DNA methylation profiling identifies epigenetic differences between early versus late stages of diabetic chronic kidney disease

Long non-coding RNAs as emerging regulators of miRNAs and epigenetics in diabetes-related chronic kidney disease

Diabetes is one of the major cause of chronic kidney disease (CKD), including "diabetic nephropathy," and is an increasingly prevalent accelerator of the progression of non-diabetic forms of CKD. The long non-coding RNAs (lncRNAs) have come into the limelight in the past few years as one of the emerging weapons against CKD in diabetes. Available data over the past few years demonstrate the interaction of lncRNAs with miRNAs and epigenetic machinery. Interestingly, the evolving data suggest that lncRNAs play a vital role in diabetes-associated CKD by regulation of epigenetic enzymes such as DNA methyltransferase, histone deacetylases, and histone methyltransferases. LncRNAs are also engaged in the regulation of several miRNAs in diabetic nephropathy. Hence this review will elaborate on the association between lncRNAs and their interaction with epigenetic regulators involved in different aspects and thus the progression of CKD in diabetes.

Nutrition and Developmental Origins of Kidney Disease

The developmental programming hypothesis proposes that adverse environmental insults during critical developmental periods increase the risk of diseases later in life. The kidneys are deemed susceptible to such a process, although the exact mechanisms remain elusive. Many factors have been reported to contribute to the developmental origin of chronic kidney diseases (CKD), among which peri-gestational nutrition has a central role, affecting kidney development and metabolism. Physiologically, the link between malnutrition, reduced glomerular numbers, and increased blood pressure is key in the developmental programming of CKD. However, recent studies regarding oxidative stress, mitochondrial dysfunction, epigenetic modifications, and metabolic changes have revealed potential novel pathways for therapeutic intervention. This review will discuss the role of imbalanced nutrition in the development of CKD.

Epigenetic modification in diabetic kidney disease

Diabetic kidney disease (DKD) is a common microangiopathy in diabetic patients and the main cause of death in diabetic patients. The main manifestations of DKD are proteinuria and decreased renal filtration capacity. The glomerular filtration rate and urinary albumin level are two of the most important hallmarks of the progression of DKD. The classical treatment of DKD is controlling blood glucose and blood pressure. However, the commonly used clinical therapeutic strategies and the existing biomarkers only partially slow the progression of DKD and roughly predict disease progression. Therefore, novel therapeutic methods, targets and biomarkers are urgently needed to meet clinical requirements. In recent years, increasing attention has been given to the role of epigenetic modification in the pathogenesis of DKD. Epigenetic variation mainly includes DNA methylation, histone modification and changes in the noncoding RNA expression profile, which are deeply involved in DKD-related inflammation, oxidative stress, hemodynamics, and the activation of abnormal signaling pathways. Since DKD is reversible at certain disease stages, it is valuable to identify abnormal epigenetic modifications as early diagnosis and treatment targets to prevent the progression of end-stage renal disease (ESRD). Because the current understanding of the epigenetic mechanism of DKD is not comprehensive, the purpose of this review is to summarize the role of epigenetic modification in the occurrence and development of DKD and evaluate the value of epigenetic therapies in DKD.

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.

Epigenome-wide association study of diabetic chronic kidney disease progression in the Korean population: the KNOW-CKD study

Since the etiology of diabetic chronic kidney disease (CKD) is multifactorial, studies on DNA methylation for kidney function deterioration have rarely been performed despite the need for an epigenetic approach. Therefore, this study aimed to identify epigenetic markers associated with CKD progression based on the decline in the estimated glomerular filtration rate in diabetic CKD in Korea. An epigenome-wide association study was performed using whole blood samples from 180 CKD recruited from the KNOW-CKD cohort. Pyrosequencing was also performed on 133 CKD participants as an external replication analysis. Functional analyses, including the analysis of disease-gene networks, reactome pathways, and protein-protein interaction networks, were conducted to identify the biological mechanisms of CpG sites. A phenome-wide association study was performed to determine the associations between CpG sites and other phenotypes. Two epigenetic markers, cg10297223 on AGTR1 and cg02990553 on KRT28 indicated a potential association with diabetic CKD progression. Based on the functional analyses, other phenotypes (blood pressure and cardiac arrhythmia for AGTR1) and biological pathways (keratinization and cornified envelope for KRT28) related to CKD were also identified. This study suggests a potential association between the cg10297223 and cg02990553 and the progression of diabetic CKD in Koreans. Nevertheless, further validation is needed through additional studies.

DNA-damaged podocyte-CD8 T cell crosstalk exacerbates kidney injury by altering DNA methylation

Recent epigenome-wide studies suggest an association between blood DNA methylation and kidney function. However, the pathological importance remains unclear. Here, we show that the homing endonuclease I-PpoI-induced DNA double-strand breaks in kidney glomerular podocytes cause proteinuria, glomerulosclerosis, and tubulointerstitial fibrosis with DNA methylation changes in blood cells as well as in podocytes. Single-cell RNA-sequencing analysis reveals an increase in cytotoxic CD8+ T cells with the activating/costimulatory receptor NKG2D in the kidneys, which exhibit a memory precursor effector cell phenotype, and the CD44high memory CD8+ T cells are also increased in the peripheral circulation. NKG2D blockade attenuates the renal phenotype caused by podocyte DNA damage. Blood methylome shows increased DNA methylation in binding sites for STAT1, a transcription factor contributing to CD8+ T cell homeostasis. Collectively, podocyte DNA damage alters the blood methylome, leading to changes in CD8+ T cells, which contribute to sustained renal injury in chronic kidney disease.

Epigenome-wide meta-analysis identifies DNA methylation biomarkers associated with diabetic kidney disease

Type 1 diabetes affects over nine million individuals globally, with approximately 40% developing diabetic kidney disease. Emerging evidence suggests that epigenetic alterations, such as DNA methylation, are involved in diabetic kidney disease. Here we assess differences in blood-derived genome-wide DNA methylation associated with diabetic kidney disease in 1304 carefully characterised individuals with type 1 diabetes and known renal status from two cohorts in the United Kingdom-Republic of Ireland and Finland. In the meta-analysis, we identify 32 differentially methylated CpGs in diabetic kidney disease in type 1 diabetes, 18 of which are located within genes differentially expressed in kidneys or correlated with pathological traits in diabetic kidney disease. We show that methylation at 21 of the 32 CpGs predict the development of kidney failure, extending the knowledge and potentially identifying individuals at greater risk for diabetic kidney disease in type 1 diabetes.

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.

Blood Plasma Metabolites in Diabetes-Associated Chronic Kidney Disease: A Focus on Lipid Profiles and Cardiovascular Risk

Background

We investigated a cross-sectional metabolomic analysis of plasma and urine of patients with early and late stage diabetes associated chronic kidney disease (CKD), inclusive of stages 1–5 CKD, to identify potential metabolomic profiles between the two groups.

Methods

This cross-sectional study recruited 119 adults. Metabolomic biomarkers were quantified in 119 non-fasted plasma and 57 urine samples using a high-throughput proton Nuclear Magnetic Resonance platform. Analyses were conducted using R with the ggforestplot package. Linear regression models were minimally adjusted for age, sex, and body mass index and p-values were adjusted for multiple comparisons using the Benjamini-Hockberg method with a false discovery rate of 0.05.

Results

Apolipoprotein A1 concentration (ApoA1) was reduced (adj. p = 0.04) and apolipoprotein B/apolipoprotein A1 ratio (ApoB/ApoA1) was increased (adj. p = 0.04) in late CKD compared with early CKD. Low-density lipoprotein triglyceride (LDL-TG) had an increased concentration (adj. p = 0.01), while concentrations of high-density lipoprotein cholesterol (HDL-C) were reduced (adj. p = 0.04) in late CKD compared to early stages of disease.

Conclusion

Our results highlight the presence of abnormal lipid metabolism namely significant reduction in the protective ApoA1 and significant increase in atherogenic ApoB/ApoA1 ratio. The study also demonstrates significantly elevated levels of triglyceride-rich lipoproteins such as LDL-TG. We illustrate the significant reduction in protective HDL-C in individuals with diabetic CKD. It explores a detailed plasma lipid profile that significantly differentiates between the late and early CKD groups as well as each CKD stage. The study of complex metabolite profiles may provide additional data required to enable more specific cardiovascular risk stratification.

Integrative omics reveals subtle molecular perturbations following ischemic conditioning in a porcine kidney transplant model

BACKGROUND

Remote Ischemic Conditioning (RIC) has been proposed as a therapeutic intervention to circumvent the ischemia/reperfusion injury (IRI) that is inherent to organ transplantation. Using a porcine kidney transplant model, we aimed to decipher the subclinical molecular effects of a RIC regime, compared to non-RIC controls.

METHODS

Kidney pairs (n = 8 + 8) were extracted from brain dead donor pigs and transplanted in juvenile recipient pigs following a period of cold ischemia. One of the two kidney recipients in each pair was subjected to RIC prior to kidney graft reperfusion, while the other served as non-RIC control. We designed an integrative Omics strategy combining transcriptomics, proteomics, and phosphoproteomics to deduce molecular signatures in kidney tissue that could be attributed to RIC.

RESULTS

In kidney grafts taken out 10 h after transplantation we detected minimal molecular perturbations following RIC compared to non-RIC at the transcriptome level, which was mirrored at the proteome level. In particular, we noted that RIC resulted in suppression of tissue inflammatory profiles. Furthermore, an accumulation of muscle extracellular matrix assembly proteins in kidney tissues was detected at the protein level, which may be in response to muscle tissue damage and/or fibrosis. However, the majority of these protein changes did not reach significance (p < 0.05).

CONCLUSIONS

Our data identifies subtle molecular phenotypes in porcine kidneys following RIC, and this knowledge could potentially aid optimization of remote ischemic conditioning protocols in renal transplantation.

The Use of 'Omics for Diagnosing and Predicting Progression of Chronic Kidney Disease: A Scoping Review

Globally, chronic kidney disease (CKD) contributes substantial morbidity and mortality. Recently, various ‘omics platforms have provided insight into the molecular basis of kidney dysfunction. This scoping review is a synthesis of the current literature on the use of different ‘omics platforms to identify biomarkers that could be used to detect early-stage CKD, predict disease progression, and identify pathways leading to CKD. This review includes 123 articles published from January 2007 to May 2021, following a structured selection process. The most common type of ‘omic platform was proteomics, appearing in 55 of the studies and two of these included a metabolomics component. Most studies (n = 91) reported on CKD associated with diabetes mellitus. Thirteen studies that provided information on the biomarkers associated with CKD and explored potential pathways involved in CKD are discussed. The biomarkers that are associated with risk or early detection of CKD are SNPs in the MYH9/APOL1 and UMOD genes, the proteomic CKD273 biomarker panel and metabolite pantothenic acid. Pantothenic acid and the CKD273 biomarker panel were also involved in predicting CKD progression. Retinoic acid pathway genes, UMOD, and pantothenic acid provided insight into potential pathways leading to CKD. The biomarkers were mainly used to detect CKD and predict progression in high-income, European ancestry populations, highlighting the need for representative ‘omics research in other populations with disparate socio-economic strata, including Africans, since disease etiologies may differ across ethnic groups. To assess the transferability of findings, it is essential to do research in diverse populations.

Potential for Novel Biomarkers in Diabetes-Associated Chronic Kidney Disease: Epigenome, Metabolome, and Gut Microbiome

Diabetes-associated chronic kidney disease is a pandemic issue. Despite the global increase in the number of individuals with this chronic condition together with increasing morbidity and mortality, there are currently only limited therapeutic options to slow disease progression. One of the reasons for this is that the current-day "gold standard" biomarkers lack adequate sensitivity and specificity to detect early diabetic chronic kidney disease (CKD). This review focuses on the rapidly evolving areas of epigenetics, metabolomics, and the gut microbiome as potential sources of novel biomarkers in diabetes-associated CKD and discusses their relevance to clinical practice. However, it also highlights the problems associated with many studies within these three areas-namely, the lack of adequately powered longitudinal studies, and the lack of reproducibility of results which impede biomarker development and clinical validation in this complex and susceptible population.