"Forens-OMICS": the application of -omics to human bones for forensics
Research type
Research Study
Full title
"Forens-OMICS": a cross disciplinary implementation of omics sciences to in vivo and post-mortem ageing investigations for forensic applications
IRAS ID
313259
Contact name
Noemi Procopio
Contact email
Sponsor organisation
University of Central Lancashire
Duration of Study in the UK
6 years, 7 months, 1 days
Research summary
The aim of this research project is to apply some of the most cutting-edge technologies available in modern biology laboratories to address two of the most important questions that a forensic scientist could be asked to answer in order to solve a crime, namely the post-mortem interval (PMI) of the victim (the time elapsed from his/her death) and the age of the victim (AAD, age-at-death). Nowadays, technological progress allows researchers to extract an invaluable amount of biological information starting from very small amounts of material such as very small fragment of bone. This includes genetic information, as well as protein and metabolite information, and these are generally summarised under the common term of "omics" disciplines. Interestingly, all the biomolecules cited here can bring a specific "signature" depending on in-vivo and post-mortem ageing phenomena of the biological tissue that contains them, and these signatures could be investigated within a small biological sample in a non-targeted way, in order to evaluate their linkage with ageing phenomena (both PMI and AAD) and their predictive power.
The term "Forens-OMICS" indicates here the first global application of several "omics" technologies aimed to address ageing phenomena primarily for forensic applications, but also for archaeological ones. To achieve these aims, several collaborations with several anthropological facilities in the United States of America allowed the collection and the sampling of a significant number of human bones of either individuals with a wide age and PMI. The bone samples collected will be then used to extract DNA, proteins and metabolites, and high-throughput analyses will be performed on each of these specific biomolecules to extrapolate quantifiable features associated with both PMI and AAD. All the recovered information will then be combined together with advanced bioinformatics tools, in order to develop a mathematical model that will estimate PMI and AAD.REC name
HSC REC B
REC reference
22/NI/0118
Date of REC Opinion
4 Jul 2022
REC opinion
Further Information Favourable Opinion