Flavia Noelia Mazzini1, Frank Cook2, John Gounarides2, Sebastián Marciano3, Leila Haddad3, Ana Jesica Tamaroff4, Paola Casciato3, Adrián Narvaez3, María Florencia Mascardi1, Margarita Anders5, Federico Orozco5, Nicolás Quiróz1, Marcelo Risk1, Susana Gutt4, Adrián Gadano3, Celia Méndez García6, Martin L Marro7, Alberto Penas-Steinhardt8, Julieta Trinks9. 1. Instituto de Medicina Traslacional e Ingeniería Biomédica (IMTIB) - CONICET - Instituto Universitario del Hospital Italiano (IUHI) - Hospital Italiano de Buenos Aires (HIBA), Potosí 4240, C1199ACL, Ciudad Autónoma de Buenos Aires, Argentina. 2. Analytical Sciences & Imaging (AS&I) Department, Novartis Institutes for Biomedical Research (NIBR), Cambridge, MA, USA. 3. Liver Unit of Hospital Italiano de Buenos Aires, Ciudad Autónoma de Buenos Aires, Argentina. 4. Nutrition Department of Hospital Italiano de Buenos Aires, Ciudad Autónoma de Buenos Aires, Argentina. 5. Liver Unit of Hospital Alemán, Ciudad Autónoma de Buenos Aires, Argentina. 6. Chemical Biology & Therapeutics (CBT) Department, NIBR, Cambridge, MA, USA. 7. Cardiovascular and Metabolic Disease Area, NIBR, Cambridge, MA, USA. 8. Laboratorio de Genómica Computacional, Departamento de Ciencias Básicas, Universidad Nacional de Luján, Luján, Buenos Aires, Argentina. 9. Instituto de Medicina Traslacional e Ingeniería Biomédica (IMTIB) - CONICET - Instituto Universitario del Hospital Italiano (IUHI) - Hospital Italiano de Buenos Aires (HIBA), Potosí 4240, C1199ACL, Ciudad Autónoma de Buenos Aires, Argentina. julieta.trinks@hospitalitaliano.org.ar.
Abstract
INTRODUCTION: Non-invasive biomarkers are needed for metabolic dysfunction-associated fatty liver disease (MAFLD), especially for patients at risk of disease progression in high-prevalence areas. The microbiota and its metabolites represent a niche for MAFLD biomarker discovery. However, studies are not reproducible as the microbiota is variable. OBJECTIVES: We aimed to identify microbiota-derived metabolomic biomarkers that may contribute to the higher MAFLD prevalence and different disease severity in Latin America, where data is scarce. METHODS: We compared the plasma and stool metabolomes, gene patatin-like phospholipase domain-containing 3 (PNPLA3) rs738409 single nucleotide polymorphism (SNP), diet, demographic and clinical data of 33 patients (12 simple steatosis and 21 steatohepatitis) and 19 healthy volunteers (HV). The potential predictive utility of the identified biomarkers for MAFLD diagnosis and progression was evaluated by logistic regression modelling and ROC curves. RESULTS: Twenty-four (22 in plasma and 2 in stool) out of 424 metabolites differed among groups. Plasma triglyceride (TG) levels were higher among MAFLD patients, whereas plasma phosphatidylcholine (PC) and lysoPC levels were lower among HV. The PNPLA3 risk genotype was related to higher plasma levels of eicosenoic acid or fatty acid 20:1 (FA(20:1)). Body mass index and plasma levels of PCaaC24:0, FA(20:1) and TG (16:1_34:1) showed the best AUROC for MAFLD diagnosis, whereas steatosis and steatohepatitis could be discriminated with plasma levels of PCaaC24:0 and PCaeC40:1. CONCLUSION: This study identified for the first time MAFLD potential non-invasive biomarkers in a Latin American population. The association of PNPLA3 genotype with FA(20:1) suggests a novel metabolic pathway influencing MAFLD pathogenesis.
INTRODUCTION: Non-invasive biomarkers are needed for metabolic dysfunction-associated fatty liver disease (MAFLD), especially for patients at risk of disease progression in high-prevalence areas. The microbiota and its metabolites represent a niche for MAFLD biomarker discovery. However, studies are not reproducible as the microbiota is variable. OBJECTIVES: We aimed to identify microbiota-derived metabolomic biomarkers that may contribute to the higher MAFLD prevalence and different disease severity in Latin America, where data is scarce. METHODS: We compared the plasma and stool metabolomes, gene patatin-like phospholipase domain-containing 3 (PNPLA3) rs738409 single nucleotide polymorphism (SNP), diet, demographic and clinical data of 33 patients (12 simple steatosis and 21 steatohepatitis) and 19 healthy volunteers (HV). The potential predictive utility of the identified biomarkers for MAFLD diagnosis and progression was evaluated by logistic regression modelling and ROC curves. RESULTS: Twenty-four (22 in plasma and 2 in stool) out of 424 metabolites differed among groups. Plasma triglyceride (TG) levels were higher among MAFLD patients, whereas plasma phosphatidylcholine (PC) and lysoPC levels were lower among HV. The PNPLA3 risk genotype was related to higher plasma levels of eicosenoic acid or fatty acid 20:1 (FA(20:1)). Body mass index and plasma levels of PCaaC24:0, FA(20:1) and TG (16:1_34:1) showed the best AUROC for MAFLD diagnosis, whereas steatosis and steatohepatitis could be discriminated with plasma levels of PCaaC24:0 and PCaeC40:1. CONCLUSION: This study identified for the first time MAFLD potential non-invasive biomarkers in a Latin American population. The association of PNPLA3 genotype with FA(20:1) suggests a novel metabolic pathway influencing MAFLD pathogenesis.
Authors: Mohammed Eslam; Philip N Newsome; Shiv K Sarin; Quentin M Anstee; Giovanni Targher; Manuel Romero-Gomez; Shira Zelber-Sagi; Vincent Wai-Sun Wong; Jean-François Dufour; Jörn M Schattenberg; Takumi Kawaguchi; Marco Arrese; Luca Valenti; Gamal Shiha; Claudio Tiribelli; Hannele Yki-Järvinen; Jian-Gao Fan; Henning Grønbæk; Yusuf Yilmaz; Helena Cortez-Pinto; Claudia P Oliveira; Pierre Bedossa; Leon A Adams; Ming-Hua Zheng; Yasser Fouad; Wah-Kheong Chan; Nahum Mendez-Sanchez; Sang Hoon Ahn; Laurent Castera; Elisabetta Bugianesi; Vlad Ratziu; Jacob George Journal: J Hepatol Date: 2020-04-08 Impact factor: 25.083
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Authors: Raimunda S S Azevedo; Jorge R de Sousa; Marialva T F Araujo; Arnaldo J Martins Filho; Bianca N de Alcantara; Fernanda M C Araujo; Maria G L Queiroz; Ana C R Cruz; Beatriz H Baldez Vasconcelos; Jannifer O Chiang; Lívia C Martins; Livia M N Casseb; Eliana V da Silva; Valéria L Carvalho; Barbara C Baldez Vasconcelos; Sueli G Rodrigues; Consuelo S Oliveira; Juarez A S Quaresma; Pedro F C Vasconcelos Journal: Sci Rep Date: 2018-01-08 Impact factor: 4.379
Authors: Jacobo de la Cuesta-Zuluaga; Scott T Kelley; Yingfeng Chen; Juan S Escobar; Noel T Mueller; Ruth E Ley; Daniel McDonald; Shi Huang; Austin D Swafford; Rob Knight; Varykina G Thackray Journal: mSystems Date: 2019-05-14 Impact factor: 6.496