INTRODUCTION:Little is known about the association of urine metabolites with structural lesions in persons with diabetes. OBJECTIVES:We examined the relationship between 12 urine metabolites and kidney structure in American Indians with type 2 diabetes. METHODS:Data were from a 6-year clinical trial that assessed renoprotective efficacy of losartan, and included a kidney biopsy at the end of the treatment period. Metabolites were measured in urine samples collected within a median of 6.5 months before the research biopsy. Associations of the creatinine-adjusted urine metabolites with kidney structural variables were examined by Pearson's correlations and multivariable linear regression after adjustment for age, sex, diabetes duration, hemoglobin A1c, mean arterial pressure, glomerular filtration rate (iothalamate), and losartan treatment. RESULTS:Participants (n = 62, mean age 45 ± 10 years) had mean ± standard deviation glomerular filtration rate of 137 ± 50 ml/min and median (interquartile range) urine albumin:creatinine ratio of 34 (14-85) mg/g near the time of the biopsy. Urine aconitic and glycolic acids correlated positively with glomerular filtration surface density (partial r = 0.29, P = 0.030 and r = 0.50, P < 0.001) and total filtration surface per glomerulus (partial r = 0.32, P = 0.019 and r = 0.43, P = 0.001). 2-ethyl 3-OH propionate correlated positively with the percentage of fenestrated endothelium (partial r = 0.32, P = 0.019). Citric acid correlated negatively with mesangial fractional volume (partial r=-0.36, P = 0.007), and homovanillic acid correlated negatively with podocyte foot process width (partial r=-0.31, P = 0.022). CONCLUSIONS:Alterations of urine metabolites may associate with early glomerular lesions in diabetic kidney disease.

Type 1 diabetes affects over nine million individuals globally, with approximately 40% developing diabetic kidney disease. Emerging evidence suggests that epigenetic alterations, such as DNA methylation, are involved in diabetic kidney disease. Here we assess differences in blood-derived genome-wide DNA methylation associated with diabetic kidney disease in 1304 carefully characterised individuals with type 1 diabetes and known renal status from two cohorts in the United Kingdom-Republic of Ireland and Finland. In the meta-analysis, we identify 32 differentially methylated CpGs in diabetic kidney disease in type 1 diabetes, 18 of which are located within genes differentially expressed in kidneys or correlated with pathological traits in diabetic kidney disease. We show that methylation at 21 of the 32 CpGs predict the development of kidney failure, extending the knowledge and potentially identifying individuals at greater risk for diabetic kidney disease in type 1 diabetes.

Aims/hypothesis

Diabetic kidney disease (DKD) is the leading cause of kidney failure and has a substantial genetic component. Our aim was to identify novel genetic factors and genes contributing to DKD by performing meta-analysis of previous genome-wide association studies (GWAS) on DKD and by integrating the results with renal transcriptomics datasets.

Methods

We performed GWAS meta-analyses using ten phenotypic definitions of DKD, including nearly 27,000 individuals with diabetes. Meta-analysis results were integrated with estimated quantitative trait locus data from human glomerular (N=119) and tubular (N=121) samples to perform transcriptome-wide association study. We also performed gene aggregate tests to jointly test all available common genetic markers within a gene, and combined the results with various kidney omics datasets.

Results

The meta-analysis identified a novel intronic variant (rs72831309) in the TENM2 gene associated with a lower risk of the combined chronic kidney disease (eGFR<60 ml/min per 1.73 m²) and DKD (microalbuminuria or worse) phenotype (p=9.8×10^-9; although not withstanding correction for multiple testing, p>9.3×10^-9). Gene-level analysis identified ten genes associated with DKD (COL20A1, DCLK1, EIF4E, PTPRN-RESP18, GPR158, INIP-SNX30, LSM14A and MFF; p<2.7×10^-6). Integration of GWAS with human glomerular and tubular expression data demonstrated higher tubular AKIRIN2 gene expression in individuals with vs without DKD (p=1.1×10^-6). The lead SNPs within six loci significantly altered DNA methylation of a nearby CpG site in kidneys (p<1.5×10^-11). Expression of lead genes in kidney tubules or glomeruli correlated with relevant pathological phenotypes (e.g. TENM2 expression correlated positively with eGFR [p=1.6×10^-8] and negatively with tubulointerstitial fibrosis [p=2.0×10^-9], tubular DCLK1 expression correlated positively with fibrosis [p=7.4×10^-16], and SNX30 expression correlated positively with eGFR [p=5.8×10^-14] and negatively with fibrosis [p<2.0×10^-16]).

Conclusions/interpretation

Altogether, the results point to novel genes contributing to the pathogenesis of DKD.

Data availability

The GWAS meta-analysis results can be accessed via the type 1 and type 2 diabetes (T1D and T2D, respectively) and Common Metabolic Diseases (CMD) Knowledge Portals, and downloaded on their respective download pages ( https://t1d.hugeamp.org/downloads.html ; https://t2d.hugeamp.org/downloads.html ; https://hugeamp.org/downloads.html ).

Identification of sequence variants robustly associated with predisposition to diabetic kidney disease (DKD) has the potential to provide insights into the pathophysiological mechanisms responsible. We conducted a genome-wide association study (GWAS) of DKD in type 2 diabetes (T2D) using eight complementary dichotomous and quantitative DKD phenotypes: the principal dichotomous analysis involved 5,717 T2D subjects, 3,345 with DKD. Promising association signals were evaluated in up to 26,827 subjects with T2D (12,710 with DKD). A combined T1D+T2D GWAS was performed using complementary data available for subjects with T1D, which, with replication samples, involved up to 40,340 subjects with diabetes (18,582 with DKD). Analysis of specific DKD phenotypes identified a novel signal near GABRR1 (rs9942471, P = 4.5 × 10^-8) associated with microalbuminuria in European T2D case subjects. However, no replication of this signal was observed in Asian subjects with T2D or in the equivalent T1D analysis. There was only limited support, in this substantially enlarged analysis, for association at previously reported DKD signals, except for those at UMOD and PRKAG2, both associated with estimated glomerular filtration rate. We conclude that, despite challenges in addressing phenotypic heterogeneity, access to increased sample sizes will continue to provide more robust inference regarding risk variant discovery for DKD.