Long-term favorable prognosis in late onset dominant distal titinopathy: Tibial muscular dystrophy.

BACKGROUND AND PURPOSE: Tibial muscular dystrophy (TMD) is a dominant late onset distal titinopathy. It was first described in Finnish patients 3 decades ago. TMD patients with several other TTN mutations occur in many European populations. In this retrospective study, we were able to obtain longitudinal follow-up data of the disease progression over 15 years in 137 TMD patients. METHODS: We retrieved clinical data retrospectively from three examinations spanning a period of 15 years. The data were analyzed in R. Frequencies, percentages, and median values were used to describe data. Probability values were determined with the chi-squared test. RESULTS: In the cohort, the first symptoms were walking difficulties (97.8%) and weakness in distal lower limbs (98.5%). The progression of the weakness in distal lower limbs was moderate, and in the proximal lower limbs and proximal upper limbs it was mild. The distal upper limbs were not affected. Magnetic resonance imaging results indicated fatty degeneration preferentially in lower leg anterior muscles, gluteus minimus, and hamstring muscles. Serum creatine kinase values in the cohort were mostly normal (40.7%) or mildly elevated (53.7%). The data suggest that 50% of patients need walking aids by the age of 88 years. CONCLUSIONS: Despite individual variability of severity, the overall disability due to walking difficulties and upper limb weakness remained moderate even at very advanced ages, and cardiomyopathy did not develop due to the titin defect alone. The acquired results promote the correct identification of TMD, and the obtained trajectories of disease evolution can be used as natural history data for any therapeutic intervention.

Urinary metabolite profiling and risk of progression of diabetic nephropathy in 2670 individuals with type 1 diabetes.

AIMS/HYPOTHESIS: This prospective, observational study examines associations between 51 urinary metabolites and risk of progression of diabetic nephropathy in individuals with type 1 diabetes by employing an automated NMR metabolomics technique suitable for large-scale urine sample collections. METHODS: We collected 24-h urine samples for 2670 individuals with type 1 diabetes from the Finnish Diabetic Nephropathy study and measured metabolite concentrations by NMR. Individuals were followed up for 9.0 ± 5.0 years until their first sign of progression of diabetic nephropathy, end-stage kidney disease or study end. Cox regressions were performed on the entire study population (overall progression), on 1999 individuals with normoalbuminuria and 347 individuals with macroalbuminuria at baseline. RESULTS: Seven urinary metabolites were associated with overall progression after adjustment for baseline albuminuria and chronic kidney disease stage (p < 8 × 10-4): leucine (HR 1.47 [95% CI 1.30, 1.66] per 1-SD creatinine-scaled metabolite concentration), valine (1.38 [1.22, 1.56]), isoleucine (1.33 [1.18, 1.50]), pseudouridine (1.25 [1.11, 1.42]), threonine (1.27 [1.11, 1.46]) and citrate (0.84 [0.75, 0.93]). 2-Hydroxyisobutyrate was associated with overall progression (1.30 [1.16, 1.45]) and also progression from normoalbuminuria (1.56 [1.25, 1.95]). Six amino acids and pyroglutamate were associated with progression from macroalbuminuria. CONCLUSIONS/INTERPRETATION: Branched-chain amino acids and other urinary metabolites were associated with the progression of diabetic nephropathy on top of baseline albuminuria and chronic kidney disease. We found differences in associations for overall progression and progression from normo- and macroalbuminuria. These novel discoveries illustrate the utility of analysing urinary metabolites in entire population cohorts.

Genome-wide meta-analysis and omics integration identifies novel genes associated with diabetic kidney disease.

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 ).

Association of Coding Variants in Hydroxysteroid 17-beta Dehydrogenase 14 (HSD17B14) with Reduced Progression to End Stage Kidney Disease in Type 1 Diabetes.

BACKGROUND: Rare variants in gene coding regions likely have a greater impact on disease-related phenotypes than common variants through disruption of their encoded protein. We searched for rare variants associated with onset of ESKD in individuals with type 1 diabetes at advanced kidney disease stage. METHODS: Gene-based exome array analyses of 15,449 genes in five large incidence cohorts of individuals with type 1 diabetes and proteinuria were analyzed for survival time to ESKD, testing the top gene in a sixth cohort (n=2372/1115 events all cohorts) and replicating in two retrospective case-control studies (n=1072 cases, 752 controls). Deep resequencing of the top associated gene in five cohorts confirmed the findings. We performed immunohistochemistry and gene expression experiments in human control and diseased cells, and in mouse ischemia reperfusion and aristolochic acid nephropathy models. RESULTS: Protein coding variants in the hydroxysteroid 17-ß dehydrogenase 14 gene (HSD17B14), predicted to affect protein structure, had a net protective effect against development of ESKD at exome-wide significance (n=4196; P value=3.3 × 10-7). The HSD17B14 gene and encoded enzyme were robustly expressed in healthy human kidney, maximally in proximal tubular cells. Paradoxically, gene and protein expression were attenuated in human diabetic proximal tubules and in mouse kidney injury models. Expressed HSD17B14 gene and protein levels remained low without recovery after 21 days in a murine ischemic reperfusion injury model. Decreased gene expression was found in other CKD-associated renal pathologies. CONCLUSIONS: HSD17B14 gene is mechanistically involved in diabetic kidney disease. The encoded sex steroid enzyme is a druggable target, potentially opening a new avenue for therapeutic development.

Differential metabolomic signatures of declining renal function in Types 1 and 2 diabetes.

BACKGROUND: Chronic kidney disease (CKD) shows different clinical features in Types1 (T1D) and 2 diabetes (T2D). Metabolomics have recently provided useful contribution to the identification of biomarkers of CKD progression in either form of the disease. However, no studies have so far compared plasma metabolomics between T1D and T2D in order to identify differential signatures of progression of estimated glomerular filtration rate (eGFR) decline. METHODS: We used two large cohorts of T1D (from Finland) and T2D (from Italy) patients followed up to 7 and 3 years, respectively. In both groups, progression was defined as the top quartile of yearly decline in eGFR. Pooled data from the two groups were analysed by univariate and bivariate random forest (RF), and confirmed by bivariate partial least squares (PLS) analysis, the response variables being type of diabetes and eGFR progression. RESULTS: In progressors, yearly eGFR loss was significantly larger in T2D [-5.3 (3.0), median (interquartile range)mL/min/1.73 m2/year] than T1D [-3.7 (3.1) mL/min/1.73 m2/year ; P = 0.018]. Out of several hundreds, bivariate RF extracted 22 metabolites associated with diabetes type (all higher in T1D than T2D except for 5-methylthioadenosine, pyruvate and ß-hydroxypyruvate) and 13 molecules associated with eGFR progression (all higher in progressors than non-progressors except for sphyngomyelin). Three of the selected metabolites (histidylphenylalanine, leucylphenylalanine, tryptophylasparagine) showed a significant interaction between disease type and progression. Only eight metabolites were common to both bivariate RF and PLS. CONCLUSIONS: Identification of metabolomic signatures of CKD progression is partially dependent on the statistical model. Dual analysis identified molecules specifically associated with progressive renal impairment in both T1D and T2D.

Whole-Genome Sequencing of Finnish Type 1 Diabetic Siblings Discordant for Kidney Disease Reveals DNA Variants associated with Diabetic Nephropathy.

BACKGROUND: Several genetic susceptibility loci associated with diabetic nephropathy have been documented, but no causative variants implying novel pathogenetic mechanisms have been elucidated. METHODS: We carried out whole-genome sequencing of a discovery cohort of Finnish siblings with type 1 diabetes who were discordant for the presence (case) or absence (control) of diabetic nephropathy. Controls had diabetes without complications for 15-37 years. We analyzed and annotated variants at genome, gene, and single-nucleotide variant levels. We then replicated the associated variants, genes, and regions in a replication cohort from the Finnish Diabetic Nephropathy study that included 3531 unrelated Finns with type 1 diabetes. RESULTS: We observed protein-altering variants and an enrichment of variants in regions associated with the presence or absence of diabetic nephropathy. The replication cohort confirmed variants in both regulatory and protein-coding regions. We also observed that diabetic nephropathy-associated variants, when clustered at the gene level, are enriched in a core protein-interaction network representing proteins essential for podocyte function. These genes include protein kinases (protein kinase C isoforms ε and ι) and protein tyrosine kinase 2. CONCLUSIONS: Our comprehensive analysis of a diabetic nephropathy cohort of siblings with type 1 diabetes who were discordant for kidney disease points to variants and genes that are potentially causative or protective for diabetic nephropathy. This includes variants in two isoforms of the protein kinase C family not previously linked to diabetic nephropathy, adding support to previous hypotheses that the protein kinase C family members play a role in diabetic nephropathy and might be attractive therapeutic targets.

Sphingomyelin and progression of renal and coronary heart disease in individuals with type 1 diabetes.

AIMS/HYPOTHESIS: Lipid abnormalities are associated with diabetic kidney disease and CHD, although their exact role has not yet been fully explained. Sphingomyelin, the predominant sphingolipid in humans, is crucial for intact glomerular and endothelial function. Therefore, the objective of our study was to investigate whether sphingomyelin impacts kidney disease and CHD progression in individuals with type 1 diabetes. METHODS: Individuals (n = 1087) from the Finnish Diabetic Nephropathy (FinnDiane) prospective cohort study with serum sphingomyelin measured using a proton NMR metabolomics platform were included. Kidney disease progression was defined as change in eGFR or albuminuria stratum. Data on incident end-stage renal disease (ESRD) and CHD were retrieved from national registries. HRs from Cox regression models and regression coefficients from the logistic or linear regression analyses were reported per 1 SD increase in sphingomyelin level. In addition, receiver operating curves were used to assess whether sphingomyelin improves eGFR decline prediction compared with albuminuria. RESULTS: During a median (IQR) 10.7 (6.4, 13.5) years of follow-up, sphingomyelin was independently associated with the fastest eGFR decline (lowest 25%; median [IQR] for eGFR change: <-4.4 [-6.8, -3.1] ml min-1 [1.73 m-2] year-1), even after adjustment for classical lipid variables such as HDL-cholesterol and triacylglycerols (OR [95% CI]: 1.36 [1.15, 1.61], p < 0.001). Similarly, sphingomyelin increased the risk of progression to ESRD (HR [95% CI]: 1.53 [1.19, 1.97], p = 0.001). Moreover, sphingomyelin increased the risk of CHD (HR [95% CI]: 1.24 [1.01, 1.52], p = 0.038). However, sphingomyelin did not perform better than albuminuria in the prediction of eGFR decline. CONCLUSIONS/INTERPRETATION: This study demonstrates for the first time in a prospective setting that sphingomyelin is associated with the fastest eGFR decline and progression to ESRD in type 1 diabetes. In addition, sphingomyelin is a risk factor for CHD. These data suggest that high sphingomyelin level, independently of classical lipid risk factors, may contribute not only to the initiation and progression of kidney disease but also to CHD. Graphical abstract.

Decreased plasma kallikrein activity is associated with reduced kidney function in individuals with type 1 diabetes.

AIMS/HYPOTHESIS: Plasma kallikrein is the central mediator of the plasma kallikrein-kinin system, which is involved both in vascular control and thrombin formation cascades. The plasma kallikrein-kinin system has also been considered protective in pathological conditions, but the impact of plasma kallikreins on diabetic nephropathy remains unknown. The objective of this cross-sectional study was to explore the association of plasma kallikrein with diabetic nephropathy. METHODS: We measured plasma kallikrein activity in 295 individuals with type 1 diabetes at various stages of diabetic nephropathy, and we tested the genetic association between the plasma kallikrein-kinin system and kidney function in 4400 individuals with type 1 diabetes. RESULTS: Plasma kallikrein activity was associated with diabetes duration (p < 0.001) and eGFR (p < 0.001), and plasma kallikrein activity was lower with more advanced diabetic nephropathy, being lowest in individuals on dialysis. The minor alleles of the KNG1 rs5030062 and rs710446 variants, which have previously been associated with increased plasma pre-kallikrein and/or factor XI (FXI) protein levels, were associated with higher eGFR (rs5030062 ß = 0.03, p = 0.01; rs710446 ß = 0.03, p = 0.005) in the FinnDiane cohort of 4400 individuals with type 1 diabetes. CONCLUSIONS/INTERPRETATION: Plasma kallikrein activity and genetic variants known to increase the plasma kallikrein level are associated with higher eGFR in individuals with type 1 diabetes, suggesting that plasma kallikrein might have a protective effect in diabetic nephropathy.

Relationship between ABO blood groups and cardiovascular disease in type 1 diabetes according to diabetic nephropathy status.

BACKGROUND: ABO blood groups have previously been associated with cardiovascular disease (CVD) in the general population. This study aimed to investigate the potential relationship between ABO blood groups and CVD in individuals with type 1 diabetes according to diabetic nephropathy (DN) status. METHODS: Adults with type 1 diabetes (4531 individuals) from the FinnDiane Study were evaluated. DN was determined by two out of three measurements of urinary albumin excretion rate. Albuminuria was defined as an excretion rate above 20 µg/min. CVD events were identified by linking the data with the Finnish Care Register for Health Care and the Finnish Cause of Death Register. Follow-up ranged from the baseline visit until a CVD event, death or the end of 2017. The impact of ABO blood groups on CVD risk was estimated by multivariable Cox-regression analyses adjusted for traditional risk factors. RESULTS: At baseline, the median age was 38.5 (IQR 29.2-47.9) years, 47.5% were female and median duration of diabetes was 20.9 (11.4-30.7) years. There were 893 incident ischemic heart disease (IHD) events, 301 ischemic strokes (IS), and 415 peripheral artery disease (PAD) events during a median follow up of 16.5 (IQR 12.8-18.6) years. The A blood group showed the highest risk of IHD versus the O blood group, when microalbuminuria was present. Comparing the population with microalbuminuria with those with normoalbuminuria, only the A blood group elevated the risk of IHD. This increased risk was neither explained by the FUT2 secretor phenotype nor by the A-genotype distribution. The risk of IS or PAD was no different among the ABO blood groups regardless of diabetic nephropathy stage. CONCLUSION: The A blood group is a risk factor for IHD in individuals with type 1 diabetes and microalbuminuria.

A Targeted Multiomics Approach to Identify Biomarkers Associated with Rapid eGFR Decline in Type 1 Diabetes.

BACKGROUND: Individuals with type 1 diabetes (T1D) demonstrate varied trajectories of estimated glomerular filtration rate (eGFR) decline. The molecular pathways underlying rapid eGFR decline in T1D are poorly understood, and individual-level risk of rapid eGFR decline is difficult to predict. METHODS: We designed a case-control study with multiple exposure measurements nested within 4 well-characterized T1D cohorts (FinnDiane, Steno, EDC, and CACTI) to identify biomarkers associated with rapid eGFR decline. Here, we report the rationale for and design of these studies as well as results of models testing associations of clinical characteristics with rapid eGFR decline in the study population, upon which "omics" studies will be built. Cases (n = 535) and controls (n = 895) were defined as having an annual eGFR decline of ≥3 and <1 mL/min/1.73 m2, respectively. Associations of demographic and clinical variables with rapid eGFR decline were tested using logistic regression, and prediction was evaluated using area under the curve (AUC) statistics. Targeted metabolomics, lipidomics, and proteomics are being performed using high-resolution mass-spectrometry techniques. RESULTS: At baseline, the mean age was 43 years, diabetes duration was 27 years, eGFR was 94 mL/min/1.73 m2, and 62% of participants were normoalbuminuric. Over 7.6-year median follow-up, the mean annual change in eGFR in cases and controls was -5.7 and 0.6 mL/min/1.73 m2, respectively. Younger age, longer diabetes duration, and higher baseline HbA1c, urine albumin-creatinine ratio, and eGFR were significantly associated with rapid eGFR decline. The cross-validated AUC for the predictive model incorporating these variables plus sex and mean arterial blood pressure was 0.74 (95% CI: 0.68-0.79; p < 0.001). CONCLUSION: Known risk factors provide moderate discrimination of rapid eGFR decline. Identification of blood and urine biomarkers associated with rapid eGFR decline in T1D using targeted omics strategies may provide insight into disease mechanisms and improve upon clinical predictive models using traditional risk factors.

Genome-Wide Association Study of Diabetic Kidney Disease Highlights Biology Involved in Glomerular Basement Membrane Collagen.

BACKGROUND: Although diabetic kidney disease demonstrates both familial clustering and single nucleotide polymorphism heritability, the specific genetic factors influencing risk remain largely unknown. METHODS: To identify genetic variants predisposing to diabetic kidney disease, we performed genome-wide association study (GWAS) analyses. Through collaboration with the Diabetes Nephropathy Collaborative Research Initiative, we assembled a large collection of type 1 diabetes cohorts with harmonized diabetic kidney disease phenotypes. We used a spectrum of ten diabetic kidney disease definitions based on albuminuria and renal function. RESULTS: Our GWAS meta-analysis included association results for up to 19,406 individuals of European descent with type 1 diabetes. We identified 16 genome-wide significant risk loci. The variant with the strongest association (rs55703767) is a common missense mutation in the collagen type IV alpha 3 chain (COL4A3) gene, which encodes a major structural component of the glomerular basement membrane (GBM). Mutations in COL4A3 are implicated in heritable nephropathies, including the progressive inherited nephropathy Alport syndrome. The rs55703767 minor allele (Asp326Tyr) is protective against several definitions of diabetic kidney disease, including albuminuria and ESKD, and demonstrated a significant association with GBM width; protective allele carriers had thinner GBM before any signs of kidney disease, and its effect was dependent on glycemia. Three other loci are in or near genes with known or suggestive involvement in this condition (BMP7) or renal biology (COLEC11 and DDR1). CONCLUSIONS: The 16 diabetic kidney disease-associated loci may provide novel insights into the pathogenesis of this condition and help identify potential biologic targets for prevention and treatment.

Soluble receptor for AGE in diabetic nephropathy and its progression in Finnish individuals with type 1 diabetes.

AIMS/HYPOTHESIS: Activation of the receptor for AGE (RAGE) has been shown to be associated with diabetic nephropathy. The soluble isoform of RAGE (sRAGE) is considered to function as a decoy receptor for RAGE ligands and thereby protects against diabetic complications. A possible association between sRAGE and diabetic nephropathy is still, however, controversial and a more comprehensive analysis of sRAGE with respect to diabetic nephropathy in type 1 diabetes is therefore warranted. METHODS: sRAGE was measured in baseline serum samples from 3647 participants with type 1 diabetes from the nationwide multicentre Finnish Diabetic Nephropathy (FinnDiane) Study. Associations between sRAGE and diabetic nephropathy, as well as sRAGE and diabetic nephropathy progression, were evaluated by regression, competing risks and receiver operating characteristic curve analyses. The non-synonymous SNP rs2070600 (G82S) was used to test causality in the Mendelian randomisation analysis. RESULTS: Baseline sRAGE concentrations were highest in participants with diabetic nephropathy, compared with participants with a normal AER or those with microalbuminuria. Baseline sRAGE was associated with progression from macroalbuminuria to end-stage renal disease (ESRD) in the competing risks analyses, but this association disappeared when eGFR was entered into the model. The SNP rs2070600 was strongly associated with sRAGE concentrations and with progression from macroalbuminuria to ESRD. However, Mendelian randomisation analysis did not support a causal role for sRAGE in progression to ESRD. CONCLUSIONS/INTERPRETATION: sRAGE is associated with progression from macroalbuminuria to ESRD, but does not add predictive value on top of conventional risk factors. Although sRAGE is a biomarker of diabetic nephropathy, in light of the Mendelian randomisation analysis it does not seem to be causally related to progression from macroalbuminuria to ESRD.

Biomarker panels associated with progression of renal disease in type 1 diabetes.

AIMS/HYPOTHESIS: We aimed to identify a sparse panel of biomarkers for improving the prediction of renal disease progression in type 1 diabetes. METHODS: We considered 859 individuals recruited from the Scottish Diabetes Research Network Type 1 Bioresource (SDRNT1BIO) and 315 individuals from the Finnish Diabetic Nephropathy (FinnDiane) study. All had an entry eGFR between 30 and 75 ml min-1[1.73 m]-2, with those from FinnDiane being oversampled for albuminuria. A total of 297 circulating biomarkers (30 proteins, 121 metabolites, 146 tryptic peptides) were measured in non-fasting serum samples using the Luminex platform and LC electrospray tandem MS (LC-MS/MS). We investigated associations with final eGFR adjusted for baseline eGFR and with rapid progression (a loss of more than 3 ml min-1[1.73 m]-2 year-1) using linear and logistic regression models. Panels of biomarkers were identified using a penalised Bayesian approach, and their performance was evaluated through 10-fold cross-validation and compared with using clinical record data alone. RESULTS: For final eGFR, 16 proteins and 30 metabolites or tryptic peptides showed significant association in SDRNT1BIO, and nine proteins and five metabolites or tryptic peptides in FinnDiane, beyond age, sex, diabetes duration, study day eGFR and length of follow-up (all at p < 10-4). The strongest associations were with CD27 antigen (CD27), kidney injury molecule 1 (KIM-1) and α1-microglobulin. Including the Luminex biomarkers on top of baseline covariates increased the r2 for prediction of final eGFR from 0.47 to 0.58 in SDRNT1BIO and from 0.33 to 0.48 in FinnDiane. At least 75% of the increment in r2 was attributable to CD27 and KIM-1. However, using the weighted average of historical eGFR gave similar performance to biomarkers. The LC-MS/MS platform performed less well. CONCLUSIONS/INTERPRETATION: Among a large set of associated biomarkers, a sparse panel of just CD27 and KIM-1 contains most of the predictive information for eGFR progression. The increment in prediction beyond clinical data was modest but potentially useful for oversampling individuals with rapid disease progression into clinical trials, especially where there is little information on prior eGFR trajectories.

A novel rare CUBN variant and three additional genes identified in Europeans with and without diabetes: results from an exome-wide association study of albuminuria.

AIMS/HYPOTHESIS: Identifying rare coding variants associated with albuminuria may open new avenues for preventing chronic kidney disease and end-stage renal disease, which are highly prevalent in individuals with diabetes. Efforts to identify genetic susceptibility variants for albuminuria have so far been limited, with the majority of studies focusing on common variants. METHODS: We performed an exome-wide association study to identify coding variants in a two-stage (discovery and replication) approach. Data from 33,985 individuals of European ancestry (15,872 with and 18,113 without diabetes) and 2605 Greenlanders were included. RESULTS: We identified a rare (minor allele frequency [MAF]: 0.8%) missense (A1690V) variant in CUBN (rs141640975, ß = 0.27, p = 1.3 × 10-11) associated with albuminuria as a continuous measure in the combined European meta-analysis. The presence of each rare allele of the variant was associated with a 6.4% increase in albuminuria. The rare CUBN variant had an effect that was three times stronger in individuals with type 2 diabetes compared with those without (pinteraction = 7.0 × 10-4, ß with diabetes = 0.69, ß without diabetes = 0.20) in the discovery meta-analysis. Gene-aggregate tests based on rare and common variants identified three additional genes associated with albuminuria (HES1, CDC73 and GRM5) after multiple testing correction (pBonferroni < 2.7 × 10-6). CONCLUSIONS/INTERPRETATION: The current study identifies a rare coding variant in the CUBN locus and other potential genes associated with albuminuria in individuals with and without diabetes. These genes have been implicated in renal and cardiovascular dysfunction. The findings provide new insights into the genetic architecture of albuminuria and highlight target genes and pathways for the prevention of diabetes-related kidney disease.

Genome-Wide Association of CKD Progression: The Chronic Renal Insufficiency Cohort Study.

The rate of decline of renal function varies significantly among individuals with CKD. To understand better the contribution of genetics to CKD progression, we performed a genome-wide association study among participants in the Chronic Renal Insufficiency Cohort Study. Our outcome of interest was CKD progression measured as change in eGFR over time among 1331 blacks and 1476 whites with CKD. We stratified all analyses by race and subsequently, diabetes status. Single-nucleotide polymorphisms (SNPs) that surpassed a significance threshold of P<1×10-6 for association with eGFR slope were selected as candidates for follow-up and secondarily tested for association with proteinuria and time to ESRD. We identified 12 such SNPs among black patients and six such SNPs among white patients. We were able to conduct follow-up analyses of three candidate SNPs in similar (replication) cohorts and eight candidate SNPs in phenotype-related (validation) cohorts. Among blacks without diabetes, rs653747 in LINC00923 replicated in the African American Study of Kidney Disease and Hypertension cohort (discovery P=5.42×10-7; replication P=0.039; combined P=7.42×10-9). This SNP also associated with ESRD (hazard ratio, 2.0 (95% confidence interval, 1.5 to 2.7); P=4.90×10-6). Similarly, rs931891 in LINC00923 associated with eGFR decline (P=1.44×10-4) in white patients without diabetes. In summary, SNPs in LINC00923, an RNA gene expressed in the kidney, significantly associated with CKD progression in individuals with nondiabetic CKD. However, the lack of equivalent cohorts hampered replication for most discovery loci. Further replication of our findings in comparable study populations is warranted.

The Genetic Landscape of Renal Complications in Type 1 Diabetes.

Diabetes is the leading cause of ESRD. Despite evidence for a substantial heritability of diabetic kidney disease, efforts to identify genetic susceptibility variants have had limited success. We extended previous efforts in three dimensions, examining a more comprehensive set of genetic variants in larger numbers of subjects with type 1 diabetes characterized for a wider range of cross-sectional diabetic kidney disease phenotypes. In 2843 subjects, we estimated that the heritability of diabetic kidney disease was 35% (P=6.4×10-3). Genome-wide association analysis and replication in 12,540 individuals identified no single variants reaching stringent levels of significance and, despite excellent power, provided little independent confirmation of previously published associated variants. Whole-exome sequencing in 997 subjects failed to identify any large-effect coding alleles of lower frequency influencing the risk of diabetic kidney disease. However, sets of alleles increasing body mass index (P=2.2×10-5) and the risk of type 2 diabetes (P=6.1×10-4) associated with the risk of diabetic kidney disease. We also found genome-wide genetic correlation between diabetic kidney disease and failure at smoking cessation (P=1.1×10-4). Pathway analysis implicated ascorbate and aldarate metabolism (P=9.0×10-6), and pentose and glucuronate interconversions (P=3.0×10-6) in pathogenesis of diabetic kidney disease. These data provide further evidence for the role of genetic factors influencing diabetic kidney disease in those with type 1 diabetes and highlight some key pathways that may be responsible. Altogether these results reveal important biology behind the major cause of kidney disease.

The serum uric acid concentration is not causally linked to diabetic nephropathy in type 1 diabetes.

Previous studies have shown a relationship between uric acid concentration and progression of renal disease. Here we studied causality between the serum uric acid concentration and progression of diabetic nephropathy in 3895 individuals with type 1 diabetes in the FinnDiane Study. The renal status was assessed with the urinary albumin excretion rate and estimated glomerular filtration rate (eGFR) at baseline and at the end of the follow-up. Based on previous genomewide association studies on serum uric acid concentration, 23 single nucleotide polymorphisms (SNPs) with good imputation quality were selected for the SNP score. This score was used to assess the causality between serum uric acid and renal complications using a Mendelian randomization approach. At baseline, the serum uric acid concentration was higher with worsening renal status. In multivariable Cox regression analyses, baseline serum uric acid concentration was not independently associated with progression of diabetic nephropathy over a mean follow-up of 7 years. However, over the same period, baseline serum uric acid was independently associated with the decline in eGFR. In the cross-sectional logistic regression analyses, the SNP score was associated with the serum uric acid concentration. Nevertheless, the Mendelian randomization showed no causality between uric acid and diabetic nephropathy, eGFR categories, or eGFR as a continuous variable. Thus, our results suggest that the serum uric acid concentration is not causally related to diabetic nephropathy but is a downstream marker of kidney damage.

An excess of risk-increasing low-frequency variants can be a signal of polygenic inheritance in complex diseases.

In most complex diseases, much of the heritability remains unaccounted for by common variants. It has been postulated that lower-frequency variants contribute to the remaining heritability. Here, we describe a method to test for polygenic inheritance from lower-frequency variants by using GWAS summary association statistics. We explored scenarios with many causal low-frequency variants and showed that there is more power to detect risk variants than to detect protective variants, resulting in an increase in the ratio of detected risk to protective variants (R/P ratio). Such an excess can also occur if risk variants are present and kept at lower frequencies because of negative selection. The R/P ratio can be falsely elevated because of reasons unrelated to polygenic inheritance, such as uneven sample sizes or asymmetric population stratification, so precautions to correct for these confounders are essential. We tested our method on published GWAS results and observed a strong signal in some diseases (schizophrenia and type 2 diabetes) but not others. We also explored the shared genetic component in overlapping phenotypes related to inflammatory bowel disease (Crohn disease [CD] and ulcerative colitis [UC]) and diabetic nephropathy (macroalbuminuria and end-stage renal disease [ESRD]). Although the signal was still present when both CD and UC were jointly analyzed, the signal was lost when macroalbuminuria and ESRD were jointly analyzed, suggesting that these phenotypes should best be studied separately. Thus, our method may also help guide the design of future genetic studies of various traits and diseases.

Progress in Defining the Genetic Basis of Diabetic Complications.

PURPOSE OF REVIEW: Diabetic complications affecting the kidneys, retina, nerves, and the cardiovasculature are the major causes of morbidity and mortality in diabetes. This paper aims to review the current understanding of the genetic basis of these complications, based on recent findings especially from genome-wide association studies. RECENT FINDINGS: Variants in or near AFF3, RGMA-MCTP2, SP3-CDCA7, GLRA3, CNKSR3, and UMOD have reached genome-wide significance (p value <5 × 10-8) for association with diabetic kidney disease, and recently, GRB2 was reported to be associated at genome-wide significance with diabetic retinopathy. While some loci affecting cardiovascular disease in the general population have been replicated in diabetes, GLUL affects the risk of cardiovascular disease specifically in diabetic subjects. Genetic findings are emerging for diabetic complications, although the studies remain relatively small compared to those for type 1 and type 2 diabetes. In addition to pinpointing specific loci, the studies also reveal biological information on correlated traits and pathways.

SORBS1 gene, a new candidate for diabetic nephropathy: results from a multi-stage genome-wide association study in patients with type 1 diabetes.

AIMS/HYPOTHESIS: The genetic determinants of diabetic nephropathy remain poorly understood. We aimed to identify novel susceptibility genes for diabetic nephropathy. METHODS: We performed a genome-wide association study using 1000 Genomes-based imputation to compare type 1 diabetic nephropathy cases with proteinuria and with or without renal failure with control patients who have had diabetes for more than 15 years and no evidence of renal disease. RESULTS: None of the single nucleotide polymorphisms (SNPs) tested in a discovery cohort composed of 683 cases and 779 controls reached genome-wide statistical significance. The 46 top hits (p < 10(-5)) were then sought for first-stage analysis in the Genetics of Kidneys in Diabetes US (US-GoKinD) study, an independent population of 820 cases and 885 controls. Two SNPs in strong linkage disequilibrium with each other and located in the SORBS1 gene were consistently and significantly (p < 10(-4)) associated with diabetic nephropathy. The minor rs1326934-C allele was less frequent in cases than in controls (0.34 vs 0.43) and was associated with a decreased risk for diabetic nephropathy (OR 0.70; 95% CI 0.60, 0.82). However, this association was not observed in a second stage with two additional diabetic nephropathy cohorts, the All Ireland-Warren 3-Genetics of Kidneys in Diabetes UK and Republic of Ireland (UK-ROI; p = 0.15) and the Finnish Diabetic Nephropathy (FinnDiane; p = 0.44) studies, totalling 2,142 cases and 2,494 controls. Altogether, the random-effect meta-analysed rs1326934-C allele OR for diabetic nephropathy was 0.83 (95% CI 0.72, 0.96; p = 0.009). CONCLUSIONS/INTERPRETATION: These data suggest that SORBS1 might be a gene involved in diabetic nephropathy.