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. 2024 Apr 16;5(4):101480.
doi: 10.1016/j.xcrm.2024.101480. Epub 2024 Mar 22.

Neuroactive metabolites and bile acids are altered in extremely premature infants with brain injury

Affiliations

Neuroactive metabolites and bile acids are altered in extremely premature infants with brain injury

Manuel Pristner et al. Cell Rep Med. .

Abstract

The gut microbiome is associated with pathological neurophysiological evolvement in extremely premature infants suffering from brain injury. The exact underlying mechanism and its associated metabolic signatures in infants are not fully understood. To decipher metabolite profiles linked to neonatal brain injury, we investigate the fecal and plasma metabolome of samples obtained from a cohort of 51 extremely premature infants at several time points, using liquid chromatography (LC)-high-resolution mass spectrometry (MS)-based untargeted metabolomics and LC-MS/MS-based targeted analysis for investigating bile acids and amidated bile acid conjugates. The data are integrated with 16S rRNA gene amplicon gut microbiome profiles as well as patient cytokine, growth factor, and T cell profiles. We find an early onset of differentiation in neuroactive metabolites between infants with and without brain injury. We detect several bacterially derived bile acid amino acid conjugates in plasma and feces. These results provide insights into the early-life metabolome of extremely premature infants.

Keywords: bile acid amino acid conjugates; extremely premature infant; gut-immune-brain axis; neonatal brain injury; untargeted metabolomics.

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Conflict of interest statement

Declaration of interests The authors declare no competing interests.

Figures

None
Graphical abstract
Figure 1
Figure 1
Study design and metabolomic differences over time (A) Visualization of the study design. (B) PCA of untargeted metabolomics dataset and respective distances to the centroid for (B) feces and (C) plasma.
Figure 2
Figure 2
Observed metabolic changes at the pathway level (A–C) Enriched metabolic pathways and their combined p values for (A) plasma, (B) feces, and (C) their intersection. (D) Activity networks of feces created by mummichog.
Figure 3
Figure 3
Selected metabolites altered between groups at different time points in plasma and feces (A–G) Box plots of selected metabolites. Plasma: day 3: nCTR = 14, nPAT = 10; day 7: nCTR = 16, nPAT = 11; day 28: nCTR = 14, nPAT = 7; week 32: nCTR = 15, nPAT = 8; term age: nCTR = 16, nPAT = 9. Feces: day 7: nCTR = 4, nPAT = 8; day 28: nCTR = 31, nPAT = 11. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001. (H) Selected overview of differentiated metabolites and pathways between groups over all time points. Arrows pointing up indicate an increase in the pathological group.
Figure 4
Figure 4
Multi-omics correlation matrix Correlation matrix of 16S rRNA microbiome, T cell, cytokine, and growth factor data with metabolomics data over all time points of (A) plasma (T cell: n = 27; cytokines and growth factors: n = 23; 16S rRNA: n = 78) and (B) feces (T cell: n = 34; cytokines and growth factors: n = 27; 16S rRNA: n = 71). ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001.
Figure 5
Figure 5
Profiles of bile acids and their conjugates in feces and plasma (A and C) Presence of bile acids (%) in experimental groups at different time points. (B and D) Bile acid profiles of individual samples. (E) Box plots of bile acids altered between experimental groups (plasma: nCTR = 14, nPAT = 10; feces: nCTR = 3, nPAT = 8). ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001. (F) Chromatographic peaks of the detected analytes.

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