Genetic risk factors affecting mitochondrial function are associated with kidney disease in people with Type 1 diabetes

AIM: To evaluate the association with diabetic kidney disease of single nucleotide polymorphisms (SNPs) that may contribute to mitochondrial dysfunction.

METHODS: The mitochondrial genome and 1039 nuclear genes that are integral to mitochondrial function were investigated using a case (n=823 individuals with diabetic kidney disease) vs. control (n=903 individuals with diabetes and no renal disease) approach. All people included in the analysis were of white European origin and were diagnosed with Type 1 diabetes before the age of 31 years. Replication was conducted in 5093 people with similar phenotypes to those of the discovery collection. Association analyses were performed using the plink genetic analysis toolset, with adjustment for relevant covariates.

RESULTS: A total of 25 SNPs were evaluated in the mitochondrial genome, but none were significantly associated with diabetic kidney disease or end-stage renal disease. A total of 38 SNPs in nuclear genes influencing mitochondrial function were nominally associated with diabetic kidney disease and 16 SNPS were associated with end-stage renal disease, secondary to diabetic kidney disease, with meta-analyses confirming the same direction of effect. Three independent signals (seven SNPs) were common to the replication data for both phenotypes with Type 1 diabetes and persistent proteinuria or end-stage renal disease.

CONCLUSIONS: Our results suggest that SNPs in nuclear genes that influence mitochondrial function are significantly associated with diabetic kidney disease in a white European population

Distinct methylation patterns in genes that affect mitochondrial function are associated with kidney disease in blood-derived DNA from individuals with Type 1 diabetes

AIMS: Epigenetic modifications, such as DNA methylation, can influence the risk of developing kidney disease. We studied methylation profiles in genes related to mitochondrial function to assess whether differences in these epigenetic features were associated with diabetic kidney disease in people with Type 1 diabetes.

METHODS: A case-control association study was undertaken (n = 196 individuals with diabetic kidney disease vs. n = 246 individuals without renal disease). Participants were White and diagnosed with Type 1 diabetes before 31 years of age. Genes that encode mitochondrial proteins (n = 780) were downloaded from mitoproteome. org. DNA methylation profiles from blood-derived DNA were generated using the Illumina Infinium HumanMethylation450 (262 samples) and Illumina Infinium HumanMethylation27 (192 samples) arrays. Beta values (β) were calculated and quality control was conducted, including evaluating blind duplicate DNA samples.

RESULTS: Fifty-four Cytosine-phosphate-Guanine probes across 51 unique genes were significantly associated (P ≤ 10(-8) ) with diabetic kidney disease across both the 450K and the 27K methylation arrays. A subanalysis, employing the 450K array, identified 755 Cytosine-phosphate-Guanine probes in 374 genes that were significantly associated (P ≤ 10(-8) ) with end-stage renal disease. Forty-six of the top-ranked variants for diabetic kidney disease were also identified as being differentially methylated in individuals with end-stage renal disease. The largest change in methylation (Δβ = 0.2) was observed for cg03169527 in the TAMM41 gene, chromosome 3p25.2. Three genes, PMPCB, TSFM and AUH, were observed with differential methylation at multiple Cytosine-phosphate-Guanine sites each (P < 10(-12) ).

CONCLUSIONS: Differential methylation in genes that influence mitochondrial function are associated with kidney disease in individuals with Type 1 diabetes. 

Genetic Evidence for a Causal Role of Obesity in Diabetic Kidney Disease

Obesity has been posited as an independent risk factor for diabetic kidney disease (DKD), but establishing causality from observational data is problematic. We aimed to test whether obesity is causally related to DKD using Mendelian randomization, which exploits the random assortment of genes during meiosis. In 6,049 subjects with type 1 diabetes, we used a weighted genetic risk score (GRS) comprised of 32 validated BMI loci as an instrument to test the relationship of BMI with macroalbuminuria, end-stage renal disease (ESRD), or DKD defined as presence of macroalbuminuria or ESRD. We compared these results with cross-sectional and longitudinal observational associations. Longitudinal analysis demonstrated a U-shaped relationship of BMI with development of macroalbuminuria, ESRD, or DKD over time. Cross-sectional observational analysis showed no association with overall DKD, higher odds of macroalbuminuria (for every 1 kg/m(2) higher BMI, odds ratio [OR] 1.05, 95% CI 1.03-1.07, P < 0.001), and lower odds of ESRD (OR 0.95, 95% CI 0.93-0.97, P < 0.001). Mendelian randomization analysis showed a 1 kg/m(2) higher BMI conferring an increased risk in macroalbuminuria (OR 1.28, 95% CI 1.11-1.45, P = 0.001), ESRD (OR 1.43, 95% CI 1.20-1.72, P < 0.001), and DKD (OR 1.33, 95% CI 1.17-1.51, P < 0.001). Our results provide genetic evidence for a causal link between obesity and DKD in type 1 diabetes. As obesity prevalence rises, this finding predicts an increase in DKD prevalence unless intervention should occur.