Predicting age from blood by droplet digital PCR using a set of three DNA methylation markers.

Evaluation of DNA methylation (DNAm) patterns is a promising tool for age estimation. The duplex droplet digital PCR (ddPCR) method has been recently investigated for DNAm evaluation, revealing to be a potential methodology for DNAm evaluation and molecular age estimation. In this study, we evaluated DNAm levels of CpGs located at the three age-associated genes ELOVL2, FHL2 and PDE4C using ddPCR to develop an age prediction model. Blood-derived DNA samples from 58 healthy individuals (42 women and 16 men; aged 1-93 years old) were submitted to bisulfite conversion followed by ddPCR using dual-labeled probes targeting methylated and unmethylated DNA sequences. Simple linear regression statistics revealed a strong correlation between DNAm levels and chronological age for FHL2 (R = 0.948; P = 1.472 × 10-29) and PDE4C (R = 0.819; P = 3.917 × 10-15), addressing only one CpG for each gene. For the ELOVL2 gene, evaluating five CpG sites in simultaneous, revealed a strong age correlation (R = 0.887; P = 2.099 × 10-20) in a simple linear regression statistics and very strong age correlation (R = 0.926; P = 2.202 × 10-25) when using quadratic regression statistics. The multivariable regression analysis, using methylation information captured on ELOVL2 (squared), FHL2 and PDE4C genes, revealed a very strong age correlation (R = 0.970; P = 5.356 ×10-33), explaining 93.7 % of age variance, displaying a mean absolute deviation (MAD) between chronological and predicted age of 4.657 years (RMSE = 6.044). We postulate that the ddPCR method should be further investigated for DNAm-based age prediction, because it is a relatively simple and an accurate method that can be routinely used in forensic laboratories for testing a few numbers of markers.

DNA methylation analysis of ELOVL2 gene using droplet digital PCR for age estimation purposes.

DNA methylation (DNAm) evaluation has been investigated in various tissues and body fluids allowing the identification of many CpG markers with high correlations with chronological age, potentially useful for forensic analysis. We developed a duplex droplet digital PCR (ddPCR) assay to address methylation levels of ELOVL2 gene CpG sites. DNA samples obtained from peripheral blood of 56 healthy individuals (35 women, 21 men; aged 1-94 years old) were submitted to bisulfite conversion, followed by ddPCR analysis for a selected region of ELOVL2 and the reference gene C-LESSC1. Simple linear regression revealed a strong correlation between DNAm simultaneous captured from five CpG sites of ELOVL2 gene and chronological age (R = 0.892; P = 2.84 × 10-20), explaining 79.2% of age variation. The obtained mean absolute deviation (MAD) between predicted and chronological ages was 10.07 years. Here we describe a ddPCR-based assay to assess DNAm in ELOVL2 gene as a biomarker for potential use in forensic age prediction.

DNA methylation age estimation in blood samples of living and deceased individuals using a multiplex SNaPshot assay.

Many studies in the forensic field have reported that analysis of DNA methylation is the most reliable method of predicting age. In a previous study, 5 CpG sites located in ELOVL2, FHL2, KLF14, C1orf132 and TRIM59 genes were tested for age prediction purposes in blood, saliva and buccal swab samples from Korean individuals using a multiplex methylation SNaPshot assay. The main goals of the present study were i) to replicate the same multiplex SNaPshot assay in blood samples from Portuguese individuals, ii) to compare DNA methylation status between two different populations and iii) to address putative differences in the methylation status between blood from living and deceased individuals. Blood samples from 59 living individuals (37 females, 22 males; aged 1-94 years-old) and from 62 deceased individuals (13 females, 49 males; aged 28-86 years-old) were evaluated. The specific primers were those previously described. Linear regression models were used to analyse relationships between methylation levels and chronological age using IBM SPSS software v.24. Our results allowed to build a final age prediction model (APM) for blood samples of living individuals with 3 CpG sites, at ELOVL2, FHL2 and C1orf132 genes, explaining 96.3% of age variation, with a mean absolute deviation (MAD) from chronological age of 4.25 years. Some differences were found in the extent of the age association in the targeted loci comparing Portuguese with Korean individuals. The final APM built for deceased individuals included 4 CpG sites, at ELOVL2, FHL2, C1orf132 and TRIM59 genes, explaining 79.3% of age variation, with a MAD of 5.36 years. Combining both sets of samples from living and deceased individuals, the most accurate APM with 4 CpGs, at ELOVL2, FHL2, C1orf132 and TRIM59 genes, explained 92.5% of variation in age, with a MAD of 4.97 years. In conclusion, our study replicated in blood samples of Portuguese living individuals a previous SNaPshot assay for age estimation. The possibility that age markers might be population specific and that postmortem changes can alter the methylation status among specific loci was suggested by our data. Our study showed the usefulness of the multiplex methylation SNaPshot assay for forensic analysis in blood samples of living and deceased individuals.