Dataset Information

A discriminant analysis of plasma metabolomics for the assessment of metabolic responsiveness to red raspberry consumption.

ABSTRACT:

Background

Many studies show that the intake of raspberries is beneficial to immune-metabolic health, but the responses of individuals are heterogeneous and not fully understood.

Methods

In a two-arm parallel-group, randomized, controlled trial, immune-metabolic outcomes and plasma metabolite levels were analyzed before and after an 8-week red raspberry consumption. Based on partial least squares discriminant analysis (PLS-DA) on plasma xenobiotic levels, adherence to the intervention was first evaluated. A second PLS-DA followed by hierarchical clustering was used to classify individuals into response subgroups. Clinical immune and metabolic outcomes, including insulin resistance (HOMA-IR) and sensitivity (Matsuda, QUICKI) indices, during the intervention were assessed and compared between response subgroups.

Results

Two subgroups of participants, type 1 responders (n = 17) and type 2 responders (n = 5), were identified based on plasma metabolite levels measured during the intervention. Type 1 responders showed neutral to negative effects on immune-metabolic clinical parameters after raspberry consumption, and type 2 responders showed positive effects on the same parameters. Changes in waist circumference, waist-to-hip ratio, fasting plasma apolipoprotein B, C-reactive protein and insulin levels as well as Matsuda, HOMA-IR and QUICKI were significantly different between the two response subgroups. A deleterious effect of two carotenoid metabolites was also observed in type 1 responders but these variables were significantly associated with beneficial changes in the QUICKI index and in fasting insulin levels in type 2 responders. Increased 3-ureidopropionate levels were associated with a decrease in the Matsuda index in type 2 responders, suggesting that this metabolite is associated with a decrease in insulin sensitivity for those subjects, whereas the opposite was observed for type 1 responders.

Conclusion

The beneficial effects associated with red raspberry consumption are subject to inter-individual variability. Metabolomics-based clustering appears to be an effective way to assess adherence to a nutritional intervention and to classify individuals according to their immune-metabolic responsiveness to the intervention. This approach may be replicated in future studies to provide a better understanding of how interindividual variability impacts the effects of nutritional interventions on immune-metabolic health.

SUBMITTER: Barbe V

PROVIDER: S-EPMC10130762 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Publications

A discriminant analysis of plasma metabolomics for the assessment of metabolic responsiveness to red raspberry consumption.

Barbe Valentin V de Toro-Martín Juan J San-Cristobal Rodrigo R Garneau Véronique V Pilon Geneviève G Couture Patrick P Roy Denis D Couillard Charles C Marette André A Vohl Marie-Claude MC

Frontiers in nutrition 20230323

<h4>Background</h4>Many studies show that the intake of raspberries is beneficial to immune-metabolic health, but the responses of individuals are heterogeneous and not fully understood.<h4>Methods</h4>In a two-arm parallel-group, randomized, controlled trial, immune-metabolic outcomes and plasma metabolite levels were analyzed before and after an 8-week red raspberry consumption. Based on partial least squares discriminant analysis (PLS-DA) on plasma xenobiotic levels, adherence to the interven ...[more]

PMID: 37125033

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Project description:BackgroundWalnut consumption is associated with lower risk of type 2 diabetes (T2D) and cardiovascular disease (CVD). However, it is unknown whether plasma metabolites related to walnut consumption are also associated with lower risk of cardiometabolic diseases.ObjectivesThe study aimed to identify plasma metabolites associated with walnut consumption and evaluate the prospective associations between the identified profile and risk of T2D and CVD.MethodsThe discovery population included 1833 participants at high cardiovascular risk from the PREvención con DIeta MEDiterránea (PREDIMED) study with available metabolomics data at baseline. The study population included 57% women (baseline mean BMI (in kg/m2): 29.9; mean age: 67 y). A total of 1522 participants also had available metabolomics data at year 1 and were used as the internal validation population. Plasma metabolomics analyses were performed using LC-MS. Cross-sectional associations between 385 known metabolites and walnut consumption were assessed using elastic net continuous regression analysis. A 10-cross-validation (CV) procedure was used, and Pearson correlation coefficients were assessed between metabolite weighted models and self-reported walnut consumption in each pair of training-validation data sets within the discovery population. We further estimated the prospective associations between the identified metabolite profile and incident T2D and CVD using multivariable Cox regression models.ResultsA total of 19 metabolites were significantly associated with walnut consumption, including lipids, purines, acylcarnitines, and amino acids. Ten-CV Pearson correlation coefficients between self-reported walnut consumption and the plasma metabolite profile were 0.16 (95% CI: 0.11, 0.20) in the discovery population and 0.15 (95% CI: 0.10, 0.20) in the validation population. The metabolite profile was inversely associated with T2D incidence (HR per 1 SD: 0.83; 95% CI: 0.71, 0.97; P = 0.02). For CVD incidence, the HR per 1-SD was 0.71 (95% CI: 0.60, 0.85; P < 0.001).ConclusionsA metabolite profile including 19 metabolites was associated with walnut consumption and with a lower risk of incident T2D and CVD in a Mediterranean population at high cardiovascular risk.

Dataset Information

A discriminant analysis of plasma metabolomics for the assessment of metabolic responsiveness to red raspberry consumption.

Background

Methods

Results

Conclusion

Publications

A discriminant analysis of plasma metabolomics for the assessment of metabolic responsiveness to red raspberry consumption.

Similar Datasets

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