Vitamin D receptor activation raises soluble thrombomodulin levels in chronic kidney disease patients: a double blind, randomized trial

Vitamin D receptor activation raises soluble thrombomodulin levels in chronic kidney disease... Abstract Background Thrombomodulin (TM) is a proteoglycan highly represented in the endothelial glycocalix that regulates the haemostasis and the endothelial response to inflammation. High soluble TM levels underlie a lower risk for coronary heart disease in population studies. Activation of vitamin D receptor (VDR) upregulates TM, but the effect of this intervention on soluble TM has never been tested in chronic kidney disease (CKD) patients. Methods We performed a post hoc analysis of a 12 weeks double blind, randomized, placebo-controlled trial testing the effect of VDR activation by paricalcitol (PCT) on endothelium-dependent flow-mediated vasodilatation (FMD) in the forearm (ClinicalTrials.gov identifier: NCT01680198). Circulating TM was measured in the whole CKD population [88 patients: PCT n = 44; placebo n = 44] that took part into this trial. Results Soluble TM at baseline was inversely related to the glomerular filtration rate (r = −0.65, P < 0.001) and to FMD (Spearman’s ρ = −0.29, P = 0.01). Alongside the expected effects on bone mineral biomarkers, PCT produced a consistent rise (P = 0.005) in TM levels, from a median value of 8446.0 pg/mL [interquartile range (IQR): 6227.8–10 910.8 pg/mL] to 9127.5 pg/mL (6393.0–11 287.3 pg/mL) while placebo had no effect (between-groups difference P = 0.008). TM levels re-approached baseline values 2 weeks after stopping PCT. TM changes across the trial paralleled simultaneous changes in FMD. Conclusions VDR activation by PCT raises TM levels and FMD and such effects are rapidly reversible after stopping the treatment. The TM rise induced by PCT is a possible mechanism whereby improvement in endothelial function by VDR activation may favourably impact upon vascular health in CKD patients. cardiovascular, chronic kidney disease, endothelial function, thrombomodulin, thrombosis INTRODUCTION Endothelial dysfunction [1] and a pro-coagulant state [2] are considered as hallmarks of chronic kidney disease (CKD). Such disturbances are strongly interrelated, causally linked to inflammation [3] and predict a high risk of progression to kidney failure and cardiovascular events [4]. Among the several coagulation biomarkers that are deranged in CKD, circulating thrombomodulin (TM)—a large glycoprotein with a molecular weight of 74 000 Da—appears of almost unique interest because it is the one that shows the strongest association with the glomerular filtration rate (GFR) [5] in these patients. TM is highly represented in the endothelial glycocalix where it has a fundamental regulatory function for the endothelium-dependent response to inflammation [6, 7] and the coagulation cascade [7]. Endothelial-bound TM interacts with thrombin and Protein C to form a high-affinity complex that inhibits the interaction between thrombin and fibrinogen and protease-activated receptor-1. Due to the high representation of TM in the endothelium, under normal conditions the bulk of thrombin being generated rapidly combines with TM establishing a constitutive inhibition of the pro-coagulant function of thrombin. On the other hand, activation of Protein C by TM represents an essential anticoagulant mechanism [7]. High levels of circulating TM robustly associated with a lower risk for incident coronary heart disease in individuals without background cardiovascular disease in the Atherosclerosis Risk in the Community (ARIC) cohort [8]. Mineral disorders and altered vitamin D metabolism are exceedingly common in CKD [9]. The synthesis of 1,25-dihydroxy vitamin D (1,25VD) levels reduces early in the course of renal diseases and this alteration is increasingly severe as renal function deteriorates [9]. Interestingly, in human aortic smooth muscle cells and endothelial cells activation of vitamin D receptor (VDR) by 1,25VD or paricalcitol (PCT) upregulates the synthesis of TM [10] and recent studies show that this effect is not confined to the vascular system, but extends to the bone [11]. Treatment with a high dose of vitamin D3 increases the expression of the TM in elderly individuals with impaired glucose homeostasis [12] further highlighting the potential relevance of vitamin D in the regulation of this haemostatic factor by the endothelium. In a randomized trial, the Paricalcitol and ENdothelial fuNction in chronic kidneY disease (PENNY) study (ClinicalTrials.gov identifier: NCT01680198) [13] we showed that PCT treatment improves endothelial function as measured by the forearm blood flow-mediated vasodilatation (FMD) in response to ischaemia in CKD patients [13]. Studies in vitro [10] suggest that TM may be an integral part of the vasculo-protective effect of vitamin D. However, the question of whether VDR activation influences circulating levels of TM has not been investigated in human studies, either in CKD patients or in patients with diseases other than CKD. To test this hypothesis we performed a post hoc analysis in the PENNY trial by measuring circulating levels of soluble TM in the whole study population of this trial (no missing values). Furthermore, alongside TM, we also measured serum levels of two relevant pro-coagulant factors that have been reported to be affected by vitamin D treatment, namely plasminogen activator inhibitor-1 (PAI-1) [14] and thrombospondin-1 [10]. MATERIALS AND METHODS The protocol of the PENNY trial as well as the Consolidated Standards of Reporting Trials (CONSORT) flow diagram were reported in detail in the source study [13]. In brief, PENNY enroled Stage G3–4 CKD patients with age ranging between 18 and 80 years, intact parathyroid hormone (iPTH) >65 pg/mL, serum total calcium between 2.2 and 2.5 mmol/L and phosphate levels between 2.9 mg/dL and 4, 5 mg/dL who were not being treated with vitamin D compounds or anti-epileptic drugs, without neoplasia or symptomatic cardiovascular disease or liver disease. After baseline measurements, CKD patients were randomized (double blinded) to receive 2 µg PCT capsules (or matching placebo) daily, for 12 weeks. This dose was adjusted on the basis of serum iPTH and calcium and the maximum dose allowed was 2 μg daily. Biochemical measurements and GFR Serum calcium, phosphate, glucose, lipids were measured in the routine clinical pathology laboratory at our institution. Plasma PTH was measured by Immunoradiometric assay (DiaSorin Stillwater, MN, USA), 1,25VD by radioimmunoassay (Immunodiagnostic Systems, Boldon, UK) and FGF-23 by enzyme-linked immunosorbent assay (ELISA) (Kainos Laboratories, Bunkyo, Tokyo, Japan). Serum creatinine was measured by the Roche enzymatic, sotope dilution mass spectrometry calibrated, method and serum cystatin C by the Siemens Dade Behring kit, which is traceable to the International Federation of Clinical Chemistry Working Group for Standardization of serum cystatin C, and the GFR was calculated by the Chronic Kidney Disease Epidemiology Collaboration creatinine-cystatin formula [15]. Soluble TM, thrombospondin-1, PAI-1 and interleukin-6 (IL-6 HS) were measured by the human TM/BDCA-3, human thrombospondin-1, human IL-6, human serpin E1/PAI-1 Quantikine ELISA kits (R&D Systems, Ltd, Abingdon, UK) [16–19]. Total nitric oxide (NO) was measured by parameter total NO and Nitrate/Nitrite Kit (R&D Systems, Ltd) [20]. Measurements of these biomarkers were separately performed in single laboratory runs. The intra-assay precision of these measurements ranged from 2.3 to 3.6% for TM, from 6.0 to 6.7% for thrombospondin-1, from 4.4 to 7.8% for PAI-1, from 6.9 to 7.8 for IL-6 HS and from 1.4 to 2.5 for NO. Statistical analysis Data are reported as mean ± SD (normally distributed data), median and interquartile range (non-normally distributed data) or as per cent frequency. Between-groups comparisons were made by independent t-test, Mann–Whitney test, or Chi-Squared test, as appropriate. Within-groups comparisons were performed by paired t-test and Wilcoxon test. In the bidimensional space, outliers were identified by calculating the Mahalanobis distance [21]. To minimize the effect of outliers on the interrelationship between two variables considered simultaneously, we firstly log transformed (ln) the variable. In the case log transformation did not adequately minimize the influence of outliers, a rank transformation was applied. Thus, depending on data distribution, correlation analysis was performed either by calculating the Pearson’s r or the Spearman’s ρ (rank correlation). The relationships between TM with estimated GFR (eGFR) and FMD at baseline (cross-sectional analysis) were investigated by adjusting for age and gender [22]. The longitudinal association between repeated values of FMD and TM, i.e. measurements of these variables made at baseline and at the 12th week of treatment with PCT or placebo, was assessed by weighted regression analysis adjusting for age, gender and allocation arm. To assess the independent effect of PCT on soluble TM, changes in TM by the study treatments were adjusted for potential confounders [i.e. eGFR, fibroblast growth factor-23 (FGF-23) and treatment with calcium carbonate]. Potential modifiers of the effect of PCT on study outcomes were investigated by simultaneously introducing into the same model the allocation arm (0 = placebo; 1 = PCT), the candidate effect modifier and their multiplicative term. Along with the original analytical plan of the PENNY study [13], the effect of PCT on serum TM, thrombospondin-1 and PAI-1 levels was analysed by comparing the changes in these biomarkers brought about by PCT and placebo. Data analysis was performed by SPSS for Windows (version 22.0; IBM, NY, USA and IL, USA) and STATA (version 13, College Station, TX, USA). RESULTS Baseline values in the PCT and placebo groups did not show significant differences but the eGFR (which was tendentially higher, P = 0.06) and FGF-23 (which was tendentially lower, P = 0.07) in the PCT group (Table 1). Vitamin D insufficiency (>25 nmol/L and <75 nmol/L) or deficiency (<25 nmol/L) was present in the vast majority (95%) of patients with no between-group difference (42 patients in each group). At baseline, plasma levels of mineral metabolism biomarkers including serum calcium and phosphate, 25VD, 1,25VD and PTH were quite similar in the two study arms (Table 1). As detailed in the PENNY study [13], drug treatments, including angiotensin-converting enzyme inhibitors, sartans, hypoglicemizing agents, statins and proton-pump inhibitors did not differ in the two groups. However, calcium carbonate was more commonly used in patients on placebo (22.7%) than in those in the PCT arm (0%) (P = 0.003). TM, thrombospondin-1 and PAI-1 levels were comparable in the two groups (all P > 0.16) as was baseline FMD (Table 1). Table 1. Demographic, clinical, biochemical and vascular function characteristics of the two study arms at baseline   Active group  Placebo group  P-value  (n = 44)  (n = 44)  Age (years)  63 ± 11  62 ± 12  0.65  Male, sex (%)  59  70  0.27  Current smokers (%)  12  19  0.37  Past smokers (%)  45  41  0.66  Diabetes (%)  34  36  0.82  BMI (kg/m2)  29 ± 5  29 ± 5  0.66  Systolic BP (mmHg)  123 ± 16  129 ± 21  0.16  Diastolic BP (mmHg)  73 ± 9  73 ± 11  0.81  Heart rate (beats/min)  67 ± 8  68 ± 10  0.64  Red blood cells (106)  4.29 ± 0.62  4.08 ± 0.63  0.12  White blood cells (103)  6.39 ± 1.92  6.42 ± 1.57  0.95  Platelet counts (103)  226.3 ± 100.6  230.4 ± 56.3  0.81  Cholesterol (mg/dL)  164 ± 41  162 ± 43  0.84  HDL cholesterol (mg/dL)  47 ± 11  50 ± 13  0.18  LDL cholesterol (mg/dL)  88 ± 34  88 ± 36  0.91  eGFRCyst (mL/min/1.73 m2)  34 ± 12  29 ± 13  0.06  Haemoglobin (g/dL)  12.2 ± 1.8  12.0 ± 1.9  0.49  Calcium (mmol/L)  2.25 ± 0.12  2.21 ± 0.10  0.16  Phosphate (mmol/L)  1.20 ± 0.19  1.23 ± 0.16  0.29  PTH (pg/mL)  102 (81–146)  102 (85–154)  0.70  FGF-23 (pg/mL)  64.7 (52.7–81.2)  78.0 (53.7–103.1)  0.07  1,25VD (pmol/L)  101.4 ± 41.6  93.6 ± 41.8  0.32  25VD (nmol/L)  33 ± 16  38 ± 16  0.19  Total NO (µmol/L)  20.5 (13.4–35.6)  20.6 (11.8–41.3)  0.80  C-reactive protein (mg/L)  1.18 (0.68–3.02)  2.49 (0.99–3.74)  0.11  IL-6 (pg/mL)  3.2(2.0–5.6)  3.7(2.2–6.8)  0.37  TM (pg/mL)  8466.0 (6227.8–10 910.8)  9458.0 (7673.0–11 469.3)  0.16  Thrombospondin-1 (ng/mL)  10 857.3 ± 3077.8  10 609.4 ± 3487.9  0.72  PAI-1 (ng/mL)  1.5 (0.9–2.3)  1.4 (0.9–1.8)  0.77  FMD (%)  3.62 ± 2.93  3.65 ± 2.88  0.97    Active group  Placebo group  P-value  (n = 44)  (n = 44)  Age (years)  63 ± 11  62 ± 12  0.65  Male, sex (%)  59  70  0.27  Current smokers (%)  12  19  0.37  Past smokers (%)  45  41  0.66  Diabetes (%)  34  36  0.82  BMI (kg/m2)  29 ± 5  29 ± 5  0.66  Systolic BP (mmHg)  123 ± 16  129 ± 21  0.16  Diastolic BP (mmHg)  73 ± 9  73 ± 11  0.81  Heart rate (beats/min)  67 ± 8  68 ± 10  0.64  Red blood cells (106)  4.29 ± 0.62  4.08 ± 0.63  0.12  White blood cells (103)  6.39 ± 1.92  6.42 ± 1.57  0.95  Platelet counts (103)  226.3 ± 100.6  230.4 ± 56.3  0.81  Cholesterol (mg/dL)  164 ± 41  162 ± 43  0.84  HDL cholesterol (mg/dL)  47 ± 11  50 ± 13  0.18  LDL cholesterol (mg/dL)  88 ± 34  88 ± 36  0.91  eGFRCyst (mL/min/1.73 m2)  34 ± 12  29 ± 13  0.06  Haemoglobin (g/dL)  12.2 ± 1.8  12.0 ± 1.9  0.49  Calcium (mmol/L)  2.25 ± 0.12  2.21 ± 0.10  0.16  Phosphate (mmol/L)  1.20 ± 0.19  1.23 ± 0.16  0.29  PTH (pg/mL)  102 (81–146)  102 (85–154)  0.70  FGF-23 (pg/mL)  64.7 (52.7–81.2)  78.0 (53.7–103.1)  0.07  1,25VD (pmol/L)  101.4 ± 41.6  93.6 ± 41.8  0.32  25VD (nmol/L)  33 ± 16  38 ± 16  0.19  Total NO (µmol/L)  20.5 (13.4–35.6)  20.6 (11.8–41.3)  0.80  C-reactive protein (mg/L)  1.18 (0.68–3.02)  2.49 (0.99–3.74)  0.11  IL-6 (pg/mL)  3.2(2.0–5.6)  3.7(2.2–6.8)  0.37  TM (pg/mL)  8466.0 (6227.8–10 910.8)  9458.0 (7673.0–11 469.3)  0.16  Thrombospondin-1 (ng/mL)  10 857.3 ± 3077.8  10 609.4 ± 3487.9  0.72  PAI-1 (ng/mL)  1.5 (0.9–2.3)  1.4 (0.9–1.8)  0.77  FMD (%)  3.62 ± 2.93  3.65 ± 2.88  0.97  Data are expressed as mean ± SD, median and interquartile range or as per cent frequency as appropriate. BP, blood pressure; LDL, low-density lipoprotein; HDL, high-density lipoprotein. Table 1. Demographic, clinical, biochemical and vascular function characteristics of the two study arms at baseline   Active group  Placebo group  P-value  (n = 44)  (n = 44)  Age (years)  63 ± 11  62 ± 12  0.65  Male, sex (%)  59  70  0.27  Current smokers (%)  12  19  0.37  Past smokers (%)  45  41  0.66  Diabetes (%)  34  36  0.82  BMI (kg/m2)  29 ± 5  29 ± 5  0.66  Systolic BP (mmHg)  123 ± 16  129 ± 21  0.16  Diastolic BP (mmHg)  73 ± 9  73 ± 11  0.81  Heart rate (beats/min)  67 ± 8  68 ± 10  0.64  Red blood cells (106)  4.29 ± 0.62  4.08 ± 0.63  0.12  White blood cells (103)  6.39 ± 1.92  6.42 ± 1.57  0.95  Platelet counts (103)  226.3 ± 100.6  230.4 ± 56.3  0.81  Cholesterol (mg/dL)  164 ± 41  162 ± 43  0.84  HDL cholesterol (mg/dL)  47 ± 11  50 ± 13  0.18  LDL cholesterol (mg/dL)  88 ± 34  88 ± 36  0.91  eGFRCyst (mL/min/1.73 m2)  34 ± 12  29 ± 13  0.06  Haemoglobin (g/dL)  12.2 ± 1.8  12.0 ± 1.9  0.49  Calcium (mmol/L)  2.25 ± 0.12  2.21 ± 0.10  0.16  Phosphate (mmol/L)  1.20 ± 0.19  1.23 ± 0.16  0.29  PTH (pg/mL)  102 (81–146)  102 (85–154)  0.70  FGF-23 (pg/mL)  64.7 (52.7–81.2)  78.0 (53.7–103.1)  0.07  1,25VD (pmol/L)  101.4 ± 41.6  93.6 ± 41.8  0.32  25VD (nmol/L)  33 ± 16  38 ± 16  0.19  Total NO (µmol/L)  20.5 (13.4–35.6)  20.6 (11.8–41.3)  0.80  C-reactive protein (mg/L)  1.18 (0.68–3.02)  2.49 (0.99–3.74)  0.11  IL-6 (pg/mL)  3.2(2.0–5.6)  3.7(2.2–6.8)  0.37  TM (pg/mL)  8466.0 (6227.8–10 910.8)  9458.0 (7673.0–11 469.3)  0.16  Thrombospondin-1 (ng/mL)  10 857.3 ± 3077.8  10 609.4 ± 3487.9  0.72  PAI-1 (ng/mL)  1.5 (0.9–2.3)  1.4 (0.9–1.8)  0.77  FMD (%)  3.62 ± 2.93  3.65 ± 2.88  0.97    Active group  Placebo group  P-value  (n = 44)  (n = 44)  Age (years)  63 ± 11  62 ± 12  0.65  Male, sex (%)  59  70  0.27  Current smokers (%)  12  19  0.37  Past smokers (%)  45  41  0.66  Diabetes (%)  34  36  0.82  BMI (kg/m2)  29 ± 5  29 ± 5  0.66  Systolic BP (mmHg)  123 ± 16  129 ± 21  0.16  Diastolic BP (mmHg)  73 ± 9  73 ± 11  0.81  Heart rate (beats/min)  67 ± 8  68 ± 10  0.64  Red blood cells (106)  4.29 ± 0.62  4.08 ± 0.63  0.12  White blood cells (103)  6.39 ± 1.92  6.42 ± 1.57  0.95  Platelet counts (103)  226.3 ± 100.6  230.4 ± 56.3  0.81  Cholesterol (mg/dL)  164 ± 41  162 ± 43  0.84  HDL cholesterol (mg/dL)  47 ± 11  50 ± 13  0.18  LDL cholesterol (mg/dL)  88 ± 34  88 ± 36  0.91  eGFRCyst (mL/min/1.73 m2)  34 ± 12  29 ± 13  0.06  Haemoglobin (g/dL)  12.2 ± 1.8  12.0 ± 1.9  0.49  Calcium (mmol/L)  2.25 ± 0.12  2.21 ± 0.10  0.16  Phosphate (mmol/L)  1.20 ± 0.19  1.23 ± 0.16  0.29  PTH (pg/mL)  102 (81–146)  102 (85–154)  0.70  FGF-23 (pg/mL)  64.7 (52.7–81.2)  78.0 (53.7–103.1)  0.07  1,25VD (pmol/L)  101.4 ± 41.6  93.6 ± 41.8  0.32  25VD (nmol/L)  33 ± 16  38 ± 16  0.19  Total NO (µmol/L)  20.5 (13.4–35.6)  20.6 (11.8–41.3)  0.80  C-reactive protein (mg/L)  1.18 (0.68–3.02)  2.49 (0.99–3.74)  0.11  IL-6 (pg/mL)  3.2(2.0–5.6)  3.7(2.2–6.8)  0.37  TM (pg/mL)  8466.0 (6227.8–10 910.8)  9458.0 (7673.0–11 469.3)  0.16  Thrombospondin-1 (ng/mL)  10 857.3 ± 3077.8  10 609.4 ± 3487.9  0.72  PAI-1 (ng/mL)  1.5 (0.9–2.3)  1.4 (0.9–1.8)  0.77  FMD (%)  3.62 ± 2.93  3.65 ± 2.88  0.97  Data are expressed as mean ± SD, median and interquartile range or as per cent frequency as appropriate. BP, blood pressure; LDL, low-density lipoprotein; HDL, high-density lipoprotein. Relationship between TM and endothelial function and other functional links of TM with haemostasis biomarkers at baseline Soluble TM at baseline (n = 88) was inversely correlated with the GFR (r = −0.65, P < 0.001) and with FMD (ρ =−0.29, P = 0.006, ρ =−0.27, P = 0.01 calculated without an outlier) (Figure 1), implying that the release of the soluble form of this biomarker may underlie a protective response to endothelial dysfunction. Of note, these relationships held true in a multiple linear regression model adjusting for age and gender (soluble TM–eGFR link, β =−0.65, P < 0.001; soluble TM-FMD, β =−0.20, P = 0.01). Thrombospondin-1 and PAI-1 were unrelated to the GFR (P = 0.57 and P = 0.59, respectively). Neither thrombospondin-1 nor PAI-1 correlated with FMD (P = 0.28 and P = 0.71, respectively). Soluble TM did not correlate with thrombospondin-1 and PAI-1 levels (P = 0.13 and P = 0.39, respectively). FIGURE 1: View largeDownload slide Relationship between TM and the FMD. In the figure we report the Spearman’s ρ calculated in the whole population and after the exclusion of an apparent outlier (arrow). The lower panel shows the relationship between TM and the eGFR as estimated by the creatinine–cystatin method [15], data are Pearson product moment correlation coefficient and P-value. FIGURE 1: View largeDownload slide Relationship between TM and the FMD. In the figure we report the Spearman’s ρ calculated in the whole population and after the exclusion of an apparent outlier (arrow). The lower panel shows the relationship between TM and the eGFR as estimated by the creatinine–cystatin method [15], data are Pearson product moment correlation coefficient and P-value. Effect of PCT on TM and other haemostasis biomarkers After a 12-week treatment, PCT produced the expected effects on PTH, 1,25VD and FGF-23 levels (see Supplementary data, Figure SI and Zoccali et al. [13]), increased FMD by the 61% as compared with placebo (FMD at 12 weeks: PCT 4.5 ± 3.4%, placebo 2.8 ± 2.8, P = 0.013, Figure 2) and produced a small but statistically significant decline in the GFR (−3.8 mL/min/1.73 m2; 95% confidence interval from −5.2 to −2.5 mL/min/1.73 m2, P < 0.001). In parallel with the rise in FMD, VDR activation caused a consistent rise (P = 0.005) in TM levels, from a median value of 8446.0 pg/mL (IQR: 6227.8–10 910.8 pg/mL) to 9127.5 pg/mL (6393.0–11 287.3 pg/mL) (Figure 2) while placebo had no effect (P = 0.25) and the between-groups difference in median TM changes was highly significant (P = 0.008). These results remained substantially unchanged (between-groups difference, P = 0.01) after adjustment for the variables that differed at baseline between the study arms (P ≤ 0.10), i.e. eGFR, calcium carbonate treatment and FGF-23 (Supplementary data, Figure SII) as well as for changes in serum calcium and phosphate (P = 0.02). Effect modification analyses did not show any interaction of age, gender, baseline 25VD, 1,25VD, calcium, phosphate, PTH and FGF-23 on the TM response to PCT (P ranging from 0.13 to 0.98). In line with the TM–FMD relationship registered at baseline (Figure 1), in a global, longitudinal analysis including baseline and 12-week data, weighted for repeated intrasubject measurements and adjusting for age, gender, GFR and allocation arm, soluble TM again associated fairly well with FMD (β =−0.23, P = 0.003). Two weeks after stopping PCT, FMD and TM levels reverted to baseline levels (Figure 2) and TM declined from a median value of 9127.5 pg/mL (IQR: 6393.0–11 287.3 pg/mL) at the 12th week to a median value of 8619.0 pg/mL (IQR: 6241.0–10 678.0 pg/mL) at the 14th week, while the GFR reattained the baseline levels being almost identical in the two study arms (PCT versus placebo P = 0.71). TM remained again unchanged in the placebo arm (Figure 2). No changes in thrombospondin-1 and in PAI-1 levels were observed throughout in both study arms (Supplementary data, Figure SIII and Supplementary data, Table S1). By the same token, PCT treatment did not affect serum total NO levels, C-reactive protein and IL-6 levels (Supplementary data, Table S1). FIGURE 2: View largeDownload slide Effect of PCT and placebo on soluble TM levels. The grey area refers to values measured 2 weeks after having stopped the study interventions. TM data are given as median and interquartile range. FMD data are summarized as mean and SD. FIGURE 2: View largeDownload slide Effect of PCT and placebo on soluble TM levels. The grey area refers to values measured 2 weeks after having stopped the study interventions. TM data are given as median and interquartile range. FMD data are summarized as mean and SD. DISCUSSION In this placebo-controlled, randomized trial in CKD patients VDR activation by PCT produced a well-defined rise in soluble TM levels that was rapidly reversible after stopping treatment with this drug, while placebo had no effect on the same parameter. TM levels at baseline were strongly related to the GFR and associated with endothelium (NO)-dependent forearm blood flow (FMD) response to ischaemia. Furthermore, FMD and TM levels were coherently associated both at baseline and across the trial. Overall, these data suggest that the rise in soluble TM is an additional mechanism whereby improvement in endothelial function by VDR activation may favourably impact upon vascular health in CKD patients. TM is a large proteoglycan (74 000 Da) and as such it is filtered to a negligible extent at glomerular level. This molecule is shed from the endothelium surface in response to stimuli that perturb endothelial function, like inflammation [23]. As alluded to before, PCT upregulates the synthesis of TM [10] and the TM gene emerged as a vitamin D target in transcriptomic studies in a cohort of prediabetic Finnish individuals [12]. In the present study performed in the frame of a randomized clinical trial we show for the first time a meaningful rise in TM in response to PCT treatment in CKD patients, an effect that parallels the endothelium-dependent forearm blood flow response to ischaemia. Even though the biological implication of this observation remains undefined, estimates reported in the ARIC study suggest that the magnitude of the TM increase in the present study may underlie a mild-to-moderate decline in the risk for coronary artery disease events [8]. Like in previous studies [24] we found that TM is inversely related with the GFR, suggesting that TM shedding may be a counter-regulatory response to the several factors that alter endothelial function in CKD patients [1]. Of note, the GFR was not a confounder for the TM response to PCT because the same response remained highly significant also in analyses adjusting for the GFR and other factors. Due to its high molecular weight, TM is not filtered at glomerular level and urinary TM is completely independent of the GFR [24]. Thus, the TM rise following PCT treatment most likely reflects a class effect of VD receptor activation [10] on the endothelium. This interpretation is also supported by the fact that the TM rise went along with an increase in endothelium-dependent FMD and that both these responses reverted to pre-treatment levels after stopping PCT (Figure 2). At variance with an in vitro study [10], PAI-1 and thrombospondin-1 in our study were unaffected by PCT treatment. A discrepancy has been noted between in vitro and in vivo data concerning the effect of other interventions on PAI-1 levels, e.g. for insulin treatment [25]. Similarly, thrombospondin-1 serum levels do not reflect the levels of the same protein at tissue level in other chronic conditions like bronchopulmonary diseases [26]. The TM rise by PCT documented in the present study ought to be framed into a broader context considering the possible implication of this effect for adverse cardiovascular outcomes. As previously alluded to, high TM signals a lower risk for incident coronary heart disease in the general population, free of background cardiovascular events [9]. The cardiovascular protective effect of TM is supported by molecular genetic studies documenting that a complete loss of TM function in humans goes along with a very high risk for thrombotic complications including pulmonary embolism, cerebral venous sinus thrombosis and stroke [27]. In experimental models in the rabbit TM delivery to dilated femoral arteries reduces thrombus formation, inflammation and neo-intima formation [28]. Thus, if sustained in the long term, the TM rise by PCT registered in our 12-week trial may in theory contribute to the putatively protective effect of vitamin D, particularly active vitamin D forms like calcitriol and PCT, for all-cause and cardiovascular death registered in a meta-analysis including 20 cohort studies in CKD patients [29]. However, the hypothesis that vitamin D may prevent death and cardiovascular disease in vitamin D deficient subjects [30] and the corollary hypothesis that emerged in the present study that TM may contribute to avert death and cardiovascular disease in CKD still deserve to be tested into specifically designed clinical trials in this population. This study has limitations. First, it is post hoc analysis of a clinical trial stimulated by experimental studies in vitro [10] and by transcriptomic analyses in humans [12]. However, the fact that we performed our analyses in the whole database of a double-blind randomized trial with no missing sample for TM measurement is a strength. Second, TM is inversely related to the GFR and since PCT triggers minor, reversible changes in the GFR we cannot a priori exclude that these changes contributed to the TM rise by this drug. However, the quite small entity of the GFR changes (about 3 mL/min/1.73 m2) and the fact that adjustment for the GFR and other potential confounders had no virtual influence on the effect in question, makes it unlikely that the GFR was a confounder in our study. As alluded to before, TM is not filtered by the glomerulus and circulating TM is considered as an expression of the endothelial shedding of this proteoglycan both in Type 2 diabetes [24] and in CKD [31]. In conclusion, in a post hoc analysis in the PENNY trial in CKD patients, VDR activation by PCT raised TM levels as well as the endothelium-dependent vascular response to ischaemia, and such effects were rapidly reversible after stopping the treatment. The TM rise induced by PCT is a potential additional mechanism whereby improvement in endothelial function by VDR activation may favourably impact upon vascular health in CKD patients. Clinical studies based on meaningful clinical endpoints are needed to confirm and extend the relevance of the findings in the present study. SUPPLEMENTARY DATA Supplementary data are available at ndt online. FUNDING Our institution received funding by AbbVie for the PENNY study. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. AUTHORS’ CONTRIBUTIONS C.Z. conceived the study; G.D. performed the data analysis with G.T. and prepared the first draft of the article with C.Z.; P.P. and S.C. performed all laboratory analyses; F.M. participated into the clinical management of patients and contributed to the conception of the study. R.T. performed all FMD studies. All authors provided critical comments and significant intellectual contribution to the draft prepared by G.D. and C.Z. and approved the final version of the article. CONFLICT OF INTEREST STATEMENT None declared. The authors declare that there is no conflict of interest regarding the publication of this article. REFERENCES 1 Goligorsky MS. Pathogenesis of endothelial cell dysfunction in chronic kidney disease: a retrospective and what the future may hold. Kidney Res Clin Pract  2015; 34: 76– 82 Google Scholar CrossRef Search ADS PubMed  2 Lutz J, Menke J, Sollinger D et al.   Haemostasis in chronic kidney disease. Nephrol Dial Transplant  2014; 29: 29– 40 Google Scholar CrossRef Search ADS PubMed  3 Recio-Mayoral A, Banerjee D, Streather C et al.   Endothelial dysfunction, inflammation and atherosclerosis in chronic kidney disease–a cross-sectional study of predialysis, dialysis and kidney-transplantation patients. Atherosclerosis  2011; 216: 446– 451 Google Scholar CrossRef Search ADS PubMed  4 Fliser D, Wiecek A, Suleymanlar G et al.   The dysfunctional endothelium in CKD and in cardiovascular disease: mapping the origin(s) of cardiovascular problems in CKD and of kidney disease in cardiovascular conditions for a research agenda. Kidney Int Suppl  2011; 1: 6– 9 Google Scholar CrossRef Search ADS   5 Dubin R, Cushman M, Folsom AR et al.   Kidney function and multiple hemostatic markers: cross sectional associations in the multi-ethnic study of atherosclerosis. BMC Nephrol  2011; 12: 3 Google Scholar CrossRef Search ADS PubMed  6 Conway EM. Thrombomodulin and its role in inflammation. 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J Vasc Res  2007; 44: 11– 18 Google Scholar CrossRef Search ADS PubMed  11 Tarroni P, Villa I, Mrak E et al.   Microarray analysis of 1, 25(OH)2D3 regulated gene expression in human primary osteoblasts. J Cell Biochem  2012; 113: 640– 649 Google Scholar CrossRef Search ADS PubMed  12 Carlberg C, Seuter S, de Mello VDF et al.   Primary vitamin D target genes allow a categorization of possible benefits of vitamin D3 supplementation. PLoS One  2013; 8: e71042 Google Scholar CrossRef Search ADS PubMed  13 Zoccali C, Curatola G, Panuccio V et al.   Paricalcitol and endothelial function in chronic kidney disease trial. Hypertension  2014; 64: 1005– 1011 Google Scholar CrossRef Search ADS PubMed  14 Wu-Wong JR, Nakane M, Ma J. Effects of vitamin D analogs on the expression of plasminogen activator inhibitor-1 in human vascular cells. 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Anal Chim Acta  2013; 787: 1– 9 Google Scholar CrossRef Search ADS PubMed  22 Bland JM, Altman DG. Statistics notes: correlation, regression, and repeated data. BMJ  1994; 308: 896 Google Scholar CrossRef Search ADS PubMed  23 Boehme MW, Deng Y, Raeth U et al.   Release of thrombomodulin from endothelial cells by concerted action of TNF-alpha and neutrophils: in vivo and in vitro studies. Immunology  1996; 87: 134– 140 Google Scholar PubMed  24 Aso Y, Inukai T, Takemura Y. Mechanisms of elevation of serum and urinary concentrations of soluble thrombomodulin in diabetic patients: possible application as a marker for vascular endothelial injury. Metabolism  1998; 47: 362– 365 Google Scholar CrossRef Search ADS PubMed  25 Juhan-Vague I, Alessi MC, Vague P. Increased plasma plasminogen activator inhibitor 1 levels. A possible link between insulin resistance and atherothrombosis. Diabetologia  1991; 34: 457– 462 Google Scholar CrossRef Search ADS PubMed  26 Ide M, Ishii H, Mukae H et al.   High serum levels of thrombospondin-1 in patients with idiopathic interstitial pneumonia. Respir Med  2008; 102: 1625– 1630 Google Scholar CrossRef Search ADS PubMed  27 Glaser CB, Morser J, Clarke JH et al.   Oxidation of a specific methionine in thrombomodulin by activated neutrophil products blocks cofactor activity: a potential rapid mechanism for modulation of coagulation. J Clin Invest  1992; 90: 2565– 2573 Google Scholar CrossRef Search ADS PubMed  28 Waugh JM, Li-Hawkins J, Yuksel E et al.   Thrombomodulin overexpression to limit neointima formation. Circulation  2000; 102: 332– 337 Google Scholar CrossRef Search ADS PubMed  29 Zheng Z, Shi H, Jia J et al.   Vitamin D supplementation and mortality risk in chronic kidney disease: a meta-analysis of 20 observational studies. BMC Nephrol  2013; 14: 199 Google Scholar CrossRef Search ADS PubMed  30 Wimalawansa SJ. Vitamin D and cardiovascular diseases: causality. J Steroid Biochem Mol Biol  2018; 175: 29– 43 Google Scholar CrossRef Search ADS PubMed  31 Dane MJC, Khairoun M, Lee DH et al.   Association of kidney function with changes in the endothelial surface layer. Clin J Am Soc Nephrol  2014; 9: 698– 704 Google Scholar CrossRef Search ADS PubMed  © The Author(s) 2018. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Nephrology Dialysis Transplantation Oxford University Press

Vitamin D receptor activation raises soluble thrombomodulin levels in chronic kidney disease patients: a double blind, randomized trial

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Oxford University Press
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© The Author(s) 2018. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.
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0931-0509
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10.1093/ndt/gfy085
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Abstract

Abstract Background Thrombomodulin (TM) is a proteoglycan highly represented in the endothelial glycocalix that regulates the haemostasis and the endothelial response to inflammation. High soluble TM levels underlie a lower risk for coronary heart disease in population studies. Activation of vitamin D receptor (VDR) upregulates TM, but the effect of this intervention on soluble TM has never been tested in chronic kidney disease (CKD) patients. Methods We performed a post hoc analysis of a 12 weeks double blind, randomized, placebo-controlled trial testing the effect of VDR activation by paricalcitol (PCT) on endothelium-dependent flow-mediated vasodilatation (FMD) in the forearm (ClinicalTrials.gov identifier: NCT01680198). Circulating TM was measured in the whole CKD population [88 patients: PCT n = 44; placebo n = 44] that took part into this trial. Results Soluble TM at baseline was inversely related to the glomerular filtration rate (r = −0.65, P < 0.001) and to FMD (Spearman’s ρ = −0.29, P = 0.01). Alongside the expected effects on bone mineral biomarkers, PCT produced a consistent rise (P = 0.005) in TM levels, from a median value of 8446.0 pg/mL [interquartile range (IQR): 6227.8–10 910.8 pg/mL] to 9127.5 pg/mL (6393.0–11 287.3 pg/mL) while placebo had no effect (between-groups difference P = 0.008). TM levels re-approached baseline values 2 weeks after stopping PCT. TM changes across the trial paralleled simultaneous changes in FMD. Conclusions VDR activation by PCT raises TM levels and FMD and such effects are rapidly reversible after stopping the treatment. The TM rise induced by PCT is a possible mechanism whereby improvement in endothelial function by VDR activation may favourably impact upon vascular health in CKD patients. cardiovascular, chronic kidney disease, endothelial function, thrombomodulin, thrombosis INTRODUCTION Endothelial dysfunction [1] and a pro-coagulant state [2] are considered as hallmarks of chronic kidney disease (CKD). Such disturbances are strongly interrelated, causally linked to inflammation [3] and predict a high risk of progression to kidney failure and cardiovascular events [4]. Among the several coagulation biomarkers that are deranged in CKD, circulating thrombomodulin (TM)—a large glycoprotein with a molecular weight of 74 000 Da—appears of almost unique interest because it is the one that shows the strongest association with the glomerular filtration rate (GFR) [5] in these patients. TM is highly represented in the endothelial glycocalix where it has a fundamental regulatory function for the endothelium-dependent response to inflammation [6, 7] and the coagulation cascade [7]. Endothelial-bound TM interacts with thrombin and Protein C to form a high-affinity complex that inhibits the interaction between thrombin and fibrinogen and protease-activated receptor-1. Due to the high representation of TM in the endothelium, under normal conditions the bulk of thrombin being generated rapidly combines with TM establishing a constitutive inhibition of the pro-coagulant function of thrombin. On the other hand, activation of Protein C by TM represents an essential anticoagulant mechanism [7]. High levels of circulating TM robustly associated with a lower risk for incident coronary heart disease in individuals without background cardiovascular disease in the Atherosclerosis Risk in the Community (ARIC) cohort [8]. Mineral disorders and altered vitamin D metabolism are exceedingly common in CKD [9]. The synthesis of 1,25-dihydroxy vitamin D (1,25VD) levels reduces early in the course of renal diseases and this alteration is increasingly severe as renal function deteriorates [9]. Interestingly, in human aortic smooth muscle cells and endothelial cells activation of vitamin D receptor (VDR) by 1,25VD or paricalcitol (PCT) upregulates the synthesis of TM [10] and recent studies show that this effect is not confined to the vascular system, but extends to the bone [11]. Treatment with a high dose of vitamin D3 increases the expression of the TM in elderly individuals with impaired glucose homeostasis [12] further highlighting the potential relevance of vitamin D in the regulation of this haemostatic factor by the endothelium. In a randomized trial, the Paricalcitol and ENdothelial fuNction in chronic kidneY disease (PENNY) study (ClinicalTrials.gov identifier: NCT01680198) [13] we showed that PCT treatment improves endothelial function as measured by the forearm blood flow-mediated vasodilatation (FMD) in response to ischaemia in CKD patients [13]. Studies in vitro [10] suggest that TM may be an integral part of the vasculo-protective effect of vitamin D. However, the question of whether VDR activation influences circulating levels of TM has not been investigated in human studies, either in CKD patients or in patients with diseases other than CKD. To test this hypothesis we performed a post hoc analysis in the PENNY trial by measuring circulating levels of soluble TM in the whole study population of this trial (no missing values). Furthermore, alongside TM, we also measured serum levels of two relevant pro-coagulant factors that have been reported to be affected by vitamin D treatment, namely plasminogen activator inhibitor-1 (PAI-1) [14] and thrombospondin-1 [10]. MATERIALS AND METHODS The protocol of the PENNY trial as well as the Consolidated Standards of Reporting Trials (CONSORT) flow diagram were reported in detail in the source study [13]. In brief, PENNY enroled Stage G3–4 CKD patients with age ranging between 18 and 80 years, intact parathyroid hormone (iPTH) >65 pg/mL, serum total calcium between 2.2 and 2.5 mmol/L and phosphate levels between 2.9 mg/dL and 4, 5 mg/dL who were not being treated with vitamin D compounds or anti-epileptic drugs, without neoplasia or symptomatic cardiovascular disease or liver disease. After baseline measurements, CKD patients were randomized (double blinded) to receive 2 µg PCT capsules (or matching placebo) daily, for 12 weeks. This dose was adjusted on the basis of serum iPTH and calcium and the maximum dose allowed was 2 μg daily. Biochemical measurements and GFR Serum calcium, phosphate, glucose, lipids were measured in the routine clinical pathology laboratory at our institution. Plasma PTH was measured by Immunoradiometric assay (DiaSorin Stillwater, MN, USA), 1,25VD by radioimmunoassay (Immunodiagnostic Systems, Boldon, UK) and FGF-23 by enzyme-linked immunosorbent assay (ELISA) (Kainos Laboratories, Bunkyo, Tokyo, Japan). Serum creatinine was measured by the Roche enzymatic, sotope dilution mass spectrometry calibrated, method and serum cystatin C by the Siemens Dade Behring kit, which is traceable to the International Federation of Clinical Chemistry Working Group for Standardization of serum cystatin C, and the GFR was calculated by the Chronic Kidney Disease Epidemiology Collaboration creatinine-cystatin formula [15]. Soluble TM, thrombospondin-1, PAI-1 and interleukin-6 (IL-6 HS) were measured by the human TM/BDCA-3, human thrombospondin-1, human IL-6, human serpin E1/PAI-1 Quantikine ELISA kits (R&D Systems, Ltd, Abingdon, UK) [16–19]. Total nitric oxide (NO) was measured by parameter total NO and Nitrate/Nitrite Kit (R&D Systems, Ltd) [20]. Measurements of these biomarkers were separately performed in single laboratory runs. The intra-assay precision of these measurements ranged from 2.3 to 3.6% for TM, from 6.0 to 6.7% for thrombospondin-1, from 4.4 to 7.8% for PAI-1, from 6.9 to 7.8 for IL-6 HS and from 1.4 to 2.5 for NO. Statistical analysis Data are reported as mean ± SD (normally distributed data), median and interquartile range (non-normally distributed data) or as per cent frequency. Between-groups comparisons were made by independent t-test, Mann–Whitney test, or Chi-Squared test, as appropriate. Within-groups comparisons were performed by paired t-test and Wilcoxon test. In the bidimensional space, outliers were identified by calculating the Mahalanobis distance [21]. To minimize the effect of outliers on the interrelationship between two variables considered simultaneously, we firstly log transformed (ln) the variable. In the case log transformation did not adequately minimize the influence of outliers, a rank transformation was applied. Thus, depending on data distribution, correlation analysis was performed either by calculating the Pearson’s r or the Spearman’s ρ (rank correlation). The relationships between TM with estimated GFR (eGFR) and FMD at baseline (cross-sectional analysis) were investigated by adjusting for age and gender [22]. The longitudinal association between repeated values of FMD and TM, i.e. measurements of these variables made at baseline and at the 12th week of treatment with PCT or placebo, was assessed by weighted regression analysis adjusting for age, gender and allocation arm. To assess the independent effect of PCT on soluble TM, changes in TM by the study treatments were adjusted for potential confounders [i.e. eGFR, fibroblast growth factor-23 (FGF-23) and treatment with calcium carbonate]. Potential modifiers of the effect of PCT on study outcomes were investigated by simultaneously introducing into the same model the allocation arm (0 = placebo; 1 = PCT), the candidate effect modifier and their multiplicative term. Along with the original analytical plan of the PENNY study [13], the effect of PCT on serum TM, thrombospondin-1 and PAI-1 levels was analysed by comparing the changes in these biomarkers brought about by PCT and placebo. Data analysis was performed by SPSS for Windows (version 22.0; IBM, NY, USA and IL, USA) and STATA (version 13, College Station, TX, USA). RESULTS Baseline values in the PCT and placebo groups did not show significant differences but the eGFR (which was tendentially higher, P = 0.06) and FGF-23 (which was tendentially lower, P = 0.07) in the PCT group (Table 1). Vitamin D insufficiency (>25 nmol/L and <75 nmol/L) or deficiency (<25 nmol/L) was present in the vast majority (95%) of patients with no between-group difference (42 patients in each group). At baseline, plasma levels of mineral metabolism biomarkers including serum calcium and phosphate, 25VD, 1,25VD and PTH were quite similar in the two study arms (Table 1). As detailed in the PENNY study [13], drug treatments, including angiotensin-converting enzyme inhibitors, sartans, hypoglicemizing agents, statins and proton-pump inhibitors did not differ in the two groups. However, calcium carbonate was more commonly used in patients on placebo (22.7%) than in those in the PCT arm (0%) (P = 0.003). TM, thrombospondin-1 and PAI-1 levels were comparable in the two groups (all P > 0.16) as was baseline FMD (Table 1). Table 1. Demographic, clinical, biochemical and vascular function characteristics of the two study arms at baseline   Active group  Placebo group  P-value  (n = 44)  (n = 44)  Age (years)  63 ± 11  62 ± 12  0.65  Male, sex (%)  59  70  0.27  Current smokers (%)  12  19  0.37  Past smokers (%)  45  41  0.66  Diabetes (%)  34  36  0.82  BMI (kg/m2)  29 ± 5  29 ± 5  0.66  Systolic BP (mmHg)  123 ± 16  129 ± 21  0.16  Diastolic BP (mmHg)  73 ± 9  73 ± 11  0.81  Heart rate (beats/min)  67 ± 8  68 ± 10  0.64  Red blood cells (106)  4.29 ± 0.62  4.08 ± 0.63  0.12  White blood cells (103)  6.39 ± 1.92  6.42 ± 1.57  0.95  Platelet counts (103)  226.3 ± 100.6  230.4 ± 56.3  0.81  Cholesterol (mg/dL)  164 ± 41  162 ± 43  0.84  HDL cholesterol (mg/dL)  47 ± 11  50 ± 13  0.18  LDL cholesterol (mg/dL)  88 ± 34  88 ± 36  0.91  eGFRCyst (mL/min/1.73 m2)  34 ± 12  29 ± 13  0.06  Haemoglobin (g/dL)  12.2 ± 1.8  12.0 ± 1.9  0.49  Calcium (mmol/L)  2.25 ± 0.12  2.21 ± 0.10  0.16  Phosphate (mmol/L)  1.20 ± 0.19  1.23 ± 0.16  0.29  PTH (pg/mL)  102 (81–146)  102 (85–154)  0.70  FGF-23 (pg/mL)  64.7 (52.7–81.2)  78.0 (53.7–103.1)  0.07  1,25VD (pmol/L)  101.4 ± 41.6  93.6 ± 41.8  0.32  25VD (nmol/L)  33 ± 16  38 ± 16  0.19  Total NO (µmol/L)  20.5 (13.4–35.6)  20.6 (11.8–41.3)  0.80  C-reactive protein (mg/L)  1.18 (0.68–3.02)  2.49 (0.99–3.74)  0.11  IL-6 (pg/mL)  3.2(2.0–5.6)  3.7(2.2–6.8)  0.37  TM (pg/mL)  8466.0 (6227.8–10 910.8)  9458.0 (7673.0–11 469.3)  0.16  Thrombospondin-1 (ng/mL)  10 857.3 ± 3077.8  10 609.4 ± 3487.9  0.72  PAI-1 (ng/mL)  1.5 (0.9–2.3)  1.4 (0.9–1.8)  0.77  FMD (%)  3.62 ± 2.93  3.65 ± 2.88  0.97    Active group  Placebo group  P-value  (n = 44)  (n = 44)  Age (years)  63 ± 11  62 ± 12  0.65  Male, sex (%)  59  70  0.27  Current smokers (%)  12  19  0.37  Past smokers (%)  45  41  0.66  Diabetes (%)  34  36  0.82  BMI (kg/m2)  29 ± 5  29 ± 5  0.66  Systolic BP (mmHg)  123 ± 16  129 ± 21  0.16  Diastolic BP (mmHg)  73 ± 9  73 ± 11  0.81  Heart rate (beats/min)  67 ± 8  68 ± 10  0.64  Red blood cells (106)  4.29 ± 0.62  4.08 ± 0.63  0.12  White blood cells (103)  6.39 ± 1.92  6.42 ± 1.57  0.95  Platelet counts (103)  226.3 ± 100.6  230.4 ± 56.3  0.81  Cholesterol (mg/dL)  164 ± 41  162 ± 43  0.84  HDL cholesterol (mg/dL)  47 ± 11  50 ± 13  0.18  LDL cholesterol (mg/dL)  88 ± 34  88 ± 36  0.91  eGFRCyst (mL/min/1.73 m2)  34 ± 12  29 ± 13  0.06  Haemoglobin (g/dL)  12.2 ± 1.8  12.0 ± 1.9  0.49  Calcium (mmol/L)  2.25 ± 0.12  2.21 ± 0.10  0.16  Phosphate (mmol/L)  1.20 ± 0.19  1.23 ± 0.16  0.29  PTH (pg/mL)  102 (81–146)  102 (85–154)  0.70  FGF-23 (pg/mL)  64.7 (52.7–81.2)  78.0 (53.7–103.1)  0.07  1,25VD (pmol/L)  101.4 ± 41.6  93.6 ± 41.8  0.32  25VD (nmol/L)  33 ± 16  38 ± 16  0.19  Total NO (µmol/L)  20.5 (13.4–35.6)  20.6 (11.8–41.3)  0.80  C-reactive protein (mg/L)  1.18 (0.68–3.02)  2.49 (0.99–3.74)  0.11  IL-6 (pg/mL)  3.2(2.0–5.6)  3.7(2.2–6.8)  0.37  TM (pg/mL)  8466.0 (6227.8–10 910.8)  9458.0 (7673.0–11 469.3)  0.16  Thrombospondin-1 (ng/mL)  10 857.3 ± 3077.8  10 609.4 ± 3487.9  0.72  PAI-1 (ng/mL)  1.5 (0.9–2.3)  1.4 (0.9–1.8)  0.77  FMD (%)  3.62 ± 2.93  3.65 ± 2.88  0.97  Data are expressed as mean ± SD, median and interquartile range or as per cent frequency as appropriate. BP, blood pressure; LDL, low-density lipoprotein; HDL, high-density lipoprotein. Table 1. Demographic, clinical, biochemical and vascular function characteristics of the two study arms at baseline   Active group  Placebo group  P-value  (n = 44)  (n = 44)  Age (years)  63 ± 11  62 ± 12  0.65  Male, sex (%)  59  70  0.27  Current smokers (%)  12  19  0.37  Past smokers (%)  45  41  0.66  Diabetes (%)  34  36  0.82  BMI (kg/m2)  29 ± 5  29 ± 5  0.66  Systolic BP (mmHg)  123 ± 16  129 ± 21  0.16  Diastolic BP (mmHg)  73 ± 9  73 ± 11  0.81  Heart rate (beats/min)  67 ± 8  68 ± 10  0.64  Red blood cells (106)  4.29 ± 0.62  4.08 ± 0.63  0.12  White blood cells (103)  6.39 ± 1.92  6.42 ± 1.57  0.95  Platelet counts (103)  226.3 ± 100.6  230.4 ± 56.3  0.81  Cholesterol (mg/dL)  164 ± 41  162 ± 43  0.84  HDL cholesterol (mg/dL)  47 ± 11  50 ± 13  0.18  LDL cholesterol (mg/dL)  88 ± 34  88 ± 36  0.91  eGFRCyst (mL/min/1.73 m2)  34 ± 12  29 ± 13  0.06  Haemoglobin (g/dL)  12.2 ± 1.8  12.0 ± 1.9  0.49  Calcium (mmol/L)  2.25 ± 0.12  2.21 ± 0.10  0.16  Phosphate (mmol/L)  1.20 ± 0.19  1.23 ± 0.16  0.29  PTH (pg/mL)  102 (81–146)  102 (85–154)  0.70  FGF-23 (pg/mL)  64.7 (52.7–81.2)  78.0 (53.7–103.1)  0.07  1,25VD (pmol/L)  101.4 ± 41.6  93.6 ± 41.8  0.32  25VD (nmol/L)  33 ± 16  38 ± 16  0.19  Total NO (µmol/L)  20.5 (13.4–35.6)  20.6 (11.8–41.3)  0.80  C-reactive protein (mg/L)  1.18 (0.68–3.02)  2.49 (0.99–3.74)  0.11  IL-6 (pg/mL)  3.2(2.0–5.6)  3.7(2.2–6.8)  0.37  TM (pg/mL)  8466.0 (6227.8–10 910.8)  9458.0 (7673.0–11 469.3)  0.16  Thrombospondin-1 (ng/mL)  10 857.3 ± 3077.8  10 609.4 ± 3487.9  0.72  PAI-1 (ng/mL)  1.5 (0.9–2.3)  1.4 (0.9–1.8)  0.77  FMD (%)  3.62 ± 2.93  3.65 ± 2.88  0.97    Active group  Placebo group  P-value  (n = 44)  (n = 44)  Age (years)  63 ± 11  62 ± 12  0.65  Male, sex (%)  59  70  0.27  Current smokers (%)  12  19  0.37  Past smokers (%)  45  41  0.66  Diabetes (%)  34  36  0.82  BMI (kg/m2)  29 ± 5  29 ± 5  0.66  Systolic BP (mmHg)  123 ± 16  129 ± 21  0.16  Diastolic BP (mmHg)  73 ± 9  73 ± 11  0.81  Heart rate (beats/min)  67 ± 8  68 ± 10  0.64  Red blood cells (106)  4.29 ± 0.62  4.08 ± 0.63  0.12  White blood cells (103)  6.39 ± 1.92  6.42 ± 1.57  0.95  Platelet counts (103)  226.3 ± 100.6  230.4 ± 56.3  0.81  Cholesterol (mg/dL)  164 ± 41  162 ± 43  0.84  HDL cholesterol (mg/dL)  47 ± 11  50 ± 13  0.18  LDL cholesterol (mg/dL)  88 ± 34  88 ± 36  0.91  eGFRCyst (mL/min/1.73 m2)  34 ± 12  29 ± 13  0.06  Haemoglobin (g/dL)  12.2 ± 1.8  12.0 ± 1.9  0.49  Calcium (mmol/L)  2.25 ± 0.12  2.21 ± 0.10  0.16  Phosphate (mmol/L)  1.20 ± 0.19  1.23 ± 0.16  0.29  PTH (pg/mL)  102 (81–146)  102 (85–154)  0.70  FGF-23 (pg/mL)  64.7 (52.7–81.2)  78.0 (53.7–103.1)  0.07  1,25VD (pmol/L)  101.4 ± 41.6  93.6 ± 41.8  0.32  25VD (nmol/L)  33 ± 16  38 ± 16  0.19  Total NO (µmol/L)  20.5 (13.4–35.6)  20.6 (11.8–41.3)  0.80  C-reactive protein (mg/L)  1.18 (0.68–3.02)  2.49 (0.99–3.74)  0.11  IL-6 (pg/mL)  3.2(2.0–5.6)  3.7(2.2–6.8)  0.37  TM (pg/mL)  8466.0 (6227.8–10 910.8)  9458.0 (7673.0–11 469.3)  0.16  Thrombospondin-1 (ng/mL)  10 857.3 ± 3077.8  10 609.4 ± 3487.9  0.72  PAI-1 (ng/mL)  1.5 (0.9–2.3)  1.4 (0.9–1.8)  0.77  FMD (%)  3.62 ± 2.93  3.65 ± 2.88  0.97  Data are expressed as mean ± SD, median and interquartile range or as per cent frequency as appropriate. BP, blood pressure; LDL, low-density lipoprotein; HDL, high-density lipoprotein. Relationship between TM and endothelial function and other functional links of TM with haemostasis biomarkers at baseline Soluble TM at baseline (n = 88) was inversely correlated with the GFR (r = −0.65, P < 0.001) and with FMD (ρ =−0.29, P = 0.006, ρ =−0.27, P = 0.01 calculated without an outlier) (Figure 1), implying that the release of the soluble form of this biomarker may underlie a protective response to endothelial dysfunction. Of note, these relationships held true in a multiple linear regression model adjusting for age and gender (soluble TM–eGFR link, β =−0.65, P < 0.001; soluble TM-FMD, β =−0.20, P = 0.01). Thrombospondin-1 and PAI-1 were unrelated to the GFR (P = 0.57 and P = 0.59, respectively). Neither thrombospondin-1 nor PAI-1 correlated with FMD (P = 0.28 and P = 0.71, respectively). Soluble TM did not correlate with thrombospondin-1 and PAI-1 levels (P = 0.13 and P = 0.39, respectively). FIGURE 1: View largeDownload slide Relationship between TM and the FMD. In the figure we report the Spearman’s ρ calculated in the whole population and after the exclusion of an apparent outlier (arrow). The lower panel shows the relationship between TM and the eGFR as estimated by the creatinine–cystatin method [15], data are Pearson product moment correlation coefficient and P-value. FIGURE 1: View largeDownload slide Relationship between TM and the FMD. In the figure we report the Spearman’s ρ calculated in the whole population and after the exclusion of an apparent outlier (arrow). The lower panel shows the relationship between TM and the eGFR as estimated by the creatinine–cystatin method [15], data are Pearson product moment correlation coefficient and P-value. Effect of PCT on TM and other haemostasis biomarkers After a 12-week treatment, PCT produced the expected effects on PTH, 1,25VD and FGF-23 levels (see Supplementary data, Figure SI and Zoccali et al. [13]), increased FMD by the 61% as compared with placebo (FMD at 12 weeks: PCT 4.5 ± 3.4%, placebo 2.8 ± 2.8, P = 0.013, Figure 2) and produced a small but statistically significant decline in the GFR (−3.8 mL/min/1.73 m2; 95% confidence interval from −5.2 to −2.5 mL/min/1.73 m2, P < 0.001). In parallel with the rise in FMD, VDR activation caused a consistent rise (P = 0.005) in TM levels, from a median value of 8446.0 pg/mL (IQR: 6227.8–10 910.8 pg/mL) to 9127.5 pg/mL (6393.0–11 287.3 pg/mL) (Figure 2) while placebo had no effect (P = 0.25) and the between-groups difference in median TM changes was highly significant (P = 0.008). These results remained substantially unchanged (between-groups difference, P = 0.01) after adjustment for the variables that differed at baseline between the study arms (P ≤ 0.10), i.e. eGFR, calcium carbonate treatment and FGF-23 (Supplementary data, Figure SII) as well as for changes in serum calcium and phosphate (P = 0.02). Effect modification analyses did not show any interaction of age, gender, baseline 25VD, 1,25VD, calcium, phosphate, PTH and FGF-23 on the TM response to PCT (P ranging from 0.13 to 0.98). In line with the TM–FMD relationship registered at baseline (Figure 1), in a global, longitudinal analysis including baseline and 12-week data, weighted for repeated intrasubject measurements and adjusting for age, gender, GFR and allocation arm, soluble TM again associated fairly well with FMD (β =−0.23, P = 0.003). Two weeks after stopping PCT, FMD and TM levels reverted to baseline levels (Figure 2) and TM declined from a median value of 9127.5 pg/mL (IQR: 6393.0–11 287.3 pg/mL) at the 12th week to a median value of 8619.0 pg/mL (IQR: 6241.0–10 678.0 pg/mL) at the 14th week, while the GFR reattained the baseline levels being almost identical in the two study arms (PCT versus placebo P = 0.71). TM remained again unchanged in the placebo arm (Figure 2). No changes in thrombospondin-1 and in PAI-1 levels were observed throughout in both study arms (Supplementary data, Figure SIII and Supplementary data, Table S1). By the same token, PCT treatment did not affect serum total NO levels, C-reactive protein and IL-6 levels (Supplementary data, Table S1). FIGURE 2: View largeDownload slide Effect of PCT and placebo on soluble TM levels. The grey area refers to values measured 2 weeks after having stopped the study interventions. TM data are given as median and interquartile range. FMD data are summarized as mean and SD. FIGURE 2: View largeDownload slide Effect of PCT and placebo on soluble TM levels. The grey area refers to values measured 2 weeks after having stopped the study interventions. TM data are given as median and interquartile range. FMD data are summarized as mean and SD. DISCUSSION In this placebo-controlled, randomized trial in CKD patients VDR activation by PCT produced a well-defined rise in soluble TM levels that was rapidly reversible after stopping treatment with this drug, while placebo had no effect on the same parameter. TM levels at baseline were strongly related to the GFR and associated with endothelium (NO)-dependent forearm blood flow (FMD) response to ischaemia. Furthermore, FMD and TM levels were coherently associated both at baseline and across the trial. Overall, these data suggest that the rise in soluble TM is an additional mechanism whereby improvement in endothelial function by VDR activation may favourably impact upon vascular health in CKD patients. TM is a large proteoglycan (74 000 Da) and as such it is filtered to a negligible extent at glomerular level. This molecule is shed from the endothelium surface in response to stimuli that perturb endothelial function, like inflammation [23]. As alluded to before, PCT upregulates the synthesis of TM [10] and the TM gene emerged as a vitamin D target in transcriptomic studies in a cohort of prediabetic Finnish individuals [12]. In the present study performed in the frame of a randomized clinical trial we show for the first time a meaningful rise in TM in response to PCT treatment in CKD patients, an effect that parallels the endothelium-dependent forearm blood flow response to ischaemia. Even though the biological implication of this observation remains undefined, estimates reported in the ARIC study suggest that the magnitude of the TM increase in the present study may underlie a mild-to-moderate decline in the risk for coronary artery disease events [8]. Like in previous studies [24] we found that TM is inversely related with the GFR, suggesting that TM shedding may be a counter-regulatory response to the several factors that alter endothelial function in CKD patients [1]. Of note, the GFR was not a confounder for the TM response to PCT because the same response remained highly significant also in analyses adjusting for the GFR and other factors. Due to its high molecular weight, TM is not filtered at glomerular level and urinary TM is completely independent of the GFR [24]. Thus, the TM rise following PCT treatment most likely reflects a class effect of VD receptor activation [10] on the endothelium. This interpretation is also supported by the fact that the TM rise went along with an increase in endothelium-dependent FMD and that both these responses reverted to pre-treatment levels after stopping PCT (Figure 2). At variance with an in vitro study [10], PAI-1 and thrombospondin-1 in our study were unaffected by PCT treatment. A discrepancy has been noted between in vitro and in vivo data concerning the effect of other interventions on PAI-1 levels, e.g. for insulin treatment [25]. Similarly, thrombospondin-1 serum levels do not reflect the levels of the same protein at tissue level in other chronic conditions like bronchopulmonary diseases [26]. The TM rise by PCT documented in the present study ought to be framed into a broader context considering the possible implication of this effect for adverse cardiovascular outcomes. As previously alluded to, high TM signals a lower risk for incident coronary heart disease in the general population, free of background cardiovascular events [9]. The cardiovascular protective effect of TM is supported by molecular genetic studies documenting that a complete loss of TM function in humans goes along with a very high risk for thrombotic complications including pulmonary embolism, cerebral venous sinus thrombosis and stroke [27]. In experimental models in the rabbit TM delivery to dilated femoral arteries reduces thrombus formation, inflammation and neo-intima formation [28]. Thus, if sustained in the long term, the TM rise by PCT registered in our 12-week trial may in theory contribute to the putatively protective effect of vitamin D, particularly active vitamin D forms like calcitriol and PCT, for all-cause and cardiovascular death registered in a meta-analysis including 20 cohort studies in CKD patients [29]. However, the hypothesis that vitamin D may prevent death and cardiovascular disease in vitamin D deficient subjects [30] and the corollary hypothesis that emerged in the present study that TM may contribute to avert death and cardiovascular disease in CKD still deserve to be tested into specifically designed clinical trials in this population. This study has limitations. First, it is post hoc analysis of a clinical trial stimulated by experimental studies in vitro [10] and by transcriptomic analyses in humans [12]. However, the fact that we performed our analyses in the whole database of a double-blind randomized trial with no missing sample for TM measurement is a strength. Second, TM is inversely related to the GFR and since PCT triggers minor, reversible changes in the GFR we cannot a priori exclude that these changes contributed to the TM rise by this drug. However, the quite small entity of the GFR changes (about 3 mL/min/1.73 m2) and the fact that adjustment for the GFR and other potential confounders had no virtual influence on the effect in question, makes it unlikely that the GFR was a confounder in our study. As alluded to before, TM is not filtered by the glomerulus and circulating TM is considered as an expression of the endothelial shedding of this proteoglycan both in Type 2 diabetes [24] and in CKD [31]. In conclusion, in a post hoc analysis in the PENNY trial in CKD patients, VDR activation by PCT raised TM levels as well as the endothelium-dependent vascular response to ischaemia, and such effects were rapidly reversible after stopping the treatment. The TM rise induced by PCT is a potential additional mechanism whereby improvement in endothelial function by VDR activation may favourably impact upon vascular health in CKD patients. Clinical studies based on meaningful clinical endpoints are needed to confirm and extend the relevance of the findings in the present study. SUPPLEMENTARY DATA Supplementary data are available at ndt online. FUNDING Our institution received funding by AbbVie for the PENNY study. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. AUTHORS’ CONTRIBUTIONS C.Z. conceived the study; G.D. performed the data analysis with G.T. and prepared the first draft of the article with C.Z.; P.P. and S.C. performed all laboratory analyses; F.M. participated into the clinical management of patients and contributed to the conception of the study. R.T. performed all FMD studies. All authors provided critical comments and significant intellectual contribution to the draft prepared by G.D. and C.Z. and approved the final version of the article. CONFLICT OF INTEREST STATEMENT None declared. The authors declare that there is no conflict of interest regarding the publication of this article. REFERENCES 1 Goligorsky MS. Pathogenesis of endothelial cell dysfunction in chronic kidney disease: a retrospective and what the future may hold. Kidney Res Clin Pract  2015; 34: 76– 82 Google Scholar CrossRef Search ADS PubMed  2 Lutz J, Menke J, Sollinger D et al.   Haemostasis in chronic kidney disease. 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Journal

Nephrology Dialysis TransplantationOxford University Press

Published: Apr 13, 2018

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