Phenotypic changes in low-density lipoprotein particles as markers of adverse clinical outcomes in COVID-19

BACKGROUND AND AIMS

Low-density lipoprotein (LDL) plasma concentration decline is a biomarker for acute inflammatory diseases, including coronavirus disease-2019 (COVID-19). Phenotypic changes in LDL during COVID-19 may be equally related to adverse clinical outcomes.

METHODS

Individuals hospitalized due to COVID-19 (n = 40) were enrolled. Blood samples were collected on days 0, 2, 4, 6, and 30 (D0, D2, D4, D6, and D30). Oxidized LDL (ox-LDL), and lipoprotein-associated phospholipase A2 (Lp-PLA2) activity were measured. In a consecutive series of cases (n = 13), LDL was isolated by gradient ultracentrifugation from D0 and D6 and was quantified by lipidomic analysis. Association between clinical outcomes and LDL phenotypic changes was investigated.

RESULTS

In the first 30 days, 42.5% of participants died due to Covid-19. The serum ox-LDL increased from D0 to D6 (p < 0.005) and decreased at D30. Moreover, individuals who had an ox-LDL increase from D0 to D6 to over the 90th percentile died. The plasma Lp-PLA2 activity also increased progressively from D0 to D30 (p < 0.005), and the change from D0 to D6 in Lp-PLA2 and ox-LDL were positively correlated (r = 0.65, p < 0.0001). An exploratory untargeted lipidomic analysis uncovered 308 individual lipids in isolated LDL particles. Paired-test analysis from D0 and D6 revealed higher concentrations of 32 lipid species during disease progression, mainly represented by lysophosphatidyl choline and phosphatidylinositol. In addition, 69 lipid species were exclusively modulated in the LDL particles from non-survivors as compared to survivors.

CONCLUSIONS

Phenotypic changes in LDL particles are associated with disease progression and adverse clinical outcomes in COVID-19 patients and could serve as a potential prognostic biomarker.

Brain region-specific lipid alterations in the PLB4 hBACE1 knock-in mouse model of Alzheimer's disease

BACKGROUND

Lipid dysregulation is associated with several key characteristics of Alzheimer's disease (AD), including amyloid-β and tau neuropathology, neurodegeneration, glucose hypometabolism, as well as synaptic and mitochondrial dysfunction. The β-site amyloid precursor protein cleavage enzyme 1 (BACE1) is associated with increased amyloidogenesis, and has been affiliated with diabetes via its role in metabolic regulation.

METHODS

The research presented herein investigates the role of hBACE1 in lipid metabolism and whether specific brain regions show increased vulnerability to lipid dysregulation. By utilising advanced mass spectrometry techniques, a comprehensive, quantitative lipidomics analysis was performed to investigate the phospholipid, sterol, and fatty acid profiles of the brain from the well-known PLB4 hBACE1 knock-in mouse model of AD, which also shows a diabetic phenotype, to provide insight into regional alterations in lipid metabolism.

RESULTS

Results show extensive region - specific lipid alterations in the PLB4 brain compared to the wild-type, with decreases in the phosphatidylethanolamine content of the cortex and triacylglycerol content of the hippocampus and hypothalamus, but increases in the phosphatidylcholine, phosphatidylinositol, and diacylglycerol content of the hippocampus. Several sterol and fatty acids were also specifically decreased in the PLB4 hippocampus.

CONCLUSION

Collectively, the lipid alterations observed in the PLB4 hBACE1 knock-in AD mouse model highlights the regional vulnerability of the brain, in particular the hippocampus and hypothalamus, to lipid dysregulation, hence supports the premise that metabolic abnormalities have a central role in both AD and diabetes.

Lipidomic profiling of dairy cattle oocytes by high performance liquid chromatography-high resolution tandem mass spectrometry for developmental competence markers

A comparative lipidomic profiling analysis of dairy cattle oocytes with different developmental competences was performed using a combination of high performance liquid chromatography-high resolution tandem mass spectrometry and multivariate statistical analysis. Significant lipidomic changes were identified in degenerating oocytes. Total triacylglycerol in the degenerating oocytes was 1.8-fold higher than that in the normal oocytes; however, total cardiolipin was 53.5% lesser than that in the normal oocytes, which indicated attenuation of energy metabolism. Compared to those in the normal oocytes, triacylglycerols in the degenerating oocytes were composed of longer and more unsaturated acyl chains. In contrast, the acyl chains in free fatty acids present in the degenerating oocytes were shorter and with lesser degree of unsaturation compared to those in the normal oocytes. Moreover, a significant decrease in degenerating oocytes were found in total phosphatidylinositol (14.8 ± 7.6 pmol vs. 24.8 ± 5.5 pmol), total phosphatidylcholine (20.8 ± 8.7 pmol vs. 33.5 ± 7.2 pmol), and total plasmalogen ethanolamine (9.0 ± 4.7 pmol vs. 16.8 ± 5.2 pmol), which indicated dysfunction of lipid-metabolizing enzymes in oocytes during degeneration. Thus, increase of triacylglycerols together with the decrease of certain phospholipid species could be potential markers of oocyte developmental competence. In addition to providing a new approach to investigate the lipidomic changes in oocyte development, the lipidomic profiling in the present study has revealed insights that hold potential to unravel the role of lipid metabolism in oocyte developmental competence in cattle.

Quantitative lipidomics reveals alterations in donkey milk lipids according to lactation

The composition of donkey milk is similar to that of human milk. However, the lipid content in donkey milk is lower than that in human milk. Thus far, the lipid composition of donkey milk during lactation has not been well-studied. Through mass spectroscopy-based quantitative lipidomics, we analyzed lipids in donkey colostrum (DC) and mature milk (DM). Thirteen subclasses of 335 lipids were identified in both DC and DM; 60 lipids - 17 upregulated and 43 downregulated - were differentially regulated between DM and DC (Variable Importance in Projection >1, P < 0.05), demonstrating that lipid composition changed with lactation. These different lipids were involved in 19 metabolic pathways, of which glycerophospholipid, linoleic acid, alpha-linolenic acid, glycosylphosphatidylinositol-anchor, glycerolipid, and arachidonic acid metabolism were the most relevant. Our results provide insights into quantitative alterations in donkey milk lipids during lactation, development of donkey milk products, and screening of potential biomarkers.

Lipidomics by ultrahigh performance liquid chromatography-high resolution mass spectrometry and its application to complex biological samples

An improved approach for selective and sensitive identification and quantitation of lipid molecular species using reversed phase chromatography coupled to high resolution mass spectrometry was developed. The method is applicable to a wide variety of biological matrices using a simple liquid-liquid extraction procedure. Together, this approach combines multiple selectivity criteria: Reversed phase chromatography separates lipids according to their acyl chain length and degree of unsaturation and is capable of resolving positional isomers of lysophospholipids, as well as structural isomers of diacyl phospholipids and glycerolipids. Orbitrap mass spectrometry delivers the elemental composition of both positive and negative ions with high mass accuracy. Finally, automatically generated tandem mass spectra provide structural insight into numerous glycerolipids, phospholipids, and sphingolipids within a single run. Calibration showed linearity ranges of more than four orders of magnitude, good values for accuracy and precision at biologically relevant concentration levels, and limits of quantitation of a few femtomoles on column. Hundreds of lipid molecular species were detected and quantified in three different biological matrices, which cover well the wide variety and complexity of various model organisms in lipidomic research. Together with a software package, this method is a prime choice for global lipidomic analysis of even the most complex biological samples.