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Cardiac vagal activity is associated with gut-microbiome patterns in women—An exploratory pilot study

INTRODUCTION: A functional reciprocity between the gut microbiome and vagal nerve activity has been suggested, however, human studies addressing this phenomenon are limited. METHODS: Twenty-four-hour cardiac vagal activity (CVA) was assessed from 73 female participants (aged 24.5 ± 4.3 years). Addit...

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Detalles Bibliográficos
Autores principales: Mörkl, Sabrina, Oberascher, Andreas, Tatschl, Josef M., Lackner, Sonja, Bastiaanssen, Thomaz F. S., Butler, Mary I., Moser, Maximilian, Frühwirth, Matthias, Mangge, Harald, Cryan, John F., Dinan, Timothy G., Holasek, Sandra J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9559470/
https://www.ncbi.nlm.nih.gov/pubmed/36246995
http://dx.doi.org/10.1080/19585969.2022.2128697
Descripción
Sumario:INTRODUCTION: A functional reciprocity between the gut microbiome and vagal nerve activity has been suggested, however, human studies addressing this phenomenon are limited. METHODS: Twenty-four-hour cardiac vagal activity (CVA) was assessed from 73 female participants (aged 24.5 ± 4.3 years). Additionally, stool samples were subjected to 16SrRNA gene analysis (V1–V2). Quantitative Insights Into Microbial Ecology (QIIME) was used to analyse microbiome data. Additionally, inflammatory parameters (such as CRP and IL-6) were derived from serum samples. RESULTS: Daytime CVA correlated significantly with gut microbiota diversity (r(sp) = 0.254, p = 0.030), CRP (r(sp) = −0.348, p = 0.003), and IL-6 (r(sp) = −0.320, p = 0.006). When the group was divided at the median of 24 h CVA (Mdn = 1.322), the following features were more abundant in the high CVA group: Clostridia (Linear discriminant analysis effect size (LDA) = 4.195, p = 0.029), Clostridiales (LDA = 4.195, p = 0.029), Lachnospira (LDA = 3.489, p = 0.004), Ruminococcaceae (LDA = 4.073, p = 0.010), Faecalibacterium (LDA = 3.982, p = 0.042), Lactobacillales (LDA = 3.317, p = 0.029), Bacilli (LDA = 3.294, p = 0.0350), Streptococcaceae (LDA = 3.353, p = 0.006), Streptococcus (LDA = 3.332, p = 0.011). Based on Dirichlet multinomial mixtures two enterotypes could be detected, which differed significantly in CVA, age, BMI, CRP, IL-6, and diversity. CONCLUSIONS: As an indicator of gut-brain communication, gut microbiome analysis could be extended by measurements of CVA to enhance our understanding of signalling via microbiota-gut-brain-axis and its alterations through psychobiotics.