Cost-effective optimisation and validation of the VISAGE enhanced tool assay on the Illumina NovaSeq 6000 platform

Numerous forensic age prediction models based on DNA methylation markers have been developed, each differing in the number of predictive markers, statistical method, biomatrix, and sequencing platform used. This variability highlighted the need for more uniformity in the development of epigenetic clocks. To partially address this need, the VISAGE Consortium introduced the VISAGE enhanced tool assay, a multi-tissue assay that targets eight age-associated genes (ELOVL2, EDARADD, ASPA, FHL2, MIR29B2CHG, KLF14, TRIM59, and PDE4C). So far, three models were built using this assay for age prediction in blood, buccal cells, and bones, based on Illumina MiSeq sequencing data with the v3 reagent kit (2 × 300 bp). Unfortunately, the existing models are neither publicly accessible nor permitted for use in forensic casework. To address this limitation, we developed our own age estimation model utilising the VISAGE enhanced tool assay in combination with the Illumina NovaSeq 6000 platform and the v1.5 reagent kit (2 × 150 bp). By employing the same assay, we streamlined the workflow and enhanced uniformity, as there was no need to identify additional age-associated genes. By adjusting the assay's primer concentrations, we achieved sufficient read depths to accurately determine methylation levels, even for longer amplicons with partial sequencing strand coverage. This modified assay was used to develop an age estimation model in blood (n = 98) with a mean absolute error (MAE) of 3.22 years and root mean squared error (RMSE) of 3.77 years in the test set (n = 30). Overall, this study demonstrated that by adjusting primer concentrations, equal age estimation performances can be achieved with the added benefit of drastically reduced costs and turn-around-time by using a 2 × 150 bp sequencing strategy. Additionally, this study was the first to independently validate the VISAGE enhanced tool assay on a different sequencing platform, exploring its potential for broader applications and partially answering the need for more uniformity.