Interlaboratory analytical comparison of fatty acid concentrations in serum or plasma

Lipidomic and Fatty Acid Biomarkers in Whole Blood Can Predict the Dietary Intake of Eicosapentaenoic and Docosahexaenoic Acids in a Danish Population

BACKGROUND

The intake of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) have been associated with health benefits. Blood levels of these fatty acids, measured by gas chromatography (GC), are associated with their dietary intake, but the relationships with lipidomic measurements are not well defined.

OBJECTIVES

This study aimed to determine the lipidomic biomarkers in whole blood that predict intakes of EPA + DHA and examine the relationship between lipidomic and GC-based n-3 polyunsaturated fatty acid (n-3 PUFA) biomarkers.

METHODS

Lipidomic and fatty acid analyses were completed on 120 whole blood samples collected from Danish participants. Dietary intakes were completed using a web-based 7-d food diary. Stepwise multiple linear regression was used to identify the fatty acid and lipidomic variables that predict intakes of EPA + DHA and to determine lipidomic species that predict commonly used fatty acid biomarkers.

RESULTS

Stepwise regression selected lipidomic variables with an R2 = 0.52 for predicting EPA + DHA intake compared to R2 = 0.40 for the selected fatty acid GC-based variables. More predictive models were generated when the lipidomic variables were selected for females only (R2 = 0.62, n = 68) and males only (R2 = 0.72, n = 52). Phosphatidylethanolamine plasmalogen species containing EPA or DHA tended to be the most predictive lipidomic variables. Stepwise regression also indicated that selected lipidomic variables can predict commonly used fatty acid GC-based n-3 PUFA biomarkers as the R2 values ranged from 0.84 to 0.91.

CONCLUSIONS

Both fatty acid and lipidomic data can be used to predict EPA + DHA intakes, and fatty acid GC-based biomarkers can be emulated by lipidomic species. Lipidomic-based biomarkers appear to be influenced by sex differences, probably in n-3 PUFA and lipoprotein metabolism. These results improve our ability to understand the relationship between novel lipidomic data and GC fatty acid data and will increase our ability to apply lipidomic methods to fatty acid and lipid nutritional research.

Single-cell profiling of vascular endothelial cells reveals progressive organ-specific vulnerabilities during obesity

Obesity promotes diverse pathologies, including atherosclerosis and dementia, which frequently involve vascular defects and endothelial cell (EC) dysfunction. Each organ has distinct EC subtypes, but whether ECs are differentially affected by obesity is unknown. Here we use single-cell RNA sequencing to analyze transcriptomes of ~375,000 ECs from seven organs in male mice at progressive stages of obesity to identify organ-specific vulnerabilities. We find that obesity deregulates gene expression networks, including lipid handling, metabolic pathways and AP1 transcription factor and inflammatory signaling, in an organ- and EC-subtype-specific manner. The transcriptomic aberrations worsen with sustained obesity and are only partially mitigated by dietary intervention and weight loss. For example, dietary intervention substantially attenuates dysregulation of liver, but not kidney, EC transcriptomes. Through integration with human genome-wide association study data, we further identify a subset of vascular disease risk genes that are induced by obesity. Our work catalogs the impact of obesity on the endothelium, constitutes a useful resource and reveals leads for investigation as potential therapeutic targets.

Reference materials for MS-based untargeted metabolomics and lipidomics: a review by the metabolomics quality assurance and quality control consortium (mQACC)

INTRODUCTION

The metabolomics quality assurance and quality control consortium (mQACC) is enabling the identification, development, prioritization, and promotion of suitable reference materials (RMs) to be used in quality assurance (QA) and quality control (QC) for untargeted metabolomics research.

OBJECTIVES

This review aims to highlight current RMs, and methodologies used within untargeted metabolomics and lipidomics communities to ensure standardization of results obtained from data analysis, interpretation and cross-study, and cross-laboratory comparisons. The essence of the aims is also applicable to other 'omics areas that generate high dimensional data.

RESULTS

The potential for game-changing biochemical discoveries through mass spectrometry-based (MS) untargeted metabolomics and lipidomics are predicated on the evolution of more confident qualitative (and eventually quantitative) results from research laboratories. RMs are thus critical QC tools to be able to assure standardization, comparability, repeatability and reproducibility for untargeted data analysis, interpretation, to compare data within and across studies and across multiple laboratories. Standard operating procedures (SOPs) that promote, describe and exemplify the use of RMs will also improve QC for the metabolomics and lipidomics communities.

CONCLUSIONS

The application of RMs described in this review may significantly improve data quality to support metabolomics and lipidomics research. The continued development and deployment of new RMs, together with interlaboratory studies and educational outreach and training, will further promote sound QA practices in the community.

Total Fatty Acid Analysis of Human Blood Samples in One Minute by High-Resolution Mass Spectrometry

Total fatty acid analysis is a routine method in many areas, including lipotyping of individuals in personalized medicine, analysis of foodstuffs, and optimization of oil production in biotechnology. This analysis is commonly done by converting fatty acyl (FA) chains of intact lipids into FA methyl esters (FAMEs) and monitoring these by gas-chromatography (GC)-based methods, typically requiring at least 15 min of analysis per sample. Here, we describe a novel method that supports fast, precise and accurate absolute quantification of total FA levels in human plasma and serum samples. The method uses acid-catalyzed transesterification with ¹⁸O-enriched H₂O (i.e., H₂¹⁸O) to convert FA chains into ¹⁸O-labeled free fatty acids. The resulting “mass-tagged” FA analytes can be specifically monitored with improved signal-to-background by 1 min of high resolution Fourier transform mass spectrometry (FTMS) on an Orbitrap-based mass spectrometer. By benchmarking to National Institute of Standards and Technology (NIST) certified standard reference materials we show that the performance of our method is comparable, and at times superior, to that of gold-standard GC-based methods. In addition, we demonstrate that the method supports the accurate quantification of FA differences in samples obtained in dietary intervention studies and also affords specific monitoring of ingested stable isotope-labeled fatty acids (¹³C₁₆-palmitate) in normoinsulinemic and hyperinsulinemic human subjects. Overall, our novel high-throughput method is generic and suitable for many application areas, spanning basic research to personalized medicine, and is particularly useful for laboratories equipped with high resolution mass spectrometers, but lacking access to GC-based instrumentation.

Improving metabolome coverage and data quality: advancing metabolomics and lipidomics for biomarker discovery

This Feature Article highlights some of the key challenges within the field of metabolomics and examines what role separation and analytical sciences can play to improve the use of metabolomics in biomarker discovery and personalized medicine. Recent progress in four key areas is highlighted: (i) improving metabolite coverage, (ii) developing accurate methods for unstable metabolites including in vivo global metabolomics methods, (iii) advancing inter-laboratory studies and reference materials and (iv) improving data quality, standardization and quality control of metabolomics studies.

Standard Reference Material (SRM) 2378 fatty acids in frozen human serum. Certification of a clinical SRM based on endogenous supplementation of polyunsaturated fatty acids

Dietary fatty acids can be both beneficial and detrimental to human health depending on the degree and type of saturation. Healthcare providers and research scientists monitor the fatty acid content of human plasma and serum as an indicator of health status and diet. In addition, both the Centers for Disease Control & Prevention (CDC) and the National Institutes of Health - Office of Dietary Supplements are interested in circulating fatty acids (FAs) because they may be predictive of coronary heart disease. The National Institute of Standards and Technology (NIST) provides a wide variety of reference materials (RMs) and Standard Reference Materials® (SRM®s) including blood, serum, plasma, and urine with values assigned for analytes of clinical interest. NIST SRM 2378 Fatty Acids in Frozen Human Serum was introduced in 2015 to help validate methods used for the analysis of FAs in serum, and consists of three different pools of serum acquired from (1) healthy donors who had taken fish oil dietary supplements (at least 1000 mg per day) for at least one month (level 1 material), (2) healthy donors who had taken flaxseed oil dietary supplements (at least 1000 mg per day) for at least one month (level 2 material), and (3) healthy donors eating "normal" diets who had not taken dietary supplements containing fish or plant oils (level 3 material). The use of dietary supplements by donors provided SRMs with natural endogenous ranges of FAs at concentrations observed in human populations. Results from analyses using two methods at NIST, including one involving a novel microwave-assisted acid hydrolysis procedure, and one at the CDC are presented here. These results and their respective uncertainties were combined to yield certified values with expanded uncertainties for 12 FAs and reference values with expanded uncertainties for an additional 18 FAs.