Recent Analytical Methodologies in Lipid Analysis.
Ivana GerhardtovaTimotej JankechPetra MajerovaJuraj PiešťanskýDominika OlesovaAndrej KováčJosef JampilekPublished in: International journal of molecular sciences (2024)
Lipids represent a large group of biomolecules that are responsible for various functions in organisms. Diseases such as diabetes, chronic inflammation, neurological disorders, or neurodegenerative and cardiovascular diseases can be caused by lipid imbalance. Due to the different stereochemical properties and composition of fatty acyl groups of molecules in most lipid classes, quantification of lipids and development of lipidomic analytical techniques are problematic. Identification of different lipid species from complex matrices is difficult, and therefore individual analytical steps, which include extraction, separation, and detection of lipids, must be chosen properly. This review critically documents recent strategies for lipid analysis from sample pretreatment to instrumental analysis and data interpretation published in the last five years (2019 to 2023). The advantages and disadvantages of various extraction methods are covered. The instrumental analysis step comprises methods for lipid identification and quantification. Mass spectrometry (MS) is the most used technique in lipid analysis, which can be performed by direct infusion MS approach or in combination with suitable separation techniques such as liquid chromatography or gas chromatography. Special attention is also given to the correct evaluation and interpretation of the data obtained from the lipid analyses. Only accurate, precise, robust and reliable analytical strategies are able to bring complex and useful lipidomic information, which may contribute to clarification of some diseases at the molecular level, and may be used as putative biomarkers and/or therapeutic targets.
Keyphrases
- mass spectrometry
- liquid chromatography
- fatty acid
- gas chromatography
- cardiovascular disease
- tandem mass spectrometry
- type diabetes
- healthcare
- multiple sclerosis
- systematic review
- low dose
- adipose tissue
- high resolution
- machine learning
- simultaneous determination
- glycemic control
- subarachnoid hemorrhage
- quantum dots
- gram negative
- cerebral ischemia