Forensic bone proteomics: novel biomarkers and technologies for estimating the postmortem interval (a review)

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Abstract

Bone proteomics is a rapidly evolving field in forensic medicine aimed at determining the postmortem interval. Unlike traditional approaches, this method enables quantitative and molecular-level analysis of protein composition changes in bone tissue. Highly degradation-resistant proteins are considered reliable biomarkers for estimating the postmortem interval, providing more accurate and objective results. Mass spectrometry, in combination with modern bioinformatics tools and machine learning technologies, allows for a detailed investigation of postmortem protein degradation processes and the identification of time-dependent molecular patterns. However, environmental factors such as humidity, temperature, soil composition, and microbial activity significantly affect protein preservation in bone tissue, underscoring the need for standardized analytical protocols.

This review summarizes key methods of bone proteomic analysis, prospects for its integration with metabolomics and lipidomics, and the potential of machine learning in postmortem interval estimation. Further research in this field should aim at validating biomarkers, standardizing techniques, and integrating these methods into forensic practice.

The development of forensic bone proteomics opens new possibilities, offering more precise data in complex medico-legal cases.

About the authors

Gulgena R. Mustafina

Bashkir State Medical University

Email: gulgenarm@mail.ru
ORCID iD: 0000-0003-2534-6385
SPIN-code: 8904-2046

MD, Cand. Sci. (Medicine), Assistant Professor

Russian Federation, Ufa

Airat A. Khalikov

Bashkir State Medical University

Email: airat.expert@mail.ru
ORCID iD: 0000-0003-1045-5677
SPIN-code: 1895-7300

MD, Dr. Sci. (Medicine), Professor

Russian Federation, Ufa

Kirill O. Kuznetsov

Ufa University of Science and Technology; Bureau of Forensic Medical Examination

Author for correspondence.
Email: kuznetsovarticles@mail.ru
ORCID iD: 0000-0002-2405-1801
SPIN-code: 3053-3773

MD

Russian Federation, Ufa; Ufa

Elmira M. Nazarova

Bashkir State Medical University

Email: egevan@list.ru
ORCID iD: 0000-0002-1160-7241
SPIN-code: 6340-5202

MD, Cand. Sci. (Medicine), Assistant Professor

Russian Federation, Ufa

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