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Fetal cardiac growth is associated with in utero gut colonization

Background and aims Intra-uterine metabolic environment predicts newborns’ cardiac morphology, metabolism and future health. In adults, gut microbiota composition relates to altered cardiac structure and metabolism. We investigated the relationship between gut microbiota colonization and fetal cardiac growth. Methods and results Bacterial composition in meconium samples of 26 healthy, full-term newborns was assessed by 16S rDNA gene sequencing. Its relationship with birth echocardiographic parameters, and the interaction with cord blood levels of inflammatory markers were investigated. Correlative and cluster analysis, linear discriminant analysis effect size and predictive functional analysis based on Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were applied. Fetal left ventricle growth was related to gut microbiota composition at birth. Specifically, left ventricle posterior wall thickness (LVPW) greater than 4 mm was associated with lower microbiota beta and alpha diversity, depletion (LDA score > 3) of several bacteria at each taxonomic level, including Lactobacillales, and enrichment (LDA score > 5) in Enterobacteriales and Enterobacteriaceae. The latter was significantly related to cord blood gamma-glutamyltransferase levels (r = 0.58, p = 0.0057). Functionally, a thicker LVPW was related to up-regulation of pathways involved in lipopolysaccharide biosynthesis (+50%, p = 0.045 in correlative analysis) and energy metabolism (+12%, p = 0.028), and down-regulation of pathways involved in xenobiotic biodegradation (−21 to −53%, p = 0.0063–0.039), PPAR signaling (−24%, p = 0.021) and cardiac muscle contraction (−100%, p = 0.049). Conclusion Fetal cardiac growth and gut colonization are associated. Greater neonatal LVPW thickness is related to lower diversity of the gut microbiota community, depletion of bacteria having anti-remodeling effects, and enrichment in bacteria functionally linked to inflammation.

Nutrition, Metabolism and Cardiovascular Diseases, 2019

Autori esterni: MA Guzzardi (IFC-CNR), P Iozzo (IFC-CNR), L Ait Ali (FTGM, Pisa)
Autori IIT:

Tipo: Contributo in rivista ISI
Area di disciplina: Computer Science & Engineering

File: 1-s2.0-S0939475318303028-main-2.pdf

Attività: Biologia computazionale