Evidence map›Paper›PMID 31162145›Full record

ArticleJCI insight2019

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

Wee Siong Chew, Federico Torta, Shanshan Ji, Hyungwon Choi, Husna Begum, Xueling Sim, Chin Meng Khoo, Eric Yin Hao Khoo, Wei-Yi Ong, Rob M Van Dam and 3 more

Open access · goldAbstract read
In one paragraph

Article in JCI insight, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 92 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
92citing papers in PubMed, 1 pooled it
7.5field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

92 citing papers in PubMed, 1 synthesis or guideline pooled it, 158 citations in OpenAlex.

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32 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 4 institutions in 2 countries.

Wee Siong ChewDepartment of Pharmacology and.
Federico TortaDepartment of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
Shanshan JiSingapore Lipidomics Incubator, Life Sciences Institute, National University of Singapore, Singapore.
Hyungwon ChoiSaw Swee Hock School of Public Health, National University of Singapore, Singapore.
Husna BegumDepartment of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
Xueling SimSaw Swee Hock School of Public Health, National University of Singapore, Singapore.
Chin Meng KhooDepartment of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National Health System, Singapore.
Eric Yin Hao KhooDepartment of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National Health System, Singapore.
Wei-Yi OngDepartment of Anatomy, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
Rob M Van DamSaw Swee Hock School of Public Health, National University of Singapore, Singapore.
Markus R WenkDepartment of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
E Shyong TaiSaw Swee Hock School of Public Health, National University of Singapore, Singapore.
Deron R HerrDepartment of Pharmacology and.
National University of Singapore · SGNational University Health System · SGAgency for Science, Technology and Research · SGSan Diego State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSphingolipids (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.

methodsWe 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.

resultsWe 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).

conclusionWe 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.

fundingFunding sources are listed in the Acknowledgements section.

Indexed as

LipidomicsAdultBody Mass IndexCeramidesChinaChromatography, LiquidDiabetes Mellitus, Type 2FemaleHumansIncidenceInsulin ResistanceMaleMiddle AgedMultivariate AnalysisProportional Hazards ModelsSingaporeCeramidesSphingolipidsSphingomyelinsSphingosineDiabetesEndocrinologyEpidemiologyObesity

Identifiers

PMID31162145
PMCPMC6629294
OpenAlexW2948192940

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.