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Updated: Jul 23, 2025

Assessing Whole-Body Lipid-Handling Capacity in Mice
Published on: November 24, 2020
Diet-Related Lipidomic Signatures and Changed Type 2 Diabetes Risk in a Randomized Controlled Feeding Study With
Yaogan Luo1, Liang Sun2, Qingqing Wu3
1Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
Objective:
Few trials studied the links of food components in different diets with their induced lipidomic changes and related metabolic outcomes. Thus, we investigated specific lipidomic signatures with habitual diets and modified diabetes risk by using a trial and a cohort.
Research Design And Methods:
We included 231 Chinese with overweight and prediabetes in a randomized feeding trial with Mediterranean, traditional, or transitional diets (control diet) from February to September 2019. Plasma lipidomic profiles were measured at baseline, third month, and sixth month by high-throughput targeted liquid chromatography-mass spectrometry. Associations of the identified lipids with habitual dietary intakes were examined in another lipidomic database of a Chinese cohort (n = 1,117). The relationships between diet-induced changes of lipidomic species and diabetes risk factors were further investigated through both individual lipids and relevant modules in the trial.
Results:
Out of 364 lipidomic species, 26 altered across groups, including 12 triglyceride (TAG) fractions, nine plasmalogens, four phosphatidylcholines (PCs), and one phosphatidylethanolamine. TAG fractions and PCs were associated with habitual fish intake while plasmalogens were associated with red meat intake in the cohort. Of the diet-related lipidomic metabolites, 10 TAG fractions and PC(16:0/22:6) were associated with improved Matsuda index (β = 0.12 to 0.42; PFDR < 0.030). Two plasmalogens were associated with deteriorated fasting glucose (β = 0.29 to 0.31; PFDR < 0.014). Similar results were observed for TAG and plasmalogen related modules.
Conclusions:
These fish- and red meat-related lipidomic signatures sensitively reflected different diets and modified type 2 diabetes risk factors, critical for optimizing dietary patterns.
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