Literature DB >> 32613532

Post-mortem changes in metabolomic profiles of human serum, aqueous humor and vitreous humor.

Ekaterina A Zelentsova1,2, Lyudmila V Yanshole1, Arsenty D Melnikov1, Ivan S Kudryavtsev3, Vladimir P Novoselov3, Yuri P Tsentalovich4.   

Abstract

INTRODUCTION: 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.
OBJECTIVES: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: 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.

Entities:  

Keywords:  Aqueous humor; NMR spectroscopy; PMI estimation; Quantitative metabolomics; Serum; Vitreous humor

Mesh:

Year:  2020        PMID: 32613532     DOI: 10.1007/s11306-020-01700-3

Source DB:  PubMed          Journal:  Metabolomics        ISSN: 1573-3882            Impact factor:   4.290


  6 in total

1.  A novel method for determining postmortem interval based on the metabolomics of multiple organs combined with ensemble learning techniques.

Authors:  Xiao-Jun Lu; Jian Li; Xue Wei; Na Li; Li-Hong Dang; Guo-Shuai An; Qiu-Xiang Du; Qian-Qian Jin; Jie Cao; Ying-Yuan Wang; Jun-Hong Sun
Journal:  Int J Legal Med       Date:  2022-06-03       Impact factor: 2.686

2.  A preliminary study on early postmortem submersion interval (PMSI) estimation and cause-of-death discrimination based on nontargeted metabolomics and machine learning algorithms.

Authors:  Fu-Yuan Zhang; Lin-Lin Wang; Wen-Wen Dong; Miao Zhang; Dilichati Tash; Xin-Jie Li; Shu-Kui Du; Hao-Miao Yuan; Rui Zhao; Da-Wei Guan
Journal:  Int J Legal Med       Date:  2022-01-31       Impact factor: 2.686

3.  IPMICALC: an Integrated Post-mortem Interval Calculator.

Authors:  Manuel Febrero Bande; Lucía Ordóñez Mayán; Cristina Cordeiro; Duarte Nuno Vieira; José Ignacio Muñoz Barús
Journal:  Forensic Sci Med Pathol       Date:  2022-10-06       Impact factor: 2.456

4.  Metabolomic Analysis Reveals That the Moor Frog Rana arvalis Uses Both Glucose and Glycerol as Cryoprotectants.

Authors:  Sergei V Shekhovtsov; Nina A Bulakhova; Yuri P Tsentalovich; Ekaterina A Zelentsova; Ekaterina N Meshcheryakova; Tatiana V Poluboyarova; Daniil I Berman
Journal:  Animals (Basel)       Date:  2022-05-17       Impact factor: 3.231

5.  Application of Innovative TGA/Chemometric Approach for Forensic Purposes: The Estimation of the Time since Death in Contaminated Specimens.

Authors:  Roberta Risoluti; Giuseppina Gullifa; Vittorio Fineschi; Paola Frati; Stefano Materazzi
Journal:  Diagnostics (Basel)       Date:  2021-01-14

6.  Comparative use of aqueous humour 1H NMR metabolomics and potassium concentration for PMI estimation in an animal model.

Authors:  Emanuela Locci; Matteo Stocchero; Rossella Gottardo; Fabio De-Giorgio; Roberto Demontis; Matteo Nioi; Alberto Chighine; Franco Tagliaro; Ernesto d'Aloja
Journal:  Int J Legal Med       Date:  2020-11-20       Impact factor: 2.686

  6 in total

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