Design of metabolomic studies: pre-analytical process
https://doi.org/10.18705/2782-3806-2024-4-2-145-155
EDN: PEIXAL
Abstract
Metabolomics is the comprehensive analysis of small molecules involved in metabolic pathways that control biochemical processes and functions of cells in the body. Metabolomic studies consist of three major steps: pre-analytical, analytical and post-analytical. The review emphasizes the importance of the pre-analytical stage, which is the journey of a biosample from the patient to the biobank and then to the analytical laboratory. Based on the literature analysis, the review presents the factors that influence the quality of the sample and therefore the quality of the final research result: clinical information collection, biosample selection, biosample collection and processing, and subsequent storage. Proper design of metabolomic studies, quality control of samples from collection to analysis by physicochemical methods provides data that can improve the quality of disease diagnosis, provide a transition to personalized medicine.
About the Authors
E. D. Kessenikh
Almazov National Medical Research Centre, World-Class Research Centre for Personalized Medicine
Russian Federation
Russian Federation
Kessenikh Elizaveta D., researcher, Laboratory of metabolomic and metabolic profiling, Research Centre of unknown, rare and genetically determined diseases
Saint Petersburg
E. A. Osintseva
Almazov National Medical Research Centre, Institute of medical education
Russian Federation
Russian Federation
Osintseva Ekaterina S., student, Medical faculty
Saint Petersburg
M. А. Migunova
Almazov National Medical Research Centre, World-Class Research Centre for Personalized Medicine
Russian Federation
Russian Federation
Migunova Margarita A., research assistant, Laboratory of metabolomic and metabolic profiling, Research Centre of unknown, rare and genetically determined diseases
Saint Petersburg
M. I. Krivosheina
Almazov National Medical Research Centre, World-Class Research Centre for Personalized Medicine
Russian Federation
Russian Federation
Krivosheina Maria I., research assistant, Laboratory of metabolomic and metabolic profiling, Research Centre of unknown, rare and genetically determined diseases
Saint Petersburg
E. A. Murashko
Almazov National Medical Research Centre, World-Class Research Centre for Personalized Medicine; Almazov National Medical Research Centre, Institute of medical education
Russian Federation
Russian Federation
Murashko Ekaterina A., Ph.D, head of laboratory, Laboratory of metabolomic and metabolic profiling, Research Centre of unknown, rare and genetically determined diseases
Akkuratova str., 2, Saint Petersburg, 97314
References
1. Marques C, Liu L, Duncan KD, et al. A Direct Infusion Probe for Rapid Metabolomics of Low-Volume Samples. Anal. Chem. 2022;94:12875–12883.
2. Rischke S, Hahnefeld L, Burla B, et al. Small molecule biomarker discovery: Proposed workflow for LC-MSbased clinical research projects. Journal of Mass Spectrometry and Advances in the Clinical Lab 2023;28:47–55.
3. Yan M, Xu G. Current and future perspectives of functional metabolomics in disease studies — A review. Analytica Chimica Acta 2018;1037:41–54.
4. Wishart DS. Metabolomics for Investigating Physiological and Pathophysiological Processes. Physiological Reviews 2019;99:1819–1875.
5. Goncharov NV, Ukolov AI, Orlova TI, et al. Metabolomika: na puti integracii biohimii, analiticheskoj himii, informatiki. Uspekhi sovremennoj biologii 2015;135:3–17. In Russian [Гончаров Н.В., Уколов А.И., Орлова Т.И. и др. Метаболомика: на пути интеграции биохимии, аналитической химии, информатики. Успехи современной биологии 2015;135:3–17].
6. Kozlova A, Shkrigunov T, Gusev S, et al. An Open-Source Pipeline for Processing Direct Infusion Mass Spectrometry Data of the Human Plasma Metabolome. Metabolites 2022;12:768.
7. Rey-Stolle F, Dudzik D, Gonzalez-Riano C, et al. Low and high resolution gas chromatography-mass spectrometry for untargeted metabolomics: A tutorial. Analytica Chimica Acta 2022;1210:339043.
8. Segers K, Declerck S, Mangelings D, et al. Analytical techniques for metabolomic studies: a review. Bioanalysis 2019;11:2297–2318.
9. Howell A, Yaros C. Downloading and Analysis of Metabolomic and Lipidomic Data from Metabolomics Workbench Using MetaboAnalyst 5.0 [Internet]. In: Bhattacharya SK, editor. Lipidomics. New York, NY: Springer US; 2023:313–321.
10. Pang Z, Zhou G, Ewald J, et al. Using MetaboAnalyst 5.0 for LC–HRMS spectra processing, multi-omics integration and covariate adjustment of global metabolomics data. Nat Protoc 2022;17:1735–1761.
11. Wishart DS, Guo A, Oler E, et al. HMDB 5.0: the Human Metabolome Database for 2022. Nucleic Acids Research 2022;50:D622–631.
12. Lippi G, Von Meyer A, Cadamuro J, et al. Blood sample quality. Diagnosis 2019;6:25–31.
13. Chen L, Zhong F, Zhu J. Bridging Targeted and Untargeted Mass Spectrometry-Based Metabolomics via Hybrid Approaches. Metabolites 2020;10:348.
14. Broadhurst DI, Kell DB. Statistical strategies for avoiding false discoveries in metabolomics and related experiments. Metabolomics 2007;2:171–196.
15. Kirwan JA, Brennan L, Broadhurst D, et al. Preanalytical Processing and Biobanking Procedures of Biological Samples for Metabolomics Research: A White Paper, Community Perspective (for “Precision Medicine and Pharmacometabolomics Task Group” — The Metabolomics Society Initiative). Clinical Chemistry 2018;64:1158–1182.
16. Bi H, Guo Z, Jia X, et al. The key points in the pre-analytical procedures of blood and urine samples in metabolomics studies. Metabolomics 2020;16:68.
17. Yin P, Lehmann R, Xu G. Effects of pre-analytical processes on blood samples used in metabolomics studies. Anal Bioanal Chem 2015;407:4879–4892.
18. González-Domínguez R, González-Domínguez Á, Sayago A, et al. Recommendations and Best Practices for Standardizing the Pre-Analytical Processing of Blood and Urine Samples in Metabolomics. Metabolites 2020;10:229.
19. Stevens VL, Hoover E, Wang Y, et al. Pre-Analytical Factors that Affect Metabolite Stability in Human Urine, Plasma, and Serum: A Review. Metabolites 2019;9:156.
20. Trifonova, Maslov, Balashova, et al. Evaluation of Dried Blood Spot Sampling for Clinical Metabolomics: Effects of Different Papers and Sample Storage Stability. Metabolites 2019;9:277.
21. Li K, Naviaux JC, Monk JM, et al. Improved Dried Blood Spot-Based Metabolomics: A Targeted, Broad-Spectrum, Single-Injection Method. Metabolites 2020;10:82.
22. Tobin NH, Murphy A, Li F, et al. Comparison of dried blood spot and plasma sampling for untargeted metabolomics. Metabolomics 2021;17:62.
23. Jain A, Morris M, Lin EZ, et al. Hemoglobin normalization outperforms other methods for standardizing dried blood spot metabolomics: A comparative study. Science of The Total Environment 2023;854:158716.
24. Ward C, Nallamshetty S, Watrous JD, et al. Nontargeted mass spectrometry of dried blood spots for interrogation of the human circulating metabolome. J Mass Spectrom 2021;56:e4772.
25. Chen D, Zhao S, Li L, et al. Controlling pre-analytical process in human serum/plasma metabolomics. TrAC Trends in Analytical Chemistry 2023;169:117364.
26. Vignoli A, Tenori L, Morsiani C, et al. Serum or Plasma (and Which Plasma), That Is the Question. J. Proteome Res. 2022;21:1061–1072.
27. Paglia G, Del Greco FM, Sigurdsson BB, et al. Influence of collection tubes during quantitative targeted metabolomics studies in human blood samples. Clinica Chimica Acta 2018;486:320–328.
28. Ercan M, Fırat Oğuz E, Akbulut ED, et al. Comparison of the effect of gel used in two different serum separator tubes for thyroid function tests. Clinical Laboratory Analysis 2018;32:e22427.
29. Bovo S, Schiavo G, Galimberti G, et al. Comparative targeted metabolomic profiles of porcine plasma and serum. animal 2023;17:101029.
30. Sotelo-Orozco J, Chen SY, Hertz-Picciotto I, et al. A Comparison of Serum and Plasma Blood Collection Tubes for the Integration of Epidemiological and Metabolomics Data. Front. Mol. Biosci. 2021;8:682134.
31. Kamlage B, Maldonado SG, Bethan B, et al. Quality Markers Addressing Preanalytical Variations of Blood and Plasma Processing Identified by Broad and Targeted Metabolite Profiling. Clinical Chemistry 2014;60:399–412.
32. Moriya T, Satomi Y, Kobayashi H. Intensive determination of storage condition effects on human plasma metabolomics. Metabolomics 2016;12:179.
33. Nishiumi S, Suzuki M, Kobayashi T, et al. Differences in metabolite profiles caused by pre-analytical blood processing procedures. Journal of Bioscience and Bioengineering 2018;125:613–618.
34. Wang Y, Carter BD, Gapstur SM, et al. Reproducibility of non-fasting plasma metabolomics measurements across processing delays. Metabolomics 2018;14:129.
35. Jain M, Kennedy AD, Elsea SH, et al. Analytes related to erythrocyte metabolism are reliable biomarkers for preanalytical error due to delayed plasma processing in metabolomics studies. Clinica Chimica Acta 2017;466:105–111.
36. Lehmann R. From bedside to bench — practical considerations to avoid pre-analytical pitfalls and assess sample quality for high-resolution metabolomics and lipidomics analyses of body fluids. Anal Bioanal Chem 2021;413:5567–5585.
37. Lesche D, Geyer R, Lienhard D, et al. Does centrifugation matter? Centrifugal force and spinning time alter the plasma metabolome. Metabolomics 2016;12:159.
38. Liu X, Hoene M, Wang X, et al. Serum or plasma, what is the difference? Investigations to facilitate the sample material selection decision making process for metabolomics studies and beyond. Analytica Chimica Acta 2018;1037:293–300.
39. Lippi G, Blanckaert N, Bonini P, et al. Haemolysis: an overview of the leading cause of unsuitable specimens in clinical laboratories. Clinical Chemistry and Laboratory Medicine 2008;46.
40. Piskunov DP, Danilova LA, Peterson AI, et al. Evaluation of methods of determination of hemolized samples at the preanalytical stage of laboratory studies in the performance of biochemical analysis of human blood. Lab. sluzh. 2018;7:111.
41. Sivakova OV, Pokrovskaya MS, Efimova IA, et al. Quality control of serum and plasma samples for scientific research. Profil. med. 2019;22:91.
42. Anisimov SV, Meshkov AN, Glotov AS, et al. National Association of Biobanks and Biobanking Specialists: New Community for Promoting Biobanking Ideas and Projects in Russia. Biopreservation and Biobanking 2021;19:73–82.
43. Haid M, Muschet C, Wahl S, et al. Long-Term Stability of Human Plasma Metabolites during Storage at −80 °C. J. Proteome Res. 2018;17:203–211.
44. Wagner-Golbs A, Neuber S, Kamlage B, et al. Effects of Long-Term Storage at −80 °C on the Human Plasma Metabolome. Metabolites 2019;9:99.
Review
For citations:
Kessenikh E.D., Osintseva E.A., Migunova M.А., Krivosheina M.I., Murashko E.A. Design of metabolomic studies: pre-analytical process. Russian Journal for Personalized Medicine. 2024;4(2):145-155. (In Russ.) https://doi.org/10.18705/2782-3806-2024-4-2-145-155. EDN: PEIXAL
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