Genetic variants affecting mitochondrial function provide further insights for kidney disease.

BACKGROUND: Chronic kidney disease (CKD) is a complex disorder that has become a high prevalence global health problem, with diabetes being its predominant pathophysiologic driver. Autosomal genetic variation only explains some of the predisposition to kidney disease. Variations in the mitochondrial genome (mtDNA) and nuclear-encoded mitochondrial genes (NEMG) are implicated in susceptibility to kidney disease and CKD progression, but they have not been thoroughly explored. Our aim was to investigate the association of variation in both mtDNA and NEMG with CKD (and related traits), with a particular focus on diabetes. METHODS: We used the UK Biobank (UKB) and UK-ROI, an independent collection of individuals with type 1 diabetes mellitus (T1DM) patients. RESULTS: Fourteen mitochondrial variants were associated with estimated glomerular filtration rate (eGFR) in UKB. Mitochondrial variants and haplogroups U, H and J were associated with eGFR and serum variables. Mitochondrial haplogroup H was associated with all the serum variables regardless of the presence of diabetes. Mitochondrial haplogroup X was associated with end-stage kidney disease (ESKD) in UKB. We confirmed the influence of several known NEMG on kidney disease and function and found novel associations for SLC39A13, CFL1, ACP2 or ATP5G1 with serum variables and kidney damage, and for SLC4A1, NUP210 and MYH14 with ESKD. The G allele of TBC1D32-rs113987180 was associated with higher risk of ESKD in patients with diabetes (OR:9.879; CI95%:4.440-21.980; P = 2.0E-08). In UK-ROI, AGXT2-rs71615838 and SURF1-rs183853102 were associated with diabetic nephropathies, and TFB1M-rs869120 with eGFR. CONCLUSIONS: We identified novel variants both in mtDNA and NEMG which may explain some of the missing heritability for CKD and kidney phenotypes. We confirmed the role of MT-ND5 and mitochondrial haplogroup H on renal disease (serum variables), and identified the MT-ND5-rs41535848G variant, along with mitochondrial haplogroup X, associated with higher risk of ESKD. Despite most of the associations were independent of diabetes, we also showed potential roles for NEMG in T1DM.

Integrated multiomic analyses: An approach to improve understanding of diabetic kidney disease.

AIM: Diabetes is increasing in prevalence worldwide, with a 20% rise in prevalence predicted between 2021 and 2030, bringing an increased burden of complications, such as diabetic kidney disease (DKD). DKD is a leading cause of end-stage kidney disease, with significant impacts on patients, families and healthcare providers. DKD often goes undetected until later stages, due to asymptomatic disease, non-standard presentation or progression, and sub-optimal screening tools and/or provision. Deeper insights are needed to improve DKD diagnosis, facilitating the identification of higher-risk patients. Improved tools to stratify patients based on disease prognosis would facilitate the optimisation of resources and the individualisation of care. This review aimed to identify how multiomic approaches provide an opportunity to understand the complex underlying biology of DKD. METHODS: This review explores how multiomic analyses of DKD are improving our understanding of DKD pathology, and aiding in the identification of novel biomarkers to detect disease earlier or predict trajectories. RESULTS: Effective multiomic data integration allows novel interactions to be uncovered and empathises the need for harmonised studies and the incorporation of additional data types, such as co-morbidity, environmental and demographic data to understand DKD complexity. This will facilitate a better understanding of kidney health inequalities, such as social-, ethnicity- and sex-related differences in DKD risk, onset and progression. CONCLUSION: Multiomics provides opportunities to uncover how lifetime exposures become molecularly embodied to impact kidney health. Such insights would advance DKD diagnosis and treatment, inform preventative strategies and reduce the global impact of this disease.

When should we offer antenatal sequencing for urinary tract malformations? A systematic review, cohort study and meta-analysis.

OBJECTIVE: Determine the incremental yield of prenatal exome sequencing (PES) over chromosome microarray (CMA) and/or karyotype for urinary tract malformations (UTMs). METHOD: A prospective cohort study encompassing data from the English Genomic Medicine Service North Thames Laboratory Hub for fetuses with bilateral echogenic kidneys (BEKs) was combined with data from a systematic review. MEDLINE, EMBASE, Web of Science, MedRxiv and GreyLit were searched from 01/2010-02/2023 for studies reporting on the yield of PES over CMA or karyotype in fetuses with UTMs. Pooled incremental yield was determined using a random effects model. PROSPERO CRD42023364544. RESULTS: Fourteen studies (410 cases) were included. The incremental yield for multisystem UTMs, any isolated UTMs, and BEKs was 31% [95% CI, 18%-46%; I2  = 78%], 16% [95% CI, 6%-26%; I2  = 80%] and 51% [95% CI, 27%-75%; I2  = 34%]. The most common clinical diseases and syndromes identified, based on the variant genes detected, were Bardet-Biedl syndrome (BBS genes), dominant and recessive polycystic kidney diseases (PKD1, PKD2 and PKHD1) and renal cysts and diabetes syndrome (HNF1B). CONCLUSION: There was a notable incremental genetic diagnostic yield when PES was applied to multisystem UTMs and BEKs. There was a modest incremental yield when this technique was used for UTMs other than BEKs.

Albuminuria-Related Genetic Biomarkers: Replication and Predictive Evaluation in Individuals with and without Diabetes from the UK Biobank.

Increased albuminuria indicates underlying glomerular pathology and is associated with worse renal disease outcomes, especially in diabetic kidney disease. Many single nucleotide polymorphisms (SNPs), associated with albuminuria, could be potentially useful to construct polygenic risk scores (PRSs) for kidney disease. We investigated the diagnostic accuracy of SNPs, previously associated with albuminuria-related traits, on albuminuria and renal injury in the UK Biobank population, with a particular interest in diabetes. Multivariable logistic regression was used to evaluate the influence of 91 SNPs on urine albumin-to-creatinine ratio (UACR)-related traits and kidney damage (any pathology indicating renal injury), stratifying by diabetes. Weighted PRSs for microalbuminuria and UACR from previous studies were used to calculate the area under the receiver operating characteristic curve (AUROC). CUBN-rs1801239 and DDR1-rs116772905 were associated with all the UACR-derived phenotypes, in both the overall and non-diabetic cohorts, but not with kidney damage. Several SNPs demonstrated different effects in individuals with diabetes compared to those without. SNPs did not improve the AUROC over currently used clinical variables. Many SNPs are associated with UACR or renal injury, suggesting a role in kidney dysfunction, dependent on the presence of diabetes in some cases. However, individual SNPs or PRSs did not improve the diagnostic accuracy for albuminuria or renal injury compared to standard clinical variables.

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 ).

Information on Genetic Variants Does Not Increase Identification of Individuals at Risk of Esophageal Adenocarcinoma Compared to Clinical Risk Factors.

We previously developed a tool that identified individuals who later developed esophageal adenocarcinoma (based on age, sex, body mass index, smoking status, and prior esophageal conditions) with an area under the curve of 0.80. In this study, we collected data from 329,463 individuals in the UK Biobank cohort who were tested for genetic susceptibility to esophageal adenocarcinoma (a polygenic risk score based on 18 recognized genetic variants). We found that after inclusion of this genetic information, the area under the curve for identification of individuals who developed esophageal adenocarcinoma remained at 0.80. Testing for genetic variants associated with esophageal adenocarcinoma therefore seems unlikely to improve identification of individuals at risk of esophageal adenocarcinoma.

Contribution of cystatin C- and creatinine-based definitions of chronic kidney disease to cardiovascular risk assessment in 20 population-based and 3 disease cohorts: the BiomarCaRE project.

BACKGROUND: Chronic kidney disease has emerged as a strong cardiovascular risk factor, and in many current guidelines, it is already considered as a coronary heart disease (CHD) equivalent. Routinely, creatinine has been used as the main marker of renal function, but recently, cystatin C emerged as a more promising marker. The aim of this study was to assess the comparative cardiovascular and mortality risk of chronic kidney disease (CKD) using cystatin C-based and creatinine-based equations of the estimated glomerular filtration rate (eGFR) in participants of population-based and disease cohorts. METHODS: The present study has been conducted within the BiomarCaRE project, with harmonized data from 20 population-based cohorts (n = 76,954) from 6 European countries and 3 cardiovascular disease (CVD) cohorts (n = 4982) from Germany. Cox proportional hazards models were used to assess hazard ratios (HRs) for the various CKD definitions with adverse outcomes and mortality after adjustment for the Systematic COronary Risk Evaluation (SCORE) variables and study center. Main outcome measures were cardiovascular diseases, cardiovascular death, and all-cause mortality. RESULTS: The overall prevalence of CKD stage 3-5 by creatinine- and cystatin C-based eGFR, respectively, was 3.3% and 7.4% in the population-based cohorts and 13.9% and 14.4% in the disease cohorts. CKD was an important independent risk factor for subsequent CVD events and mortality. For example, in the population-based cohorts, the HR for CVD mortality was 1.72 (95% CI 1.53 to 1.92) with creatinine-based CKD and it was 2.14 (95% CI 1.90 to 2.40) based on cystatin-based CKD compared to participants without CKD. In general, the HRs were higher for cystatin C-based CKD compared to creatinine-based CKD, for all three outcomes and risk increased clearly below the conventional threshold for CKD, also in older adults. Net reclassification indices were larger for a cystatin-C based CKD definition. Differences in HRs (between the two CKD measures) in the disease cohorts were less pronounced than in the population-based cohorts. CONCLUSION: CKD is an important risk factor for subsequent CVD events and total mortality. However, point estimates of creatinine- and cystatin C-based CKD differed considerably between low- and high-risk populations. Especially in low-risk settings, the use of cystatin C-based CKD may result in more accurate risk estimates and have better prognostic value.

Polygenic risk score as a determinant of risk of non-melanoma skin cancer in a European-descent renal transplant cohort.

Renal transplant recipients have an increased risk of non-melanoma skin cancer (NMSC) compared to in the general population. Here, we show polygenic risk scores (PRS) calculated from genome-wide association studies (GWAS) of NMSC in a general, nontransplant setting, can predict risk of, and time to posttransplant skin cancer. Genetic variants, reaching predefined P-value thresholds were chosen from published squamous cell carcinoma (SCC) and basal cell carcinoma (BCC) nontransplant GWAS. Using these GWAS, BCC and SCC PRS were calculated for each sample across three European ancestry renal transplant cohorts (n = 889) and tested as predictors of case:control status and time to NMSC posttransplant. BCC PRS calculated at P-value threshold 1 × 10-5 was the most significant predictor of case:control status of NMSC posttransplant (OR = 1.61; adjusted P = .0022; AUC [full model adjusted for clinical predictors and PRS] = 0.81). SCC PRS at P-value threshold 1 × 10-5 was the most significant predictor of time to posttransplant NMSC (adjusted P = 9.39 × 10-7 ; HR = 1.41, concordance [full model] = 0.74). PRS of nontransplant NMSC is predictive of case:control status and time to NMSC posttransplant. These results are relevant to how genomics can risk stratify patients to help develop personalized treatment regimens.

The impact of donor and recipient common clinical and genetic variation on estimated glomerular filtration rate in a European renal transplant population.

Genetic variation across the human leukocyte antigen loci is known to influence renal-transplant outcome. However, the impact of genetic variation beyond the human leukocyte antigen loci is less clear. We tested the association of common genetic variation and clinical characteristics, from both the donor and recipient, with posttransplant eGFR at different time-points, out to 5 years posttransplantation. We conducted GWAS meta-analyses across 10 844 donors and recipients from five European ancestry cohorts. We also analyzed the impact of polygenic risk scores (PRS), calculated using genetic variants associated with nontransplant eGFR, on posttransplant eGFR. PRS calculated using the recipient genotype alone, as well as combined donor and recipient genotypes were significantly associated with eGFR at 1-year posttransplant. Thirty-two percent of the variability in eGFR at 1-year posttransplant was explained by our model containing clinical covariates (including weights for death/graft-failure), principal components and combined donor-recipient PRS, with 0.3% contributed by the PRS. No individual genetic variant was significantly associated with eGFR posttransplant in the GWAS. This is the first study to examine PRS, composed of variants that impact kidney function in the general population, in a posttransplant context. Despite PRS being a significant predictor of eGFR posttransplant, the effect size of common genetic factors is limited compared to clinical variables.

Differential methylation as a diagnostic biomarker of rare renal diseases: a systematic review.

BACKGROUND: The challenges in diagnosis of rare renal conditions can negatively impact patient prognosis, quality of life and result in significant healthcare costs. Differential methylation is emerging as an important biomarker for rare diseases and should be evaluated for rare renal conditions. METHODS: A comprehensive systematic review of methylation and rare renal disorders was conducted by searching the electronic databases MEDLINE, EMBASE, PubMed, Cochrane Library, alongside grey literature from GreyLit and OpenGrey databases, for publications published before September 2018. Additionally, the reference lists of the included papers were searched. Data was extracted and appraised including the primary focus, measurement and methodological rigour of the source. Eligibility criteria were adapted using the inclusion criteria from 'The 100,000 Genomes Project' and The National Registry of Rare Kidney Diseases, with additional focus on methylation. RESULTS: Thirteen full text articles were included in the review. Diseases analysed for differential methylation included glomerular disease, IgA nephropathy, ADPKD, rare causes of proteinuria, congenital renal agenesis, and membranous nephropathy. CONCLUSIONS: Differential methylation has been observed for several rare renal diseases, highlighting its potential for improving molecular characterisation of these disorders. Further investigation of methylation following a standardised reporting structure is necessary to improve research quality. Multi-omic data will provide insights for improved diagnosis, prognosis and support for individuals living and working with rare renal diseases.

Novel risk genes identified in a genome-wide association study for coronary artery disease in patients with type 1 diabetes.

BACKGROUND: Patients with type 1 diabetes are more at risk of coronary artery disease than the general population. Although evidence points to a genetic risk there have been no study investigating genetic risk factors of coronary artery disease specific to individuals with type 1 diabetes. To identify low frequency and common genetic variations associated with coronary artery disease in populations of individuals with type 1 diabetes. METHODS: A two-stage genome wide association study was conducted. The discovery phase involved the meta-analysis of three genome-wide association cohorts totaling 434 patients with type 1 diabetes and coronary artery disease (cases) and 3123 T1D individuals with no evidence of coronary artery disease (controls). Replication of the top association signals (p < 10-5) was performed in five additional independent cohorts totaling 585 cases and 2612 controls. RESULTS: One locus (rs115829748, located upstream of the MAP1B gene) reached the statistical threshold of 5 × 10-8 for genome-wide significance but did not replicate. Nevertheless, three single nucleotide polymorphisms provided suggestive evidence for association with coronary artery disease in the combined studies: CDK18 rs138760780 (OR = 2.60 95% confidence interval [1.75-3.85], p = 2.02 × 10-6), FAM189A2 rs12344245 (OR = 1.85 [1.41-2.43], p = 8.52 × 10-6) and PKD1 rs116092985 (OR = 1.53 [1.27-1.85], p = 1.01 × 10-5). In addition, our analyses suggested that genetic variations at the ANKS1A, COL4A2 and APOE loci previously found associated with coronary artery disease in the general population could have stronger effects in patients with type 1 diabetes. CONCLUSIONS: This study suggests three novel candidate genes for coronary artery disease in the subgroup of patients affected with type 1 diabetes. The detected associations deserve to be definitively validated in additional epidemiological studies.

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.

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.

Whole-mitochondrial genome sequencing in primary open-angle glaucoma using massively parallel sequencing identifies novel and known pathogenic variants.

PURPOSE: The aim of this study was to determine whether mutations in mitochondrial DNA play a role in high-pressure primary open-angle glaucoma (OMIM 137760) by analyzing new data from massively parallel sequencing of mitochondrial DNA. METHODS: Glaucoma patients with high-tension primary open-angle glaucoma and ethnically matched and age-matched control subjects without glaucoma were recruited. The entire human mitochondrial genome was amplified in two overlapping fragments by long-range polymerase chain reaction and used as a template for massively parallel sequencing on an Ion Torrent Personal Genome Machine. All variants were confirmed by conventional Sanger sequencing. RESULTS: Whole-mitochondrial genome sequencing was performed in 32 patients with primary open-angle glaucoma from India (n = 16) and Ireland (n = 16). In 16 of the 32 patients with primary open-angle glaucoma (50% of cases), there were 22 mitochondrial DNA mutations consisting of 7 novel mutations and 8 previously reported disease-associated sequence variants. Eight of 22 (36.4%) of the mitochondrial DNA mutations were in complex I mitochondrial genes. CONCLUSION: Massively parallel sequencing using the Ion Torrent Personal Genome Machine with confirmation by Sanger sequencing detected a pathogenic mitochondrial DNA mutation in 50% of the primary open-angle glaucoma cohort. Our findings support the emerging concept that mitochondrial dysfunction results in the development of glaucoma and, more specifically, that complex I defects play a significant role in primary open-angle glaucoma pathogenesis.

Genetics of diabetic nephropathy: a long road of discovery.

The global prevalence of diabetic nephropathy is rising in parallel with the increasing incidence of diabetes in most countries. Unfortunately, up to 40 % of persons diagnosed with diabetes may develop kidney complications. Diabetic nephropathy is associated with substantially increased risks of cardiovascular disease and premature mortality. An inherited susceptibility to diabetic nephropathy exists, and progress is being made unravelling the genetic basis for nephropathy thanks to international research collaborations, shared biological resources and new analytical approaches. Multiple epidemiological studies have highlighted the clinical heterogeneity of nephropathy and the need for better phenotyping to help define important subgroups for analysis and increase the power of genetic studies. Collaborative genome-wide association studies for nephropathy have reported unique genes, highlighted novel biological pathways and suggested new disease mechanisms, but progress towards clinically relevant risk prediction models for diabetic nephropathy has been slow. This review summarises the current status, recent developments and ongoing challenges elucidating the genetics of diabetic nephropathy.

New susceptibility loci associated with kidney disease in type 1 diabetes.

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-ß1) 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.

Genetics of new-onset diabetes after transplantation.

New-onset diabetes after transplantation is a common complication that reduces recipient survival. Research in renal transplant recipients has suggested that pancreatic ß-cell dysfunction, as opposed to insulin resistance, may be the key pathologic process. In this study, clinical and genetic factors associated with new-onset diabetes after transplantation were identified in a white population. A joint analysis approach, with an initial genome-wide association study in a subset of cases followed by de novo genotyping in the complete case cohort, was implemented to identify single-nucleotide polymorphisms (SNPs) associated with the development of new-onset diabetes after transplantation. Clinical variables associated with the development of diabetes after renal transplantation included older recipient age, female sex, and percentage weight gain within 12 months of transplantation. The genome-wide association study identified 26 SNPs associated with new-onset diabetes after transplantation; this association was validated for eight SNPs (rs10484821, rs7533125, rs2861484, rs11580170, rs2020902, rs1836882, rs198372, and rs4394754) by de novo genotyping. These associations remained significant after multivariate adjustment for clinical variables. Seven of these SNPs are associated with genes implicated in ß-cell apoptosis. These results corroborate recent clinical evidence implicating ß-cell dysfunction in the pathophysiology of new-onset diabetes after transplantation and support the pursuit of therapeutic strategies to protect ß cells in the post-transplant period.

Novel genetic susceptibility loci for diabetic end-stage renal disease identified through robust naive Bayes classification.

AIMS/HYPOTHESIS: Diabetic nephropathy is a major diabetic complication, and diabetes is the leading cause of end-stage renal disease (ESRD). Family studies suggest a hereditary component for diabetic nephropathy. However, only a few genes have been associated with diabetic nephropathy or ESRD in diabetic patients. Our aim was to detect novel genetic variants associated with diabetic nephropathy and ESRD. METHODS: We exploited a novel algorithm, 'Bag of Naive Bayes', whose marker selection strategy is complementary to that of conventional genome-wide association models based on univariate association tests. The analysis was performed on a genome-wide association study of 3,464 patients with type 1 diabetes from the Finnish Diabetic Nephropathy (FinnDiane) Study and subsequently replicated with 4,263 type 1 diabetes patients from the Steno Diabetes Centre, the All Ireland-Warren 3-Genetics of Kidneys in Diabetes UK collection (UK-Republic of Ireland) and the Genetics of Kidneys in Diabetes US Study (GoKinD US). RESULTS: Five genetic loci (WNT4/ZBTB40-rs12137135, RGMA/MCTP2-rs17709344, MAPRE1P2-rs1670754, SEMA6D/SLC24A5-rs12917114 and SIK1-rs2838302) were associated with ESRD in the FinnDiane study. An association between ESRD and rs17709344, tagging the previously identified rs12437854 and located between the RGMA and MCTP2 genes, was replicated in independent case-control cohorts. rs12917114 near SEMA6D was associated with ESRD in the replication cohorts under the genotypic model (p < 0.05), and rs12137135 upstream of WNT4 was associated with ESRD in Steno. CONCLUSIONS/INTERPRETATION: This study supports the previously identified findings on the RGMA/MCTP2 region and suggests novel susceptibility loci for ESRD. This highlights the importance of applying complementary statistical methods to detect novel genetic variants in diabetic nephropathy and, in general, in complex diseases.

Genome-wide association study of urinary albumin excretion rate in patients with type 1 diabetes.

AIMS/HYPOTHESIS: An abnormal urinary albumin excretion rate (AER) is often the first clinically detectable manifestation of diabetic nephropathy. Our aim was to estimate the heritability and to detect genetic variation associated with elevated AER in patients with type 1 diabetes. METHODS: The discovery phase genome-wide association study (GWAS) included 1,925 patients with type 1 diabetes and with data on 24 h AER. AER was analysed as a continuous trait and the analysis was stratified by the use of antihypertensive medication. Signals with a p value <10(-4) were followed up in 3,750 additional patients with type 1 diabetes from seven studies. RESULTS: The narrow-sense heritability, captured with our genotyping platform, was estimated to explain 27.3% of the total AER variability, and 37.6% after adjustment for covariates. In the discovery stage, five single nucleotide polymorphisms in the GLRA3 gene were strongly associated with albuminuria (p < 5 × 10(-8)). In the replication group, a nominally significant association (p = 0.035) was observed between albuminuria and rs1564939 in GLRA3, but this was in the opposite direction. Sequencing of the surrounding genetic region in 48 Finnish and 48 UK individuals supported the possibility that population-specific rare variants contribute to the synthetic association observed at the common variants in GLRA3. The strongest replication (p = 0.026) was obtained for rs2410601 between the PSD3 and SH2D4A genes. Pathway analysis highlighted natural killer cell mediated immunity processes. CONCLUSIONS/INTERPRETATION: This study suggests novel pathways and molecular mechanisms for the pathogenesis of albuminuria in type 1 diabetes.

Genetic polymorphisms and kidney transplant outcomes.

PURPOSE OF REVIEW: Gene polymorphism studies are growing at a quasiexponential rate and aim to improve immediate and long-term outcomes in renal transplantation. This review highlights recent evidence and potential future directions for genetic research studies. RECENT FINDINGS: Studies are largely based on immunity, inflammation and pharmacogenetics, investigating mostly 'surrogate' outcomes with sometimes conflicting results. However, the last 12 months has also heralded the emergence of important genome-wide association studies on transplantation, more robust replicated multicentre analyses of candidate gene variants, meta-analyses, and an increasing interest in copy number variation and donor genetics. SUMMARY: These studies set the scene for further investigation, aiming to understand pathways of disease and biomarkers of risk, and are leading to a greater understanding of the biology of transplantation. Future studies will require focus on donor : recipient and gene : environment interactions, and an integrated approach of 'transplantomics' to evaluate long-term outcomes in multinational collaborations.