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

doi:10.3389/fendo.2022.966823

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

Front Endocrinol (Lausanne). 2022 Aug 15:13:966823. doi: 10.3389/fendo.2022.966823. eCollection 2022.

Authors

Qiuhui Xuan^{1

2

3}, Chunxiu Hu^{1

3}, Yinan Zhang⁴, Qingqing Wang^{1

3}, Xinjie Zhao^{1

3}, Xinyu Liu^{1

3}, Congrong Wang⁵, Weiping Jia⁴, Guowang Xu^{1

3}

Affiliations

¹ Chinese Academy of Sciences (CAS) Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China.
² Department of Endocrinology, Shandong Provincial Hospital, Shandong University, Jinan, China.
³ University of Chinese Academy of Sciences, Beijing, China.
⁴ Shanghai 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.
⁵ Department of Endocrinology and Metabolism, Shanghai Fourth People's Hospital, Tongji University School of Medicine, Shanghai, China.

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 p< 0.05 for PreDM (all) and subtypes of PreDM. The defined lipid markers not only significantly improve the diagnostic accuracy of PreDM and T2DM but also effectively evaluating the risk of developing into each subtype of PreDM and T2DM when addition of age, sex, BMI, and FPG, respectively.

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.

Keywords: biomarkers; diabetes; dyslipidemia; impaired fasting glucose; impaired glucose tolerance; lipidomics; subtypes of prediabetes.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Biomarkers
Blood Glucose / analysis
Case-Control Studies
Diabetes Mellitus, Type 2* / diagnosis
Humans
Lipidomics
Lipids
Prediabetic State* / diagnosis

Substances

Biomarkers
Blood Glucose
Lipids