Clinical lipidomics – A community-driven roadmap to translate research into clinical applications

Vvedenskaya, Olga; Holčapek, Michal; Vogeser, Michael; Ekroos, Kim; Meikle, Peter J.; Bendt, Anne K.

doi:10.1016/j.jmsacl.2022.02.002

Cited by 19 publications

(12 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The translation of lipid profiling to clinical laboratories is still hindered by the lack of the necessary amount of cross-comparable quantitative lipid data acquired on different populations worldwide. , However, the fundamental efforts to establish analytical consensus values in reference materials (e.g., NIST SRM 1950 plasma) and investigate strategies for data harmonization have already been made by the lipidomics community (). ,− The systematic analysis of shared reference materials has emerged as the best normalization strategy to correct method-specific biases (e.g., application of different extraction procedures and analytical platforms for lipid measurement). − Thus, the time is right to foresee the collection of biologically relevant data necessary to establish the reference intervals for populations with different ethnic backgrounds and dietary regimens across different geographical regions.…”

Section: Introductionmentioning

confidence: 99%

Omic-Scale High-Throughput Quantitative LC–MS/MS Approach for Circulatory Lipid Phenotyping in Clinical Research

et al. 2023

View full text Add to dashboard Cite

Lipid analysis at the molecular species level represents a valuable opportunity for clinical applications due to the essential roles that lipids play in metabolic health. However, a comprehensive and high-throughput lipid profiling remains challenging given the lipid structural complexity and exceptional diversity. Herein, we present an ‘omic-scale targeted LC–MS/MS approach for the straightforward and high-throughput quantification of a broad panel of complex lipid species across 26 lipid (sub)classes. The workflow involves an automated single-step extraction with 2-propanol, followed by lipid analysis using hydrophilic interaction liquid chromatography in a dual-column setup coupled to tandem mass spectrometry with data acquisition in the timed-selective reaction monitoring mode (12 min total run time). The analysis pipeline consists of an initial screen of 1903 lipid species, followed by high-throughput quantification of robustly detected species. Lipid quantification is achieved by a single-point calibration with 75 isotopically labeled standards representative of different lipid classes, covering lipid species with diverse acyl/alkyl chain lengths and unsaturation degrees. When applied to human plasma, 795 lipid species were measured with median intra- and inter-day precisions of 8.5 and 10.9%, respectively, evaluated within a single and across multiple batches. The concentration ranges measured in NIST plasma were in accordance with the consensus intervals determined in previous ring-trials. Finally, to benchmark our workflow, we characterized NIST plasma materials with different clinical and ethnic backgrounds and analyzed a sub-set of sera (n = 81) from a clinically healthy elderly population. Our quantitative lipidomic platform allowed for a clear distinction between different NIST materials and revealed the sex-specificity of the serum lipidome, highlighting numerous statistically significant sex differences.

show abstract

Section: Introductionmentioning

confidence: 99%

Omic-Scale High-Throughput Quantitative LC–MS/MS Approach for Circulatory Lipid Phenotyping in Clinical Research

et al. 2023

View full text Add to dashboard Cite

show abstract

“…The aim of clinical routine should be to expand from single lipid analysis to multianalyte lipid panels or lipidomic analysis in order to aim for more specific readouts concerning lipid-associated pathophysiologies with a potential application in personalized and “precision medicine”. In order to achieve these aims, interdisciplinary collaborations including routine clinics should be initialized in order to obtain workflows for clinical adaptation [ 71 ]. The NIH Common Fund Undiagnosed Disease Network (UDN) started an initiative to perform metabolomics and lipidomics analysis of 148 patients and family members in biofluids (urine, CSF, blood plasma) and make the raw and processed data available to the research community.…”

Section: Lipid*omic*s In Rare Diseasesmentioning

confidence: 99%

Lipidomics—Paving the Road towards Better Insight and Precision Medicine in Rare Metabolic Diseases

Zandl-Lang

Plecko

Köfeler

2023

IJMS

View full text Add to dashboard Cite

Even though the application of Next-Generation Sequencing (NGS) has significantly facilitated the identification of disease-associated mutations, the diagnostic rate of rare diseases is still below 50%. This causes a diagnostic odyssey and prevents specific treatment, as well as genetic counseling for further family planning. Increasing the diagnostic rate and reducing the time to diagnosis in children with unclear disease are crucial for a better patient outcome and improvement of quality of life. In many cases, NGS reveals variants of unknown significance (VUS) that need further investigations. The delineation of novel (lipid) biomarkers is not only crucial to prove the pathogenicity of VUS, but provides surrogate parameters for the monitoring of disease progression and therapeutic interventions. Lipids are essential organic compounds in living organisms, serving as building blocks for cellular membranes, energy storage and signaling molecules. Among other disorders, an imbalance in lipid homeostasis can lead to chronic inflammation, vascular dysfunction and neurodegenerative diseases. Therefore, analyzing lipids in biological samples provides great insight into the underlying functional role of lipids in healthy and disease statuses. The method of choice for lipid analysis and/or huge assemblies of lipids (=lipidome) is mass spectrometry due to its high sensitivity and specificity. Due to the inherent chemical complexity of the lipidome and the consequent challenges associated with analyzing it, progress in the field of lipidomics has lagged behind other omics disciplines. However, compared to the previous decade, the output of publications on lipidomics has increased more than 17-fold within the last decade and has, therefore, become one of the fastest-growing research fields. Combining multiple omics approaches will provide a unique and efficient tool for determining pathogenicity of VUS at the functional level, and thereby identifying rare, as well as novel, genetic disorders by molecular techniques and biochemical analyses.

show abstract

“…In turn, this has facilitated the measurement of a greater spectrum of lipids within a single acquisition, while maintaining enhanced sensitivity of QQQ-MS compared to HRAM-MS. 6,28,29 This paradigm shift in mass spectrometry based lipidomics presents opportunities to readily and rapidly screen many lipid targets, with direct applicability to large-scale clinical and molecular epidemiology research as well as having tangible translational impact. 11,30 However, within such large-scale studies remain inherent challenges. For example, variation introduced through multicenter or longitudinal sample collections, or the use of historical biobanked samples collected without prior consideration for lipidomic specific workflows.…”

Section: ■ Introductionmentioning

confidence: 99%

Comprehensive Lipidomic Workflow for Multicohort Population Phenotyping Using Stable Isotope Dilution Targeted Liquid Chromatography-Mass Spectrometry

et al. 2023

View full text Add to dashboard Cite

Dysregulated lipid metabolism underpins many chronic diseases including cardiometabolic diseases. Mass spectrometry-based lipidomics is an important tool for understanding mechanisms of lipid dysfunction and is widely applied in epidemiology and clinical studies. With ever-increasing sample numbers, single batch acquisition is often unfeasible, requiring advanced methods that are accurate and robust to batch-to-batch and interday analytical variation. Herein, an optimized comprehensive targeted workflow for plasma and serum lipid quantification is presented, combining stable isotope internal standard dilution, automated sample preparation, and ultrahigh performance liquid chromatography-tandem mass spectrometry with rapid polarity switching to target 1163 lipid species spanning 20 subclasses. The resultant method is robust to common sources of analytical variation including blood collection tubes, hemolysis, freeze–thaw cycles, storage stability, analyte extraction technique, interinstrument variation, and batch-to-batch variation with 820 lipids reporting a relative standard deviation of <30% in 1048 replicate quality control plasma samples acquired across 16 independent batches (total injection count = 6142). However, sample hemolysis of ≥0.4% impacted lipid concentrations, specifically for phosphatidylethanolamines (PEs). Low interinstrument variability across two identical LC-MS systems indicated feasibility for intra/inter-lab parallelization of the assay. In summary, we have optimized a comprehensive lipidomic protocol to support rigorous analysis for large-scale, multibatch applications in precision medicine. The mass spectrometry lipidomics data have been deposited to massIVE: data set identifiers MSV000090952 and 10.25345/C5NP1WQ4S.

show abstract

Clinical lipidomics – A community-driven roadmap to translate research into clinical applications

Cited by 19 publications

References 22 publications

Omic-Scale High-Throughput Quantitative LC–MS/MS Approach for Circulatory Lipid Phenotyping in Clinical Research

Omic-Scale High-Throughput Quantitative LC–MS/MS Approach for Circulatory Lipid Phenotyping in Clinical Research

Lipidomics—Paving the Road towards Better Insight and Precision Medicine in Rare Metabolic Diseases

Comprehensive Lipidomic Workflow for Multicohort Population Phenotyping Using Stable Isotope Dilution Targeted Liquid Chromatography-Mass Spectrometry

Contact Info

Product

Resources

About