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Lipidomics and Transcriptomics in Neurological Diseases

Lipidomics and Transcriptomics in Neurological Diseases

Published on: March 18, 2022

Recommendations for good practice in MS-based lipidomics.

Harald C Köfeler¹, Robert Ahrends², Erin S Baker³

¹Core Facility Mass Spectrometry, Medical University of Graz, Graz, Austria.

Journal of Lipid Research

|October 18, 2021

Summary

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This summary is machine-generated.

Lipidomics, a rapidly growing biomedical field, requires quality standards. This review outlines best practices for lipidomic workflows, from sample prep to data analysis, to ensure high data quality for researchers.

Area of Science:

Biomedical Research
Analytical Chemistry

Background:

Lipidomics has rapidly expanded over the past two decades.
Increasing numbers of research groups necessitate standardized data quality guidelines.
The Lipidomics Standards Initiative aims to coordinate best practice guidelines within the International Lipidomics Society.

Purpose of the Study:

To highlight quality-relevant aspects of the lipidomics workflow.
To provide examples of best practices in lipidomics.
To discuss strengths, drawbacks, and pitfalls in lipidomic analysis.

Main Methods:

Review of preanalytics, sample preparation, and mass spectrometry (MS) in lipidomics.
Focus on lipid species identification and quantitation.
Compilation of state-of-the-art practices and relevant literature.

Keywords:

LC-MS MS chromatography ion mobility spectrometry lipid identification lipidomics metabolomics phospholipids sphingolipids

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Main Results:

Identification of key quality-relevant aspects across the lipidomics workflow.
Examples of best practices for improving data quality.
Analysis of challenges and potential pitfalls in lipidomic studies.

Conclusions:

Establishing and adhering to best practices is crucial for high-quality lipidomics data.
This review serves as a guide to state-of-the-art lipidomics methodologies.
Further resources are provided for a comprehensive understanding of lipidomics practices.