Introduction

Post mortem interval is the time that has elapsed since an individual's death, and it is a crucial parameter in forensic investigations. When estimating the PMI, a forensic anthropologist or pathologist can use qualitative categories that describe the soft tissue decay in the early stages of relying on his understanding of the local environment and decomposition. The traditional methods of PMI estimation, such as the use of insect activity and body temperature, have limitations when it comes to skeletal remains. The decomposition process in skeletal remains is slow, and the traditional methods may not be accurate in estimating PMI, especially in cases where the remains have been exposed to the elements for an extended period. Omic sciences is an interdisciplinary field that combines biology, genetics, and informatics to study the complex interactions between genes, proteins, and other molecules within an organism. Omic sciences has been widely used in biomedical research to understand the genetic basis of diseases and develop personalized medicine. However, its application in forensic science is relatively new, and it has shown great potential in PMI estimation. Omic sciences uses several methods for PMI estimation, such as transcriptomics, proteomics, and metabolomics. Transcriptomics is the study of changes in gene expression after an individual's death. Proteomics is the study of changes in protein degradation after an individual's death (Procopio et al., 2017). Metabolomics is the study of changes in metabolite levels after an individual's death.

Transcriptomics involves the analysis of RNA molecules to identify changes in gene expression patterns. The changes in gene expression can be used as molecular markers for PMI estimation. Proteomics involves the analysis of protein degradation patterns to identify changes in protein levels. The changes in protein levels can be used as molecular markers for PMI estimation. Metabolomics involves the analysis of metabolite levels to identify changes in metabolic pathways. The changes in metabolic pathways can be used as molecular markers for PMI estimation.

Lipidomics tests have only been utilized in three studies so far to estimate PMI. Two of them, performed on muscle tissue, revealed an increase in free fatty acids and a general negative connection between PMI and the majority of lipid classes (Langley et al., 2019; Wood and Shirley, 2013). The third study used lipidomics to examine trabecular bone samples from calcanei with an average PMI of about 7 years. It found 76 potential N-acyl AAs that could be used to estimate PMI, though their correlation with PMI has not yet been fully explained

In both animal and human investigations, it has been attempted to measure the extent of protein survival and the accumulation of post-translational modifications (PTMs) in bones (Procopio et al., 2017; Mickleburgh et al., 2021; Prieto-Bonete et al., 2019; Procopio et al., 2021; Bonicelli et al., 2022) as well as under various circumstances (for example, in aquatic environments, with various types of coffins, buried vs. surface). The underlying idea behind these investigations is that the protective effect of hydroxyapatite is anticipated to increase protein survival, thereby enabling estimate of longer PMIs.