The Epigenetic Clock Concept as an Emerging Molecular Tool for Post-Mortem Interval Estimation in Forensic Investigations

Classical methods for postmortem interval (PMI) estimation have been applied for nearly a century. Contrary to the notion of being simple or easily accessible, these approaches require highly specialized training, including a medical degree, postgraduate specialization in forensic pathology, and extensive practical experience. Classical PMI estimation relies on observable physical and chemical changes in the human cadaver, such as rigor mortis, livor mortis, algor mortis, and transformative processes during decomposition. These methods are fundamental in medicolegal practice but remain largely influenced by environmental and individual variability. Recent advances in forensic research, particularly in microbiology and biochemistry, have introduced innovative approaches that complement traditional methods, offering greater accuracy and reliability, though resource-intensive. Emerging approaches leverage the predictable postmortem succession of microbial communities (thanatomicrobiome) and biochemical alterations in cadaver fluids and tissues. Techniques such as metagenomics, metatranscriptomics, and metabolomics enable detailed analysis of these changes, while computational models and machine learning further refine PMI estimates. Despite advancements, challenges persist, including variability due to environmental factors and limited access to human decomposition data. Integrating multi-omics approaches and artificial intelligence offers a path forward, addressing these limitations and enhancing the accuracy of PMI estimation. This review provides a comprehensive overview of PMI estimation, critically examining classical approaches and highlighting cutting-edge methodologies rooted in thanatomicrobiology and thanatochemistry. We emphasize the transformative potential of multi-omics integration and artificial intelligence in improving PMI accuracy. Importantly, we propose a paradigm shift: redefining PMI estimation through evidence-based, interdisciplinary research that bridges scientific rigor and judicial application. Transdisciplinary collaboration and standardized methodologies will be essential to translate emerging knowledge into robust forensic tools that serve both science and justice.

Accurate postmortem interval (PMI) estimation is critical for forensic investigations, aiding case classification and providing vital trial evidence. Early postmortem signs, such as body temperature and rigor mortis, are reliable for estimating PMI shortly after death. However, these indicators become less useful as decomposition progresses, making late-stage PMI estimation a significant challenge. Decomposition involves predictable microbial activity, which may serve as an objective criterion for PMI estimation. During decomposition, anaerobic microbes metabolize body tissues, producing gases and organic acids, leading to significant changes in skin and soil microbial communities. These shifts, especially the transition from anaerobic to aerobic microbiomes, can objectively segment decomposition into pre- and post-rupture stages according to rupture point. Microbial communities change markedly after death, with anaerobic bacteria dominating early stages and aerobic bacteria prevalent post-rupture. Different organs exhibit distinct microbial successions, providing valuable PMI insights. Alongside microbial changes, metabolic and volatile organic compound (VOC) profiles also shift, reflecting the body's biochemical environment. Due to insufficient information, unimodal models could not comprehensively reflect the PMI, so a muti-modal model should be used to estimate the PMI. Machine learning (ML) offers promising methods for integrating these multimodal data sources, enabling more accurate PMI predictions. Despite challenges such as data quality and ethical considerations, developing human-specific multimodal databases and exploring microbial-insect interactions can significantly enhance PMI estimation accuracy, advancing forensic science.

Forensic entomology is a crucial discipline in forensic investigations, primarily used for postmortem interval (PMI) estimation, species identification, and crime scene reconstruction. Recent advancements in molecular techniques, computational models, and climate-adaptive forensic entomology have enhanced the field's forensic applications. However, challenges related to methodological standardization, environmental variability, and legal admissibility persist. This comprehensive review examines recent developments in forensic entomology, focusing on molecular methodologies, AI-assisted species identification, and environmental influences on forensic insect succession. Literature was sourced from Scopus, Web of Science, and PubMed, emphasizing peer-reviewed studies published in the last 2 decades. Key themes include PMI estimation advancements, forensic insect ecology, and legal challenges in forensic entomology. Findings highlight improved accuracy in PMI estimation through genetic and computational approaches, the expansion of forensic molecular entomology applications, and the impact of climate change on forensic insect activity. While AI and molecular forensics have revolutionized species identification, standardization and legal frameworks remain insufficient. The study underscores the need for globally harmonized forensic entomology protocols, forensic training programs, and ethical guidelines. Future research should integrate metagenomics, forensic AI, and climate-adaptive forensic models to enhance forensic accuracy and reliability.

Circular RNAs (circRNAs) are conserved, abundant, stable, and specifically expressed in mammals. The postmortem interval (PMI) estimation is crucial in forensic medicine, particularly for case investigation and civil action. CircRNAs may serve as ideal PMI biomarkers. However, no research has explored PMI estimation in the brain using circRNAs. The total RNA, including circRNA, was sampled from mouse brain tissues at multiple temperatures (4℃, 25℃, and 35℃). The semi-quantitative reverse transcription (RT)-PCR and real-time quantitative PCR (RT-qPCR) were used to test the postmortem degradation levels at different PMIs. As a result, we found circFat3 is highly and specifically expressed in mouse brain tissue, with postmortem levels significantly correlated with PMI across multiple temperatures. In addition, mt-co1 and 28 S rRNA demonstrated stability under various temperature conditions, supporting their use as reliable reference genes for PMI models. Moreover, the error rates showed that the circFat3/28S rRNA model was more accurate at 4℃. The circFat3/mt-co1 and circFat3/28S rRNA models provided slightly better predictions for short-term and long-term PMI, respectively at 25℃, while the circFat3/mt-co1 model was more accurate at 35℃. The combined application of the two reference genes was beneficial primarily for long-term PMI estimation. Furthermore, the validation results confirmed that these models were more accurate for long-term PMI estimation. Thus, our mathematical models were constructed at multiple temperatures based on circFat3 and these two reference genes. Taken together, this is the first study to identify circRNA circFat3 as a novel biomarker that may serve as a complementary tool for PMI estimation.

Background: Accurate estimation of the postmortem interval (PMI) is critical in forensic death investigations. Traditional signs of death—algor mortis, livor mortis, and rigor mortis—are generally reliable only within the first two to three days after death, with their accuracy decreasing as decomposition progresses. This paper presents a systematic review conducted in accordance with PRISMA guidelines, aiming to evaluate and compare current methods for estimating the PMI. Specifically, the study identifies both traditional and modern techniques, analyzes their advantages, limitations, and applicable timeframes, critically synthesizes the literature, and highlights the importance of combining multiple approaches to improve accuracy. Methods: A systematic search was conducted in the PubMed, Scopus, and Web of Science databases, following the PRISMA guidelines. The review included original articles and reviews that evaluated PMI estimation methods (through thanatological signs, entomology, microbial succession, molecular, imaging, and omics approaches). Extracted data included study design, methodology, PMI range, and accuracy information. Out of the 1245 identified records, 50 studies met the inclusion criteria for qualitative synthesis. Results: Emerging methods, such as molecular markers, microbial succession, omics technologies, and advanced imaging show improved accuracy across extended postmortem intervals. RNA degradation methods demonstrated higher accuracy within the first 72 h, while entomology and microbial analysis are more applicable during intermediate and late decomposition stages. Although no single method is universally reliable, combining traditional and modern approaches tailored to case-specific factors improves overall PMI estimation accuracy. Conclusions: This study supports the use of an integrative, multidisciplinary, and evidence-based approach to improve time-since-death estimation. Such a strategy enhances forensic outcomes by enabling more precise PMI estimates in complex or delayed cases, increasing legal reliability, and supporting court-admissible expert testimony based on validated, multi-method protocols.

Post-mortem interval (PMI) estimation remains one of the major challenges in forensic practice, especially for late PMIs beyond 7-10 days after the death of the subject. In 2022, an innovative method to investigate the occurrence of mutations induced by the death of a subject in the DNA of post-mortem dental pulps at different PMIs was developed, applying a next-generation sequencing (NGS) analysis. The present study aims to apply the same method of analysis to a small sample of teeth belonging to the same subject and analyzed at different PMIs/accumulated degree days (ADDs), and of teeth extracted from different subjects but analyzed at the same PMI/ADD to verify the repeatability of the results obtained in relation to the time elapsed since death. A total of 10 teeth were collected from 6 patients (3 males and 3 females) with PMI varying from 8 to 35 days, and ADD from 157.4 to 753.8. We found 1754 mutations in 56 genes, with more than 700 mutations having a prevalence > 5% and more than 300 variants considered of interest for the purposes of the study. Mutations that were not present at lower PMIs but manifested in later PMIs in pulps belonging to the same subject demonstrate that they can only have been acquired by the subject after death and according to the time elapsed since death. In total, 67 somatic mutations in 29 out of the 56 genes of the used panel occurred in a fashion that allows an association with specific PMI/ADD ranges (within 8 days, between 17 and 28, and beyond 30 days after death). The results suggest that temperature and humidity could influence the rate of DNA degeneration in dental pulps, thus PMI should be estimated in ADD more than days. The preliminary validation supports the hypothesis that the innovative method could be a useful tool for estimating the post-mortem interval even beyond the first week after death, but further analyses are needed to customize a specific genetic panel for forensic investigations and verify the influence of degenerative processes of soft tissues surrounding dental elements on DNA degeneration of pulps.

Application of metabolomic methods to forensic studies may expand the limits of the post-mortem interval (PMI) estimation, and improve the accuracy of the estimation. To this end, it is important to determine which tissue is the most suitable for analysis, and which compounds are the most promising candidates for PMI estimation. This work is aimed at the comparison of human serum, aqueous humor (AH), and vitreous humor (VH) as perspective tissues for metabolomic-based PMI estimation, at the determination of most promising PMI biomarkers, and at the development of method of PMI estimation based on the measurement of concentrations of PMI biomarkers. Quantitative metabolomic profiling of samples of the human serum, AH, and VH taken at different PMIs has been performed with the use of NMR spectroscopy. It is found that the metabolomic changes in anatomically isolated ocular fluids are slower and smoother than that in blood. A good positive time correlation (Pearson coefficient r > 0.5) was observed for several metabolites, including hypoxanthine, choline, creatine, betaine, glutamate, and glycine. A model for PMI estimation based on concentrations of several metabolites in AH and VH is proposed. The obtained results demonstrate that the metabolomic analysis of AH and VH is more suitable for the PMI estimation than that of serum. The compounds with good positive time correlation can be considered as potential PMI biomarkers.

Postmortem interval arises one of the most important research topics in worldwide modern forensic science applications. In spite of utilizing morphological, biochemical, flow-cytometric, microbiological, entomological, anthropological, spectroscopic and main postmortem changes in postmortem interval estimation, it does not seem possible to get certain results by only one test or method. Because, there are many physical, chemical and biological processes affecting the parameters. Therefore, postmortem interval estimation needs development of previous methods and implementation of novel methods. In this regard, taphonomic methods need to be improved in postmortem interval estimation and regional factors and climate impact need to be determined by experimental studies. In particular, we are of the opinion that that more accurate estimation of postmortem interval will be achieved by determining regional factor involving postmortem period. This paper aims to evaluate the relationship between postmortem interval and accumulated degree days in respect of decomposition stages.Key Words: Forensic Taphonomy, Postmortem Interval, Forensic Anthropology

Age determination of necrophagous flies serves as an important tool for postmortem interval (PMI) estimation in forensic investigations. Drugs or toxins in cadavers may alter the developmental time of larvae, and lead to deviation in PMI estimation. Methamphetamine (MA), as one of the most abused psychostimulant drugs in Asia and North America, is often involved in forensic entomotoxicological cases. This study investigated the effects of MA (0, 45, 90, and 180 ng/mg) on the developmental rate, morphology, and survival of Aldrichina grahami (Aldrich, 1930). The results showed that 1) the developmental time to reach the pupal instar was statistically slower for the larvae reared on rabbit mince containing MA than for the control; 2) the mean length of the larvae exposed to MA concentrations was longer than those of the control; 3) the mean weight of the pupae exposed to the highest concentration of MA was significantly lighter than those of the control; 4) the GC-MS method can detect the content of MA in A. grahami immatures and empty puparia (EP).

The decomposition of organic remains is a complex ecological process governed by intricate interactions among insects, microorganisms, and environmental factors. This review comprehensively examines the colonisation dynamics and behavioural ecology of insects associated with human cadavers and animal carcasses, emphasizing their significance in forensic investigations. Over the past two decades (2005-2025), research has advanced substantially in understanding the role of necrophagous Diptera and Coleoptera in mediating tissue breakdown and providing crucial evidence for postmortem interval (PMI) estimation. Early colonisers, such as blowflies (Calliphoridae) and flesh flies (Sarcophagidae), exhibit predictable oviposition, feeding, and breeding behaviours influenced by temperature, humidity, and habitat type. Comparative analyses reveal broad ecological similarities between human and animal decomposition but also highlight physiological and microbial differences affecting colonisation timing, volatile organic compound (VOC) emission, and insect succession. Recent studies integrating molecular diagnostics, microbial profiling, and volatile analysis have improved accuracy in species identification and PMI estimation. Furthermore, the emerging field of entomotoxicology has demonstrated the potential of insect larvae as biological indicators of drugs and toxicants in advanced decomposition. Environmental and ecological determinants-including microclimate, seasonality, soil type, and vegetation-profoundly influence decomposition trajectories and insect behaviour, particularly in tropical regions such as India. Despite these advancements, gaps persist in methodological standardization, region-specific reference datasets, and the effects of climate change on insect distribution. Future research should focus on standardized global protocols, molecular integration, and climate-adaptive forensic models to enhance precision and reproducibility. This synthesis underscores that a comprehensive understanding of insect behaviour and colonisation ecology is fundamental to modern forensic science, bridging biological theory with practical legal application.

It is observed that there is not enough literature to support the usefulness of dental tissue in forensic medicine for the estimation of postmortem interval (PMI). Therefore, the authors of this article have systematically reviewed the available literature to understand the most used dental tissues, the methods employed to evaluate these tissues, and their reliability in PMI estimation. A MEDLINE–PubMed search engine was used to review the literature using the keywords “teeth,” “dental tissues,” “post-mortem interval,” and “forensic dentistry” from 2001 until 2020. The most used tissue was dental pulp, but other cellular- and molecular-level dental tissues such as enamel, dentin, cementum, periodontal ligament, odontoblast, and mitochondrial and nuclear DNA and RNA were also used. Based on this observation, the authors have provided the categorical classification to evaluate these dental tissues into morphological, histopathological, and molecular-level examination to understand the reliability of these dental tissues. The molecular examinations to evaluate these tissues were widely employed and emerging in the estimation of PMI as this method could provide a reliable outcome when compared with others. Since the literature reviewed was not enough to answer our questions, however, to conclude, the dental pulp is the widely used tissue so far. Further, more studies are required to authenticate the role of other dental tissues to predict the PMI at an early stage with cost-effective and most convenient techniques.

In forensic pathology, estimating the postmortem interval (PMI) is crucial for legal investigations, particularly in homicide cases. Traditional methods for determining the time since death offer only estimations, and formulas related to solute concentrations in vitreous humor vary, complicating the process. To present a novel software solution that integrates body temperature data and solute concentrations in the vitreous humor (potassium, albumin, hypoxanthine, and urea). The software combines the Henssge method with current knowledge of solute concentration evolution in the vitreous humor post-death. Formulas derived from the scientific literature were implemented in a Java-based program. The program features a intuitive interface and is compatible with Windows and MacOS. Functional and non-functional requirements were addressed, ensuring quick data input, low resource consumption, and easy interpretation of results. The software provides more precise PMI estimations by unifying the Henssge method with regression equations from existing literature. This integration enhances usability for practical applications and academic research. This study introduces a cohesive software solution that integrates traditional and modern methodologies for PMI estimation. The program's comprehensive approach and intuitive design promise to improve accuracy and facilitate broader application in forensic investigations.

Assessing the forensic implications of DNA degradation for PMI estimation using comet assay: A systematic review.

Estimation of postmortem interval (PMI) is vitally important in forensic investigations. Although many studies have examined the chemical changes of various tissues over time, no reports using spectroscopic methods in adipose tissue are available. In this study, attenuated total reflectance–Fourier transform infrared (ATR–FTIR) spectroscopy was utilized to collect comprehensive biochemical information from human adipose tissues in vitro at different times. Thereafter, mice were used as samples for in vivo experiments for more detailed studies on PMI. Then, partial least squares (PLS) model for PMI estimation was established based on the acquired spectral dataset of mouse samples. The spectral variable associated with C=O arising from lipids and free fatty acids was most susceptible to PMI. Moreover, the PLS model appeared to achieve a satisfactory prediction with a root mean square error of cross-validation of 1.78 days, and the reliability of the model was determined in an external validation set with a root mean square error of prediction of 1.87 days. The study shows the possibility of application of ATR–FTIR methods in PMI estimation using adipose tissue.

A computational approach to estimate postmortem interval using opacity development of eye for human subjects