Table 5 Methylation studies in chronic kidney disease
From: Genomic approaches in the search for molecular biomarkers in chronic kidney disease
PMID | Author | Year | Sample | Patients (n) | Controls (n) | Ethnicity | Methodology | Main findings |
|---|---|---|---|---|---|---|---|---|
28609449 | Bailie | 2017 | Blood | CKD (n = 255) | No evidence of CKD (n = 152) | Caucasian | 450 K array 485,577 CpG sites: UMOD1, UMOL1 and UMODL1-AS1 genes | Differential methylation of three CpG sites in UMOD. The most significant was cg03140788 (p = 3.7∙10−10) Eight associated CpG sites in UMODL1 and UMODL1-AS1 genes, with genome wide significance. The most significant for non-diabetic ESRD was cg16624482 (p = 2.9∙10−32) |
28755807 | Zinellu | 2017 | Blood | CKD (n = 30) | Healthy (n = 30) Age- and sex-matched controls | Italy | Percentage of methylated to total cytosine | Lower DNA methylation in CKD (4.06 ± 0.20% vs. 4.27 ± 0.17%; p = 0.0001 Cholesterol lowering treatment significantly increased DNA methylcytosine concentrations in all patients (4.06 ± 0.04% at baseline; 4.12 ± 0.03% at 4 months; 4.17 ± 0.03% at 8 months; and 4.20 ± 0.02% at 12 months; p = 0.0001 for trend) The combined 10/40 mg/day ezetimibe/simvastatin treatment showed a trend for a greater effect on DNA methylation (+5.2% after one year treatment) |
27018948 | Zawada | 2016 | Differentiated intermediate monocytes from haematopoietic stem cells, isolated from healthy donors | ESRD (n = 5) RRT | Healthy (n = 5) Age- and sex-matched controls | Germany Primary culture (Treatment with serum from CKD patients (uraemic) or control patients) | Methyl-Seq 813,267 Genomic loci | Patients had higher counts of intermediate (p < 0.05) and nonclassical (p < 0.01) monocytes Upon stimulation with uremic serum, more intermediate monocytes were generated as compared to control conditions (p < 0.001) Monocytes generated under uremic conditions were closer related to circulating intermediate monocytes than monocytes generated under control conditions Five of the top 50 DMRs included in the comparison between “CKD” and “control” monocytes had been found involved with CKD by other authors |
24363223 | Ghattas | 2014 | Blood | ESRD (n = 96) | Healthy (n = 96) | Egyptian | Methylation-specific PCR MTHFR gene | The frequency of MTHFR methylation was significantly higher in ESRD patients (p = 0.003) eGFR was significantly lower when MTHFR promoter was methylated (p = 0.026) |
24253112 | Smyth | 2014 | Blood | CKD (n = 255) | No evidence of CKD (n = 152) | Caucasian | 450 K array 485,577 CpG sites | More than one significantly affected CpG in 23 unique genes after adjustment (p < 10−8) RNA-seq data also supported a functional role for DM in ELMO1 and PRKAG2, as they saw altered expression in the expected manner, even if change in PRKAG2 expression was not statistically significant CUX1, ELMO1, FKBP5, INHBA-AS1, PTPRN2, and PRKAG2 genes proposed as biological candidates for kidney disease |
24516231 | Wing | 2014 | Blood | “Rapid Progression” CKD (n = 20) eGFR 20–70 ml/min/1.73 m2 “Highest Rate of Decline” CRIC cohort | “Stable Kidney Function” CKD (n = 20) eGFR 20–70 ml/min/1.73 m2 “Slowest Rate of Decline” | Caucasian (50%) African American/Black (40%) Oher (10%) | 450 K array 485,577 CpG sites | No gene reached significance after FDR Of the 15 genes most strongly associated with rapid progression, 14 of them were more heavily affected in the slow progression group UMODL1 among several others, proposed as “top candidates” |
24224012 | Chen | 2013 | Renal biopsy/PBMC | CKD (n = 47) | Renal cell carcinoma (Renal biopsy, n = 47) Healthy (PBMC, n = 46) | China | Pyrosequencing: 6 CpGs assessed in Klotho (KL) Gene | KL gene was hypermethylated in 68% tissue and 70% PMBC samples from CKD patients when compared to controls, significance reached across all CpG sites (p < 0.001) Methylation of PBMC KL positively correlated with renal KL methylation (p < 0.001) eGFR inverse correlation with renal and PBMC levels of KL promoter methylation (both p < 0.001) |
18287179 | Nanayakkara | 2008 | Genomic DNA extracted from Leukocytes | CKD 2–4 (n = 78) (eGFR 15-70 ml/min/1.73 m2) ATIC study | 109 healthy volunteers | The Netherlands | LC–MS | No association was found between DNA methylation and renal function |
18067454 | Geisel | 2007 | PBMC | ESRD (n = 22) all receiving RRT (22 HT, 20 DM and 14 CVD) | Healthy (n = 26). Age- and sex-matched | Germany | Pyrosequencing: LINE-1 (nCpG = 7) p66Shc Promoter (nCpG = 3) | Methylation of p66Shc promoter significantly reduced in ESRD patients (p < 0.01). LINE-1 (used as surrogate marker of global methylation) significantly hypermethylated in ESRD patients (p < 0.01) |
17444888 | Stenvinkel | 2007 | Peripheral blood leukocytes | 4 Groups: Group 1: Non-Inflamed (CRP < 10mgL-1) stage 3 or 4 (7 GN, 1 DKD, 4 PCKD, 5 = nephrosclerosis, 5 = other, 6 = unknown) Group 2A: stage 5 + RRT + Non-inflamed (n = 56) Group 2B: stage 5 + RRT + Inflamed (n = 42). Group 3: stage 5 + RRT + Constant Inflammation (weekly CRP measurements for 3 months) (n = 20) | Group 4: Healthy controls randomly selected from the population (n = 36) | Sweden | LUMA HpaII/MspI ratio | No association found between DNA methylation and eGFR No differences found between diabetic and non-diabetic patients Association of global hypermethylation with CVD (p < 0.01) Inflammation associated with global hypermethylation (p = 0.0001) In essence, the association was with inflammation, not CKD |