DNA methylation of the ELOVL2, FHL2, KLF14, C1orf132, and TRIM59 genes in blood, saliva, and buccal swab samples

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1 DNA methylation of the ELOVL2, FHL2, KLF14, C1orf132, and TRIM59 genes in blood, saliva, and buccal swab samples Nine Hallmarks of Aging Genomic instability Telomere attrition Epigenetic alterations Loss of proteostasis Deregulated nutrient sensing Mitochondrial dysfunction Cellular senescence Stem cell exhaustion Altered intercellular communication López-Otín et all. Cell

2 DNA Methylation Variation (Adult) (Infant) Unsupervised clustering of average beta values in normal human tissues. Christensen et al. PLoS Genet (2009) Age Prediction Based on DNA Methylation Met Met GGACAGGGGCGTGGCGCCTGCT 71 CpGs Age = a + b CpG 1 + c CpG 2 + d CpG 3 + Training set Test set Hannum et al. Mol Cell (2013) 2

3 Multi-tissue Age Predictor Horvath s model: 393 CpGs, less than 4 year error Horvath, Genome Biol (2013) Tissue-specific Age Predictors Sample Model Genes No. CpGs Error (y) Platform Weidner et al. ITGA2B, ASPA, PDE4C Zbieć- Piekarska et al. Zbieć- Piekarska et al. ELOVL ELOVL2, FHL2, KLF14, C1orf132, TRIM Park et al. ELOVL2, ZNF423, CCDC102B Saliva Bocklandt et al. EDARADD, TOM1L1, NPTX k array Hong et al. SST, CNGA3, KLF14, TSSK6, TBR1, SLC12A5, PTPN SNaPshot Semen Lee et al. TTC7B, NOX4, unknown SNaPshot, teeth Bekaert et al. ASPA, PED4C, ELOVL2, EDARADD Teeth Giuliani et al. ELOVL2, FHL2, PENK EpiTyper 3

4 Independent Validation of Models Zbieć-Piekarska s model: ELOVL2, FHL2, KLF14, C1orf132, TRIM59 Analysis platform: 300 Polish 100 Koreans Spearman s rho = MAD = 3.90 Cho S et al., Forensic Sci Int Genet (2017) Independent Validation of Models Another model with 5 CpGs explaining the highest% of age variance in each gene Gene Target (GRCh37) Coefficient Intercept ELOVL2 6: FHL2 2: KLF14 7: C1orf132 1: TRIM59 3: Cho S et al., Forensic Sci Int Genet (2017) 4

5 Change in Analysis Platform Multiplex methylation SNaPshot for age prediction in blood Yellow: methylation Red: non-methylation Blue: methylation Green: non-methylation ELOVL2 FHL2 KLF14 C1orf132 TRIM59 20s 30s 40s 50s 60s Change in Analysis Platform FORWARD C T REVERSE G A C intensity %methyl = 100 (C+T) intensity G intensity %methyl = 100 (G+A) intensity Estimated DNA methylation (%) Actual DNA methylation (%) DNA methylation difference (%) Actual DNA methylation (%) 1.5-fold high 1.7-fold high 2-fold high 5

6 Change in Analysis Platform Methylation SNaPshot MAD = 3.38 MAD = 4.37 rho = ELOVL2 FHL2 KLF14 C1orf132 TRIM59 Yellow: methylation Red: non-methylation Blue: methylation Green: non-methylation Methylation of, Saliva and Buccal Swab ELOVL2 FHL2 KLF14 R² = (blood) R² = (saliva) R² = (buccal swab) R² = (blood) R² = (saliva) R² = (buccal swab) R² = (blood) R² = R² = (blood) (saliva) R² R² = = (buccal (saliva) swab) R² = (buccal swab) C1orf132 TRIM59 R² = (blood) R² = (saliva) R² = (buccal swab) R² = (blood) R² = (saliva) R² = (buccal swab) Saliva Buccal swab 6

7 Age Prediction model Training set (n = 240 ) Test set (n = 60) 80 Pearson s rho = Pearson s rho = Predicted Age (years) MAD = 3.38 Predicted Age (years) MAD = 3.54 Saliva buccal swab Chronological Age (years) Chronological Age (years) Summary DNA methylation at 5 CpG sites from the ELOVL2, FHL2, KLF14, C1orf132, and TRIM59 genes was investigated in samples from blood, saliva, and buccal swabs using a multiplex methylation SNaPshot assay. An age prediction model trained on 240 samples including 80 of each blood, saliva and buccal swab samples exhibited high correlation between predicted and chronological ages with a MAD of 3.38 years. The model showed a MAD of 3.54 years in a validation set of 60 samples including 20 of each blood, saliva and buccal swab samples. These results suggest that these age-associated markers are less tissuespecific than others 7

8 Acknowledgment Kyoung-Jin Shin Sang-Eun Jung Eun Hee Lee Sae Rom Hong Bomin Kim Mi Hyeon Moon SeungMin Lim Yelim Kwon 8