Loris Riccardo Lopetuso1, Andrea Quagliariello2, Mario Schiavoni2, Valentina Petito3, Alessandra Russo2, Sofia Reddel2, Federica Del Chierico2, Gianluca Ianiro3, Franco Scaldaferri4, Matteo Neri5, Giovanni Cammarota4, Lorenza Putignani6, Antonio Gasbarrini7. 1. UOC Medicina Interna e Gastroenterologia, Area Medicina Interna, Gastroenterologia ed Oncologia Medica, Dipartimento di Scienze Gastroenterologiche, Endocrino-Metaboliche e Nefro-Urologiche, Fondazione Policlinico Universitario A. Gemelli IRCCS, Largo Gemelli, 8, 00168 Rome, Italy; Department of Medicine and Ageing Sciences, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy; Center for Advanced Studies and Technology (CAST), "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy. 2. Unità di Microbioma Umano, Ospedale Pediatrico "Bambino Gesù", IRCCS, Rome, Italy. 3. UOC Medicina Interna e Gastroenterologia, Area Medicina Interna, Gastroenterologia ed Oncologia Medica, Dipartimento di Scienze Gastroenterologiche, Endocrino-Metaboliche e Nefro-Urologiche, Fondazione Policlinico Universitario A. Gemelli IRCCS, Largo Gemelli, 8, 00168 Rome, Italy. 4. UOC Medicina Interna e Gastroenterologia, Area Medicina Interna, Gastroenterologia ed Oncologia Medica, Dipartimento di Scienze Gastroenterologiche, Endocrino-Metaboliche e Nefro-Urologiche, Fondazione Policlinico Universitario A. Gemelli IRCCS, Largo Gemelli, 8, 00168 Rome, Italy; Istituto di Patologia Speciale Medica, Università Cattolica del Sacro Cuore, Rome, Italy. 5. Department of Medicine and Ageing Sciences, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy; Center for Advanced Studies and Technology (CAST), "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy. 6. Unità di Parassitologia ed Unità di Microbioma Umano, Ospedale Pediatrico "Bambino Gesù", IRCCS, Rome, Italy. 7. UOC Medicina Interna e Gastroenterologia, Area Medicina Interna, Gastroenterologia ed Oncologia Medica, Dipartimento di Scienze Gastroenterologiche, Endocrino-Metaboliche e Nefro-Urologiche, Fondazione Policlinico Universitario A. Gemelli IRCCS, Largo Gemelli, 8, 00168 Rome, Italy; Istituto di Patologia Speciale Medica, Università Cattolica del Sacro Cuore, Rome, Italy. Electronic address: antonio.gasbarrini@unicatt.it.
Abstract
BACKGROUND: Gut microbiota exerts a crucial role in gastrointestinal (GI) and extra-intestinal (EI) disorders. In this context, Akkermansia muciniphila is pivotal for the maintenance of host health and has been correlated with several disorders. AIM: To explore the potential role of A. muciniphila as common dysbiotic marker linked to the disease status. METHODS: A cohort of patients affected by GI and EI disorders was enrolled and compared to healthy controls (CTRLs). A targeted-metagenomics approach combined to unsupervised cluster and machine learning (ML) analyses provided microbiota signatures. RESULTS: Microbiota composition was associated to disease phenotype, therapies, diet and anthropometric features, identifying phenotype and therapies as the most impacting variables on microbiota ecology. Unsupervised cluster analyses identified one cluster composed by the majority of patients. DESeq2 algorithm identified ten microbial discriminatory features of patients and CTRLs clusters. Among these microbes, Akkermansia muciniphila resulted the discriminating ML node between patients and CTRLs, independently of specific GI/EI disease or confounding effects. A. muciniphila decrease represented a transversal signature of gut microbiota alteration, showing also an inverse correlation with α-diversity. CONCLUSION: Overall, A. muciniphila decline may have a crucial role in affecting microbial ecology and in discriminating patients from healthy subjects. Its grading may be considered as a gut dysbiosis feature associated to disease-related microbiota profile.
BACKGROUND: Gut microbiota exerts a crucial role in gastrointestinal (GI) and extra-intestinal (EI) disorders. In this context, Akkermansia muciniphila is pivotal for the maintenance of host health and has been correlated with several disorders. AIM: To explore the potential role of A. muciniphila as common dysbiotic marker linked to the disease status. METHODS: A cohort of patients affected by GI and EI disorders was enrolled and compared to healthy controls (CTRLs). A targeted-metagenomics approach combined to unsupervised cluster and machine learning (ML) analyses provided microbiota signatures. RESULTS: Microbiota composition was associated to disease phenotype, therapies, diet and anthropometric features, identifying phenotype and therapies as the most impacting variables on microbiota ecology. Unsupervised cluster analyses identified one cluster composed by the majority of patients. DESeq2 algorithm identified ten microbial discriminatory features of patients and CTRLs clusters. Among these microbes, Akkermansia muciniphila resulted the discriminating ML node between patients and CTRLs, independently of specific GI/EI disease or confounding effects. A. muciniphila decrease represented a transversal signature of gut microbiota alteration, showing also an inverse correlation with α-diversity. CONCLUSION: Overall, A. muciniphila decline may have a crucial role in affecting microbial ecology and in discriminating patients from healthy subjects. Its grading may be considered as a gut dysbiosis feature associated to disease-related microbiota profile.
Authors: Ram Prasad; Bright Asare-Bediko; Angela Harbour; Jason L Floyd; Dibyendu Chakraborty; Yaqian Duan; Regina Lamendella; Justin Wright; Maria B Grant Journal: Invest Ophthalmol Vis Sci Date: 2022-01-03 Impact factor: 4.799
Authors: Lorenza Romani; Federica Del Chierico; Gabriele Macari; Stefania Pane; Maria Vittoria Ristori; Valerio Guarrasi; Simone Gardini; Giuseppe Rubens Pascucci; Nicola Cotugno; Carlo Federico Perno; Paolo Rossi; Alberto Villani; Stefania Bernardi; Andrea Campana; Paolo Palma; Lorenza Putignani Journal: Front Cell Infect Microbiol Date: 2022-07-08 Impact factor: 6.073