of kidney
function reserve capacity is therefore an accepted definition of hyperfiltration, that, moreover, allows to study hyperfiltration at all stages of chronic kidney disease. In our study, GFR was similar in ADPKD patients compared to healthy controls in the youngest age group, despite considerable cyst burden. These results suggest that there is a compensation to account for the loss in kidney function that is assumed to occur due to the cyst formation. Yet, there was no loss of kidney function reserve capacity in the youngest age group of ADPKD patients when compared to healthy age and sex matched controls as well as in ADPKD patients with CKD stages 1 and 2. One might therefore conclude that there is no hyperfiltration in early ADPKD. This conclusion is corroborated by the fact that filtration fraction, another surrogate measure of hyperfiltration, was also not elevated at young age and early CKD stages. At older age, and in later CKD stages, kidney function reserve capacity was impaired suggesting that at later stage ADPKD there is indeed hyperfiltration. Taken together, these results suggest that there is no hyperfiltration in early stage ADPKD and that cyst formation in this stage does not lead to significant nephron loss. Therefore there may be a possibility that treatments that influence vascular tone, like RAAS-inhibitors, may not have a benefit over other blood pressure lowering agents in early stage ADPKD to prevent future kidney function decline. It may be that only when disease progresses, and cyst burden becomes even more prominent and other disease mechanisms come into play (like inflammation and fibrosis), nephrons are lost and compensatory hyperfiltration occurs.
As expected, a lower measured GFR was associated with a lower kidney function reserve capacity in ADPKD patients. Since we observed differences in kidney function reserve capacity between age groups, we tested whether there were determinants, other than disease severity (i.e. measured GFR or height adjusted total kidney volume), which could explain differences in kidney function reserve capacity and filtration fraction between ADPKD patients and healthy controls in the different age groups. Adjustment for RAAS-inhibitor use, BMI24, 25, sodium and urea excretion (as surrogates
for sodium intake and protein intake, respectively) did not materially change our results with respect to kidney function reserve capacity. However, we did observe that a higher sodium intake was associated with a higher filtration fraction in ADPKD patients, even after adjustment for sex, measured GFR, PKD mutation and height adjusted total kidney volume. This is in line with literature which shows that sodium intake affects kidney hemodynamics in subjects with CKD26, 27. No association was
found between sodium excretion and kidney function reserve capacity in healthy controls nor in ADPKD patients.
Importantly, since kidney function reserve capacity is not impaired early in the disease course, it cannot serve as an early biomarker for disease severity and risk of future disease progression in ADPKD. This is corroborated by the fact that kidney function reserve capacity was not different across Mayo height adjusted total kidney volume risk classes for future disease progression across the entire study population, nor in patients with early CKD stages, and across different types of PKD mutation.
Our study has some limitations. First, our study is cross-sectional in nature and we can therefore not draw conclusions about associations with disease progression. We used therefore a risk classification for future disease progression (based on kidney volume indexed for age) and investigated differences between PKD mutations to overcome this limitation. Second, it is not clear whether maximal kidney function reserve capacity is reached with dopamine alone. An increase in measured GFR can also be obtained with infusion of amino acids28. However, other authors found that
simultaneous infusion of dopamine and amino acids in patients with ADPKD did not lead to a significant increase in kidney function reserve capacity compared to infusion of dopamine alone.29. Third, our subjects did not consume a standardized diet prior
to the kidney function measurement. In our multivariable analyses we therefore adjusted for sodium and urea excretion, reliable measures for sodium and protein intake, respectively. These adjustments did not change the results. Strengths of our study are that we performed extensive kidney hemodynamic measurements with gold-standard methods to measure GFR, effective kidney plasma flow, kidney function reserve capacity and filtration fraction. Although the sample size of this study may seem small, a study with such extensive measurements has, as far as we are informed, never been performed. Therefore this study entails rather a relatively large population of ADPKD patients and healthy controls. In addition, information was available on other disease parameters like total kidney volume and PKD mutation analysis. In conclusion, ADPKD patients at young adult age or early CKD stages have a GFR in the normal range, and are still able to increase their GFR in response to dopamine. Hyperfiltration, measured as loss of kidney function reserve capacity, can therefore not be used as an early biomarker of disease severity. Filtration fraction was also not elevated. Taken together, these results suggest that there may be no hyperfiltration in early stage ADPKD.
DISCLOSURES
All authors stated not to have conflicts of interest.
ACKNOWLEDGEMENTS
The DIPAK Consortium is an inter-university collaboration in The Netherlands established to study Autosomal Dominant Polycystic Kidney Disease and to develop treatment strategies for this disease.
The DIPAK Consortium is sponsored by the Dutch Kidney Foundation (grants CP10.12 and CP15.01) and Dutch government (LSHM15018). For the present study, we acknowledge R.L. Kadijk for assistance at the outpatient clinic; R. Karsten-Barelds, D. Hesseling-Swaving and M. Vroom-Dallinga for their assistance during kidney function measurements; P. Kappert, J. Grozema and A. Sibeijn-Kuiper for assistance during MR imaging and T.L. Kline for measuring kidney volumes.
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SUPPLEMENTARY METHODS
Kidney function measurements and Kidney Function Reserve Capacity
After a loading dose of 20 mL NaCl 0.9% with 0.3 MBq 125I-iothalamate and 0.4 MBq 131I-hippuran, a continuous infusion consisting of 0.0075 MBq/ml 125I iothalamate and
0.02 MBq/ml 131I-hippuran was given at a rate of 9 mL/hr over 7.5 hours. During the
final two hours of this investigation, kidney function reserve capacity was determined by adding a constant infusion of dopamine of 4.4 mg/h in subjects less than 100 kg and 6.0 mg/h in subjects of 100 kg or more. The coefficient of variation is 2.5% for measured GFR and 5% for effective kidney plasma flow using this method13.
Infusion of a low dose of dopamine, by binding to specific dopaminergic vascular receptors in the kidney, causes vasodilatation of especially afferent arterioles. This results in an increase in single nephron blood flow. In addition, nephrons can be recruited which normally do not or only minimally contribute to the GFR. Both phenomena allow the kidney to utilize its full filtrating capacity, which in normal conditions results in an increase in GFR22, 23. When the kidney already utilizes its full
filtrating capacity, the GFR will not increase in response to dopamine, which indicates hyperfiltration.
Ta bl e S 1. Cl in ic al c ha ra ct er is tic s o f A D PK D p at ie nt s a nd m at ch ed h ea lth y c on tr ol s a cc or di ng t o a ge g ro up . A ge (y ear s) 18 -2 9 30 -39 40 -49 50 -59 ≥6 0 P f or t re n d Var iab le s A D PK D Con tro l A D PK D Con tro l A D PK D Con tro l A D PK D Con tro l A D PK D Con tro l A D PK D Con tro l N 17 17 26 26 41 41 50 50 16 16 -Fe m al e, n (% ) 12 (7 1) * 4 ( 24 ) 15 (5 8) 14 (5 4) 26 (6 3) 27 ( 66 ) 25 ( 50 ) 25 ( 50 ) 10 (6 3) 10 (6 3) 0. 33 0.1 2 A ge (yea rs ) 24 ±3 25± 3 36 ±3 35 ±3 45 ±3 45 ±3 55 ±3 54± 3 63± 4 63± 3 <0 .0 01 <0 .0 01 W ei gh t (k g) 79 .4 ±2 2.5 75 .9 ±1 1.9 85 .7 ±1 7. 5 81. 1± 14 .4 85 .8 ±1 9. 6 80 .1 ±1 0. 9 82 .4 ±1 6.1 83. 0± 13. 5 77. 7± 12 .9 81 .3 ±1 0. 7 0.6 2 0.1 8 He ig ht (cm ) 17 6± 11 17 7± 8 17 7± 11 17 7± 9 17 8±1 0 17 5± 9 17 6± 11 17 6±1 0 17 4± 8 17 2± 7 0. 50 0.0 8 BM I (k g/ m 2) 25. 5± 6. 2 24 .1 ±3 .9 27. 4± 5. 8 25 .7 ±3 .5 27. 0± 5. 1 26 .3 ±3 .0 26 .5± 3. 8 26 .6 ±2 .9 25 .8 ±3 .9 27. 3± 2. 6 0.9 0 0. 002 Sy st ol ic b lo od pr es su re (m m H g) 12 6±1 3 * 11 8± 9 12 8± 8 * 12 1±1 0 12 7± 12 * 12 2± 11 12 9±1 4 12 6± 12 12 7±1 5 12 6± 12 0. 80 0.0 08 Di as to lic b lood pr es su re (m m H g) 74 ±1 1 69 ±6 79 ±7 * 72 ±9 79 ±9 * 74 ±8 80± 10 77 ±8 73± 9 76 ±8 0.7 2 0. 002 A nt ih yp er te nsi ve us e, n (% ) 9 ( 53 ) ** 0 (0 .0) 15 (5 8) ** 2 (8) 32 ( 78 ) ** 0 (0 .0) 44 (8 8) ** 8 ( 16 ) 14 (8 8) ** 2 ( 13 ) <0 .0 01 0. 03 R A A S-in hi bi to r us e, n (% ) 9 ( 53 ) ** 0 (0 .0) 14 (5 4) ** 0 (0 .0) 30 ( 73 ) ** 0 (0 .0) 39 ( 78 ) ** 2 (4 ) 12 (75 .0) ** 0 (0 .0) 0. 02 0. 30 Pr ot ei n i nt ake (g /2 4h r) 76 ±2 0 85 ±1 7 93 ±2 5 88 ±23 90 ±21 93 ±3 9 85 ±2 5 94 ±2 9 75 ±1 6 82 ±1 6 0. 54 0.9 9 So diu m in ta ke (mm ol /2 4h r) 13 9± 66 18 3± 74 18 1± 58 20 4± 67 15 8± 58 186 ±9 2 15 5± 62 * 19 5± 71 14 0± 53 * 19 3± 72 0. 59 0. 84 eG FR (m l/ mi n/ 1. 73 m 2) 11 0± 22 11 3± 11 85 ±2 0 * 98 ±1 3 58± 25 ** 91 ±1 0 50 ±21 ** 86 ±1 2 34 .5 ±2 0. 7 ** 83 .1 ±1 3.1 <0 .0 01 <0 .0 01 CK D s ta ge , n ( % ) <0 .0 01 -- 1 13 (7 7) -8 ( 31) -5 ( 12 ) -1 ( 2) -0 (-0 .0) -- 2 4 ( 24 ) -16 (6 2) -13 (3 2) -16 (3 2) -3 ( 19 ) -- 3 A 0 (0 .0) -0 (-0 .0) -9 ( 22 ) -12 (2 4) -1 ( 6) -- 3 B 0 (0 .0) -2 (8) -7 ( 17 ) -11 (2 2) -3 ( 19 ) -- 4 0 (0 .0) -0 (-0 .0) -6 ( 15 ) -9 ( 18 ) -8 ( 50 ) -- 5 0 (0 .0) -0 (-0 .0) -1 ( 2) -1 ( 2) -1 ( 6)
-6
Ta bl e S 1. C on tin ue d. A ge (y ear s) 18 -2 9 30 -39 40 -49 50 -59 ≥6 0 P f or t re n d Var iab le s A D PK D Con tro l A D PK D Con tro l A D PK D Con tro l A D PK D Con tro l A D PK D Con tro l A D PK D Con tro l htT K V ( m l/ m ) 44 5 ( 34 7-74 9) -72 3 (4 86 -10 09 ) -929 (5 23 -1395 ) -11 21 (5 11 -15 05 ) -99 8 ( 50 7-13 62 ) -0. 03 -M ay o h tT K V cl as s, n ( % ) 0.0 06 -- 1A 0 (0 .0) -0 (-0 .0) -3 ( 7) -5 ( 10 ) -1 ( 6) -- 1B 2 ( 12 ) -4 ( 15 ) -8 ( 20 ) -13 (2 6) -4 ( 25 ) -- 1C 6 ( 35) -9 ( 35) -11 (2 7) -18 (3 6) -6 ( 38 ) -- 1D 1 ( 6) -7 ( 27 ) -13 (3 2) -8 ( 16 ) -1 ( 6) -- 1E 7 ( 41) -4 ( 15 ) -5 ( 12 ) -0 (-0 .0) -0 (-0 .0) -- 2 1 ( 6) -1 (4 ) -0 (-0 .0) -1 ( 2) -4 ( 25 ) -- M is sin g 0 (0 .0) -1 (4 ) -1 ( 2) -5 ( 10 ) -APK D m ut at io n 0.0 09 -PK D1 T , n ( % ) 8 (4 7) -16 (6 2) -13 (3 2) -16 (3 2) -8 ( 50 ) -PK D1 n -T , n ( % ) 5 ( 29 ) -4 ( 15 ) -16 (3 9) -11 (2 2) -5 ( 31) -PK D2 , n (%) 2 ( 12 ) -1 (4 ) -6 ( 15 ) -13 (2 6) -1 ( 6) -NMD , n (% ) 1 ( 6) -2 (8) -2 ( 5) -0 (-0 .0) -0 (-0 .0) -Mi ss in g, n (% ) 1 ( 6) -3 ( 12 ) -4 ( 10 ) -10 (2 0) -2 ( 13 ) -Va ri ab le s a re p re se nt ed as m ea n ± SD , o r a s m ed ia n (IQ R) in ca se o f n on -n or m al d is tr ib ut io n or o th er w is e s ta te d. P v al ue s a re o bt ai ne d us in g o ne -w ay A N O VA in ca se of n or m al d is tr ib ut io n, K ru sk al -W al lis t es t i n c as e o f n on -n or m al d is tr ib ut io n a nd l in ea r c hi -s qu ar ed t es t i n c as e o f c at eg or ic al d at a. Ab br ev ia tion s ar e: N , n um be r; A D PK D , a ut os om al do m in an t p ol yc ys tic ki dn ey di se as e; B M I, bo dy m as s in de x; eG FR , e st im at ed gl om er ul ar fil tr at io n ra te ; C KD , c hr on ic ki dn ey d is ea se ; h tT K V, h ei gh t a dj us te d t ot al k id ne y v ol um e; PK D, p ol yc ys tic k id ne y d is ea se ; T , t ru nc at in g; n -T , n on -t ru nc at in g; N M D , n o m ut at io n d et ec te d. * p< 0. 05 c om pa re d t o c on tr ol s am e a ge g ro up **p< 0. 00 1 c om pa re d t o c on tr ol s am e a ge g ro up
Figure S1. Absolute kidney function reserve capacity in ADPKD patients and healthy controls
according to age group (upper panel) and CKD stage (lower panel). Data are expressed as Tukey boxplots with median, IQR, and minimum and maximum within 1.5 IQR and outliers.
*p<0.05 **p<0.001. Abbreviations are: ADPKD, autosomal dominant polycystic kidney disease;
CKD, chronic kidney disease.
Figure S2. Kidney function reserve capacity (as percentage) according to Mayo height
adjust-ed total kidney volume class 1A-1E (upper panel) and PKD mutation (lower panel). Data are expressed as Tukey boxplots with median, IQR, and minimum and maximum within 1.5 IQR and outliers. *p<0.05 **p<0.001. Abbreviations are: htTKV, height adjusted total kidney volume;
ADPKD, autosomal dominant polycystic kidney disease; PKD, polycystic kidney disease; NMD, no mutation detected.
Figure S3. Effective kidney plasma flow in ADPKD patients and healthy controls according to age
group (upper panel) and CKD stage (lower panel). Data are expressed as Tukey boxplots with
median, IQR, and minimum and maximum within 1.5 IQR and outliers. *p<0.05 **p<0.001.
Abbre-viations are: ADPKD, autosomal dominant polycystic kidney disease; CKD, chronic kidney disease.
Figure S4. Kidney blood flow in ADPKD patients and healthy controls according to age group
(upper panel) and CKD stage (lower panel). Data are expressed as Tukey boxplots with median,
IQR, and minimum and maximum within 1.5 IQR and outliers. *p<0.05 **p<0.001. Abbreviations
Figure S5. Kidney vascular resistance in ADPKD patients and healthy controls according to age
group (upper panel) and CKD stage (lower panel). Data are expressed as Tukey boxplots with
median, IQR, and minimum and maximum within 1.5 IQR and outliers. *p<0.05 **p<0.001.
Abbre-viations are: ADPKD, autosomal dominant polycystic kidney disease; CKD, chronic kidney disease.
Figure S6. Filtration fraction according to Mayo height adjusted total kidney volume class
1A-1E (upper panel) and PKD mutation (lower panel). Data are expressed as Tukey boxplots with median, IQR, and minimum and maximum within 1.5 IQR and outliers. *p<0.05 **p<0.001.
Abbreviations are: htTKV, height adjusted total kidney volume; ADPKD, autosomal dominant polycystic kidney disease; PKD, polycystic kidney disease; NMD, no mutation detected.
