New susceptibility loci associated with kidney disease in type 1 diabetes

Abstract

Diabetic kidney disease, or diabetic nephropathy (DN), is a major complication of diabetes and the leading cause of end-stage renal disease (ESRD) that requires dialysis treatment or kidney transplantation. In addition to the decrease in the quality of life, DN accounts for a large proportion of the excess mortality associated with type 1 diabetes (T1D). Whereas the degree of glycemia plays a pivotal role in DN, a subset of individuals with poorly controlled T1D do not develop DN. Furthermore, strong familial aggregation supports genetic susceptibility to DN. However, the genes and the molecular mechanisms behind the disease remain poorly understood, and current therapeutic strategies rarely result in reversal of DN. In the GEnetics of Nephropathy: an International Effort (GENIE) consortium, we have undertaken a meta-analysis of genome-wide association studies (GWAS) of T1D DN comprising ~2.4 million single nucleotide polymorphisms (SNPs) imputed in 6,691 individuals. After additional genotyping of 41 top ranked SNPs representing 24 independent signals in 5,873 individuals, combined meta-analysis revealed association of two SNPs with ESRD: rs7583877 in the AFF3 gene (P = 1.2 × 10(-8)) and an intergenic SNP on chromosome 15q26 between the genes RGMA and MCTP2, rs12437854 (P = 2.0 × 10(-9)). Functional data suggest that AFF3 influences renal tubule fibrosis via the transforming growth factor-beta (TGF-β1) pathway. The strongest association with DN as a primary phenotype was seen for an intronic SNP in the ERBB4 gene (rs7588550, P = 2.1 × 10(-7)), a gene with type 2 diabetes DN differential expression and in the same intron as a variant with cis-eQTL expression of ERBB4. All these detected associations represent new signals in the pathogenesis of DN.

Figure 1. Flow chart summarizing study design.

We applied a two stage study design, where the top signals from the meta-analysis of three GENIE studies (UK-ROI, FinnDiane and GoKinD US) were followed up in phase two analysis, consisting of nine T1D cohorts. After combined meta-analysis, two signals reached genome-wide significance in the analysis of ESRD (P<5×10⁻⁸). For DN phenotype no loci reached this threshold, but the strongest association was observed for ERBB4. These signals were followed up with eQTL studies and functional analysis. The number of patients (N) refers to the number of samples after genotype quality control; either the total number of samples or divided into cases/controls.

Figure 2. Regional association plots for top ranked SNPs with associated gene expression data.

Panels represent independent signals for the primary DN and ESRD analysis. The color of the SNP symbol indicates the linkage disequilibrium (r²) with the index SNP which is colored purple. Blue and red gene colors in the lower part of each figure panel indicate up and down regulation in tubulointerstitial or glomerular DN kidney biopsies, respectively. Genes with no change in expression are indicated with black; no data on gene expression with gray color. (A) Association of rs7583877 with ESRD. (B) Association of rs12437854 with ESRD. (C) Association of rs7588550 with DN.

Figure 3. Forest plots for significant hits incorporating discovery and replication plots.

Plots show the study-specific association estimates (OR) and 95% confidence intervals for the discovery and second phase studies. (A) Association of rs7583877 with ESRD; heterogeneity P = 0.037. (B) Association of rs12437854 with ESRD; heterogeneity P = 0.046. (C) Association of rs7588550 with DN; heterogeneity P = 0.467. The association estimate and confidence interval for the meta-analysis combining the discovery and second-stage results are denoted by the diamond.

Figure 4. AFF3 is upregulated in renal epithelial cells (HK-2) stimulated with pro-fibrotic TGF-β1.

(A) Western blot of AFF3 protein expression in HK-2 cells stimulated with TGF-β1 (5 ng/ml; 24–48 h). (B) TaqMan quantitative PCR analysis of AFF3 mRNA expression in HK-2 cells stimulated with TGF-β1 (5 ng/ml; 48 h) and (C) AFF3 mRNA expression in HK-2 cells transfected with AFF3 siRNA in the presence (black bar)/absence (grey bar) of TGF-β1 (5 ng/ml; 48 h). (D) TaqMan quantitative PCR analysis of N-cadherin, CTGF, Jagged1 and E-cadherin expression in HK-2 cells transfected with AFF3 siRNA in the presence (black bar)/absence (grey bar) of TGF-β1 (5 ng/ml; 48 h). (E) Representative Western blot of N-cadherin, CTGF, Jagged1 and E-cadherin protein responses in HK-2 cells transfected with AFF3 siRNA in the presence/absence of TGF-β1 (5 ng/ml; 48 h). HK-2 cells transfected with control siRNA were selected as a control. For TaqMan PCR, expression was normalized to GAPDH. Data are plotted as mean ± SE (n = 3; *P<0.05, **P<0.01).