Sulfatase 2 Is Associated with Steroid Resistance in Childhood Nephrotic Syndrome

Abstract

Glucocorticoid (GC) resistance complicates the treatment of ~10-20% of children with nephrotic syndrome (NS), yet the molecular basis for resistance remains unclear. We used RNAseq analysis and in silico algorithm-based approaches on peripheral blood leukocytes from 12 children both at initial NS presentation and after ~7 weeks of GC therapy to identify a 12-gene panel able to differentiate steroid resistant NS (SRNS) from steroid-sensitive NS (SSNS). Among this panel, subsequent validation and analyses of one biologically relevant candidate, sulfatase 2 (SULF2), in up to a total of 66 children, revealed that both SULF2 leukocyte expression and plasma arylsulfatase activity Post/Pre therapy ratios were greater in SSNS vs. SRNS. However, neither plasma SULF2 endosulfatase activity (measured by VEGF binding activity) nor plasma VEGF levels, distinguished SSNS from SRNS, despite VEGF's reported role as a downstream mediator of SULF2's effects in glomeruli. Experimental studies of NS-related injury in both rat glomeruli and cultured podocytes also revealed decreased SULF2 expression, which were partially reversible by GC treatment of podocytes. These findings together suggest that SULF2 levels and activity are associated with GC resistance in NS, and that SULF2 may play a protective role in NS via the modulation of downstream mediators distinct from VEGF.

Keywords: FSGS; glucocorticoids; steroid resistant nephrotic syndrome; sulfatase 2; vascular endothelial growth factor (VEGF).

Figure 1

Identification of Candidate Genes by RNASeq, Statistical Analysis and ICGA-ELM Algorithm. The RNA-seq primary data set consisted of expression values for >20,000 genes in 11 out of 12 patients, which were reduced to 7334 genes by the removal of genes with little or no expression in one or several samples. These expression values were then used to calculate gene expression ratios (GER) before (Pre) and after (Post) treatment with glucocorticoids (GC) (GER(Pre/Post)). (A) “Volcano Plotting” of the gene expression ratios of 7734 genes following treatment with GC in nephrotic syndrome (NS) patients with steroid sensitive NS (SSNS) and steroid resistant NS (SRNS) identified a small set of putative marker genes. For each gene, the difference r₁-r₂ of the mean expression ratios GER(Pre/Post) of all samples of the SSNS patient group (r1) and of the SRNS patient group (r2) is plotted on the X-axis, and t-test criteria are plotted on the Y-axis. Given the selected thresholds (cut offs: p-value = 0.02 on the Y-axis; |r₁-r₂| = 0.263 on the X-axis), this plot identified 72 genes that were differentially expressed in the leukocytes of both groups of patients following treatment with GC (labeled as Set I and Set II in the upper left and right regions of the plot). The names of the 72 genes are listed in Table 2. SULF2 is among these 72 genes. (B) Clustering of the selected 72 genes according to their expression ratios results in an accurate grouping of the SRNS and SSNS patients. The 72 genes identified were hierarchically clustered, using their GER(Pre/Post). The cluster tree on the left defines Set I (genes 1–57) and Set II (genes 58–72) genes, whereas the cluster tree on the top separates the SRNS and SSNS patients. The GER(Pre/Post) of Set I and Set II genes perfectly partitioned the SRNS and SSNS patient groups. Up-regulated (green) and down-regulated (red) genes are marked, following treatment of the patients with GC. SULF2 is among the group of the Set I genes (red arrowhead at the top right of figure). The names of the 72 genes are listed in Table 2. (C) Linear separation of the expression ratios of the selected 72 genes in SRNS and SSNS patient groups suggested a high discriminatory potency. The GER(Pre/Post) for all patients were averaged for each of the selected 72 genes and plotted against each other with the ratios for the SSNS and SRNS patients shown on the Y-axis and X-axis, respectively. Set I genes (round symbols) and Set II genes (diamond symbols) formed separate clusters for both patient groups, which could be separated by a straight line (linear separation). SULF2 is labeled among the group of the Set I genes. The linear separation between these two gene groups suggested that their GER(Pre/Post) could be used to distinguish between SRNS and SSNS patients. The Integer-Coded Genetic Algorithm (ICGA) – Extreme Learning Machine (ELM) algorithm was then applied to identify smaller sets of genes which were able to distinguish between patient groups. Among them was a set of 34 genes which classified, with high accuracy, the SRNS and SSNS patient groups (closed symbols). The genes in this reduced gene set are also listed in Table 2. (D) The ICGA-ELM algorithm selected a small set of genes with high discriminatory potency. The GER(Pre/Post) of all 72 selected genes was analyzed by the ICGA-ELM algorithm. Hundreds of iterations of this algorithm produced several hundred sets of genes. Among these sets, a number of genes occurred with increased frequency. The twelve genes with the most frequent occurrences are found in the area above the dotted line and are listed in Table 3. SULF2 is among these top twelve genes.

Figure 2

SULF2 Gene Expression in Children with steroid sensitive nephrotic syndrome (SSNS) vs. steroid resistant nephrotic syndrome (SRNS). cDNA synthesized from peripheral blood leukocyte RNA from SSNS and SRNS patients was used for determination of SULF2 expression. Gene expression ratios of SULF2 were determined by qRT-PCR in samples taken before and after an average of 7 weeks of glucocorticoid (GC) therapy (SULF2 GER(Post/Pre)). (A) The SULF2 GER(Post/Pre) was significantly greater in samples from SSNS (n = 28) vs. SRNS (n = 14) patients (2.72 ± 0.37 SEM vs. 1.49 ± 0.26 SEM; p = 0.0358 by unpaired two-tailed t-test, * denotes significance). The dotted line marks a SULF2 GER(Post/Pre) = 1, which separates induced SULF2 expression (above the line) from reduced (below the line) SULF2 expression following GC treatment. Since some of these patients received one or more GC doses prior to the pre-treatment sample collection, the data were further segregated based on GC exposure. (B) Patients were included only if they were completely GC naïve with confirmation of no GC exposure prior to collection of the pre-treatment sample. In this near-ideal clinical research setting the SULF2 GER(Post/Pre) was still greater in samples from SSNS (n = 15) vs. SRNS (n = 10) patients (3.26 ± 0.64 SEM vs. 1.72 ± 0.33 SEM; p = 0.0449 by unpaired two-tailed t-test with Welch’s correction, * denotes significance).

Figure 3

Plasma arylsulfatase activity in children with steroid sensitive nephrotic syndrome (SSNS) vs. steroid resistant nephrotic syndrome (SRNS). Clarified Pre-treatment and Post-treatment plasma samples from SSNS and SRNS patients were used for determinations of arylsulfatase activity. The results are plotted as ratios of the activities in the two samples collected from each patient after glucocorticoid (GC) treatment vs. before GC treatment (Post/Pre). (A) The arylsulfatase activity (Post/Pre) was significantly greater in samples from SSNS (n = 30) vs. SRNS (n = 15) patients (1.22 ± 0.06 SEM vs. 0.93 ± 0.10 SEM; p = 0.0135 by unpaired two-tailed t-test, * denotes significance). The dotted line marks where the arylsulfatase activity ratio = 1, which separates increased (above) from reduced (below) enzyme activity after GC therapy. Since some of these patients received one or more GC doses prior to the pre-treatment sample collection, the data were further segregated based on GC exposure. (B) Patients were included only if they were completely GC naïve with confirmation of no GC exposure prior to collection of the pre-treatment sample. In this near-ideal clinical research setting the arylsulfatase activity (Post/Pre) still remained significantly greater in samples from SSNS (n = 13) vs. SRNS (n = 9) patients (1.31 ± 0.08 SEM vs. 0.76 ± 0.07 SEM; p = 0.0001 by unpaired two-tailed t-test, * denotes significance).

Figure 4

Plasma Endosulfatase Activity (Measured by Vascular Endothelial Growth Factor [VEGF] Binding to Heparin) in Children with steroid sensitive nephrotic syndrome (SSNS) vs. steroid resistant nephrotic syndrome (SRNS). Glucocorticoid (GC) naïve pre-treatment and post-treatment plasma samples from SSNS (n = 25) and SRNS (n = 13) patients were used to determine the effects on binding of VEGF to immobilized heparin as an indirect measure of plasma endosulfatase activity. (A) The mean % VEGF bound was significantly increased after GC treatment in all patients combined (n = 24 SSNS pts + n = 13 SRNS pts) (Pre: 34.44 ± 5.28 SEM vs. Post: 43.68 ± 5.20 SEM; p = 0.0005 by paired two-tailed t-test, * denotes significance). (B) The mean % VEGF bound tended to be higher in SSNS patients (Pre: 41.36 ± 6.97 SEM, Post: 52.83 ± 6.22 SEM) compared to SRNS patients (Pre: 21.66 ± 6.97 SEM, Post: 26.78 ± 7.55 SEM), but did not differ significantly amongst the four cohorts, as determined by ordinary one-way ANOVA analysis. (C) Similarly, the mean Post/Pre % VEGF bound ratios were not significantly different between SSNS vs. SRNS patients, as determined by unpaired t tests (3.61 ± 1.15 SEM vs. 1.79 ± 0.46 SEM; p = 0.2695).

Figure 5

Plasma quantitative vascular endothelial growth factor (VEGF) levels in children with steroid sensitive nephrotic syndrome (SSNS) vs. steroid resistant nephrotic syndrome (SRNS). Glucocorticoid (GC) naïve pre-treatment and post-treatment plasma samples from SSNS (n = 27) and SRNS (n = 13) patients were used to measure plasma VEGF levels. (A) The VEGF levels were significantly increased in all samples after GC treatment in all patients combined (n = 27 SSNS pts + n = 13 SRNS pts) (Pre: 324.10 ± 36.06 SEM vs. Post: 361.70 ± 37.63 SEM, p = 0.0340 by paired two-tailed t-test, * denotes significance). (B) The VEGF levels did not differ significantly amongst the four cohorts as determined by ordinary one-way ANOVA analysis (SSNS Pre: 345.00 ± 41.79 SEM, SSNS Post: 380.30 ± 40.71 SEM, SRNS Pre: 262.00 ± 68.34 SEM, SRNS Post: 323.30 ± 80.74 SEM; p = 0.4957 summarized ANOVA). (C) Similarly, the Post/Pre VEGF level ratios were not significantly different between SSNS vs. SRNS patients, as determined by unpaired t test (1.72 ± 0.40 SEM vs. 15.14 ± 11.34 SEM; p = 0.0927).

Figure 6

SULF2 Gene Expression in Nephrotic Glomeruli and Injured Podocytes. (A) Glomeruli were isolated from puromycin aminonucleoside (PAN)-induced nephrotic rats on Day 11 after PAN injection, when they showed significant proteinuria, and RNA processed for the determination of SULF2 gene expression. Glomerular SULF2 gene expression was significantly decreased (50%) in nephrotic rats vs. Controls (n = 3 rats/group) as determined by unpaired t test (Control: 1.00 ± 0.04 SEM vs. Nephrotic: 0.50 ± 0.03 SEM; p < 0.0001). (B) Cultured podocytes were exposed to PAN for 6 h, 24 h, 7d and 10d to determine the time course of podocyte SULF2 gene expression after PAN-induced injury. Podocyte SULF2 gene expression was significantly reduced in a short-term injury model with high PAN concentration after 24 h (1.01 ± 0.08 SEM vs. 0.14 ± 0.01 SEM; p < 0.0001), but not after 6 h (1.01 ± 0.08 SEM vs. 0.67 ± 0.00 SEM, p = 0.3254, ns). Podocyte SULF2 gene expression was also significantly reduced in a longer-term injury model with low PAN concentration after both 7 d (1.16 ± 0.09 SEM vs. 0.36 ± 0.16 SEM; p < 0.0001) and 10 d (0.99 ± 0.08 SEM vs. 0.41 ± 0.06 SEM; p = 0.0017), as determined by one-way ANOVA analysis of multiple comparisons. Notably, treatment of PAN-injured podocytes with GC (i.e., dexamethasone (DEX)) partially reversed the reductions in SULF2 gene expression after both 24 h and 7d injury with PAN (24 h: 0.14 ± 0.01 SEM vs. 1.47 ± 0.10 SEM; p < 0.0001; 7 d: 0.36 ± 0.16 SEM vs. 1.08 ± 0.04 SEM; p < 0.0001). (**** p < 0.0001; ** p < 0.005; ns, p > 0.05.)

Figure 7

Schematic for GC-Induced Changes in SULF2 Expression and Activity in SSNS vs. SRNS. SULF2 modulates the sulfatation pattern on heparan sulfate proteoglycans (HSPGs) by removing 6-O-sulfates. HSPGs are found on the cell surfaces and in extracellular matrix where they interact with multiple ligands such as growth factors (VEGF, PDGF and FGF), chemokines and morphogens. By regulating the sulfatation pattern on HSPGs, SULF2 modulates the availability and activity of these ligands. Our data suggest that SSNS have higher SULF2 leukocyte expression as well as activity in the plasma of patients after GC therapy compared to SRNS. This would potentially result in increased cleavage of sulfate groups from HSPGs in SSNS and release of growth factors, chemokines and morphogens. However, the SULF2 endosulfatase activity as measured by VEGF-heparin binding as well as total VEGF plasma levels were not discriminatory in SSNS vs. SRNS. Our findings together suggest that SULF2 may play a protective role in NS, independent of plasma VEGF regulation, and thus SULF2 manipulation could potentially be exploited for the development of novel treatments for NS. , SULF2, Ligands (growth factors, ; chemokines, ; morphogens).