Chromosome 2q31.1 associates with ESRD in women with type 1 diabetes

Genetic and epigenetic background of diabetic kidney disease

Diabetic kidney disease (DKD) is a severe diabetic complication that affects up to half of the individuals with diabetes. Elevated blood glucose levels are a key underlying cause of DKD, but DKD is a complex multifactorial disease, which takes years to develop. Family studies have shown that inherited factors also contribute to the risk of the disease. During the last decade, genome-wide association studies (GWASs) have emerged as a powerful tool to identify genetic risk factors for DKD. In recent years, the GWASs have acquired larger number of participants, leading to increased statistical power to detect more genetic risk factors. In addition, whole-exome and whole-genome sequencing studies are emerging, aiming to identify rare genetic risk factors for DKD, as well as epigenome-wide association studies, investigating DNA methylation in relation to DKD. This article aims to review the identified genetic and epigenetic risk factors for DKD.

Progress in genetics of type 2 diabetes and diabetic complications

Type 2 diabetes results from a complex interaction between genetic and environmental factors. Precision medicine for type 2 diabetes using genetic data is expected to predict the risk of developing diabetes and complications and to predict the effects of medications and life-style intervention more accurately for individuals. Genome-wide association studies (GWAS) have been conducted in European and Asian populations and new genetic loci have been identified that modulate the risk of developing type 2 diabetes. Novel loci were discovered by GWAS in diabetic complications with increasing sample sizes. Large-scale genome-wide association analysis and polygenic risk scores using biobank information is making it possible to predict the development of type 2 diabetes. In the ADVANCE clinical trial of type 2 diabetes, a multi-polygenic risk score was useful to predict diabetic complications and their response to treatment. Proteomics and metabolomics studies have been conducted and have revealed the associations between type 2 diabetes and inflammatory signals and amino acid synthesis. Using multi-omics analysis, comprehensive molecular mechanisms have been elucidated to guide the development of targeted therapy for type 2 diabetes and diabetic complications.

A genome-wide association study identifies a possible role for cannabinoid signalling in the pathogenesis of diabetic kidney disease

Diabetic kidney disease (DKD), also known as diabetic nephropathy, is the leading cause of renal impairment and end-stage renal disease. Patients with diabetes are at risk for DKD because of poor control of their blood glucose, as well as nonmodifiable risk factors including age, ethnicity, and genetics. This genome-wide association study (GWAS) was conducted for the first time in the Emirati population to investigate possible genetic factors associated with the development and progression of DKD. We included data on 7,921,925 single nucleotide polymorphism (SNPs) in 258 cases of type 2 diabetes mellitus (T2DM) who developed DKD and 938 control subjects with T2DM who did not develop DKD. GWAS suggestive results (P < 1 × 10-5) were further replicated using summary statistics from three cohorts with T2DM-induced DKD (Bio Bank Japan data, UK Biobank, and FinnGen Project data) and T1DM-induced DKD (UK-ROI cohort data from Belfast, UK). When conducting a multiple linear regression model for gene-set analyses, the CNR2 gene demonstrated genome-wide significance at 1.46 × 10-6. SNPs in CNR2 gene, encodes cannabinoid receptor 2 or CB2, were replicated in Japanese samples with the leading SNP rs2501391 showing a Pcombined = 9.3 × 10-7, and odds ratio = 0.67 in association with DKD associated with T2DM, but not with T1DM, without any significant association with T2DM itself. The allele frequencies of our cohort and those of the replication cohorts were in most cases markedly different. In addition, we replicated the association between rs1564939 in the GLRA3 gene and DKD in T2DM (P = 0.016, odds ratio = 0.54 per allele C). Our findings suggest evidence that cannabinoid signalling may be involved in the development of DKD through CB2, which is expressed in different kidney regions and known to be involved in insulin resistance, inflammation, and the development of kidney fibrosis.

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 ).

Harnessing the Full Potential of Multi-Omic Analyses to Advance the Study and Treatment of Chronic Kidney Disease

Chronic kidney disease (CKD) was the 12th leading cause of death globally in 2017 with the prevalence of CKD estimated at ~9%. Early detection and intervention for CKD may improve patient outcomes, but standard testing approaches even in developed countries do not facilitate identification of patients at high risk of developing CKD, nor those progressing to end-stage kidney disease (ESKD). Recent advances in CKD research are moving towards a more personalised approach for CKD. Heritability for CKD ranges from 30% to 75%, yet identified genetic risk factors account for only a small proportion of the inherited contribution to CKD. More in depth analysis of genomic sequencing data in large cohorts is revealing new genetic risk factors for common diagnoses of CKD and providing novel diagnoses for rare forms of CKD. Multi-omic approaches are now being harnessed to improve our understanding of CKD and explain some of the so-called 'missing heritability'. The most common omic analyses employed for CKD are genomics, epigenomics, transcriptomics, metabolomics, proteomics and phenomics. While each of these omics have been reviewed individually, considering integrated multi-omic analysis offers considerable scope to improve our understanding and treatment of CKD. This narrative review summarises current understanding of multi-omic research alongside recent experimental and analytical approaches, discusses current challenges and future perspectives, and offers new insights for CKD.

Genetic overlap between type 1 diabetes and other autoimmune diseases

Type 1 diabetes (T1D) is a chronic disease caused by the destruction of pancreatic β cells, which is driven by autoreactive T lymphocytes. It has been described that a high proportion of T1D patients develop other autoimmune diseases (AIDs), such as autoimmune thyroid disease, celiac disease, or vitiligo, which suggests the existence of common etiological factors among these disorders. In this regard, genetic studies have identified a high number of loci consistently associated with T1D that also represent established genetic risk factors for other AIDs. In addition, studies focused on identifying the shared genetic component in autoimmunity have described several common susceptibility loci with a potential role in T1D. Elucidation of this genetic overlap has been useful in identifying key molecular pathways with a pathogenic role in multiple disorders. In this review, we summarize recent advances in understanding the shared genetic component between T1D and other AIDs and discuss how the identification of common pathogenic mechanisms can help in the development of new therapeutic approaches as well as in improving the use of existing drugs.

Scientific Advances in Diabetes: The Impact of the Innovative Medicines Initiative

Diabetes Mellitus is one of the World Health Organization's priority diseases under research by the first and second programmes of Innovative Medicines Initiative, with the acronyms IMI1 and IMI2, respectively. Up to October of 2019, 13 projects were funded by IMI for Diabetes & Metabolic disorders, namely SUMMIT, IMIDIA, DIRECT, StemBANCC, EMIF, EBiSC, INNODIA, RHAPSODY, BEAT-DKD, LITMUS, Hypo-RESOLVE, IM2PACT, and CARDIATEAM. In general, a total of €447 249 438 was spent by IMI in the area of Diabetes. In order to prompt a better integration of achievements between the different projects, we perform a literature review and used three data sources, namely the official project's websites, the contact with the project's coordinators and co-coordinator, and the CORDIS database. From the 662 citations identified, 185 were included. The data collected were integrated into the objectives proposed for the four IMI2 program research axes: (1) target and biomarker identification, (2) innovative clinical trials paradigms, (3) innovative medicines, and (4) patient-tailored adherence programmes. The IMI funded projects identified new biomarkers, medical and research tools, determinants of inter-individual variability, relevant pathways, clinical trial designs, clinical endpoints, therapeutic targets and concepts, pharmacologic agents, large-scale production strategies, and patient-centered predictive models for diabetes and its complications. Taking into account the scientific data produced, we provided a joint vision with strategies for integrating personalized medicine into healthcare practice. The major limitations of this article were the large gap of data in the libraries on the official project websites and even the Cordis database was not complete and up to date.

Gender Differences in Diabetic Kidney Disease: Focus on Hormonal, Genetic and Clinical Factors

Diabetic kidney disease (DKD) is one of the most serious complications of both type 1 (T1DM) and type 2 diabetes mellitus (T2DM). Current guidelines recommend a personalized approach in order to reduce the burden of DM and its complications. Recognizing sex and gender- differences in medicine is considered one of the first steps toward personalized medicine, but the gender issue in DM has been scarcely explored so far. Gender differences have been reported in the incidence and the prevalence of DKD, in its phenotypes and clinical manifestations, as well as in several risk factors, with a different impact in the two genders. Hormonal factors, especially estrogen loss, play a significant role in explaining these differences. Additionally, the impact of sex chromosomes as well as the influence of gene-sex interactions with several susceptibility genes for DKD have been investigated. In spite of the increasing evidence that sex and gender should be included in the evaluation of DKD, several open issues remain uncovered, including the potentially different effects of newly recommended drugs, such as SGLT2i and GLP1Ras. This narrative review explored current evidence on sex/gender differences in DKD, taking into account hormonal, genetic and clinical factors.

Assessment of differentially methylated loci in individuals with end-stage kidney disease attributed to diabetic kidney disease: an exploratory study

BACKGROUND

A subset of individuals with type 1 diabetes mellitus (T1DM) are predisposed to developing diabetic kidney disease (DKD), the most common cause globally of end-stage kidney disease (ESKD). Emerging evidence suggests epigenetic changes in DNA methylation may have a causal role in both T1DM and DKD. The aim of this exploratory investigation was to assess differences in blood-derived DNA methylation patterns between individuals with T1DM-ESKD and individuals with long-duration T1DM but no evidence of kidney disease upon repeated testing to identify potential blood-based biomarkers. Blood-derived DNA from individuals (107 cases, 253 controls and 14 experimental controls) were bisulphite treated before DNA methylation patterns from both groups were generated and analysed using Illumina's Infinium MethylationEPIC BeadChip arrays (n = 862,927 sites). Differentially methylated CpG sites (dmCpGs) were identified (false discovery rate adjusted p ≤ × 10^-8 and fold change ± 2) by comparing methylation levels between ESKD cases and T1DM controls at single site resolution. Gene annotation and functionality was investigated to enrich and rank methylated regions associated with ESKD in T1DM.

RESULTS

Top-ranked genes within which several dmCpGs were located and supported by functional data with methylation look-ups in other cohorts include: AFF3, ARID5B, CUX1, ELMO1, FKBP5, HDAC4, ITGAL, LY9, PIM1, RUNX3, SEPTIN9 and UPF3A. Top-ranked enrichment pathways included pathways in cancer, TGF-β signalling and Th17 cell differentiation.

CONCLUSIONS

Epigenetic alterations provide a dynamic link between an individual's genetic background and their environmental exposures. This robust evaluation of DNA methylation in carefully phenotyped individuals has identified biomarkers associated with ESKD, revealing several genes and implicated key pathways associated with ESKD in individuals with T1DM.

Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability

Differences between sexes contribute to variation in the levels of fasting glucose and insulin. Epidemiological studies established a higher prevalence of impaired fasting glucose in men and impaired glucose tolerance in women, however, the genetic component underlying this phenomenon is not established. We assess sex-dimorphic (73,089/50,404 women and 67,506/47,806 men) and sex-combined (151,188/105,056 individuals) fasting glucose/fasting insulin genetic effects via genome-wide association study meta-analyses in individuals of European descent without diabetes. Here we report sex dimorphism in allelic effects on fasting insulin at IRS1 and ZNF12 loci, the latter showing higher RNA expression in whole blood in women compared to men. We also observe sex-homogeneous effects on fasting glucose at seven novel loci. Fasting insulin in women shows stronger genetic correlations than in men with waist-to-hip ratio and anorexia nervosa. Furthermore, waist-to-hip ratio is causally related to insulin resistance in women, but not in men. These results position dissection of metabolic and glycemic health sex dimorphism as a steppingstone for understanding differences in genetic effects between women and men in related phenotypes.

DNA Methylation Associated With Diabetic Kidney Disease in Blood-Derived DNA

A subset of individuals with type 1 diabetes will develop diabetic kidney disease (DKD). DKD is heritable and large-scale genome-wide association studies have begun to identify genetic factors that influence DKD. Complementary to genetic factors, we know that a person’s epigenetic profile is also altered with DKD. This study reports analysis of DNA methylation, a major epigenetic feature, evaluating methylome-wide loci for association with DKD. Unique features (n = 485,577; 482,421 CpG probes) were evaluated in blood-derived DNA from carefully phenotyped White European individuals diagnosed with type 1 diabetes with (cases) or without (controls) DKD (n = 677 samples). Explicitly, 150 cases were compared to 100 controls using the 450K array, with subsequent analysis using data previously generated for a further 96 cases and 96 controls on the 27K array, and de novo methylation data generated for replication in 139 cases and 96 controls. Following stringent quality control, raw data were quantile normalized and beta values calculated to reflect the methylation status at each site. The difference in methylation status was evaluated between cases and controls; resultant P-values for array-based data were adjusted for multiple testing. Genes with significantly increased (hypermethylated) and/or decreased (hypomethylated) levels of DNA methylation were considered for biological relevance by functional enrichment analysis using KEGG pathways. Twenty-two loci demonstrated statistically significant fold changes associated with DKD and additional support for these associated loci was sought using independent samples derived from patients recruited with similar inclusion criteria. Markers associated with CCNL1 and ZNF187 genes are supported as differentially regulated loci (P < 10^–8), with evidence also presented for AFF3, which has been identified from a meta-analysis and subsequent replication of genome-wide association studies. Further supporting evidence for differential gene expression in CCNL1 and ZNF187 is presented from kidney biopsy and blood-derived RNA in people with and without kidney disease from NephroSeq. Evidence confirming that methylation sites influence the development of DKD may aid risk prediction tools and stimulate research to identify epigenomic therapies which might be clinically useful for this disease.

Genetics of diabetes mellitus and diabetes complications

Diabetes is one of the fastest growing diseases worldwide, projected to affect 693 million adults by 2045. Devastating macrovascular complications (cardiovascular disease) and microvascular complications (such as diabetic kidney disease, diabetic retinopathy and neuropathy) lead to increased mortality, blindness, kidney failure and an overall decreased quality of life in individuals with diabetes. Clinical risk factors and glycaemic control alone cannot predict the development of vascular complications; numerous genetic studies have demonstrated a clear genetic component to both diabetes and its complications. Early research aimed at identifying genetic determinants of diabetes complications relied on familial linkage analysis suited to strong-effect loci, candidate gene studies prone to false positives, and underpowered genome-wide association studies limited by sample size. The explosion of new genomic datasets, both in terms of biobanks and aggregation of worldwide cohorts, has more than doubled the number of genetic discoveries for both diabetes and diabetes complications. We focus herein on genetic discoveries for diabetes and diabetes complications, empowered primarily through genome-wide association studies, and emphasize the gaps in research for taking genomic discovery to the next level.

Genetic Strategies to Understand Human Diabetic Nephropathy: In Silico Strategies for Molecular Data-Association Studies

Multiple genetic strategies are available to help improve understanding of diabetic nephropathy. This chapter provides detailed methodology for a single-nucleotide polymorphism association study and meta-analysis, using a protocol suitable for targeted SNP or genome-wide association studies, to identify genetic risk factors for diabetic nephropathy.

The Genetic Contribution to Type 1 Diabetes

PURPOSE OF REVIEW

To provide an updated summary of discoveries made to date resulting from genome-wide association study (GWAS) and sequencing studies, and to discuss the latest loci added to the growing repertoire of genetic signals predisposing to type 1 diabetes (T1D).

RECENT FINDINGS

Genetic studies have identified over 60 loci associated with T1D susceptibility. GWAS alone does not specifically inform on underlying mechanisms, but in combination with other sequencing and omics-data, advances are being made in our understanding of T1D genetic etiology and pathogenesis. Current knowledge indicates that genetic variation operating in both pancreatic β cells and in immune cells is central in mediating T1D risk. One of the main challenges is to determine how these recently discovered GWAS-implicated variants affect the expression and function of gene products. Once we understand the mechanism of action for disease-causing variants, we will be well placed to apply targeted genomic approaches to impede the premature activation of the immune system in an effort to ultimately prevent the onset of T1D.

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.

Genetic and Epigenetic Studies in Diabetic Kidney Disease

Chronic kidney disease is a worldwide health crisis, while diabetic kidney disease (DKD) has become the leading cause of end-stage renal disease (ESRD). DKD is a microvascular complication and occurs in 30–40% of diabetes patients. Epidemiological investigations and clinical observations on the familial clustering and heritability in DKD have highlighted an underlying genetic susceptibility. Furthermore, DKD is a progressive and long-term diabetic complication, in which epigenetic effects and environmental factors interact with an individual’s genetic background. In recent years, researchers have undertaken genetic and epigenetic studies of DKD in order to better understand its molecular mechanisms. In this review, clinical material, research approaches and experimental designs that have been used for genetic and epigenetic studies of DKD are described. Current information from genetic and epigenetic studies of DKD and ESRD in patients with diabetes, including the approaches of genome-wide association study (GWAS) or epigenome-wide association study (EWAS) and candidate gene association analyses, are summarized. Further investigation of molecular defects in DKD with new approaches such as next generation sequencing analysis and phenome-wide association study (PheWAS) is also discussed.

Kidney cytosine methylation changes improve renal function decline estimation in patients with diabetic kidney disease

Epigenetic changes might provide the biological explanation for the long-lasting impact of metabolic alterations of diabetic kidney disease development. Here we examined cytosine methylation of human kidney tubules using Illumina Infinium 450 K arrays from 91 subjects with and without diabetes and varying degrees of kidney disease using a cross-sectional design. We identify cytosine methylation changes associated with kidney structural damage and build a model for kidney function decline. We find that the methylation levels of 65 probes are associated with the degree of kidney fibrosis at genome wide significance. In total 471 probes improve the model for kidney function decline. Methylation probes associated with kidney damage and functional decline enrich on kidney regulatory regions and associate with gene expression changes, including epidermal growth factor (EGF). Altogether, our work shows that kidney methylation differences can be detected in patients with diabetic kidney disease and improve kidney function decline models indicating that they are potentially functionally important.

Patients with diabetes commonly develop diabetic kidney disease (DKD). Here Gluck et al. identify a set of probes differentially methylated in renal samples from patients with DKD, and find that inclusion of these methylation probes improves current prediction models of renal function decline.

A variant within the FTO confers susceptibility to diabetic nephropathy in Japanese patients with type 2 diabetes

To explore novel genetic loci for diabetic nephropathy, we performed genome-wide association studies (GWAS) for diabetic nephropathy in Japanese patients with type 2 diabetes. We analyzed the association of 5,768,242 single nucleotide polymorphisms (SNPs) in Japanese patients with type 2 diabetes, 2,380 nephropathy cases and 5,234 controls. We further performed GWAS for diabetic nephropathy using independent Japanese patients with type 2 diabetes, 429 cases and 358 controls and the results of these two GWAS were combined with an inverse variance meta-analysis (stage-1), followed by a de novo genotyping for the candidate SNP loci (p < 1.0 × 10⁻⁴) in an independent case-control study (Stage-2; 1,213 cases and 1,298 controls). After integrating stage-1 and stage-2 data, we identified one SNP locus, significantly associated with diabetic nephropathy; rs56094641 in FTO, P = 7.74 × 10⁻¹⁰. We further examined the association of rs56094641 with diabetic nephropathy in independent Japanese patients with type 2 diabetes (902 cases and 1,221 controls), and found that the association of this locus with diabetic nephropathy remained significant after integrating all association data (P = 7.62 × 10⁻¹⁰). We have identified FTO locus as a novel locus for conferring susceptibility to diabetic nephropathy in Japanese patients with type 2 diabetes.

Impact of diabetes and sex in heart failure with reduced ejection fraction patients from the ASIAN-HF registry

AIMS

To examine sex differences in clinical characteristics, echocardiographic features, quality of life and 1-year death or heart failure (HF) hospitalization outcomes in patients with/without diabetes mellitus (DM).

METHODS AND RESULTS

Utilizing the Asian Sudden Cardiac Death in HF (ASIAN-HF) registry, 5255 patients (mean age 59.6 ± 13.1, 78% men) with symptomatic HF with reduced ejection fraction (HFrEF) were stratified by DM status to address the research aims. Despite similar prevalence of DM between Asian men (43%) and women (42%), the odds of DM increased at lower body mass index in women vs. men (≥ 23 vs. ≥ 27.5 kg/m² , P_interaction  = 0.014). DM was more strongly related to chronic kidney disease in women vs. men [adjusted odds ratio (OR) 1.85, 95% confidence interval (CI) 1.33-2.57 vs. OR 1.32, 95% CI 1.11-1.56, P_interaction  = 0.009]. Sex also modified the relationship between DM and left ventricular geometry (P_interaction  = 0.003), whereby DM was associated with a more concentric left ventricular geometry in women than men. Women had lower quality of life than men (P < 0.001), in both DM and non-DM groups. DM was associated with worse composite outcomes at 1 year in women vs. men [hazard ratio (HR) 1.79, 95% CI 1.24-2.60 vs. HR 1.32, 95% CI 1.12-1.56; P_interaction  = 0.005).

CONCLUSIONS

Asian women with HFrEF were more likely to have DM despite a lean body mass index, a greater burden of chronic kidney disease and more concentric left ventricular geometry, compared to men. Furthermore, DM confers worse quality of life, irrespective of sex, and a greater risk of adverse outcomes in women than men. These data underscore the need for sex-specific approaches to diabetes in patients with HF.

Advances in understanding the genetic basis of diabetic kidney disease

Diabetic kidney disease (DKD) is a devastating complication of Type 1 and Type 2 diabetes and leads to increased morbidity and mortality. Earlier work in families has provided strong evidence that heredity is a major determinant of DKD. Previous linkage analyses and candidate gene studies have identified potential DKD genes; however, such approaches have largely been unsuccessful. Genome-wide association studies (GWAS) have made significant contribution in identifying SNPs associated with common complex diseases. Thanks to advanced technology, new analytical approaches, and international research collaborations, many DKD GWASs have reported unique genes, highlighted novel biological pathways and suggested new disease mechanisms. This review summarizes the current state of GWAS technology; findings from GWASs of DKD and its related traits conducted over the past 15 years and discuss the future of this field.

Validation of differentially methylated microRNAs identified from an epigenome-wide association study; Sanger and next generation sequencing approaches

Objectives

Altered DNA methylation and microRNA profiles are associated with diabetic kidney disease. This study compared different sequencing approaches to define the genetic and epigenetic architecture of sequences surrounding microRNAs associated with diabetic kidney disease.

Results

We compared Sanger and next generation sequencing to validate microRNAs associated with diabetic kidney disease identified from an epigenome-wide association study (EWAS). These microRNAs demonstrated differential methylation levels in cases with diabetic kidney disease compared to controls with long duration of type 1 diabetes and no evidence of kidney disease (P_adjusted < 10⁻⁵). Targeted next generation sequencing analysis of genomic DNA and matched cell-line transformed DNA samples identified four genomic variants within the microRNAs, two within miR-329-2 and two within miR-429. Sanger sequencing of genomic DNA replicated these findings and confirmed the altered methylation status of the CpG sites identified by the EWAS in bisulphite-treated DNA. This investigation successfully fine-mapped the genetic sequence around key microRNAs. Variants have been detected which may affect their methylation status and methylated CpG sites have been confirmed. Additionally, we explored both the fidelity of next generation sequencing analysis and the potential efficacy of cell-line transformed DNA samples in place of finite patient samples in discovery genetic and epigenetic research.

Electronic supplementary material

The online version of this article (10.1186/s13104-018-3872-x) contains supplementary material, which is available to authorized users.

Confirmation of GLRA3 as a susceptibility locus for albuminuria in Finnish patients with type 1 diabetes

Urinary albumin excretion is an early sign of diabetic kidney disease, affecting every third individual with diabetes. Despite substantial estimated heritability, only variants in the GLRA3 gene have been genome-wide significantly associated (p-value < 5 × 10⁻⁸) with diabetic albuminuria, in Finnish individuals with type 1 diabetes; However, replication attempt in non-Finnish Europeans with type 1 diabetes showed nominally significant association in the opposite direction, suggesting a population-specific effect, but simultaneously leaving the finding controversial. In this study, the association between the common rs10011025 variant in the GLRA3 locus, and albuminuria, was confirmed in 1259 independent Finnish individuals with type 1 diabetes (p = 0.0013), and meta-analysis of all Finnish individuals yielded a genome-wide significant association. The association was particularly pronounced in subjects not reaching the treatment target for blood glucose levels (HbA_1c > 7%; N = 2560, p = 1.7 × 10⁻⁹). Even though further studies are needed to pinpoint the causal variants, dissecting the association at the GLRA3 locus may uncover novel molecular mechanisms for diabetic albuminuria irrespective of population background.

Genetic basis of diabetic kidney disease and other diabetic complications

Diabetic kidney disease and other long-term complications are common in diabetes, and comprise the main cause of co-morbidity and premature mortality in individuals with diabetes. While familial clustering and heritability have been reported for all diabetic complications, the genetic background and the molecular mechanisms remain poorly understood. In recent years, genome-wide association studies have identified a few susceptibility loci for the renal complications as well as for diabetic retinopathy, diabetic cardiovascular disease and mortality. As for many complex diseases, the genetic factors increase the risk of complications in concert with the environment, and certain associations seem specific for particular conditions, for example, SP3-CDCA7 associated with end-stage renal disease only in women, or MGMT and variants on chromosome 5q13 associated with cardiovascular mortality only under tight glycaemic control. The characterization of the phenotypes is one of the main challenges for genetic research on diabetic complications, in addition to an urgent need to increase the number of individuals with diabetes with high quality phenotypic data to be included in future genetic studies.

Lessons from CKD-Related Genetic Association Studies-Moving Forward

Over the past decade, genetic association studies have uncovered numerous determinants of kidney function in the general, diabetic, hypertensive, CKD, ESRD, and GN-based study populations (e.g., IgA nephropathy, membranous nephropathy, FSGS). These studies have led to numerous novel and unanticipated findings, which are helping improve our understanding of factors and pathways affecting both normal and pathologic kidney function. In this review, we report on major discoveries and advances resulting from this rapidly progressing research domain. We also predict some of the next steps the nephrology community should embrace to accelerate the identification of genetic and molecular processes leading to kidney dysfunction, pathophysiologically based disease subgroups, and specific therapeutic targets, as we attempt to transition toward a more precision-based medicine approach.

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.

Genetic-Variation-Driven Gene-Expression Changes Highlight Genes with Important Functions for Kidney Disease

Chronic kidney disease (CKD) is a complex gene-environmental disease affecting close to 10% of the US population. Genome-wide association studies (GWASs) have identified sequence variants, localized to non-coding genomic regions, associated with kidney function. Despite these robust observations, the mechanism by which variants lead to CKD remains a critical unanswered question. Expression quantitative trait loci (eQTL) analysis is a method to identify genetic variation associated with gene expression changes in specific tissue types. We hypothesized that an integrative analysis combining CKD GWAS and kidney eQTL results can identify candidate genes for CKD. We performed eQTL analysis by correlating genotype with RNA-seq-based gene expression levels in 96 human kidney samples. Applying stringent statistical criteria, we detected 1,886 genes whose expression differs with the sequence variants. Using direct overlap and Bayesian methods, we identified new potential target genes for CKD. With respect to one of the target genes, lysosomal beta A mannosidase (MANBA), we observed that genetic variants associated with MANBA expression in the kidney showed statistically significant colocalization with variants identified in CKD GWASs, indicating that MANBA is a potential target gene for CKD. The expression of MANBA was significantly lower in kidneys of subjects with risk alleles. Suppressing manba expression in zebrafish resulted in renal tubule defects and pericardial edema, phenotypes typically induced by kidney dysfunction. Our analysis shows that gene-expression changes driven by genetic variation in the kidney can highlight potential new target genes for CKD development.

Precision Medicine Approaches to Diabetic Kidney Disease: Tissue as an Issue

PURPOSE OF REVIEW

Precision medicine approaches, that tailor medications to specific individuals has made paradigm-shifting improvements for patients with certain cancer types.

RECENT FINDINGS

Such approaches, however, have not been implemented for patients with diabetic kidney disease. Precision medicine could offer new avenues for novel diagnostic, prognostic and targeted therapeutics development. Genetic studies associated with multiscalar omics datasets from tissue and cell types of interest of well-characterized cohorts are needed to change the current paradigm. In this review, we will discuss precision medicine approaches that the nephrology community can take to analyze tissue samples to develop new therapeutics for patients with diabetic kidney disease.

Clinical worthlessness of genetic prediction of common forms of diabetes mellitus and related chronic complications: A position statement of the Italian Society of Diabetology

AIM

We are currently facing several attempts aimed at marketing genetic data for predicting multifactorial diseases, among which diabetes mellitus is one of the more prevalent. The present document primarily aims at providing to practicing physicians a summary of available data regarding the role of genetic information in predicting diabetes and its chronic complications.

DATA SYNTHESIS

Firstly, general information about characteristics and performance of risk prediction tools will be presented in order to help clinicians to get acquainted with basic methodological information related to the subject at issue. Then, as far as type 1 diabetes is concerned, available data indicate that genetic information and counseling may be useful only in families with many affected individuals. However, since no disease prevention is possible, the utility of predicting this form of diabetes is at question. In the case of type 2 diabetes, available data really question the utility of adding genetic information on top of well performing, easy available and inexpensive non-genetic markers. Finally, the possibility of using the few available genetic data on diabetic complications for improving our ability to predict them will also be presented and discussed. For cardiovascular complication, the addition of genetic information to models based on clinical features does not translate in a substantial improvement in risk discrimination. For all other diabetic complications genetic information are currently very poor and cannot, therefore, be used for improving risk stratification.

CONCLUSIONS

In all, nowadays the use of genetic testing for predicting diabetes and its chronic complications is definitively of little value in clinical practice.

Selection signature analysis reveals genes associated with tail type in Chinese indigenous sheep

Fat-tailed sheep have commercial value because consumers prefer high-protein and low-fat food and producers care about feed conversion rate. However, fat-tailed sheep still have some scientific significance, as the fat tail is commonly regarded as a characteristic of environmental adaptability. Finding the candidate genes associated with fat tail formation is essential for breeding and conservation. To identify these candidate genes, we applied FST and hapFLK approaches in fat- and thin-tailed sheep with available 50K SNP genotype data. These two methods found 6.24 Mb of overlapped regions and 43 genes that may associated with fat tail development. Gene annotation showed that HOXA11, BMP2, PPP1CC, SP3, SP9, WDR92, PROKR1 and ETAA1 may play important roles in fat tail formation. These findings provide insight into tail fat development and a guide for molecular breeding and conservation.

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.

Mendelian Randomization as an Approach to Assess Causality Using Observational Data

Mendelian randomization refers to an analytic approach to assess the causality of an observed association between a modifiable exposure or risk factor and a clinically relevant outcome. It presents a valuable tool, especially when randomized controlled trials to examine causality are not feasible and observational studies provide biased associations because of confounding or reverse causality. These issues are addressed by using genetic variants as instrumental variables for the tested exposure: the alleles of this exposure-associated genetic variant are randomly allocated and not subject to reverse causation. This, together with the wide availability of published genetic associations to screen for suitable genetic instrumental variables make Mendelian randomization a time- and cost-efficient approach and contribute to its increasing popularity for assessing and screening for potentially causal associations. An observed association between the genetic instrumental variable and the outcome supports the hypothesis that the exposure in question is causally related to the outcome. This review provides an overview of the Mendelian randomization method, addresses assumptions and implications, and includes illustrative examples. We also discuss special issues in nephrology, such as inverse risk factor associations in advanced disease, and outline opportunities to design Mendelian randomization studies around kidney function and disease.

Associations between sex and incident chronic kidney disease in a prospective diabetic cohort

Aim

Women with diabetes have a higher prevalence of chronic kidney disease (CKD) risk factors compared with men, but whether they are at higher risk for incident CKD remains uncertain.

Methods

This was a prospective, observational cohort study of 1464 patients with diabetes and normal renal function, recruited from primary care clinics at a vertically integrated healthcare system in Seattle, WA, USA. The primary predictor was sex. Incident CKD was defined by an estimated glomerular filtration rate (eGFR) <60 mL/min per 1.73 m² by Chronic Kidney Disease‐Epidemiology equations or sex‐specific microalbuminuria (urine albumin/creatinine ratio ≥25 mg/g for women or ≥17 mg/g for men).

Results

Of the 1464 patients (52.0% women), CKD incidence rates were 154.0 and 144.3 cases per 1000 patient‐years for women and men, respectively. In the competing risks regression, women had an increased risk of incident CKD (sub‐hazard ratio 1.37, 95% confidence interval (CI) 1.17, 1.60) compared with men after adjustment for demographics, baseline eGFR and duration of diabetes, which persisted after additional adjustment for CKD risk factors, depressive symptoms and diabetes self‐care (sub‐hazard ratio 1.35, 95% CI 1.15, 1.59). Sex differences in incident CKD were consistent across age groups and appeared to be driven by differences in the development of low eGFR rather than microalbuminuria.

Conclusion

Women with diabetes had a higher risk of incident CKD compared with men, which could not be entirely explained by differences in biologic CKD risk factors, depression or diabetes self‐care. Additional work is needed determine if these sex differences contribute to worse outcomes in women with diabetes.

The authors have evaluated associations between sex and chronic kidney disease (CKD) incidence in a primary care population with diabetes using Chronic Kidney Disease‐Epidemiology equations for estimating glomerular filtration rate (GFR) and sex‐specific definitions of microalbuminuria. They found that women had an increased risk of incident CKD compared with men. They also found that this difference in incident CKD was primarily driven by differences in incident eGFR < 60 mL/min per 1.73 m².

Variation in SLC19A3 and Protection From Microvascular Damage in Type 1 Diabetes

The risk of long-term diabetes complications is not fully explained by diabetes duration or long-term glycemic exposure, suggesting the involvement of genetic factors. Because thiamine regulates intracellular glucose metabolism and corrects for multiple damaging effects of high glucose, we hypothesized that variants in specific thiamine transporters are associated with risk of severe retinopathy and/or severe nephropathy because they modify an individual's ability to achieve sufficiently high intracellular thiamine levels. We tested 134 single nucleotide polymorphisms (SNPs) in two thiamine transporters (SLC19A2/3) and their transcription factors (SP1/2) for an association with severe retinopathy or nephropathy or their combination in the FinnDiane cohort. Subsequently, the results were examined for replication in the DCCT/EDIC and Wisconsin Epidemiologic Study of Diabetic Retinopathy (WESDR) cohorts. We found two SNPs in strong linkage disequilibrium in the SLC19A3 locus associated with a reduced rate of severe retinopathy and the combined phenotype of severe retinopathy and end-stage renal disease. The association for the combined phenotype reached genome-wide significance in a meta-analysis that included the WESDR cohort. These findings suggest that genetic variations in SLC19A3 play an important role in the pathogenesis of severe diabetic retinopathy and nephropathy and may explain why some individuals with type 1 diabetes are less prone than others to develop microvascular complications.

Molecular disease presentation in diabetic nephropathy

Diabetic nephropathy, as the most prevalent chronic disease of the kidney, has also become the primary cause of end-stage renal disease with the incidence of kidney disease in type 2 diabetics continuously rising. As with most chronic diseases, the pathophysiology is multifactorial with a number of deregulated molecular processes contributing to disease manifestation and progression. Current therapy mainly involves interfering in the renin-angiotensin-aldosterone system using angiotensin-converting enzyme inhibitors or angiotensin-receptor blockers. Better understanding of molecular processes deregulated in the early stages and progression of disease hold the key for development of novel therapeutics addressing this complex disease. With the advent of high-throughput omics technologies, researchers set out to systematically study the disease on a molecular level. Results of the first omics studies were mainly focused on reporting the highest deregulated molecules between diseased and healthy subjects with recent attempts to integrate findings of multiple studies on the level of molecular pathways and processes. In this review, we will outline key omics studies on the genome, transcriptome, proteome and metabolome level in the context of DN. We will also provide concepts on how to integrate findings of these individual studies (i) on the level of functional processes using the gene-ontology vocabulary, (ii) on the level of molecular pathways and (iii) on the level of phenotype molecular models constructed based on protein-protein interaction data.

Age at menarche and the risk of diabetic microvascular complications in patients with type 1 diabetes

AIMS/HYPOTHESIS

The aim of this study was to evaluate the relationship among age at onset of diabetes, age at onset of menarche and risk of diabetic nephropathy and laser-treated retinopathy in type 1 diabetes.

METHODS

Data related to age at menarche were collected through questionnaires and were available for 1,304 women who participated in the Finnish Diabetic Nephropathy Study (FinnDiane). A possible association between age at menarche and diabetic nephropathy and retinopathy was investigated.

RESULTS

There was an inverse relationship between the age at onset of diabetes and age at menarche: the younger the age at onset of diabetes, the higher the age at menarche (p < 0.0001). A non-linear relationship between the age of menarche and risk of diabetic microvascular complications was found in patients with diabetes onset before menarche, but there was no such association in patients with diabetes onset after menarche. Women with delayed menarche (> mean age + 2 years) had a 2.30 (95% CI 1.27, 4.17; p < 0.006) times higher risk of nephropathy compared with the women who underwent menarche at the mean age ± 2 years. Delayed menarche also increased the risk of retinopathy (OR 2.34 [95% CI 1.36, 4.01]). After excluding patients with nephropathy, the OR for retinopathy was 2.11 (95% CI 1.15, 3.90). Earlier menarche (< mean age - 2 years) did not have any effect on this risk.

CONCLUSIONS/INTERPRETATION

Delayed menarche was associated with an increased risk of diabetic nephropathy and retinopathy, whereas early menarche was not. Delayed menarche may be used as a new tool to identify women at risk of diabetic microvascular complications.

Novel Genetic Actors of Diabetes-Associated Microvascular Complications: Retinopathy, Kidney Disease and Neuropathy

Both type 1 and type 2 diabetes mellitus can lead to the common microvascular complications of diabetic retinopathy, kidney disease, and neuropathy. Diabetic patients do not universally develop these complications. Long duration of diabetes and poor glycemic control explain a lot of the variability in the development of microvascular complications, but not all. Genetic factors account for some of the remaining variability because of the heritability and familial clustering of these complications. There have been a large number of investigations, including linkage studies, candidate gene studies, and genome-wide association studies, all of which have sought to identify the specific variants that increase susceptibility. For retinopathy, several genome-wide association studies have been performed in small or midsize samples, but no reproducible loci across the studies have been identified. For diabetic kidney disease, genome-wide association studies in larger samples have been performed, and loci for this complication are beginning to emerge. However, validation of the existing discoveries, and further novel discoveries in larger samples is ongoing. The amount of genetic research into diabetic neuropathy has been very limited, and much is dedicated to the understanding of genetic risk factors only. Collaborations that pool samples and aim to detect phenotype classifications more precisely are promising avenues for a better explanation of the genetics of diabetic microvascular complications.

Genome-Wide Association and Trans-ethnic Meta-Analysis for Advanced Diabetic Kidney Disease: Family Investigation of Nephropathy and Diabetes (FIND)

Diabetic kidney disease (DKD) is the most common etiology of chronic kidney disease (CKD) in the industrialized world and accounts for much of the excess mortality in patients with diabetes mellitus. Approximately 45% of U.S. patients with incident end-stage kidney disease (ESKD) have DKD. Independent of glycemic control, DKD aggregates in families and has higher incidence rates in African, Mexican, and American Indian ancestral groups relative to European populations. The Family Investigation of Nephropathy and Diabetes (FIND) performed a genome-wide association study (GWAS) contrasting 6,197 unrelated individuals with advanced DKD with healthy and diabetic individuals lacking nephropathy of European American, African American, Mexican American, or American Indian ancestry. A large-scale replication and trans-ethnic meta-analysis included 7,539 additional European American, African American and American Indian DKD cases and non-nephropathy controls. Within ethnic group meta-analysis of discovery GWAS and replication set results identified genome-wide significant evidence for association between DKD and rs12523822 on chromosome 6q25.2 in American Indians (P = 5.74x10^-9). The strongest signal of association in the trans-ethnic meta-analysis was with a SNP in strong linkage disequilibrium with rs12523822 (rs955333; P = 1.31x10^-8), with directionally consistent results across ethnic groups. These 6q25.2 SNPs are located between the SCAF8 and CNKSR3 genes, a region with DKD relevant changes in gene expression and an eQTL with IPCEF1, a gene co-translated with CNKSR3. Several other SNPs demonstrated suggestive evidence of association with DKD, within and across populations. These data identify a novel DKD susceptibility locus with consistent directions of effect across diverse ancestral groups and provide insight into the genetic architecture of DKD.

Type 2 diabetes is the most common cause of severe kidney disease worldwide and diabetic kidney disease (DKD) associates with premature death. Individuals of non-European ancestry have the highest burden of type 2 DKD; hence understanding the causes of DKD remains critical to reducing health disparities. Family studies demonstrate that genes regulate the onset and progression of DKD; however, identifying these genes has proven to be challenging. The Family Investigation of Diabetes and Nephropathy consortium (FIND) recruited a large multi-ethnic collection of individuals with type 2 diabetes with and without kidney disease in order to detect genes associated with DKD. FIND discovered and replicated a DKD-associated genetic locus on human chromosome 6q25.2 (rs955333) between the SCAF8 and CNKSR genes. Findings were supported by significantly different expression of genes in this region from kidney tissue of subjects with, versus without DKD. The present findings identify a novel kidney disease susceptibility locus in individuals with type 2 diabetes which is consistent across subjects of differing ancestries. In addition, FIND results provide a rich catalogue of genetic variation in DKD patients for future research on the genetic architecture regulating this common and devastating disease.

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.

Genetic Studies on Diabetic Microvascular Complications: Focusing on Genome-Wide Association Studies

Diabetes is a common metabolic disorder with a worldwide prevalence of 8.3% and is the leading cause of visual loss, end-stage renal disease and amputation. Recently, genome-wide association studies (GWASs) have identified genetic risk factors for diabetic microvascular complications of retinopathy, nephropathy, and neuropathy. We summarized the recent findings of GWASs on diabetic microvascular complications and highlighted the challenges and our opinion on future directives. Five GWASs were conducted on diabetic retinopathy, nine on nephropathy, and one on neuropathic pain. The majority of recent GWASs were underpowered and heterogeneous in terms of study design, inclusion criteria and phenotype definition. Therefore, few reached the genome-wide significance threshold and the findings were inconsistent across the studies. Recent GWASs provided novel information on genetic risk factors and the possible pathophysiology of diabetic microvascular complications. However, further collaborative efforts to standardize phenotype definition and increase sample size are necessary for successful genetic studies on diabetic microvascular complications.

Biomarkers of vascular complications in type 2 diabetes

People with T2D are at substantially increased risk of developing severe complications, (coronary heart disease, stroke, retinopathy and nephropathy). Clinicians have an important responsibility to identify those patients who, because they are at high risk, will benefit more from a preventive program or intensified therapy. However, due to the limited accuracy of the predictive tests, and limited effectiveness of preventive measures, clinicians and their patients show a suboptimal compliance to such programs. An improved risk assessment will positively impact cost/benefit ratios, opening the door for new intervention. Research involving human genetic or genomic information becomes increasingly powerful and, in conjunction with other novel biomarkers, together with personal or health data, will offer new tools for harnessing risk factors underlying complex (multi-factorial) diseases such as T2D and its complications. Altogether, there is a rationale to develop early biomarkers with improved predictive value for vascular complications of T2D by integrating patients' genetic information with traditional and emerging biomarkers.

Genetic and epigenetic factors influencing chronic kidney disease

Chronic kidney disease (CKD) has become a serious public health problem because of its associated morbidity, premature mortality, and attendant healthcare costs. The rising number of persons with CKD is linked with the aging population structure and an increased prevalence of diabetes, hypertension, and obesity. There is an inherited risk associated with developing CKD, as evidenced by familial clustering and differing prevalence rates across ethnic groups. Previous studies to determine the inherited risk factors for CKD rarely identified genetic variants that were robustly replicated. However, improvements in genotyping technologies and analytic methods are now helping to identify promising genetic loci aided by international collaboration and multiconsortia efforts. More recently, epigenetic modifications have been proposed to play a role in both the inherited susceptibility to CKD and, importantly, to explain how the environment dynamically interacts with the genome to alter an individual's disease risk. Genome-wide, epigenome-wide, and whole transcriptome studies have been performed, and optimal approaches for integrative analysis are being developed. This review summarizes recent research and the current status of genetic and epigenetic risk factors influencing CKD using population-based information.

Genetic and epigenetic risk factors for diabetic kidney disease

Diabetes is increasing at daunting rates worldwide, and approximately 40% of affected individuals will develop kidney complications. Diabetic kidney disease (DKD) is the leading cause of end-stage kidney disease, and there are significant healthcare costs providing appropriate renal replacement therapies to affected individuals. For several decades, investigators have sought to discover inherited risk factors and biomarkers for DKD. In recent years, advances in high-throughput laboratory techniques and computational analyses, coupled with the establishment of multicenter consortia, have helped to identify genetic loci that are replicated across multiple populations. Several genome-wide association studies (GWAS) have been conducted for DKD with further meta-analysis of GWAS and comprehensive "single gene" meta-analyses now published. Despite these efforts, much of the inherited predisposition to DKD remains unexplained. Meta-analyses and integrated-omics pathway studies are being used to help elucidate underlying genetic risks. Epigenetic phenomena are increasingly recognized as important drivers of disease risk, and several epigenome-wide association studies have now been completed. This review describes key findings and ongoing genetic and epigenetic initiatives for DKD.

Podocytes, signaling pathways, and vascular factors in diabetic kidney disease

Alterations and injury to glomerular podocytes play a key role in the initiation and progression of diabetic kidney disease (DKD). Multiple factors in diabetes cause abnormalities in podocyte signaling that lead to podocyte foot process effacement, hypertrophy, detachment, loss, and death. Alterations in insulin action and mammalian target of rapamycin activation have been well documented to lead to pathology. Reduced insulin action directly leads to albuminuria, increased glomerular matrix accumulation, thickening of the glomerular basement membrane, podocyte apoptosis, and glomerulosclerosis. In addition, podocytes generate factors that alter signaling in other glomerular cells. Prominent among these is vascular endothelial growth factor-A, which maintains glomerular endothelium viability but causes endothelial cell pathology when generated at too high a level. Finally, circulating vascular factors (eg, activated protein C) have a profound effect on podocyte stability and survival. This cytoprotective factor is critical for podocyte health, and its deficiency promotes podocyte injury and apoptosis. Thus, the podocyte sits in the center of a network of paracrine and hormonal signaling systems that in health keep the podocyte adaptable and viable, but in diabetes they can lead to pathologic changes, detachment, and death.

The genetics of diabetic nephropathy

Up to 40% of patients with type 1 and type 2 diabetes will develop diabetic nephropathy (DN), resulting in chronic kidney disease and potential organ failure. There is evidence for a heritable genetic susceptibility to DN, but despite intensive research efforts the causative genes remain elusive. Recently, genome-wide association studies have discovered several novel genetic variants associated with DN. The identification of such variants may potentially allow for early identification of at risk patients. Here we review the current understanding of the key molecular mechanisms and genetic architecture of DN, and discuss the merits of employing an integrative approach to incorporate datasets from multiple sources (genetics, transcriptomics, epigenetic, proteomic) in order to fully elucidate the genetic elements contributing to this serious complication of diabetes.