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Table 3 Overview of methodology and statistical analysis

From: The applications of DNA methylation as a biomarker in kidney transplantation: a systematic review

References

Sample tissue

Epigenome-wide, candidate genes, or TSDR methylation status

Bisulfite conversion

Method

Methylation outcome

Statistical tests

Statistical thresholds

IRI, fibrosis, and long-term complications-related studies

Mehta et al. [41]

Urine

Candidate Genes (CALCA)

In-house [41]

qPCR (TaqMan, primer: designed for the CALCA gene locus)

Target Gene/β-actin*1000

Student’s t-test, ANOVA, Wilcoxon rank-sum test, Kruskal–Wallis test to compare mean CALCA values among the study groups, as appropriate

Not Provided

Bontha et al. [42]

Kidney Biopsy

Epigenome-Wide

EZ DNA methylation kit (Zymo Research)

Infinium HumanMethylation450 BeadChip (Illumina)

β and M values for statistical analysis, no value presented

Moderated Student’s t-test BY-corrected to compare DNAm levels between IFTA and NFA patients, PCA and average linkage hierarchical clustering of DNAm, GE, and miRNA integrated datasets

FDR < 0.01

McGuinness et al. [43]

Kidney Biopsy

Epigenome-Wide

EZ DNA methylation kit (Zymo Research)

Whole Genome Bisulfite Sequencing (EpiGnome Methyl‐Seq kit (Illumina) to generate libraries and NextSeq500 (Illumina) for sequencing)

Methylated cytosines within CpG dinucleotides (mCpGs)

Kruskal–Wallis test with FDR correction to compare differences in CpG DNAm status of DGF-specific transcripts among the study groups

FDR < 0.05

Heylen et al. [44]

Kidney Biopsy

Epigenome-Wide

EZ DNA methylation kit (Zymo Research)

Infinium MethylationEPIC BeadChip (Illumina)

Infinium HumanMethylation450 BeadChip (Illumina)

β and M values for statistical analysis, methylation percentage for visualization

Wilcoxon rank-sum test to compare pre- versus post- ischemia DNAm levels, linear regression to examine the effect of CIT on DNAm of all CpGs in the pre-KT cohort, paired Student’s t-test to examine the effect of CIT on DNAm of CpGs grouped per CGI in the longitudinal cohort, linear mixed model to examine the effect of CIT on DNAm of CpGs grouped per CGI in the pre-KT cohort, binomial tests to compare HrM and HoM events

FDR < 0.05

Heylen et al. [45]

Kidney Biopsy

Epigenome-Wide

EZ DNA methylation kit (Zymo Research)

Infinium MethylationEPIC BeadChip (Illumina)

Infinium HumanMethylation450 BeadChip (Illumina)

M values for statistical analysis, coefficients based on β values for visualization

Linear regression to examine the effect of age on DNAm, binomial tests to compare HrM and HoM events, linear regression to associate DNAm levels of all age-associated CpGs to histology scores, logistic regression to associated DNAm levels of all age-associated CpGs to reduced allograft function

FDR < 0.05

Schaenman et al. [46]

Blood sample (PBMCs)

Epigenome-Wide

EZ DNA methylation kit (Zymo Research)

Infinium MethylationEPIC BeadChip (Illumina)

M values and DNAmAge (Horvath method)

Kaplan–Meier analysis for time-dependent analyses of infection or rejection in relation to DNAmAge, with statistical Gray’s test to evaluate hypotheses of equality of cumulative incidence functions between study groups

p < 0.05

Immune response modulation-related studies

Bestard et al. [47]

Kidney Biopsy

TSDR methylation status

According to Wieczorek et al. [61]

qPCR (primers according to Wieczorek et al. [61])

Methylation percentage

One-way ANOVA, t-test, Kruskal–Wallis test, or Mann–Whitney U-test to compare different study groups, as appropriate

p < 0.05

Bouvy et al. [48]

Blood sample (PBMCs)

TSDR methylation status

EZ DNA methylation kit (Zymo Research)

qPCR (TaqMan, primers according to Wieczorek et al. [61])

Methylation percentage

Kruskal–Wallis test (with Dunn’s multiple comparison test) to compare multiple groups and Mann–Whitney U-test to compare different groups or time-points

p < 0.05

Braza et al. [49]

Blood sample (PBMCs)

TSDR methylation status

According to Wieczorek et al. [61]

qPCR (primers according to Wieczorek et al. [61])

Methylation percentage

Kruskal–Wallis test to compare multiple groups

p < 0.05

p < 0.01

p < 0.001

Sherston et al. [50]

Blood sample (PBMCs)

TSDR methylation status

EpiTect Bisulfite Kit (Qiagen)

qPCR

Methylation percentage

Not Provided

p < 0.05

Boer et al. [51]

Blood sample (PBMCs)

Candidate-genes (PD1 and IFNγ)

EZ DNA methylation kit (Zymo Research)

PCR amplification and pyrosequencing (primers designed for h PD1 and IFNγ genes loci)

Methylation percentage

Student’s t-test, ANOVA, or Mann–Whitney U-test, as appropriate, to compare different groups; linear mixed-effects model to determine differences after KT over time between rejectors and non-rejectors

p < 0.05

Trojan et al. [52]

Blood sample (PBLs)

TSDR methylation status

EZ DNA methylation kit (Zymo Research)

qPCR (primers: Human Foxp3 Methylation Panel, EpigenDx)

Methylation percentage

ANOVA, Wilcoxon test, Mann–Whitney U-test, and Spearman rank correlation test to compare different study groups, as appropriate

FDR < 0.01

Trojan et al. [53]

Blood sample (PBLs)

TSDR methylation status

EZ DNA methylation kit (Zymo Research)

qPCR (primers: Human Foxp3 Methylation Panel, EpigenDx)

Methylation percentage

Wilcoxon test or Mann–Whitney U-test to compare different study groups, as appropriate

FDR < 0.01

Alvarez Salazar et al. [54]

Blood sample (PBMCs)

TSDR methylation status

EZ DNA methylation kit (Zymo Research)

PCR amplification and sequencing (primers’ sequence reported)

Methylation percentage

Kruskal–Wallis test to compare more than 2 different study groups and Mann–Whitney U-test to compare 2 different study groups

p < 0.05

Peters et al. [55]

Blood sample (PBMCs)

Epigenome-wide and Candidate Genes validation (RNF180 and ZNF502)

EZ DNA methylation kit (Zymo Research)

Epigenome-wide

Infinium HumanMethylation450 BeadChip (Illumina)

Candidate Genes confirmation

PCR amplification and pyrosequencing (primers designed for the RNF180 and ZNF502 genes loci)

Β values

Linear mixed-effect model to identify DNAm differences between groups, paired Wilcoxon test to compare DNAm levels pre- and post-KT, Mann–Whitney U-test to compare different study groups, and Spearman’s rank correlation coefficient to compare the results of the whole epigenome analysis and the pyrosequencing of candidate genes

p < 0.05

FDR < 0.05

Peters et al. [56]

Blood sample (T cells)

Epigenome-wide and Candidate Genes validation (SERPINB9 and VTRNA2-1)

EZ DNA methylation kit (Zymo Research)

Epigenome-wide

Infinium HumanMethylation450 BeadChip (Illumina)

Candidate Genes confirmation

PCR amplification and pyrosequencing (primers designed for the SERPINB9 and VTRNA2-1 loci)

Β values

Linear mixed-effect model to identify DNAm differences between groups, paired Wilcoxon test to compare DNAm levels before and after transplantation, Mann–Whitney U-test to compare different study groups, Spearman’s rank correlation coefficient to compare the results of the whole epigenome analysis and the pyrosequencing of candidate genes

p < 0.05

FDR < 0.05

Cortés-Hernández et al. [57]

Blood sample (PBMCs)

TSDR methylation status

EZ DNA methylation kit (Zymo Research)

PCR amplification and Sanger sequencing (primers’ sequence reported)

Methylation percentage

Student’s t-test, Wilcoxon rank-sum test, or Mann–Whitney U-test to compare different study groups, as appropriate, and Kruskal–Wallis test or one-way ANOVA to compare more than 2 different study groups, as appropriate

p < 0.05

Zhu et al. [58]

Blood sample (PBMCs)

Epigenome-Wide and Candidate-genes (RUNX3, DDIT4, PTEN, and FOXP3)

EpiTect Bisulfite Kit (Qiagen)

Epigenome-wide

Infinium HumanMethylation450 BeadChip (Illumina)

Candidate-genes

PCR and Next-Generation Sequencing (primers designed for the RUNX3, DDIT4, PTEN, and FOXP3 genes loci)

Methylation percentage

Wilcoxon rank-sum test and array-related software packages to determine methylation-variable positions

FDR < 0.05

Soyoz et al. [59]

Blood Sample (PBLs)

Candidate-genes (IL-2 and IFN-γ)

EpiTect Bisulfite Kit (Qiagen)

qPCR and Pyrosequencing (primers designed for the IL-2 and IFN-γ genes loci)

Indicated as increased or decreased

Not provided

Not provided

Rodriguez et al. [60]

Blood sample (PBMCs)

Epigenome-Wide

EZ DNA methylation kit (Zymo Research)

Infinium MethylationEPIC BeadChip (Illumina)

M values and Β values

Mann–Whitney U-test to compare different study groups

p < 0.05

FDR < 0.05

  1. ANOVA, Analysis of variance; BY, Benjamini–Yekutieli; CALCA, Calcitonin Related Polypeptide Alpha; CGI, CpG island; CIT, Cold ischemia time; CpG, Cytosine-phosphate-guanine site; DDIT, DNA Damage Inducible Transcript; DGF, Delayed graft function; DNAm, DNA methylation; DNAmAge, Epigenetic age; FDR, False discovery rate; FOXP3, Forkhead box P3 or scurfin; GE, Gene expression; HoM, Hypomethylation; HrM, Hypermethylation; IFNγ, Interferon γ; IFTA, Interstitial fibrosis and tubular atrophy; IL, Interleukin; KT, Kidney transplantation; Lselectin, L-selectin (CD62L); NFA, stable functioning allograft with no or minimal IFTA; PBL, Peripheral blood lymphocytes; PBMC, Peripheral blood mononuclear cell; PCA, Principal component analysis; PCR, Polymerase chain reaction; PD1, Programmed cell death protein 1; PTEN, Phosphatase and tensin homolog; qPCR, Quantitative real-time PCR; RNF, Ring Finger Protein; RUNX, RUNX Family Transcription Factor; SERPINB9, Serpin Family B Member 9; TSDR, Treg-specific demethylated region; VTRNA, Vault RNA; ZNF, Zinc Finger Protein