Determining the age of a wound, i.e., the time interval between injury and death, can be essential in forensic casework in order to establish causal links between injury and death or to better characterize the time and circumstances of the injury. Traditional methods for estimating wound age commonly targeting protein biomarkers are time-consuming and often do not achieve sufficient accuracy.

With the aim of identifying a new and potentially more suitable set of biomarkers for wound age estimation, we collected 23 samples from routine autopsy cases of human skin with sharp injuries inflicted between a few seconds and 28 days prior to death as well as 23 control samples from uninjured skin regions. All samples were subjected to gene expression profiling using the Ion Ampliseq Transcriptome Human gene expression panel on an Ion Torrent S5 XL System.

A clustering analysis based on genes showing variable expression in wounded skin tissue revealed three clusters of wound age: acute (> 1 day), intermediate (1-3 days) and prolonged (>3 days). Differential expression analysis performed across these groups enabled the identification of transcriptional differences associated with wound progression. A functional analysis of the differentially expressed genes revealed various biological functions that can be assigned to the individual stages of wound healing.

In order to identify RNA biomarkers suitable for a future wound age prediction model, several (filter) criteria were defined and applied sequentially. The filters were applied to find markers that differentiate between groups (filter 1), do not exhibit low expression (filter 2), demonstrate a minimum difference in expression relative to the control, and exhibit consistent up- or downregulation within each group (filter 3). The criteria were designed to identify marker candidates that not only differentiate between wound age groups but can also be reliably detected using a targeted approach suitable for routine analyses. 

The long-term goal of this work is to establish a foundation for a gene expression-based method to estimate the age of human (sharp force) wounds.

Authors

• Annica Gosch (University Hospital of Cologne, Institute of Forensic Medicine, Germany)
• David Ast (University Hospital of Bonn, Institute of Forensic Medicine, Germany)
• Rogério Ribeiro (Department of Computer Science, University of Porto, Portugal)
• Johanna Preuß-Wössner (University Hospital Schleswig-Holstein, Institute of Forensic Medicine, Germany)
• Markus Rothschild (University Hospital of Cologne, Institute of Forensic Medicine, Germany)
• Pedro Ferreira (Department of Computer Science, University of Porto, Portugal)
• Cornelius Courts (University Hospital of Cologne, Institute of Forensic Medicine, Germany)
• Iva Gomes (Institute of Molecular Pathology and Immunology of the University of Porto, Portugal)