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

Author:

Mascardi María Florencia12,Mazzini Flavia Noelia1,Suárez Bárbara12,Ruda Vera M.3,Marciano Sebastián4,Casciato Paola24,Narvaez Adrián4,Haddad Leila4,Anders Margarita5,Orozco Federico5,Tamaroff Ana Jesica6,Cook Frank7,Gounarides John7,Gutt Susana6,Gadano Adrián4,García Celia Méndez8,Marro Martin L.9,Penas Steinhardt Alberto210,Trinks Julieta12ORCID

Affiliation:

1. Instituto de Medicina Traslacional e Ingeniería Biomédica (IMTIB) — CONICET — Instituto Universitario del Hospital Italiano (IUHI) — Hospital Italiano de Buenos Aires (HIBA) Buenos Aires Argentina

2. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) Buenos Aires Argentina

3. Biotherapeutic and Analytical Technologies Novartis Institutes for Biomedical Research (NIBR) Cambridge Massachusetts USA

4. Liver Unit of Hospital Italiano de Buenos Aires Buenos Aires Argentina

5. Liver Unit of Hospital Alemán Buenos Aires Argentina

6. Nutrition Department of Hospital Italiano de Buenos Aires Buenos Aires Argentina

7. Analytical Sciences & Imaging Department NIBR Cambridge Massachusetts USA

8. Chemical Biology & Therapeutics Department NIBR Cambridge Massachusetts USA

9. Cardiovascular and Metabolic Disease Area NIBR Cambridge Massachusetts USA

10. Departamento de Ciencias Básicas Laboratorio de Genómica Computacional Universidad Nacional de Luján Lujan Buenos Aires Argentina

Abstract

AbstractInteractions 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.

Funder

Fundación Florencio Fiorini

Publisher

Wiley

Subject

Molecular Biology,Biochemistry

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