High-Throughput Plasma Lipidomics: Detailed Mapping of the Associations with Cardiometabolic Risk Factors

Huynh, Kevin; Barlow, Christopher K.; Jayawardana, Kaushala S.; Weir, Jacquelyn M.; Mellett, Natalie A.; Cinel, Michelle; Magliano, Dianna J.; Shaw, Jonathan E.; Drew, Brian G.; Meikle, Peter J.

doi:10.1016/j.chembiol.2018.10.008

Cited by 261 publications

(331 citation statements)

References 51 publications

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“…However, the relative concentrations determined in the current study were consistent with those reported by Huynh et al (Supplemental Figure 12), and the commonalities reported among these studies independently validated some of our major findings. Neither of the recent studies evaluated longitudinal diabetes incidence data; however, Huynh et al (36) demonstrated a significant correlation between 1 of our putative prognostic markers, SM d18:1/18:0, and fasting glucose. (SM d16:1/18:0 was not evaluated.)…”

Section: L I N I C a L M E D I C I N Ementioning

confidence: 61%

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Large-scale lipidomics identifies associations between plasma sphingolipids and T2DM incidence

Chew¹,

Torta²,

Ji³

et al. 2019

JCI Insight

110

109

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BACKGROUND. Sphingolipids (SPs) are ubiquitous, structurally diverse molecules that include ceramides, sphingomyelins (SMs), and sphingosines. They are involved in various pathologies, including obesity and type 2 diabetes mellitus (T2DM). Therefore, it is likely that perturbations in plasma concentrations of SPs are associated with disease. Identifying these associations may reveal useful biomarkers or provide insight into disease processes. METHODS. We performed a lipidomics evaluation of molecularly distinct SPs in the plasma of 2302 ethnically Chinese Singaporeans using electrospray ionization mass spectrometry coupled with liquid chromatography. SP profiles were compared to clinical and biochemical characteristics, and subjects were evaluated with follow-up visits for 11 years. RESULTS. We found that ceramides correlated positively but hexosylceramides correlated negatively with BMI and homeostatic model assessment of insulin resistance (HOMA-IR). Furthermore, SPs with a d16:1 sphingoid backbone correlated more positively with BMI and HOMA-IR, while d18:2 SPs correlated less positively, relative to canonical d18:1 SPs. We also found that higher concentrations of 2 distinct SMs were associated with a higher risk of T2DM (HR 1.45 with 95% CI 1.18-1.78 for SM d16:1/18:0 and HR 1.40 with 95% CI 1.17-1.68 for SM d18:1/18:0). CONCLUSIONS. We identified significant associations between SPs and obesity/T2DM characteristics, specifically, those of hexosylceramides, d16:1 SPs, and d18:2 SPs. This suggests that the balance of SP metabolism, rather than ceramide accumulation, is associated with the pathology of obesity. We further identified 2 specific SPs that may represent prognostic biomarkers for T2DM.

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Section: L I N I C a L M E D I C I N Ementioning

confidence: 61%

“…Interestingly, while this manuscript was in preparation, 2 additional population-based lipidomics analyses evaluated plasma SPs in the context of obesity and diabetes (36,37). Relative to the study presented here, the Huynh et al study (36) . Linear regression analysis between SPs and BMI and HOMA-IR.…”

Section: L I N I C a L M E D I C I N Ementioning

confidence: 94%

Large-scale lipidomics identifies associations between plasma sphingolipids and T2DM incidence

Chew¹,

Torta²,

Ji³

et al. 2019

JCI Insight

110

109

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“…Targeted lipidomic profiling was performed in positive-ion mode using electrospray ionization-tandem mass spectrometry to quantify the major fatty acids of 596 lipid species from 33 lipid classes, from blood serum. Positive-ion mode only was selected to minimise the time required for analysis of each sample, while still providing good coverage of the lipidome (25). Profiling was performed at the Metabolomics Laboratory, Baker Heart and Diabetes Institute, Melbourne, Victoria.…”

Section: Serum Lipidomic Profilingmentioning

confidence: 99%

“…Profiling was performed at the Metabolomics Laboratory, Baker Heart and Diabetes Institute, Melbourne, Victoria. Serum lipids were isolated using a single phase butanol:methanol (BuOH:MeOH) extraction (26) and quantified by liquid chromatographytandem mass spectrometry as previously described (25). Briefly, serum samples (10 µL) were placed into a randomised order, with blank and pooled quality control samples placed every 20 and 10 serum samples, respectively.…”

Section: Serum Lipidomic Profilingmentioning

confidence: 99%

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Heritability of 596 lipid species and genetic correlation with cardiovascular traits in the Busselton Family Heart Study

Cadby

Melton

McCarthy

et al. 2020

Journal of Lipid Research

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CVD is the leading cause of death worldwide, and genetic investigations into the human lipidome may provide insight into CVD risk. The aim of this study was to estimate the heritability of circulating lipid species and their genetic correlation with CVD traits. Targeted lipidomic profiling was performed on 4,492 participants from the Busselton Family Heart Study to quantify the major fatty acids of 596 lipid species from 33 classes. We estimated narrow-sense heritabilities of lipid species/classes and their genetic correlations with eight CVD traits: BMI, HDL-C, LDL-C, triglycerides, total cholesterol, waist-hip ratio, systolic blood pressure, and diastolic blood pressure. We report heritabilities and genetic correlations of new lipid species/subclasses, including acylcarnitine (AC), ubiquinone, sulfatide, and oxidized cholesteryl esters. Over 99% of lipid species were significantly heritable (h2: 0.06–0.50) and all lipid classes were significantly heritable (h2: 0.14–0.50). The monohexosylceramide and AC classes had the highest median heritabilities (h2 = 0.43). The largest genetic correlation was between clinical triglycerides and total diacylglycerol (rg = 0.88). We observed novel positive genetic correlations between clinical triglycerides and phosphatidylglycerol species (rg: 0.64–0.82), and HDL-C and alkenylphosphatidylcholine species (rg: 0.45–0.74). Overall, 51% of the 4,768 lipid species-CVD trait genetic correlations were statistically significant after correction for multiple comparisons. This is the largest lipidomic study to address the heritability of lipids and their genetic correlation with CVD traits. Future work includes identifying putative causal genetic variants for lipid species and CVD using genome-wide SNP and whole-genome sequencing data.

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Comprehensive Lipid Profiling by Multisegment Injection–Nonaqueous Capillary Electrophoresis–Mass Spectrometry: Expanding Coverage Beyond Hydrophilic Metabolites

Ly¹,

Shanmuganathan²,

Britz‐McKibbin³

2022

Capillary Electrophoresis‐Mass Spectrometry for Proteomics and Metabolomics

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High-Throughput Plasma Lipidomics: Detailed Mapping of the Associations with Cardiometabolic Risk Factors

Cited by 261 publications

References 51 publications

Large-scale lipidomics identifies associations between plasma sphingolipids and T2DM incidence

Large-scale lipidomics identifies associations between plasma sphingolipids and T2DM incidence

Heritability of 596 lipid species and genetic correlation with cardiovascular traits in the Busselton Family Heart Study

Comprehensive Lipid Profiling by Multisegment Injection–Nonaqueous Capillary Electrophoresis–Mass Spectrometry: Expanding Coverage Beyond Hydrophilic Metabolites

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