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

Whole-exome and whole-genome sequencing of 1064 individuals with type 1 diabetes reveals novel genes for diabetic kidney disease

AIMS/HYPOTHESIS

Diabetic kidney disease (DKD) is a severe diabetic complication that affects one third of individuals with type 1 diabetes. Although several genes and common variants have been shown to be associated with DKD, much of the predicted inheritance remains unexplained. Here, we performed next-generation sequencing to assess whether low-frequency variants, extending to a minor allele frequency (MAF) ≤10% (single or aggregated) contribute to the missing heritability in DKD.

METHODS

We performed whole-exome sequencing (WES) of 498 individuals and whole-genome sequencing (WGS) of 599 individuals with type 1 diabetes. After quality control, next-generation sequencing data were available for a total of 1064 individuals, of whom 541 had developed either severe albuminuria or end-stage kidney disease, and 523 had retained normal albumin excretion despite a long duration of type 1 diabetes. Single-variant and gene-aggregate tests for protein-altering variants (PAV) and protein-truncating variants (PTV) were performed separately for WES and WGS data and combined in a meta-analysis. We also performed genome-wide aggregate analyses on genomic windows (sliding window), promoters and enhancers using the WGS dataset.

RESULTS

In the single-variant meta-analysis, no variant reached genome-wide significance, but a suggestively associated common THAP7 rs369250 variant (p=1.50 × 10-5, MAF=49%) was replicated in the FinnGen general population genome-wide association study (GWAS) data for chronic kidney disease and DKD phenotypes. The gene-aggregate meta-analysis provided suggestive evidence (p<4.0 × 10-4) at four genes for DKD, of which NAT16 (MAFPAV≤10%) and LTA (also known as TNFβ, MAFPAV≤5%) are replicated in the FinnGen general population GWAS data. The LTA rs2229092 C allele was associated with significantly lower TNFR1, TNFR2 and TNFR3 serum levels in a subset of FinnDiane participants. Of the intergenic regions suggestively associated with DKD, the enhancer on chromosome 18q12.3 (p=3.94 × 10-5, MAFvariants≤5%) showed interaction with the METTL4 gene; the lead variant was replicated, and predicted to alter binding of the MafB transcription factor.

CONCLUSIONS/INTERPRETATION

Our sequencing-based meta-analysis revealed multiple genes, variants and regulatory regions that were suggestively associated with DKD. However, as no variant or gene reached genome-wide significance, further studies are needed to validate the findings.

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.

SIGIRR gene variants in term newborns with congenital heart defects and necrotizing enterocolitis

Background

Necrotizing enterocolitis (NEC) is a common gastrointestinal emergency among neonates which is characterized by acute intestinal inflammation and necrosis. The main risk factors for NEC are prematurity, low birth weight, and some preexisting health conditions such as congenital heart defects (CHDs). Investigation of the potential genetic predisposition to NEC is a promising approach that might provide new insights into its pathogenesis. One of the most important proteins that play a significant role in the pathogenesis of NEC is Toll-like receptor 4 (TLR4) which recognizes lipopolysaccharide found in Gram-negative bacteria. In intestinal epithelial cells, a protein encoded by the SIGIRR gene is a major inhibitor of TLR4 signaling. A few SIGIRR variants, including rare p.Y168X and p.S80Y, have already been identified in preterm infants with NEC, but their pathogenic significance remains unclear. This study aimed to investigate the spectrum of SIGIRR genetic variants in term newborns with CHD and to assess their potential association with NEC.

Methods and Results

A total of 93 term newborns with critical CHD were enrolled in this study, 33 of them developed NEC. SIGIRR genetic variants were determined by Sanger sequencing of all exons. In total, eight SIGIRR genetic variants were identified, two of which were found only in newborns with NEC (P = 0.12). The rare missense p.S80Y (rs117739035) variant in exon 4 was found in two infants with NEC stage IIA. Two infants with NEC stage III and stage IB carried a novel duplication c. 102_121dup (rs552367848) variant in exon 10 that has not been previously associated with any clinical phenotype.

Conclusions

The presence of both variants only in neonates who developed NEC, together with earlier published data, may suggest their potential contribution to the risk of developing NEC in term infants with CHD and allow planning larger cohort studies to clarify their relevance.

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.

Whole-exome sequencing study identifies four novel gene loci associated with diabetic kidney disease

Diabetic kidney disease (DKD) is recognized as an important public health challenge. However, its genomic mechanisms are poorly understood. To identify rare variants for DKD, we conducted a whole-exome sequencing (WES) study leveraging large cohorts well-phenotyped for chronic kidney disease and diabetes. Our two-stage WES study included 4372 European and African ancestry participants from the Chronic Renal Insufficiency Cohort and Atherosclerosis Risk in Communities studies (stage 1) and 11 487 multi-ancestry Trans-Omics for Precision Medicine participants (stage 2). Generalized linear mixed models, which accounted for genetic relatedness and adjusted for age, sex and ancestry, were used to test associations between single variants and DKD. Gene-based aggregate rare variant analyses were conducted using an optimized sequence kernel association test implemented within our mixed model framework. We identified four novel exome-wide significant DKD-related loci through initiating diabetes. In single-variant analyses, participants carrying a rare, in-frame insertion in the DIS3L2 gene (rs141560952) exhibited a 193-fold increased odds [95% confidence interval (CI): 33.6, 1105] of DKD compared with noncarriers (P = 3.59 × 10-9). Likewise, each copy of a low-frequency KRT6B splice-site variant (rs425827) conferred a 5.31-fold higher odds (95% CI: 3.06, 9.21) of DKD (P = 2.72 × 10-9). Aggregate gene-based analyses further identified ERAP2 (P = 4.03 × 10-8) and NPEPPS (P = 1.51 × 10-7), which are both expressed in the kidney and implicated in renin-angiotensin-aldosterone system modulated immune response. In the largest WES study of DKD, we identified novel rare variant loci attaining exome-wide significance. These findings provide new insights into the molecular mechanisms underlying DKD.

Modeling SILAC Data to Assess Protein Turnover in a Cellular Model of Diabetic Nephropathy

Protein turnover rate is finely regulated through intracellular mechanisms and signals that are still incompletely understood but that are essential for the correct function of cellular processes. Indeed, a dysfunctional proteostasis often impacts the cell's ability to remove unfolded, misfolded, degraded, non-functional, or damaged proteins. Thus, altered cellular mechanisms controlling protein turnover impinge on the pathophysiology of many diseases, making the study of protein synthesis and degradation rates an important step for a more comprehensive understanding of these pathologies. In this manuscript, we describe the application of a dynamic-SILAC approach to study the turnover rate and the abundance of proteins in a cellular model of diabetic nephropathy. We estimated protein half-lives and relative abundance for thousands of proteins, several of which are characterized by either an altered turnover rate or altered abundance between diabetic nephropathic subjects and diabetic controls. Many of these proteins were previously shown to be related to diabetic complications and represent therefore, possible biomarkers or therapeutic targets. Beside the aspects strictly related to the pathological condition, our data also represent a consistent compendium of protein half-lives in human fibroblasts and a rich source of important information related to basic cell biology.

Identification of novel differentially expressed genes in type 1 diabetes mellitus complications using transcriptomic profiling of UAE patients: a multicenter study

Type 1 diabetes mellitus (T1DM) is a chronic metabolic disorder that mainly affects children and young adults. It is associated with debilitating and long-life complications. Therefore, understanding the factors that lead to the onset and development of these complications is crucial. To our knowledge this is the first study that attempts to identify the common differentially expressed genes (DEGs) in T1DM complications using whole transcriptomic profiling in United Arab Emirates (UAE) patients. The present multicenter study was conducted in different hospitals in UAE including University Hospital Sharjah, Dubai Hospital and Rashid Hospital. A total of fifty-eight Emirati participants aged above 18 years and with a BMI < 25 kg/m² were recruited and forty-five of these participants had a confirmed diagnosis of T1DM. Five groups of complications associated with the latter were identified including hyperlipidemia, neuropathy, ketoacidosis, hypothyroidism and polycystic ovary syndrome (PCOS). A comprehensive whole transcriptomic analysis using NGS was conducted. The outcomes of the study revealed the common DEGs between T1DM without complications and T1DM with different complications. The results revealed seven common candidate DEGs, SPINK9, TRDN, PVRL4, MYO3A, PDLIM1, KIAA1614 and GRP were upregulated in T1DM complications with significant increase in expression of SPINK9 (Fold change: 5.28, 3.79, 5.20, 3.79, 5.20) and MYO3A (Fold change: 4.14, 6.11, 2.60, 4.33, 4.49) in hyperlipidemia, neuropathy, ketoacidosis, hypothyroidism and PCOS, respectively. In addition, functional pathways of ion transport, mineral absorption and cytosolic calcium concentration were involved in regulation of candidate upregulated genes related to neuropathy, ketoacidosis and PCOS, respectively. The findings of this study represent a novel reference warranting further studies to shed light on the causative genetic factors that are involved in the onset and development of T1DM complications.

Genetics in chronic kidney disease: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference

Numerous genes for monogenic kidney diseases with classical patterns of inheritance, as well as genes for complex kidney diseases that manifest in combination with environmental factors, have been discovered. Genetic findings are increasingly used to inform clinical management of nephropathies, and have led to improved diagnostics, disease surveillance, choice of therapy, and family counseling. All of these steps rely on accurate interpretation of genetic data, which can be outpaced by current rates of data collection. In March of 2021, Kidney Diseases: Improving Global Outcomes (KDIGO) held a Controversies Conference on "Genetics in Chronic Kidney Disease (CKD)" to review the current state of understanding of monogenic and complex (polygenic) kidney diseases, processes for applying genetic findings in clinical medicine, and use of genomics for defining and stratifying CKD. Given the important contribution of genetic variants to CKD, practitioners with CKD patients are advised to "think genetic," which specifically involves obtaining a family history, collecting detailed information on age of CKD onset, performing clinical examination for extrarenal symptoms, and considering genetic testing. To improve the use of genetics in nephrology, meeting participants advised developing an advanced training or subspecialty track for nephrologists, crafting guidelines for testing and treatment, and educating patients, students, and practitioners. Key areas of future research, including clinical interpretation of genome variation, electronic phenotyping, global representation, kidney-specific molecular data, polygenic scores, translational epidemiology, and open data resources, were also identified.

Emerging Role of Clinical Genetics in CKD

Chronic kidney disease (CKD) afflicts 15% of adults in the United States, of whom 25% have a family history. Genetic testing is supportive in identifying and possibly confirming diagnoses of CKD, thereby guiding care. Advances in the clinical genetic evaluation include next-generation sequencing with targeted gene panels, whole exome sequencing, and whole genome sequencing. These platforms provide DNA sequence reads with excellent coverage throughout the genome and have identified novel genetic causes of CKD. New pathologic genetic variants identified in previously unrecognized biological pathways have elucidated disease mechanisms underlying CKD etiologies, potentially establishing prognosis and guiding treatment selection. Molecular diagnoses using genetic sequencing can detect rare, potentially treatable mutations, avoid misdiagnoses, guide selection of optimal therapy, and decrease the risk of unnecessary and potentially harmful interventions. Genetic testing has been widely adopted in pediatric nephrology; however, it is less frequently used to date in adult nephrology. Extension of clinical genetic approaches to adult patients may achieve similar benefits in diagnostic refinement and treatment selection. This review aimed to identify clinical CKD phenotypes that may benefit the most from genetic testing, outline the commonly available platforms, and provide examples of successful deployment of these approaches in CKD.

Diabetic kidney disease: Are the reported associations with single-nucleotide polymorphisms disease-specific?

BACKGROUND

The genetic backgrounds of diabetic kidney disease (DKD) and end-stage kidney disease (ESKD) have not been fully elucidated.

AIM

To examine the individual and cumulative effects of single-nucleotide polymorphisms (SNPs) previously associated with DKD on the risk for ESKD of diabetic etiology and to determine if any associations observed were specific for DKD.

METHODS

Fourteen SNPs were genotyped in hemodialyzed 136 patients with diabetic ESKD (DKD group) and 121 patients with non-diabetic ESKD (NDKD group). Patients were also re-classified on the basis of the primary cause of chronic kidney disease (CKD). The distribution of alleles was compared between diabetic and non-diabetic groups as well as between different sub-phenotypes. The weighted multilocus genetic risk score (GRS) was calculated to estimate the cumulative risk conferred by all SNPs. The GRS distribution was then compared between the DKD and NDKD groups as well as in the groups according to the primary cause of CKD.

RESULTS

One SNP (rs841853; SLC2A1) showed a nominal association with DKD (P = 0.048; P > 0.05 after Bonferroni correction). The GRS was higher in the DKD group (0.615 ± 0.260) than in the NDKD group (0.590 ± 0.253), but the difference was not significant (P = 0.46). The analysis of associations between GRS and individual factors did not show any significant correlation. However, the GRS was significantly higher in patients with glomerular disease than in those with tubulointerstitial disease (P = 0.014) and in those with a combined group (tubulointerstitial, vascular, and cystic and congenital disease) (P = 0.018).

CONCLUSION

Our results suggest that selected SNPs that were previously associated with DKD may not be specific for DKD and may confer risk for CKD of different etiology, particularly those affecting renal glomeruli.

Clinical Applications of Genetic Discoveries in Kidney Transplantation: a Review

Growth in knowledge of the genetics of kidney disease has revealed that significant percentages of patients with diverse types of nephropathy have causative mutations. Genetic testing is poised to play an increasing role in the care of patients with kidney disease. The role of genetic testing in kidney transplantation is not well established. This review will explore the ways in which genetic testing may be applied to improve the care of kidney transplant recipients and donors.