Assessing transcriptomic signatures of aging: Testing an mRNA marker panel for forensic age estimation of blood samples

Abstract

Estimating the age of an unknown perpetrator can be a valuable tool in narrowing down a group of suspects. Research efforts to estimate the age of a stain donor have mainly focused on epigenetic modifications, but there is evidence that RNA expression patterns, i.e. the composition of the transcriptome, change with increasing age, which could be a promising molecular alternative for age prediction. In a previous study, we identified a total of 508 mRNA markers with age related expression from two blood whole transcriptome sequencing data sets, using differential expression analysis with DESeq2 and marker selection with lasso regression. For this study, the selected markers from both approaches were combined into an RNA-specific targeted MPS assay for the Ion Torrent platform and evaluated with 100 EDTA blood samples from healthy donors (aged between 23 and 73 years). We compared three different normalization methods for the obtained sequencing data and investigated the performance of various regression techniques for age prediction. The model based on elastic net regression and dSVA-normalized data exhibited the most robust performance, achieving an MAE of 9.29 years and a correlation of 0.57 between the chronological and predicted age. Although the use of a targeted approach instead of RNA-Seq offers several advantages in a forensic setting, we observed a considerable amount of unwanted variation in the targeted sequencing data. We conclude that it is challenging to detect distinct signals associated with chronological age.