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Integrated analysis of the transcriptome and its interaction with the metabolome in metabolic associated fatty liver disease: Gut microbiome signatures, correlation networks, and effect of PNPLA3 genotype

Interactions between communities of the gut microbiome and with the host could affect the onset and progression of metabolic associated fatty liver disease (MAFLD), and can be useful as new diagnostic and prognostic biomarkers. In this study, we performed a multi-omics approach to unravel gut microb...

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Published in:Proteomics (Weinheim) 2023-09, Vol.23 (18), p.e2200414
Main Authors: Mascardi, María Florencia, Mazzini, Flavia Noelia, Suárez, Bárbara, Ruda, Vera M, Marciano, Sebastián, Casciato, Paola, Narvaez, Adrián, Haddad, Leila, Anders, Margarita, Orozco, Federico, Tamaroff, Ana Jesica, Cook, Frank, Gounarides, John, Gutt, Susana, Gadano, Adrián, García, Celia Méndez, Marro, Martin L, Penas Steinhardt, Alberto, Trinks, Julieta
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cited_by cdi_FETCH-LOGICAL-c323t-7fd902f9bec8a9f94fb1252f37ff59708ed2ee1a46d3c95c7cc5c1f889eeec033
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container_issue 18
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container_title Proteomics (Weinheim)
container_volume 23
creator Mascardi, María Florencia
Mazzini, Flavia Noelia
Suárez, Bárbara
Ruda, Vera M
Marciano, Sebastián
Casciato, Paola
Narvaez, Adrián
Haddad, Leila
Anders, Margarita
Orozco, Federico
Tamaroff, Ana Jesica
Cook, Frank
Gounarides, John
Gutt, Susana
Gadano, Adrián
García, Celia Méndez
Marro, Martin L
Penas Steinhardt, Alberto
Trinks, Julieta
description Interactions between communities of the gut microbiome and with the host could affect the onset and progression of metabolic associated fatty liver disease (MAFLD), and can be useful as new diagnostic and prognostic biomarkers. In this study, we performed a multi-omics approach to unravel gut microbiome signatures from 32 biopsy-proven patients (10 simple steatosis -SS- and 22 steatohepatitis -SH-) and 19 healthy volunteers (HV). Human and microbial transcripts were differentially identified between groups (MAFLD vs. HV/SH vs. SS), and analyzed for weighted correlation networks together with previously detected metabolites from the same set of samples. We observed that expression of Desulfobacteraceae bacterium, methanogenic archaea, Mushu phage, opportunistic pathogenic fungi Fusarium proliferatum and Candida sorbophila, protozoa Blastocystis spp. and Fonticula alba were upregulated in MAFLD and SH. Desulfobacteraceae bacterium and Mushu phage were hub species in the onset of MAFLD, whereas the activity of Fonticula alba, Faecalibacterium prausnitzii, and Mushu phage act as key regulators of the progression to SH. A combination of clinical, metabolomic, and transcriptomic parameters showed the highest predictive capacity for MAFLD and SH (AUC = 0.96). In conclusion, faecal microbiome markers from several community members contribute to the switch in signatures characteristic of MAFLD and its progression towards SH.
doi_str_mv 10.1002/pmic.202200414
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subjects Archaea
Bacteria
Biomarkers
Biopsy
Digestive system
Fatty liver
Genotypes
Intestinal microflora
Liver
Liver diseases
Metabolism
Metabolites
Metabolomics
Methanogenic archaea
Microbiomes
Microbiota
Microorganisms
Phages
Protozoa
Steatosis
Transcriptomes
Transcriptomics
title Integrated analysis of the transcriptome and its interaction with the metabolome in metabolic associated fatty liver disease: Gut microbiome signatures, correlation networks, and effect of PNPLA3 genotype
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