Evidence mapPaperPMID 36060983Full record

ArticleFrontiers in endocrinology2022

Serum lipidomics profiles reveal potential lipid markers for prediabetes and type 2 diabetes in patients from multiple communities.

Qiuhui Xuan, Chunxiu Hu, Yinan Zhang, Qingqing Wang, Xinjie Zhao, Xinyu Liu, Congrong Wang, Weiping Jia, Guowang Xu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in endocrinology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.1field-weighted citation impact, top 12% 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

11 citing papers in PubMed, 26 citations in OpenAlex.

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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

9 authors at 6 institutions in 1 country.

Qiuhui XuanChinese Academy of Sciences (CAS) Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China.
Chunxiu HuChinese Academy of Sciences (CAS) Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China.
Yinan ZhangShanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Endocrine and Metabolic Diseases, Metabolic Diseases Biobank, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.
Qingqing WangChinese Academy of Sciences (CAS) Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China.
Xinjie ZhaoChinese Academy of Sciences (CAS) Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China.
Xinyu LiuChinese Academy of Sciences (CAS) Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China.
Congrong WangDepartment of Endocrinology and Metabolism, Shanghai Fourth People's Hospital, Tongji University School of Medicine, Shanghai, China.
Weiping JiaShanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Endocrine and Metabolic Diseases, Metabolic Diseases Biobank, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.
Guowang XuChinese Academy of Sciences (CAS) Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China.
Dalian Institute of Chemical Physics · CNChinese Academy of Sciences · CNShanghai Jiao Tong University · CNShanghai Sixth People's Hospital · CNTongji University · CNUniversity of Chinese Academy of Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Dyslipidemia is a hallmark of diabetes mellitus (DM). However, specific lipid molecules closely associated with the initiation and progression of diabetes remain unclear. We used a pseudotargeted lipidomics approach to evaluate the complex lipid changes that occurred long before the diagnosis of type 2 diabetes mellitus (T2DM) and to identify novel lipid markers for screening prediabetes mellitus (PreDM) and T2DM in patients from multiple communities. Methods: Four hundred and eighty-one subjects consisting of T2DM, three subtypes of PreDM, and normal controls (NC) were enrolled as discovery cohort. Serum lipidomic profiles of 481 subjects were analyzed using an ultrahigh performance liquid chromatography-triple quadrupole mass spectrometry (UHPLC-QqQ-MS)-based pseudotargeted lipidomics method. The differential lipid molecules were further validated in an independent case-control study consisting of 150 PreDM, 234 T2DM and 94 NC. Results: Multivariate discriminative analyses show that lipidomics data have considerable potential for identifying lipidome differences among T2DM, subtypes of PreDM and NC. Statistical associations of lipid (sub)species display significant variations in 11 lipid (sub)species levels for T2DM and distinctive differences in 8 lipid (sub)species levels between prediabetic and normoglycemic individuals, with further differences in 8 lipid (sub)species levels among subtypes of PreDM. Adjusted for sex, age and BMI, only two lipid (sub)species of fatty acid (FA) and phosphatidylcholine (PC) were associated at Conclusions: Our findings improve insights into the lipid metabolic complexity and interindividual variations among subtypes of PreDM and T2DM, beyond the well-known differences in dyslipidemia in clinic.

Indexed as

Diabetes Mellitus, Type 2Prediabetic StateBiomarkersBlood GlucoseCase-Control StudiesHumansLipidomicsLipidsBiomarkersBlood GlucoseLipidsbiomarkersdiabetesdyslipidemiaimpaired fasting glucoseimpaired glucose tolerancelipidomicssubtypes of prediabetes

Identifiers

PMID36060983
PMCPMC9434798
OpenAlexW4292405542

What Socratic holds

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LicenceCC BY
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Registered trials

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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 Socratic graph.