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

Integrated analysis of blood DNA methylation, genetic variants, circulating proteins, microRNAs, and kidney failure in type 1 diabetes

Variation in DNA methylation (DNAmet) in white blood cells and other cells/tissues has been implicated in the etiology of progressive diabetic kidney disease (DKD). However, the specific mechanisms linking DNAmet variation in blood cells with risk of kidney failure (KF) and utility of measuring blood cell DNAmet in personalized medicine are not clear. We measured blood cell DNAmet in 277 individuals with type 1 diabetes and DKD using Illumina EPIC arrays; 51% of the cohort developed KF during 7 to 20 years of follow-up. Our epigenome-wide analysis identified DNAmet at 17 CpGs (5'-cytosine-phosphate-guanine-3' loci) associated with risk of KF independent of major clinical risk factors. DNAmet at these KF-associated CpGs remained stable over a median period of 4.7 years. Furthermore, DNAmet variations at seven KF-associated CpGs were strongly associated with multiple genetic variants at seven genomic regions, suggesting a strong genetic influence on DNAmet. The effects of DNAmet variations at the KF-associated CpGs on risk of KF were partially mediated by multiple KF-associated circulating proteins and KF-associated circulating miRNAs. A prediction model for risk of KF was developed by adding blood cell DNAmet at eight selected KF-associated CpGs to the clinical model. This updated model significantly improved prediction performance (c-statistic = 0.93) versus the clinical model (c-statistic = 0.85) at P = 6.62 × 10-14. In conclusion, our multiomics study provides insights into mechanisms through which variation of DNAmet may affect KF development and shows that blood cell DNAmet at certain CpGs can improve risk prediction for KF in T1D.

Pathological mechanisms of type 1 diabetes in children: investigation of the exosomal protein expression profile

Introduction

Type 1 diabetes (T1D) is a serious autoimmune disease with high morbidity and mortality. Early diagnosis and treatment remain unsatisfactory. While the potential for development of T1D biomarkers in circulating exosomes has attracted interest, progress has been limited. This study endeavors to explore the molecular dynamics of plasma exosome proteins in pediatric T1D patients and potential mechanisms correlated with T1D progression.

Methods

Liquid chromatography-tandem mass spectrometry with tandem mass tag (TMT)6 labeling was used to quantify exosomal protein expression profiles in 12 healthy controls and 24 T1D patients stratified by age (≤ 6 years old and > 6 years old) and glycated hemoglobin (HbA1c) levels (> 7% or > 7%). Integrated bioinformatics analysis was employed to decipher the functions of differentially expressed proteins, and Western blotting was used for validation of selected proteins' expression levels.

Results

We identified 1035 differentially expressed proteins (fold change > 1.3) between the T1D patients and healthy controls: 558 in those ≤ 6-year-old and 588 in those > 6-year-old. In those who reached an HbA1c level < 7% following 3 or more months of insulin therapy, the expression levels of most altered proteins in both T1D age groups returned to levels comparable to those in the healthy control group. Bioinformatics analysis revealed that differentially expressed exosome proteins are primarily related to immune function, hemostasis, cellular stress responses, and matrix organization. Western blotting confirmed the alterations in RAB40A, SEMA6D, COL6A5, and TTR proteins.

Discussion

This study delivers valuable insights into the fundamental molecular mechanisms contributing to T1D pathology. Moreover, it proposes potential therapeutic targets for improved T1D management.

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.

A Custom Target Next-Generation Sequencing 70-Gene Panel and Replication Study to Identify Genetic Markers of Diabetic Kidney Disease

Diabetic kidney disease (DKD) has been pointed out as a prominent cause of chronic and end-stage renal disease (ESRD). There is a genetic predisposition to DKD, although clinically relevant loci are yet to be identified. We utilized a custom target next-generation sequencing 70-gene panel to screen a discovery cohort of 150 controls, DKD and DKD-ESRD patients. Relevant SNPs for the susceptibility and clinical evolution of DKD were replicated in an independent validation cohort of 824 controls and patients. A network analysis aiming to assess the impact of variability along specific pathways was also conducted. Forty-eight SNPs displayed significantly different frequencies in the study groups. Of these, 28 with p-values lower than 0.01 were selected for replication. MYH9 rs710181 was inversely associated with the risk of DKD (OR = 0.52 (0.28–0.97), p = 0.033), whilst SOWAHB rs13140552 and CNDP1 rs4891564 were not carried by cases or controls, respectively (p = 0.044 and 0.023). In addition, the RGMA rs1969589 CC genotype was significantly correlated with lower albumin-to-creatinine ratios in the DKD patients (711.8 ± 113.0 vs. 1375.9 ± 474.1 mg/g for TC/TT; mean difference = 823.5 (84.46–1563.0); p = 0.030). No biological pathway stood out as more significantly affected by genetic variability. Our findings reveal new variants that could be useful as biomarkers of DKD onset and/or evolution.

Common Polymorphisms in the RGMa Promoter Are Associated With Cerebrovascular Atherosclerosis Burden in Chinese Han Patients With Acute Ischemic Cerebrovascular Accident

Repulsive guidance molecule a (RGMa) plays a vital role in the progression of numerous inflammatory diseases. However, whether it participates in atherosclerosis development is not known. Here, we explored the influence of RGMa in atherogenesis by investigating whether an association exists between functional polymorphisms in the RGMa promoter and cerebrovascular atherosclerosis burden (CAB) in Chinese Han patients diagnosed with acute ischemic cerebrovascular accident. To this end, we conducted a genetic association study on 201 patients with prior diagnoses of acute ischemic stroke or transient ischemic attack recruited from our hospital. After admission, we conducted three targeted single-nucleotide polymorphisms (SNPs) genotyping and evaluated CAB by computed tomography angiography. We used logistic regression modeling to analyze genetic associations. Functional polymorphism analysis indicated an independent association between the rs725458 T allele and increased CAB in patients with acute ischemic cerebrovascular accident [adjusted odds ratio (OR) = 1.66, 95% confidence interval (CI) = 1.01–2.74, P = 0.046]. In contrast, an association between the rs4778099 AA genotype and decreased CAB (adjusted OR = 0.10, 95% CI = 0.01–0.77, P = 0.027) was found. Our Gene Expression Omnibus analysis revealed lower RGMa levels in the atherosclerotic aortas and in the macrophages isolated from plaques than that in the normal aortas and macrophages from normal tissue, respectively. In conclusion, the relationship between RGMa and cerebrovascular atherosclerosis suggests that RGMa has a potential vasoprotective effect. The two identified functional SNPs (rs725458 and rs4778099) we identified in the RGMa promoter are associated with CAB in patients diagnosed with acute ischemic cerebrovascular accident. These findings offer a promising research direction for RGMa-related translational studies on atherosclerosis.

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.

Meta-analysis uncovers genome-wide significant variants for rapid kidney function decline

Rapid decline of glomerular filtration rate estimated from creatinine (eGFRcrea) is associated with severe clinical endpoints. In contrast to cross-sectionally assessed eGFRcrea, the genetic basis for rapid eGFRcrea decline is largely unknown. To help define this, we meta-analyzed 42 genome-wide association studies from the Chronic Kidney Diseases Genetics Consortium and United Kingdom Biobank to identify genetic loci for rapid eGFRcrea decline. Two definitions of eGFRcrea decline were used: 3 mL/min/1.73m2/year or more ("Rapid3"; encompassing 34,874 cases, 107,090 controls) and eGFRcrea decline 25% or more and eGFRcrea under 60 mL/min/1.73m2 at follow-up among those with eGFRcrea 60 mL/min/1.73m2 or more at baseline ("CKDi25"; encompassing 19,901 cases, 175,244 controls). Seven independent variants were identified across six loci for Rapid3 and/or CKDi25: consisting of five variants at four loci with genome-wide significance (near UMOD-PDILT (2), PRKAG2, WDR72, OR2S2) and two variants among 265 known eGFRcrea variants (near GATM, LARP4B). All these loci were novel for Rapid3 and/or CKDi25 and our bioinformatic follow-up prioritized variants and genes underneath these loci. The OR2S2 locus is novel for any eGFRcrea trait including interesting candidates. For the five genome-wide significant lead variants, we found supporting effects for annual change in blood urea nitrogen or cystatin-based eGFR, but not for GATM or LARP4B. Individuals at high compared to those at low genetic risk (8-14 vs. 0-5 adverse alleles) had a 1.20-fold increased risk of acute kidney injury (95% confidence interval 1.08-1.33). Thus, our identified loci for rapid kidney function decline may help prioritize therapeutic targets and identify mechanisms and individuals at risk for sustained deterioration of kidney function.

Human leukocyte antigen association with familial steroid-sensitive nephrotic syndrome

Steroid-sensitive nephrotic syndrome (SSNS) is the most common form of nephrotic syndrome in childhood. Cases with the familial occurrence of SSNS suggest that genetics may play a role in the disease. Human leucocyte antigen (HLA) alleles have been associated with SSNS. We present genetic findings in nine families (44 participants), each with at least two affected siblings. A total of 19 patients were affected with familial SSNS. Six of nine families showed linkage to markers on chromosome 6p (27.29-33.97 Mbp) (Hg19), especially to markers D6S1629 and D6S1560 on HLA dense region in this location. Interestingly, we also found linkage of disease phenotype of familial SSNS on chromosome 15 (91.7-96.9 Mbp) (Hg19) with a logarithm of odds (LOD) score Z = 3.02.Conclusion: Our findings confirm the linkage of HLA markers on chromosome 6, which strengthens the association of HLA alleles in SSNS. What is Known: • Human leukocyte antigen (HLA) alleles have been associated with idiopathic steroid-sensitive nephrotic syndrome (SSNS). Only few studies have investigated the association between HLA alleles and familial SSNS. What is New: • We present evidence of linkage of familial SSNS to chromosome 6p (27.29-33.97 Mbp) (Hg19), especially to markers D6S1629 and D6S1560 on HLA dense region in this location. We also found linkage of the disease phenotype of familial SSNS on chromosome 15 (91.7-96.9 Mbp) (Hg19) with a logarithm of odds (LOD) score of Z = 3.02 following autosomal recessive inheritance pattern.

The Role of Semaphorins in Metabolic Disorders

Semaphorins are a family originally identified as axonal guidance molecules. They are also involved in tumor growth, angiogenesis, immune regulation, as well as other biological and pathological processes. Recent studies have shown that semaphorins play a role in metabolic diseases including obesity, adipose inflammation, and diabetic complications, including diabetic retinopathy, diabetic nephropathy, diabetic neuropathy, diabetic wound healing, and diabetic osteoporosis. Evidence provides mechanistic insights regarding the role of semaphorins in metabolic diseases by regulating adipogenesis, hypothalamic melanocortin circuit, immune responses, and angiogenesis. In this review, we summarize recent progress regarding the role of semaphorins in obesity, adipose inflammation, and diabetic complications.

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.

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.

Multivariate Methods for Genetic Variants Selection and Risk Prediction in Cardiovascular Diseases

Over the last decade, high-throughput genotyping and sequencing technologies have contributed to major advancements in genetics research, as these technologies now facilitate affordable mapping of the entire genome for large sets of individuals. Given this, genome-wide association studies are proving to be powerful tools in identifying genetic variants that have the capacity to modify the probability of developing a disease or trait of interest. However, when the study’s goal is to evaluate the effect of the presence of genetic variants mapping to specific chromosomes regions on a specific phenotype, the candidate loci approach is still preferred. Regardless of which approach is taken, such a large data set calls for the establishment and development of appropriate analytical methods in order to translate such knowledge into biological or clinical findings. Standard univariate tests often fail to identify informative genetic variants, especially when dealing with complex traits, which are more likely to result from a combination of rare and common variants and non-genetic determinants. These limitations can partially be overcome by multivariate methods, which allow for the identification of informative combinations of genetic variants and non-genetic features. Furthermore, such methods can help to generate additive genetic scores and risk stratification algorithms that, once extensively validated in independent cohorts, could serve as useful tools to assist clinicians in decision-making. This review aims to provide readers with an overview of the main multivariate methods for genetic data analysis that could be applied to the analysis of cardiovascular traits.

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.

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.