DNA methylation-based forensic framework for age prediction and body fluid identification using nanopore sequencing

Abstract

Forensic DNA phenotyping applies genetic and epigenetic markers to infer biogeographical ancestry, physical appearance traits, and biological age, particularly when conventional methods fail to identify a suspect or victim. DNA methylation, a key epigenetic modification, is especially valuable for age estimation and due to its tissue-specific patterns also for body fluid identification, with the latter aiding in crime scene reconstruction. Current MPS-based methylation sample analyses require time-consuming, multi-step processing, while Nanopore sequencing offers a promising alternative by enabling real-time, direct detection of methylation without DNA conversion. This study evaluates the potential of Nanopore’s PromethION 2 platform for comprehensive, single-assay forensic epigenetic analysis of biological age estimators (epigenetic clocks) and body fluid markers, focusing on relatively low DNA samples (<100 ng.) Our results showed that low read depth coverage can invoke the occurrence of beta values equal to zero and one for the methylation status (whilst methylation has a continuous nature), provide challenges for accurate age estimation and body fluid identification. Our study demonstrates that both the age prediction models tended to estimated older ages than expected; however, applying a proof-of-concept linear correction model significantly enhanced age estimation accuracy. Body fluid identification of blood and saliva was highly accurate in conditions with high and low read depth coverage, correctly identifying 4/4 sample in each experiment. This explorative study highlights the potential of adaptive sampling on PromethION for forensic age prediction and body fluid identification, while future studies should focus on validating analysis thresholds, improving lower-quantity sample performance, advancing body fluid identification models for an extended tissue set, and mixture analysis.