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

A blood-based multi-omic landscape for the molecular characterization of kidney stone disease

Kidney stone disease (KSD, also named renal calculi, nephrolithiasis, or urolithiasis) is a common urological disease entailing the formation of minerals and salts that form inside the urinary tract, frequently caused by diabetes, high blood pressure, hypertension, and monogenetic components in most patients. 10% of adults worldwide are affected by KSD, which continues to be highly prevalent and with increasing incidence. For the identification of novel therapeutic targets in KSD, we adopted high-throughput sequencing and mass spectrometry (MS) techniques in this study and carried out an integrative analysis of exosome proteomic data and DNA methylation data from blood samples of normal and KSD individuals. Our research delineated the profiling of exosomal proteins and DNA methylation in both healthy individuals and those afflicted with KSD, finding that the overexpressed proteins and the demethylated genes in KSD samples are associated with immune responses. The consistency of the results in proteomics and epigenetics supports the feasibility of the comprehensive strategy. Our insights into the molecular landscape of KSD pave the way for a deeper understanding of its pathogenic mechanism, providing an opportunity for more precise diagnosis and targeted treatment strategies for KSD.

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.

DNA methylation and 28-year cardiovascular disease risk in type 1 diabetes: the Epidemiology of Diabetes Complications (EDC) cohort study

BACKGROUND

The potential for DNA methylation (DNAm) as an early marker for cardiovascular disease (CVD) and how such an association might differ by glycemic exposure has not been examined in type 1 diabetes, a population at increased CVD risk. We thus performed a prospective epigenome-wide association study of blood leukocyte DNAm (EPIC array) and time to CVD incidence over 28 years in a childhood-onset (< 17 years) type 1 diabetes cohort, the Pittsburgh Epidemiology of Diabetes Complications (EDC) study (n = 368 with DNA and no CVD at baseline), both overall and separately by glycemic exposure, as measured by HbA1c at baseline (split at the median: < 8.9% and ≥ 8.9%). We also assessed whether DNAm-CVD associations were independent of established cardiometabolic risk factors, including body mass index, estimated glucose disposal rate, cholesterol, triglycerides, blood pressure, pulse rate, albumin excretion rate, and estimated glomerular filtration rate.

RESULTS

CVD (first instance of CVD death, myocardial infarction, coronary revascularization, ischemic ECG, angina, or stroke) developed in 172 participants (46.7%) over 28 years. Overall, in Cox regression models for time to CVD, none of the 683,597 CpGs examined reached significance at a false discovery rate (FDR) ≤ 0.05. In participants with HbA1c < 8.9% (n = 180), again none reached FDR ≤ 0.05, but three were associated at the a priori nominal significance level FDR ≤ 0.10: cg07147033 in MIB2, cg12324048 (intergenic, chromosome 3), and cg15883830 (intergenic, chromosome 1). In participants with HbA1c ≥ 8.9% (n = 188), two CpGs in loci involved in calcium channel activity were significantly associated with CVD (FDR ≤ 0.05): cg21823999 in GPM6A and cg23621817 in CHRNA9; four additional CpGs were nominally associated (FDR ≤ 0.10). In participants with HbA1c ≥ 8.9%, DNAm-CVD associations were only modestly attenuated after cardiometabolic risk factor adjustment, while attenuation was greater in those with HbA1c < 8.9%. No pathways were enriched in those with HbA1c < 8.9%, while pathways for calcium channel activity and integral component of synaptic membrane were significantly enriched in those with HbA1c ≥ 8.9%.

CONCLUSIONS

These results provide novel evidence that DNAm at loci involved in calcium channel activity and development may contribute to long-term CVD risk beyond known risk factors in type 1 diabetes, particularly in individuals with greater glycemic exposure, warranting further study.

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.

DNA methylation markers for kidney function and progression of diabetic kidney disease

Epigenetic markers are potential biomarkers for diabetes and related complications. Using a prospective cohort from the Hong Kong Diabetes Register, we perform two independent epigenome-wide association studies to identify methylation markers associated with baseline estimated glomerular filtration rate (eGFR) and subsequent decline in kidney function (eGFR slope), respectively, in 1,271 type 2 diabetes subjects. Here we show 40 (30 previously unidentified) and eight (all previously unidentified) CpG sites individually reach epigenome-wide significance for baseline eGFR and eGFR slope, respectively. We also develop a multisite analysis method, which selects 64 and 37 CpG sites for baseline eGFR and eGFR slope, respectively. These models are validated in an independent cohort of Native Americans with type 2 diabetes. Our identified CpG sites are near genes enriched for functional roles in kidney diseases, and some show association with renal damage. This study highlights the potential of methylation markers in risk stratification of kidney disease among type 2 diabetes individuals.

Differential Methylation of Telomere-Related Genes Is Associated with Kidney Disease in Individuals with Type 1 Diabetes

Diabetic kidney disease (DKD) represents a major global health problem. Accelerated ageing is a key feature of DKD and, therefore, characteristics of accelerated ageing may provide useful biomarkers or therapeutic targets. Harnessing multi-omics, features affecting telomere biology and any associated methylome dysregulation in DKD were explored. Genotype data for nuclear genome polymorphisms in telomere-related genes were extracted from genome-wide case-control association data (n = 823 DKD/903 controls; n = 247 end-stage kidney disease (ESKD)/1479 controls). Telomere length was established using quantitative polymerase chain reaction. Quantitative methylation values for 1091 CpG sites in telomere-related genes were extracted from epigenome-wide case-control association data (n = 150 DKD/100 controls). Telomere length was significantly shorter in older age groups (p = 7.6 × 10^-6). Telomere length was also significantly reduced (p = 6.6 × 10^-5) in DKD versus control individuals, with significance remaining after covariate adjustment (p = 0.028). DKD and ESKD were nominally associated with telomere-related genetic variation, with Mendelian randomisation highlighting no significant association between genetically predicted telomere length and kidney disease. A total of 496 CpG sites in 212 genes reached epigenome-wide significance (p ≤ 10^-8) for DKD association, and 412 CpG sites in 193 genes for ESKD. Functional prediction revealed differentially methylated genes were enriched for Wnt signalling involvement. Harnessing previously published RNA-sequencing datasets, potential targets where epigenetic dysregulation may result in altered gene expression were revealed, useful as potential diagnostic and therapeutic targets for intervention.

Association of Genetic and Epigenetic changes of Insulin Like Growth Factor Binding Protein-1 in Egyptian Patients with Type 2 Diabetes Mellitus

BACKGROUND

Diabetes is one of the global health threat. Type 2 Diabetes mellitus (T2DM) is associated with life-threatening complications. This work, aimed to study the association between T2DM and IGFBP-1 gene methylation, gene polymorphism and serum levels of IGFBP-1.

METHOD

We included 100 subjects with T2DM and 100 control. DNA methylation of IGFBP-1 was analyzed using pyrosequencing, IGFBP-1 gene polymorphism was analyzed using real time polymerase chain reaction and serum level of IGFBP-1 was measured by ELISA.

RESULTS

There was DNA hyper methylation levels of IGFBP1 gene at each of the six CpG sites in T2DM patients than control (P < 0.001). IGFBP-1 gene polymorphism (rs 2854843) CC pattern was significantly associated with DM, P = 0.002. Also, there was decrease in serum IGFBP-1 in patients with T2DM than control group (P < 0.001).

CONCLUSION

We concluded that DNA hyper methylation of IGFBP-1 gene and CC polymorphism (rs 2854843) of IGFBP-1 gene are associated with T2DM in Egyptian patients, also, decrease serum level of IGFBP-1. Further cohort study is recommended with large sample size to detect which one, epigenetic changes or polymorphism of IGFBP-1 gene, is the cause of T2DM or even both.

DNA methylation enzymes in the kidneys of male and female BTBR ob/ob mice

Diabetic kidney disease (DKD) is the leading cause of the end-stage renal disease. Recent studies have shown that epigenetic modifications contribute to alterations in gene expression and the development of DKD. This study aimed to show an expression profile of key DNA (de)methylation enzymes (DNMT, TET proteins) and their differences between sexes under obesity and diabetic condition. Male and female black and tan brachyury (BTBR) ob/ob mice and their corresponding wild-type littermates (BTBR WT) were studied until 16 weeks of age. Metabolic parameters, kidney morphophysiology and the expression of fibrotic markers and epigenetic enzymes were studied in whole kidney tissue or specifically in the glomerulus. The results showed sexual dimorphism in the development of metabolic disease and in kidney morphophysiology. Female mice have a different profile of DNMTs expression in both WT and obese/diabetic condition. Furthermore, metabolic condition negatively modulated the glomerular expression of TET1 and TET3 only in females. To our knowledge, this is the first study that shows a kidney profile of the expression of key (de)methylation enzymes, DNMTs and TETs, in the BTBR ob/ob experimental model of DKD and its association with sex. The knowledge of this epigenetic profile may help future research to understand the pathophysiology of DKD in males and females.

Differential methylation in CD44 and SEC23A is associated with time preference in older individuals

Time preference is a measure used to ascertain the level of which individuals prefer smaller, immediate rewards over larger, delayed rewards. We explored how an individual's time preference associates with their epigenetic profile. Time preferences were ascertained by asking participants of the Northern Ireland COhort for the Longitudinal study of Ageing to make a series of choices between two hypothetical income scenarios. From these, eight 'time preference' categories were derived, ranging from "patient" to "impatient" on an ordinal scale. The Infinium High Density Methylation Assay, MethylationEPIC (Illumina) was used to evaluate the status of 862,927 CpGs. Time preference and DNA methylation data were obtained for 1648 individuals. Four analyses were conducted, assessing the methylation patterns at single site resolution between patient and impatient individuals using two adjustment models. In this discovery cohort analysis, two CpG sites were identified with significantly different levels of methylation (p < 9 × 10^-8) between the individuals allocated to the patient group and the remaining population following adjustment for covariates; cg08845621 within CD44 and cg18127619 within SEC23A. Neither of these genes have previously been linked to time preference. Epigenetic modifications have not previously been linked to time preference using a population cohort but they may represent important biomarkers of accumulated, complex determinants of this trait. Further analysis is warranted of both the top-ranked results and of DNA methylation as an important link between measurable biomarkers and health behaviours.

Cross-Ancestry DNA Methylation Marks of Insulin Resistance in Pregnancy: An Integrative Epigenome-Wide Association Study

Although there are some epigenome-wide association studies (EWAS) of insulin resistance, for most of them authors did not replicate their findings, and most are focused on populations of European ancestry, limiting the generalizability. In the Epigenetics in Pregnancy (EPIPREG; n = 294 Europeans and 162 South Asians) study, we conducted an EWAS of insulin resistance in maternal peripheral blood leukocytes, with replication in the Born in Bradford (n = 879; n = 430 Europeans and 449 South Asians), Methyl Epigenome Network Association (MENA) (n = 320), and Botnia (n = 56) cohorts. In EPIPREG, we identified six CpG sites inversely associated with insulin resistance across ancestry, of which five were replicated in independent cohorts (cg02988288, cg19693031, and cg26974062 in TXNIP; cg06690548 in SLC7A11; and cg04861640 in ZSCAN26). From methylation quantitative trait loci analysis in EPIPREG, we identified gene variants related to all five replicated cross-ancestry CpG sites, which were associated with several cardiometabolic phenotypes. Mediation analyses suggested that the gene variants regulate insulin resistance through DNA methylation. To conclude, our cross-ancestry EWAS identified five CpG sites related to lower insulin resistance.

Harnessing Genomic Analysis to Explore the Role of Telomeres in the Pathogenesis and Progression of Diabetic Kidney Disease

The prevalence of diabetes is increasing globally, and this trend is predicted to continue for future decades. Research is needed to uncover new ways to manage diabetes and its co-morbidities. A significant secondary complication of diabetes is kidney disease, which can ultimately result in the need for renal replacement therapy, via dialysis or transplantation. Diabetic kidney disease presents a substantial burden to patients, their families and global healthcare services. This review highlights studies that have harnessed genomic, epigenomic and functional prediction tools to uncover novel genes and pathways associated with DKD that are useful for the identification of therapeutic targets or novel biomarkers for risk stratification. Telomere length regulation is a specific pathway gaining attention recently because of its association with DKD. Researchers are employing both observational and genetics-based studies to identify telomere-related genes associated with kidney function decline in diabetes. Studies have also uncovered novel functions for telomere-related genes beyond the immediate regulation of telomere length, such as transcriptional regulation and inflammation. This review summarises studies that have revealed the potential to harness therapeutics that modulate telomere length, or the associated epigenetic modifications, for the treatment of DKD, to potentially slow renal function decline and reduce the global burden of this disease.

Longitudinal Epigenome-Wide Analysis of Kidney Transplant Recipients Pretransplant and Posttransplant

Introduction

Kidney transplantation remains the gold standard of treatment for end-stage renal disease (ESRD), with improved patient outcomes compared with dialysis. Epigenome-Wide Association Analysis (EWAS) of DNA methylation may identify markers that contribute to an individual's risk of adverse transplant outcomes, yet only a limited number of EWAS have been conducted in kidney transplant recipients. This EWAS aimed to interrogate the methylation profile of a kidney transplant recipient cohort with minimal posttransplant complications, exploring differences in samples pretransplant and posttransplant.

Methods

We compared differentially methylated cytosine-phosphate-guanine sites (dmCpGs) in samples derived from peripheral blood mononuclear cells of the same kidney transplant recipients, collected both pretransplant and posttransplant (N = 154), using the Infinium MethylationEPIC microarray (Illumina, San Diego, CA). Recipients received kidneys from deceased donors and had a mean of 17 years of follow-up.

Results

Five top-ranked dmCpGs were significantly different at false discovery rate (FDR) adjusted P ≤ 9 × 10^-8; cg23597162 within JAZF1, cg25187293 within BTNL8, cg17944885, located between ZNF788P and ZNF625-ZNF20, cg14655917 located between ASB4 and PDK4 and cg09839120 located between GIMAP6 and EIF2AP3.

Conclusion

Five dmCpGs were identified at the generally accepted EWAS critical significance level of FDR adjusted P (P _FDRadj) ≤ 9 × 10^-8, including cg23597162 (within JAZF1) and cg17944885, which have prior associations with chronic kidney disease (CKD). Comparing individuals with no evidence of posttransplant complications (N = 105) demonstrated that 693,555 CpGs (89.57%) did not display any significant difference in methylation (P _FDRadj ≥ 0.05), thereby this study establishes an important reference for future epigenetic studies that seek to identify markers of posttransplant complications.

Identification of DNA methylation change in TCF7L2 gene in the blood of type 2 diabetes mellitus as a predictive biomarker in Iraq Kurdistan region by using methylation-specific PCR

Objective. Nowadays, type 2 diabetes mellitus (T2D) is the most common chronic endocrine disorder affecting an estimated 5-10% of adults worldwide, and this disease also rapidly increased among the population in the Kurdistan region. This research aims to identify DNA methylation change in the TCF7L2 gene as a possible predictive T2D biomarker. Methods. One hundred and thirteen participants were divided into three groups: diabetic (47), prediabetic (36), and control (30). The study was carried out in patients who visited the private clinical sector between August and December 2021 in Koya city (Iraq Kurdistan region) to determine DNA methylation status using a methylation-specific PCR (MSP) with paired primers for each methylated and non-methylated region. In addition, the X2 Kruskal-Wallis statistical and Wilcoxon signed-rank tests were used, p<0.05 was considered significant. Results. The results showed hypermethylation of DNA in the promoter region in diabetic and prediabetic groups compared to the healthy controls. Different factors affected the DNA methylation level, including body max index, alcohol consumption, family history, and physical activity with the positive Coronavirus. Conclusion. The results obtained indicate that DNA methylation changes in the TCF7L2 promoter region may be used as a potential predictive biomarker of the T2D diagnosis. However, the findings obtained in this study should be supported by additional data.

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.

Plasma PFOA and PFOS Levels, DNA Methylation, and Blood Lipid Levels: A Pilot Study

Exposure to perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) is associated with blood lipids in adults, but the underlying mechanisms remain unclear. This pilot study aimed to investigate the associations between PFOA or PFOS and epigenome-wide DNA methylation and assess the mediating effect of DNA methylation on the PFOA/PFOS-blood lipid association. We measured plasma PFOA/PFOS and leukocyte DNA methylation in 98 patients enrolled from the hospital between October 2018 and August 2019. The median plasma PFOA/PFOS levels were 0.85 and 2.29 ng/mL. Plasma PFOA and PFOS levels were significantly associated with elevated total cholesterol (TC) and low-density lipoprotein cholesterol (LDL) levels. There were 63/87 CpG positions and 8/11 differentially methylated regions (DMRs) associated with plasma PFOA/PFOS levels, respectively. In addition, 5 CpG positions (annotated to AFF3, CREB5, NRG2, USF2, and intergenic region) and one DMR annotated to IRF6 may mediate the association between plasma PFOA/PFOS and LDL levels (mediated proportion from 7.29 to 46.77%); two CpG positions may mediate the association between plasma PFOA/PFOS and TC levels (annotated to CREB5 and USF2, mediated proportion is around 30%). The data suggest that PFOA/PFOS exposure alters DNA methylation. More importantly, the association of PFOA/PFOS with lipid indicators was partly mediated by DNA methylation changes in lipid metabolism-related genes.

Cardiovascular Disease in Adults with Type 1 Diabetes: Looking Beyond Glycemic Control

PURPOSE OF REVIEW

Despite improvements in treatment, people with type 1 diabetes continue to have increased cardiovascular disease (CVD) risk. Glycemic control does not fully explain this excess CVD risk, so a greater understanding of other risk factors is needed.

RECENT FINDINGS

The authors review the relationship between glycemia and CVD risk in adults with type 1 diabetes and summarize evidence regarding other factors that may explain risk beyond glycemia. Insulin resistance, weight gain, sex differences, genetics, inflammation, emerging markers of risk, including lipid subclasses and epigenetic modifications, and future directions are discussed. As glycemic control improves, an increased focus on other CVD risk factors is warranted in type 1 diabetes. Novel markers and precision medicine approaches may improve CVD prediction, but a lack of type 1 diabetes-specific guidelines for lipids, blood pressure, and physical activity are likely impediments to optimal CVD prevention in this high-risk population.

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 DNA Methylation Predicts Diabetic Kidney Disease Progression in High Fat Diet-Fed Mice

Diabetic kidney disease (DKD) progresses at different rates among patients with type 2 diabetes mellitus (T2D). Early identification of patients with a higher risk of DKD progression is essential to improve prognosis. Epigenetic modifications, particularly DNA methylation, have been independently implicated in T2D and chronic kidney disease. The current study aimed to determine changes in blood DNA methylation that reflects and predicts DKD progression. C57BL/6 mice were fed a high-fat diet (HFD) from weaning and subclassified into two groups, HFD-1 and HFD-2, according to urinary kidney injury marker KIM-1/creatinine ratios (low vs. high) and histological abnormalities (mild–moderate vs. advanced). DNA methylation profiles were determined by reduced representative bisulfide sequencing (RRBS). Our results confirmed early and established DKD at week 9 and week 32, respectively. At week 32, advanced kidney injury was associated with dysregulation of methylation and demethylation enzymes in the kidney. Blood RRBS revealed 579 and 203 differentially methylated sites (DMS) between HFD-1 and HFD-2 animals at week 32 and week 9, respectively, among which 11 were common. The DMS in blood and kidney at week 32 were both related to organ development, neurogenesis, cell junction, and Wnt signalling, while the DMS in blood at week 9 suggested a specific enrichment of kidney development processes. In conclusion, our data strongly support the implication of early blood DNA methylation modifications and DKD progression in T2D that could be used to improve the disease’s prognostication.

Meta-analyses identify DNA methylation associated with kidney function and damage

Chronic kidney disease is a major public health burden. Elevated urinary albumin-to-creatinine ratio is a measure of kidney damage, and used to diagnose and stage chronic kidney disease. To extend the knowledge on regulatory mechanisms related to kidney function and disease, we conducted a blood-based epigenome-wide association study for estimated glomerular filtration rate (n = 33,605) and urinary albumin-to-creatinine ratio (n = 15,068) and detected 69 and seven CpG sites where DNA methylation was associated with the respective trait. The majority of these findings showed directionally consistent associations with the respective clinical outcomes chronic kidney disease and moderately increased albuminuria. Associations of DNA methylation with kidney function, such as CpGs at JAZF1, PELI1 and CHD2 were validated in kidney tissue. Methylation at PHRF1, LDB2, CSRNP1 and IRF5 indicated causal effects on kidney function. Enrichment analyses revealed pathways related to hemostasis and blood cell migration for estimated glomerular filtration rate, and immune cell activation and response for urinary albumin-to-creatinineratio-associated CpGs.

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.