Raspberry consumption : identification of distinct immune-metabolic response profiles by whole blood transcriptome profiling

Authors: Franck, MaximilienToro Martín, Juan deVarin, ThibautGarneau, VéroniquePilon, GenevièveRoy, DenisCouture, PatrickCouillard, CharlesMarette, AndréVohl, Marie-Claude
Abstract: Background. Numerous studies reported that diets rich in phenolic compounds are beneficial to human health, especially for immune-metabolic conditions, yet these effects and underlying mechanisms are not well defined. Objectives. The main goal of this study was to investigate the architecture of the inter-individual variability of the immune-metabolic response to raspberry consumption, by identifying distinct subgroups of participants sharing similar transcriptomic signatures. Methods. The 24 participants assigned to the treated arm of a randomized controlled trial, and at risk of developing metabolic syndrome, received 280g/day of frozen raspberries for 8 weeks. RNAseq data from whole blood assessed at weeks 0 and 8 were used to identify sub-groups of responses to raspberry consumption, by using partial least-squares discriminant analysis (PLS-DA) and hierarchical clustering. Changes in clinical features, metabolic parameters, plasma metabolites and gut metagenomics were compared between the resulting sub-groups. Results. Transcriptomic-based clustering regrouped the initial 24 study participants into two significantly different sub-groups of response to raspberry consumption, with 13 participants being defined as responders and 11 as non-responders. Following raspberry consumption, a significant decrease in plasma triglycerides, total-cholesterol and C-reactive protein was found in the responder sub-group, as compared to the non-responder sub-group. Two major components composed respectively of 100 and 220 genes were further identified by sparse PLS-DA as those better discriminating responders and non-responders. Functional pathways related to cytokine production, leukocyte activation and immune response were significantly enriched with discriminant genes. Factor analysis revealed that the first metabolomic factor mostly composed of decreasing triglycerides and increasing phosphatidylcholines was significantly higher in responders, as compared to non-responders. Analysis of gut metagenomic data revealed differences between responders and non-responders prior to the intervention and distinct modulations, notably regarding Firmicutes and Actinobacteria phyla. Conclusions. The discrimination analysis carried out in the present study based on transcriptional changes following raspberry consumption was able to identify two divergent sub-groups of participants, which were further identified as responders and non-responders, according to their immune-metabolic and gut metagenomic responses. In the context of precision nutrition, this holistic approach represents a promising framework to tackle the issue of inter-individual variability in the understanding of the impact of foods or nutrients on immune-metabolic health.
Document Type: Article de recherche
Issue Date: 10 January 2022
Open Access Date: 10 January 2023
Document version: AM
Creative Commons Licence: https://creativecommons.org/licenses/by-nc-nd/4.0
Permalink: http://hdl.handle.net/20.500.11794/74022
This document was published in: Journal of nutritional biochemistry, Vol. 101, (2022)
Alternative version: 10.1016/j.jnutbio.2022.108946
Collection:Articles publiés dans des revues avec comité de lecture

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