Secco Laura, Palumbi Stefano, Padalino Pasquale, Grosso Eva, Perilli Matteo, Casonato Matteo, Cecchetto Giovanni, Viel Guido
Legal Medicine and Toxicology, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, Via G. Falloppio 50, 35121 Padova, Italy.
Legal Medicine, Department of Public Health, Experimental and Forensic Medicine, University of Pavia, 27100 Pavia, Italy.
Int J Mol Sci. 2025 Jan 25;26(3):1034. doi: 10.3390/ijms26031034.
Postmortem interval (PMI) estimation is a challenge of utmost importance in forensic daily practice. Traditional methods face limitations in accuracy and reliability, particularly for advanced decomposition stages. Recent advances in "omics" sciences, providing a holistic view of postmortem biochemical changes, offer promising avenues for overcoming these challenges. This systematic review aims at investigating the role of mass-spectrometry-based "omics" approaches in PMI estimation to elucidate molecular mechanisms underlying predictable time-dependent biochemical alterations occurring after death. A systematic search was performed, adhering to PRISMA guidelines, through "free-text" protocols in the databases PubMed, SCOPUS and Web of Science. The inclusion criteria were as follows: experimental studies analyzing, as investigated samples, animal or human corpses in toto or in parts and estimating PMI through MS-based untargeted omics approaches, with full texts in the English language. Quality assessment was performed using STROBE and ARRIVE critical appraisal checklists. A total of 1152 papers were screened and 26 included. Seventeen papers adopted a proteomic approach (65.4%), nine focused on metabolomics (34.6%) and two on lipidomics (7.7%). Most papers (57.7%) focused on short PMIs (<7 days), the remaining papers explored medium (7-120 days) (30.77%) and long PMIs (>120 days) (15.4%). Muscle tissue was the most frequently analyzed substrate (34.6% of papers), followed by liver (19.2%), bones (15.4%), cardiac blood and leaking fluids (11.5%), lung, kidney and serum (7.7%), and spleen, vitreous humor and heart (3.8%). Predictable time-dependent degradation patterns of macromolecules in different biological substrates have been discussed, with special attention to molecular insights into postmortem biochemical changes.
死后间隔时间（PMI）的估计是法医日常工作中一项极其重要的挑战。传统方法在准确性和可靠性方面存在局限性，尤其是对于晚期腐败阶段。“组学”科学的最新进展提供了死后生化变化的整体视角，为克服这些挑战提供了有希望的途径。本系统评价旨在研究基于质谱的“组学”方法在PMI估计中的作用，以阐明死后发生的可预测的时间依赖性生化改变背后的分子机制。按照PRISMA指南，通过在PubMed、SCOPUS和Web of Science数据库中的“自由文本”协议进行了系统检索。纳入标准如下：实验研究，分析的样本为动物或人类尸体整体或部分，通过基于质谱的非靶向组学方法估计PMI，且全文为英文。使用STROBE和ARRIVE批判性评价清单进行质量评估。共筛选了1152篇论文，纳入26篇。其中17篇采用蛋白质组学方法（65.4%），9篇聚焦于代谢组学（34.6%），2篇关注脂质组学（7.7%）。大多数论文（57.7%）关注短PMI（<7天），其余论文探讨了中等PMI（7 - 120天）（30.77%）和长PMI（>120天）（15.4%）。肌肉组织是最常分析的底物（占论文的34.6%），其次是肝脏（19.2%）、骨骼（15.4%）、心血和渗出液（11.5%）、肺、肾和血清（7.7%）以及脾脏、玻璃体液和心脏（3.8%）。讨论了不同生物底物中大分子可预测的时间依赖性降解模式，并特别关注了死后生化变化背后的分子见解。
