Plasma metabolomic profiles of plant-based dietary indices reveal potential pathways for metabolic syndrome associations

Fabian Lanuza; Tomas Meroño; Raul Zamora-Ros; Nicola P Bondonno; Agnetha Linn Rostgaard-Hansen; Alex Sánchez-Pla; Berta Miro; Francesc Carmona-Pontaque; Gabriele Riccardi; Anne Tjønneland; Rikard Landberg; Jytte Halkjær; Cristina Andres-Lacueva

doi:10.1016/j.atherosclerosis.2023.117285

Plasma metabolomic profiles of plant-based dietary indices reveal potential pathways for metabolic syndrome associations

Atherosclerosis. 2023 Oct:382:117285. doi: 10.1016/j.atherosclerosis.2023.117285. Epub 2023 Sep 9.

Affiliations

¹ Biomarkers and Nutrimetabolomics Laboratory, Department de Nutrició, Ciències de L'Alimentació i Gastronomia, Institut de Recerca en Nutrició i Seguretat Alimentària (INSA-UB), Facultat de Farmàcia i Ciències de L'Alimentació, Universitat de Barcelona (UB), 08028, Barcelona, Spain; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid, 28029, Spain.
² Biomarkers and Nutrimetabolomics Laboratory, Department de Nutrició, Ciències de L'Alimentació i Gastronomia, Institut de Recerca en Nutrició i Seguretat Alimentària (INSA-UB), Facultat de Farmàcia i Ciències de L'Alimentació, Universitat de Barcelona (UB), 08028, Barcelona, Spain; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid, 28029, Spain. Electronic address: tomasmerono@ub.edu.
³ Biomarkers and Nutrimetabolomics Laboratory, Department de Nutrició, Ciències de L'Alimentació i Gastronomia, Institut de Recerca en Nutrició i Seguretat Alimentària (INSA-UB), Facultat de Farmàcia i Ciències de L'Alimentació, Universitat de Barcelona (UB), 08028, Barcelona, Spain; Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, Catalan Institute of Oncology (ICO), Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain. Electronic address: rzamora@idibell.cat.
⁴ Danish Cancer Society Research Center, Strandboulevarden 49, DK 2100, Copenhagen, Denmark; Nutrition and Health Innovation Research Institute, School of Medical and Health Sciences, Edith Cowan University, Perth, Australia.
⁵ Danish Cancer Society Research Center, Strandboulevarden 49, DK 2100, Copenhagen, Denmark.
⁶ Statistics and Bioinformatics Research Group, Department of Genetics, Microbiology and Statistics, University of Barcelona, Barcelona, Spain.
⁷ Biomarkers and Nutrimetabolomics Laboratory, Department de Nutrició, Ciències de L'Alimentació i Gastronomia, Institut de Recerca en Nutrició i Seguretat Alimentària (INSA-UB), Facultat de Farmàcia i Ciències de L'Alimentació, Universitat de Barcelona (UB), 08028, Barcelona, Spain; Statistics and Bioinformatics Research Group, Department of Genetics, Microbiology and Statistics, University of Barcelona, Barcelona, Spain.
⁸ Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy.
⁹ Department of Biology and Biological Engineering, Division of Food and Nutrition Science, Chalmers University of Technology, Gothenburg, Sweden.

PMID: 37778133
DOI: 10.1016/j.atherosclerosis.2023.117285

Abstract

Background and aims: Plant-based dietary patterns have been associated with improved health outcomes. This study aims to describe the metabolomic fingerprints of plant-based diet indices (PDI) and examine their association with metabolic syndrome (MetS) and its components in a Danish population.

Methods: The MAX study comprised 676 participants (55% women, aged 18-67 y) from Copenhagen. Sociodemographic and dietary data were collected using questionnaires and three 24-h dietary recalls over one year (at baseline, and at 6 and 12 months). Mean dietary intakes were computed, as well as overall PDI, healthful (hPDI) and unhealthful (uPDI) scores, according to food groups for each plant-based index. Clinical variables were also collected at the same time points in a health examination that included complete blood tests. MetS was defined according to the International Diabetes Federation criteria. Plasma metabolites were measured using a targeted metabolomics approach. Metabolites associated with PDI were selected using random forest models and their relationships with PDIs and MetS were analyzed using generalized linear mixed models.

Results: The mean prevalence of MetS was 10.8%. High, compared to low, hPDI and uPDI scores were associated with a lower and higher odd of MetS, respectively [odds ratio (95%CI); hPDI: 0.56 (0.43-0.74); uPDI: 1.61 (1.26-2.05)]. Out of 411 quantified plasma metabolites, machine-learning metabolomics fingerprinting revealed 13 metabolites, including food and food-related microbial metabolites, like hypaphorine, indolepropionic acid and lignan-derived enterolactones. These metabolites were associated with all PDIs and were inversely correlated with MetS components (p < 0.05). Furthermore, they had an explainable contribution of 12% and 14% for the association between hPDI or uPDI, respectively, and MetS only among participants with overweight/obesity.

Conclusions: Metabolites associated with PDIs were inversely associated with MetS and its components, and may partially explain the effects of plant-based diets on cardiometabolic risk factors.

Keywords: Cardiovascular risk factors; Dietary patterns; Indolepropionic; Metabolic syndromes; Metabolomics; Plant-based diet.

Publication types

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

MeSH terms

Diet
Female
Humans
Male
Metabolic Syndrome* / diagnosis
Metabolic Syndrome* / epidemiology
Surveys and Questionnaires