Dataset Information

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

ABSTRACT:

Background

Sphingolipids (SPs) are ubiquitous, structurally diverse molecules that include ceramides, sphingomyelins, 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 2,302 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 by follow-up visits for 11 years.

Results

We found that ceramides correlate positively but hexosylceramides correlate negatively with body mass index (BMI) and homeostatic model assessment of insulin resistance (HOMA-IR). Furthermore, SPs with a d16:1 sphingoid backbone correlate more positively with BMI and HOMA-IR, while d18:2 SPs correlate less positively, relative to canonical d18:1 SPs. We also found that higher concentrations of two distinct sphingomyelins were associated with a higher risk of T2DM (HR 1.45, 95% CI 1.18-1.78 for SM d16:1/C18:0; and HR 1.40, 95% CI 1.17-1.68 for SM d18:1/C18:0).

Conclusion

We identified significant associations between SPs and obesity/T2DM characteristics, specifically, that 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 two specific SPs that may represent prognostic biomarkers for T2DM.

Funding

Funding sources are listed in the Acknowledgements section.

SUBMITTER: Chew WS

PROVIDER: S-EPMC6629294 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Publications

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

Chew Wee Siong WS Torta Federico F Ji Shanshan S Choi Hyungwon H Begum Husna H Sim Xueling X Khoo Chin Meng CM Khoo Eric Yin Hao EYH Ong Wei-Yi WY Van Dam Rob M RM Wenk Markus R MR Tai E Shyong ES Herr Deron R DR

JCI insight 20190604

<h4>Background</h4>Sphingolipids (SPs) are ubiquitous, structurally diverse molecules that include ceramides, sphingomyelins, 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.<h4>Methods</h4>We performed a lipidomics evaluation o ...[more]

PMID: 31162145

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Project description:BACKGROUND:Plasma lipidomic measures may enable improved prediction of cardiovascular outcomes in secondary prevention. The aim of this study is to determine the association of plasma lipidomic measurements with cardiovascular events and assess their potential to predict such events. METHODS:Plasma lipids (n = 342) were measured in a retrospective subcohort (n = 5,991) of the LIPID study. Proportional hazards regression was used to identify lipids associated with future cardiovascular events (nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death) and cardiovascular death. Multivariable models adding lipid species to traditional risk factors were created using lipid ranking established from the Akaike information criterion within a 5-fold cross-validation framework. The results were tested on a diabetic case cohort from the ADVANCE study (n = 3,779). RESULTS:Specific ceramide species, sphingolipids, phospholipids, and neutral lipids containing omega-6 fatty acids or odd-chain fatty acids were associated with future cardiovascular events (106 species) and cardiovascular death (139 species). The addition of 7 lipid species to a base model (11 conventional risk factors) resulted in an increase in the C-statistics from 0.629 (95% CI, 0.628-0.630) to 0.654 (95% CI, 0.653-0.656) for prediction of cardiovascular events and from 0.673 (95% CI, 0.671-0.675) to 0.727 (95% CI, 0.725-0.728) for prediction of cardiovascular death. Categorical net reclassification improvements for cardiovascular events and cardiovascular death were 0.083 (95% CI, 0.081-0.086) and 0.166 (95% CI, 0.162-0.170), respectively. Evaluation on the ADVANCE case cohort demonstrated significant improvement on the base models. CONCLUSIONS:The improvement in the prediction of cardiovascular outcomes, above conventional risk factors, demonstrates the potential of plasma lipidomic profiles as biomarkers for cardiovascular risk stratification in secondary prevention. FUNDING:Bristol-Myers Squibb, the National Health and Medical Research Council of Australia (grants 211086, 358395, and 1029754), and the Operational Infrastructure Support Program of the Victorian government of Australia.

Dataset Information

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

Background

Methods

Results

Conclusion

Funding

Publications

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

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