Effect of biological sex on human circulating lipidome: An overview of the literature

Cardiovascular diseases (CVD) are the leading cause of death worldwide for both men and women, but their prevalence and burden show marked sex differences. The existing knowledge gaps in research, prevention, and treatment for women emphasize the need for understanding the biological mechanisms contributing to the sex differences in CVD. Sex differences in the plasma lipids that are well-known risk factors and predictors of CVD events have been recognized and are believed to contribute to the known disparities in CVD manifestations in men and women. However, the current understanding of sex differences in lipids has mainly come from the studies on routinely measured standard lipids- low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total triglycerides, and total cholesterol, which have been the mainstay of the lipid profiling. Sex differences in individual lipid species, collectively called the lipidome, have until recently been less explored due to the technological challenges and analytic costs. With the technological advancements in the last decade and growing interest in understanding mechanisms of sexual dimorphism in metabolic disorders, many investigators utilized metabolomics and lipidomics based platforms to examine the effect of biological sex on detailed lipidomic profiles and individual lipid species. This review presents an overview of the research on sex differences in the concentrations of circulating lipid species, focusing on findings from the metabolome- and lipidome-wide studies. We also discuss the potential contribution of genetic factors including sex chromosomes and sex-specific physiological factors such as menopause and sex hormones to the sex differences in lipidomic profiles.

Lipidomics and pancreatic cancer risk in two prospective studies

Pancreatic ductal carcinoma (PDAC) is highly fatal with limited understanding of mechanisms underlying its carcinogenesis. We comprehensively investigated whether lipidomic measures were associated with PDAC in two prospective studies. We measured 904 lipid species and 252 fatty acids across 15 lipid classes in pre-diagnostic serum (up to 24 years) in a PDAC nested-case control study within the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO, NCT00002540) with 332 matched case-control sets including 272 having serial blood samples and Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study (ATBC, NCT00342992) with 374 matched case-control sets. Controls were matched to cases by cohort, age, sex, race, and date at blood draw. We used conditional logistic regression to calculate odds ratios (OR) and 95% confidence intervals (CI) per one-standard deviation increase in log-lipid concentrations within each cohort, and combined ORs using fixed-effects meta-analyses. Forty-three lipid species were associated with PDAC (false discovery rate, FDR ≤ 0.10), including lysophosphatidylcholines (LPC, n = 2), phosphatidylethanolamines (PE, n = 17), triacylglycerols (n = 13), phosphatidylcholines (PC, n = 3), diacylglycerols (n = 4), monoacylglycerols (MAG, n = 2), cholesteryl esters (CE, n = 1), and sphingomyelins (n = 1). LPC(18:2) and PE(O-16:0/18:2) showed significant inverse associations with PDAC at the Bonferroni threshold (P value < 5.5 × 10^-5). The fatty acids LPC[18:2], LPC[16:0], PC[15:0], MAG[18:1] and CE[22:0] were significantly associated with PDAC (FDR < 0.10). Similar associations were observed in both cohorts. There was no significant association for the differences between PLCO serial lipidomic measures or heterogeneity by follow-up time overall. Results support that the pre-diagnostic serum lipidome, including 43 lipid species from 8 lipid classes and 5 fatty acids, is associated with PDAC.

Study on the formation pathways of characteristic volatiles in preserved egg yolk caused by lipid species during pickling

The formation of volatiles in high-fat foods is strongly influenced by the composition and structure of lipids. The relationship between key variable lipid species and characteristic volatiles were performed by lipidomics and flavoromics to resolve the pathways of volatiles in preserved egg yolk (PEY) during pickling. The results showed that the formation of nonanal and benzaldehyde at early stage possibly derived from oleic acid sited at Sn-1 in TG(18:1_18:2_20:4), Sn-2 in PE(22:6_18:1), and linoleic acid bonded at Sn-2 in TG(18:1_18:2_20:4), respectively. 1-octen-3-ol may be formed from linoleic acid located at Sn-2 in TG(18:1_18:2_20:4) and arachidonic acid sited at Sn-3 in TG(18:1_18:2_20:4). Indole was formed through TGs(16:0_16:1_20:1;16:1_18:1_22:1;23:0_18:1_18:1) at the later stage, and acetophenone through TGs(14:0_20:0_20:4;14:0_15:0_18:1; 16:0_16:0_22:6), PCs(24:0_18:1;O-18:1_18:2), PEs(P-18:1_20:4;P-18:1_22:6) and SPH(d18:0) during whole process of pickling. Our study provides a deep and precise insight for the formation pathways of characteristic volatiles in PEY through lipids degradation during pickling at the molecular level.

Integrating lipidomics and genomics: emerging tools to understand cardiovascular diseases

Cardiovascular diseases (CVDs) are the leading cause of mortality and morbidity worldwide leading to 31% of all global deaths. Early prediction and prevention could greatly reduce the enormous socio-economic burden posed by CVDs. Plasma lipids have been at the center stage of the prediction and prevention strategies for CVDs that have mostly relied on traditional lipids (total cholesterol, total triglycerides, HDL-C and LDL-C). The tremendous advancement in the field of lipidomics in last two decades has facilitated the research efforts to unravel the metabolic dysregulation in CVDs and their genetic determinants, enabling the understanding of pathophysiological mechanisms and identification of predictive biomarkers, beyond traditional lipids. This review presents an overview of the application of lipidomics in epidemiological and genetic studies and their contributions to the current understanding of the field. We review findings of these studies and discuss examples that demonstrates the potential of lipidomics in revealing new biology not captured by traditional lipids and lipoprotein measurements. The promising findings from these studies have raised new opportunities in the fields of personalized and predictive medicine for CVDs. The review further discusses prospects of integrating emerging genomics tools with the high-dimensional lipidome to move forward from the statistical associations towards biological understanding, therapeutic target development and risk prediction. We believe that integrating genomics with lipidome holds a great potential but further advancements in statistical and computational tools are needed to handle the high-dimensional and correlated lipidome.

Identification of lipidomic profiles associated with drug-resistant prostate cancer cells

Background

The association of circulating lipids with clinical outcomes of drug-resistant castration-resistant prostate cancer (DR-CRPC) is not fully understood. While it is known that increases in select lipids correlate to decreased survival, neither the mechanisms mediating these alterations nor the correlation of resistance to drug treatments is well characterized.

Methods

This gap-in-knowledge was addressed using in vitro models of non-cancerous, hormone-sensitive, CRPC and drug-resistant cell lines combined with quantitative LC-ESI-Orbitrap-MS (LC-ESI-MS/MS) lipidomic analysis and subsequent analysis such as Metaboanalyst and Lipid Pathway Enrichment Analysis (LIPEA).

Results

Several lipid regulatory pathways were identified that are associated with Docetaxel resistance in prostate cancer (PCa). These included those controlling glycerophospholipid metabolism, sphingolipid signaling and ferroptosis. In total, 7460 features were identified as being dysregulated between the cell lines studied, and 21 lipid species were significantly altered in drug-resistant cell lines as compared to nonresistant cell lines. Docetaxel resistance cells (PC3-Rx and DU145-DR) had higher levels of phosphatidylcholine (PC), oxidized lipid species, phosphatidylethanolamine (PE), and sphingomyelin (SM) as compared to parent control cells (PC-3 and DU-145). Alterations were also identified in the levels of phosphatidic acid (PA) and diacylglyceride (DAG), whose levels are regulated by Lipin (LPIN), a phosphatidic acid phosphatase that converts PA to DAG. Data derived from cBioPortal demonstrated a population of PCa patients expressing mutations aligning with amplification of LPIN1, LPIN2 and LPIN3 genes. Lipin amplification in these genes correlated to decreased survival in these patients. Lipin-1 mRNA expression also showed a similar trend in PCa patient data. Lipin-1, but not Lipin-2 or − 3, was detected in several prostate cancer cells, and was increased in 22RV1 and PC-3 cell lines. The increased expression of Lipin-1 in these cells correlated with the level of PA.

Conclusion

These data identify lipids whose levels may correlate to Docetaxel sensitivity and progression of PCa. The data also suggest a correlation between the expression of Lipin-1 in cells and patients with regards to prostate cancer cell aggressiveness and patient survivability. Ultimately, these data may be useful for identifying markers of lethal and/or metastatic prostate cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12944-021-01437-5.

Lipids in exosomes: Current knowledge and the way forward

Lipids are essential components of exosomal membranes, and it is well-known that specific lipids are enriched in exosomes compared to their parent cells. In this review we discuss current knowledge about the lipid composition of exosomes. We compare published data for different lipid classes in exosomes, and what is known about their lipid species, i.e. lipid molecules with different fatty acyl groups. Moreover, we elaborate on the hypothesis about hand-shaking between the very-long-chain sphingolipids in the outer leaflet and PS 18:0/18:1 in the inner leaflet, and we propose this to be an important mechanism in membrane biology, not only for exosomes. The similarity between the lipid composition of exosomes, HIV particles, and detergent resistant membranes, used as lipid rafts models, is also discussed. Furthermore, we summarize knowledge about the role of specific lipids and lipid metabolizing enzymes on the formation and release of exosomes. Finally, the use of exosomal lipids as biomarkers and how the lipid composition of exosomes may be of importance for researchers aiming to use exosomes as drug delivery vehicles is discussed. In conclusion, we have summarized what is presently known about lipids in exosomes and identified issues that should be taken into consideration in future studies.

Quantitative lipidomic analysis of plasma and plasma lipoproteins using MALDI-TOF mass spectrometry

Knowledge of the plasma lipid composition is essential to clarify the specific roles of different lipid species in various pathophysiological processes. In this study, we developed an analytical strategy combining high-performance liquid chromatography with evaporative light scattering detection (HPLC-ELSD) and off-line coupling with matrix-assisted laser desorption/ionization with time-of-flight mass spectrometry (MALDI-TOF/MS) to determine the composition of plasma and major lipoproteins at two levels, lipid classes and lipid species. We confirmed the suitability of MALDI-TOF/MS as a quantitative measurement tool studying the linearity and repeatability for triglycerides (TG), phosphatidylethanolamine (PE) and phosphatidylcholine (PC). Moreover, data obtained with this method were correlated with other lipid classes and species measurements using currently available technologies. To establish the potential utility of our approach, human plasma very low density- (VLDL), low density- (LDL) and high density- (HDL) lipoproteins from 10 healthy donors were separated using ultracentrifugation, and compositions of nine lipid classes, cholesteryl esters (CE), TG, free cholesterol (FC), PE, phosphatidylinositol (PI), sulfatides (S), PC, lysophosphatidylcholine (LPC) and sphingomyelin (SM), analyzed. In total, 157 lipid species in plasma, 182 in LDL, 171 in HDL, and 148 in VLDL were quantified. The lipidomic profile was consistent with known differences in lipid classes, but also revealed unexpected differences in lipid species distribution of lipoproteins, particularly for LPC and SM. In summary, the methodology developed in this study constitutes a valid approach to determine the lipidomic composition of plasma and lipoproteins.