Plasma and stool metabolomic biomarkers of non-alcoholic fatty liver disease in Argentina

MAZZINI, FLAVIA; MARCIANO, SEBASTIÁN; CASCIATO, PAOLA; ANDERS, MARGARITA; RISK, MARCELO; MENDEZ GARCIA, CELIA; TRINKS, JULIETA; GOUNARIDES, JOHN; TAMAROFF, ANA JESICA; MASCARDI, MARIA FLORENCIA; QUIROZ, NICOLAS; GADANO, ADRIÁN; PENAS STEINHARDT, ALBERTO; COOK, FRANK; HADDAD, LEILA; NARVAEZ, ADRIÁN; OROZCO GANEM, ORLANDO NICOLAS FEDERICO; GUTT, SUSANA; MARRO, MARTIN; MAZZINI, FLAVIA; MARCIANO, SEBASTIÁN; CASCIATO, PAOLA; ANDERS, MARGARITA; RISK, MARCELO; MENDEZ GARCIA, CELIA; TRINKS, JULIETA; GOUNARIDES, JOHN; TAMAROFF, ANA JESICA; MASCARDI, MARIA FLORENCIA; QUIROZ, NICOLAS; GADANO, ADRIÁN; PENAS STEINHARDT, ALBERTO; COOK, FRANK; HADDAD, LEILA; NARVAEZ, ADRIÁN; OROZCO GANEM, ORLANDO NICOLAS FEDERICO; GUTT, SUSANA; MARRO, MARTIN

Congreso; The Liver Meeting Digital Experience 2020; 2020

American Association for the Study of Liver Diseases

Background: Non-invasive biomarkers are urgently needed to identify patients with non-alcoholic fatty liver disease (NAFLD) at risk of disease progression, particularly in high prevalence areas such as Latin America In this regard, targeted metabolomics is a powerful technology for discovering new gut microbiome-derived metabolites Thus, we aimed to identify potential metabolomic biomarkers related to NAFLD stage in Argentina, and to assess their relationship with clinical and host genetic factors Methods: Adult healthy volunteers (HV), biopsy-proven simple steatosis (SS) and non-alcoholic steatohepatitis (NASH) patients were recruitedDemographic, clinical and food frequency consumption data, as well as plasma and stool samples were collected SNP rs738409 (PNPLA3 gene) was determined in all volunteers HPLC and flow injection analysis with MS/MS in tandem was applied for metabolomic studies using the MxP Quant 500 Kit (Biocrates Life Sciences AG, Austria). Significantly different metabolites among groups were identified with MetaboAnalyst v4 0 Bivariate and multivariate analyses were used to identify variables that were independently related toNAFLD stage Forward stepwise logistic regression models were constructed to design the best feature combination that could distinguish between study groups Receiver Operating Characteristic (ROC) curves were used to evaluate models? accuracy. Results: 19 HV, 12 SS and 22 NASH patients were included in the study Diet was similar between groups The concentrations of 33 out of the 424 detected metabolites (25 in plasma and 8 in stool) were significantly different among study groups Levels of triglycerides (TG) were higher among NAFLD patients, whereas levels of phosphatidylcholines (PC) and lysoPC were higher among HV The PNPLA3 risk genotype for NAFLD and NASH (GG) was related to higher plasma levels of eicosenoic acid FA(20:1) (p