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. 2024 Jun 8;16(12):1805.
doi: 10.3390/nu16121805.

The Lipidomic Profile Is Associated with the Dietary Pattern in Subjects with and without Diabetes Mellitus from a Mediterranean Area

Marina Idalia Rojo-López  1 , Maria Barranco-Altirriba  1   2   3 , Joana Rossell  1   4 , Maria Antentas  1 , Esmeralda Castelblanco  5 , Oscar Yanes  4   6 , Ralf J M Weber  7   8   9 , Gavin R Lloyd  7   8   9 , Catherine Winder  7   8   10 , Warwick B Dunn  7   8   10 , Josep Julve  1   4 , Minerva Granado-Casas  4   11   12 , Dídac Mauricio  1   4   13   14
Affiliations

The Lipidomic Profile Is Associated with the Dietary Pattern in Subjects with and without Diabetes Mellitus from a Mediterranean Area

Marina Idalia Rojo-López et al. Nutrients. .

Abstract

Lipid functions can be influenced by genetics, age, disease states, and lifestyle factors, particularly dietary patterns, which are crucial in diabetes management. Lipidomics is an expanding field involving the comprehensive exploration of lipids from biological samples. In this cross-sectional study, 396 participants from a Mediterranean region, including individuals with type 1 diabetes (T1D), type 2 diabetes (T2D), and non-diabetic individuals, underwent lipidomic profiling and dietary assessment. Participants completed validated food frequency questionnaires, and lipid analysis was conducted using ultra-high-performance liquid chromatography coupled with mass spectrometry (UHPLC/MS). Multiple linear regression models were used to determine the association between lipid features and dietary patterns. Across all subjects, acylcarnitines (AcCa) and triglycerides (TG) displayed negative associations with the alternate Healthy Eating Index (aHEI), indicating a link between lipidomic profiles and dietary habits. Various lipid species (LS) showed positive and negative associations with dietary carbohydrates, fats, and proteins. Notably, in the interaction analysis between diabetes and the aHEI, we found some lysophosphatidylcholines (LPC) that showed a similar direction with respect to aHEI in non-diabetic individuals and T2D subjects, while an opposite direction was observed in T1D subjects. The study highlights the significant association between lipidomic profiles and dietary habits in people with and without diabetes, particularly emphasizing the role of healthy dietary choices, as reflected by the aHEI, in modulating lipid concentrations. These findings underscore the importance of dietary interventions to improve metabolic health outcomes, especially in the context of diabetes management.

Keywords: diabetes; dietary pattern; lipid species; lipidomic.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Density plot for aHEI and aMED scores. This density plot illustrates the distribution of two continuous variables, aHEI and aMED, within a population of non-diabetic control individuals, as well as T1D and T2D individuals. The x-axis represents the scores, while the y-axis represents the population density. aMED, alternate Mediterranean Diet score; aHEI, alternate Healthy Eating Index; T1D, type 1 diabetes; T2D, type 2 diabetes.
Figure 2
Figure 2
Bar plot of linear regressors of lipids significantly associated with the aHEI, carbohydrates, fats, and proteins in the studied subjects. aHEI, alternate Healthy Eating Index; All, all subjects; Controls, non-diabetic subject; T2D, type 2 diabetes. Each bar represents the regression coefficient (beta value) of a specific lipid species with respect to the corresponding dietary factor, providing insights into the relationships between lipid metabolism and dietary intake patterns in the study population.
Figure 3
Figure 3
Plot of the interactions between lipids and aHEI: (a) Interactions of LPC(18:2e)+H; (b) Interactions of PC(40:3e)+H; (c) Interactions of LPC(18:1e)+H; (d) Interactions of PC(32:1)+H. aHEI, alternate Healthy Eating Index; LPC, lysophosphatidylcholines; PC, phosphatidylcholines; T1D, type 1 diabetes; T2D, type 2 diabetes.
See this image and copyright information in PMC

References

    1. O’Donnell V.B., Ekroos K., Liebisch G., Wakelam M. Lipidomics: Current State of the Art in a Fast Moving Field. Wiley Interdiscip. Rev. Syst. Biol. Med. 2020;12:e1466. doi: 10.1002/wsbm.1466. - DOI - PubMed
    1. Tabassum R., Ripatti S. Integrating Lipidomics and Genomics: Emerging Tools to Understand Cardiovascular Diseases. Cell Mol. Life Sci. 2021;78:2565–2584. doi: 10.1007/s00018-020-03715-4. - DOI - PMC - PubMed
    1. Hyötyläinen T., Bondia-Pons I., Orešič M. Lipidomics in Nutrition and Food Research. Mol. Nutr. Food Res. 2013;57:1306–1318. doi: 10.1002/mnfr.201200759. - DOI - PubMed
    1. Playdon M.C., Moore S.C., Derkach A., Reedy J., Subar A.F., Sampson J.N., Albanes D., Gu F., Kontto J., Lassale C., et al. Identifying Biomarkers of Dietary Patterns by Using Metabolomics. Am. J. Clin. Nutr. 2017;105:450–465. doi: 10.3945/ajcn.116.144501. - DOI - PMC - PubMed
    1. Razquin C., Toledo E., Clish C.B., Ruiz-Canela M., Dennis C., Corella D., Papandreou C., Ros E., Estruch R., Guasch-Ferré M., et al. Plasma Lipidomic Profiling and Risk of Type 2 Diabetes in the PREDIMED Trial. Diabetes Care. 2018;41:2617–2624. doi: 10.2337/dc18-0840. - DOI - PMC - PubMed