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Caffeine intake exerts dual genome-wide effects on hippocampal metabolism and learning-dependent transcription
Isabel Paiva, … , Anne-Laurence Boutillier, David Blum
Isabel Paiva, … , Anne-Laurence Boutillier, David Blum
Published May 10, 2022
Citation Information: J Clin Invest. 2022;132(12):e149371. https://doi.org/10.1172/JCI149371.
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Research Article Neuroscience

Caffeine intake exerts dual genome-wide effects on hippocampal metabolism and learning-dependent transcription

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Abstract

Caffeine is the most widely consumed psychoactive substance in the world. Strikingly, the molecular pathways engaged by its regular consumption remain unclear. We herein addressed the mechanisms associated with habitual (chronic) caffeine consumption in the mouse hippocampus using untargeted orthogonal omics techniques. Our results revealed that chronic caffeine exerts concerted pleiotropic effects in the hippocampus at the epigenomic, proteomic, and metabolomic levels. Caffeine lowered metabolism-related processes (e.g., at the level of metabolomics and gene expression) in bulk tissue, while it induced neuron-specific epigenetic changes at synaptic transmission/plasticity-related genes and increased experience-driven transcriptional activity. Altogether, these findings suggest that regular caffeine intake improves the signal-to-noise ratio during information encoding, in part through fine-tuning of metabolic genes, while boosting the salience of information processing during learning in neuronal circuits.

Authors

Isabel Paiva, Lucrezia Cellai, Céline Meriaux, Lauranne Poncelet, Ouada Nebie, Jean-Michel Saliou, Anne-Sophie Lacoste, Anthony Papegaey, Hervé Drobecq, Stéphanie Le Gras, Marion Schneider, Enas M. Malik, Christa E. Müller, Emilie Faivre, Kevin Carvalho, Victoria Gomez-Murcia, Didier Vieau, Bryan Thiroux, Sabiha Eddarkaoui, Thibaud Lebouvier, Estelle Schueller, Laura Tzeplaeff, Iris Grgurina, Jonathan Seguin, Jonathan Stauber, Luisa V. Lopes, Luc Buée, Valérie Buée-Scherrer, Rodrigo A. Cunha, Rima Ait-Belkacem, Nicolas Sergeant, Jean-Sébastien Annicotte, Anne-Laurence Boutillier, David Blum

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Figure 5

Hippocampal transcriptomic alterations induced by chronic caffeine consumption in learning conditions.

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Hippocampal transcriptomic alterations induced by chronic caffeine consu...
(A) Experimental procedure for the RNA-Seq experiments in the home cage and learning groups. After chronic consumption of caffeine (or water as a control), mice were subjected to 3 days of training in the MWM, and the dorsal hippocampus was dissected 1 hour after the last trial for RNA-Seq. Cond, condition. (B) Heatmap representation of RNA-Seq results (z score) in the 4 groups. A total of 4 biological replicates were used per group. Color coding was performed according to the z score of the normalized read counts divided by gene length. (C) Left: Volcano plots show the differentially expressed hippocampal genes (adjusted P < 0.1) between water-treated control learning and control home cage groups. Right: Volcano plot showing differentially expressed genes in caffeine-treated learning and home cage mice (adjusted P < 0.1). (D) Venn diagram showing the transcriptome changes induced by learning in water- and caffeine-treated animals (adjusted P < 0.1). (E) Violin plots representing expression values (z score) of the 419 genes downregulated and the 720 upregulated by caffeine (Caff) in learning (learn), showing opposite trends among the home cage (HC) groups. (F) KEGG pathway analysis showing that most of the genes downregulated by caffeine upon learning are associated with ribosome. (G) Functional annotation performed with DAVID, and significance for the effect of learning in water- and caffeine-treated animals. (H) Venn diagram revealing 121 genes depleted in H3K27ac (bulk hippocampus ChIP-Seq; DOWN) and upregulated (RNA; UP) by learning in caffeine-treated mice. (I) Violin plots of the expression values (z score) of the 121 genes. (J) Gene ontology analysis performed with STRING of the 121 genes, showing a strong association with metabolism-related biological processes (top 16 by FDR). Statistical significance in E and I was calculated by 1-way ANOVA followed by Bonferroni’s multiple-comparison post hoc test;****P < 0.0001.

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