A comprehensive assessment of carbon monoxide caused mortality via bioinformatics assisted untargeted metabolomics analysis


Kesmen E., Asliyüksek H., Özli S., Köse E., ŞENOL O.

Forensic Science, Medicine, and Pathology, 2026 (SCI-Expanded, Scopus) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Basım Tarihi: 2026
  • Doi Numarası: 10.1007/s12024-026-01226-5
  • Dergi Adı: Forensic Science, Medicine, and Pathology
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, MEDLINE
  • Anahtar Kelimeler: Bioinformatics, Carbon Monoxide Exposure, Forensic Cases, Metabolomics, Q-TOF MS/MS
  • Atatürk Üniversitesi Adresli: Evet

Özet

Purpose: Carbon monoxide exposure can alter essential biological functions and may lead to fatality. Metabolomics is a crucial method for identifying metabolites inside these systems. The objective of the study is to differentiate fatalities resulting from carbon monoxide exposure from other causes of death in forensic cases and to offer preliminary insights into metabolic alterations associated with CO exposure, which may guide future studies on related pathological mechanisms. Methods: 39 plasma samples were meticulously collected and extracted for an untargeted metabolomics experiment. A liquid–liquid extraction was conducted to maximize the recovery of metabolites from the samples. Then extracts were placed into vials and analyzed using a Time of Flight Mass Spectrometry. Results: Metabolites that were significantly changed were found by fold analysis and Welch’s test between the groups. 33 distinct chemicals were annotated in relation to the Data Dependent Acquisition Method. Pathway analyses were conducted to elucidate the detrimental effects of carbon monoxide exposure on the human body. Conclusion: It has been reported that CO exposure may affect many metabolic processes related to bile acid biosynthesis, sphingolipids and energy metabolism. An alternative bioinformatic model was also created and validated to predict CO exposure in forensic cases. This created model successfully passes the ROC curve analysis and permutation test, accurately classifying controls and CO-exposed individuals by assessing the metabolic variations between the groups.