Accurate liquid biopsy for the diagnosis of non-Alcoholic steatohepatitis and liver fibrosis

Giulia Angelini; Simona Panunzi; Lidia Castagneto-Gissey; Francesca Pellicanò; Andrea De Gaetano; Maurizio Pompili; Laura Riccardi; Matteo Garcovich; Marco Raffaelli; Luigi Ciccoritti; Ornella Verrastro; Maria Francesca Russo; Fabio Maria Vecchio; Giovanni Casella; James Casella-Mariolo; Luigi Papa; Pier Luigi Marini; Francesco Rubino; Carel W. Le Roux; Stefan Bornstein; Geltrude Mingrone

doi:10.1136/gutjnl-2022-327498

Accurate liquid biopsy for the diagnosis of non-Alcoholic steatohepatitis and liver fibrosis

Giulia Angelini, Simona Panunzi, Lidia Castagneto-Gissey, Francesca Pellicanò, Andrea De Gaetano, Maurizio Pompili, Laura Riccardi, Matteo Garcovich, Marco Raffaelli, Luigi Ciccoritti, Ornella Verrastro, Maria Francesca Russo, Fabio Maria Vecchio, Giovanni Casella, James Casella-Mariolo, Luigi Papa, Pier Luigi Marini, Francesco Rubino, Carel W. Le Roux, Stefan BornsteinGeltrude Mingrone^*

^*Corresponding author for this work

Diabetes

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Abstract

Objective: Clinical diagnosis and approval of new medications for non-Alcoholic steatohepatitis (NASH) require invasive liver biopsies. The aim of our study was to identify non-invasive biomarkers of NASH and/or liver fibrosis. Design: This multicentre study includes 250 patients (discovery cohort, n=100 subjects (Bariatric Surgery Versus Non-Alcoholic Steato-hepatitis-BRAVES trial); validation cohort, n=150 (Liquid Biopsy for NASH and Liver Fibrosis-LIBRA trial)) with histologically proven non-Alcoholic fatty liver (NAFL) or NASH with or without fibrosis. Proteomics was performed in monocytes and hepatic stellate cells (HSCs) with iTRAQ-nano-Liquid Chromatography-Mass Spectrometry/Mass Spectrometry (LC-MS/MS), while flow cytometry measured perilipin-2 (PLIN2) and RAB14 in peripheral blood CD14+CD16- monocytes. Neural network classifiers were used to predict presence/absence of NASH and NASH stages. Logistic bootstrap-based regression was used to measure the accuracy of predicting liver fibrosis. Results: The algorithm for NASH using PLIN2 mean florescence intensity (MFI) combined with waist circumference, triglyceride, alanine aminotransferase (ALT) and presence/absence of diabetes as covariates had an accuracy of 93% in the discovery cohort and of 92% in the validation cohort. Sensitivity and specificity were 95% and 90% in the discovery cohort and 88% and 100% in the validation cohort, respectively. The area under the receiver operating characteristic (AUROC) for NAS level prediction ranged from 83.7% (CI 75.6% to 91.8%) in the discovery cohort to 97.8% (CI 95.8% to 99.8%) in the validation cohort. The algorithm including RAB14 MFI, age, waist circumference, high-density lipoprotein cholesterol, plasma glucose and ALT levels as covariates to predict the presence of liver fibrosis yielded an AUROC of 95.9% (CI 87.9% to 100%) in the discovery cohort and 99.3% (CI 98.1% to 100%) in the validation cohort, respectively. Accuracy was 99.25%, sensitivity 100% and specificity 95.8% in the discovery cohort and 97.6%, 99% and 89.6% in the validation cohort. This novel biomarker was superior to currently used FIB4, non-Alcoholic fatty liver disease fibrosis score and aspartate aminotransferase (AST)-To-platelet ratio and was comparable to ultrasound two-dimensional shear wave elastography. Conclusions: The proposed novel liquid biopsy is accurate, sensitive and specific in diagnosing the presence and severity of NASH or liver fibrosis and is more reliable than currently used biomarkers. Clinical trials: Discovery multicentre cohort: Bariatric Surgery versus Non-Alcoholic Steatohepatitis, BRAVES, ClinicalTrials.gov identifier: NCT03524365. Validation multicentre cohort: Liquid Biopsy for NASH and Fibrosis, LIBRA, ClinicalTrials.gov identifier: NCT04677101.

Original language	English
Article number	327498
Journal	Gut
Early online date	12 Jul 2022
DOIs	https://doi.org/10.1136/gutjnl-2022-327498
Publication status	E-pub ahead of print - 12 Jul 2022

Keywords

HEPATIC FIBROSIS
NONALCOHOLIC STEATOHEPATITIS

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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Angelini, G., Panunzi, S., Castagneto-Gissey, L., Pellicanò, F., De Gaetano, A., Pompili, M., Riccardi, L., Garcovich, M., Raffaelli, M., Ciccoritti, L., Verrastro, O., Russo, M. F., Vecchio, F. M., Casella, G., Casella-Mariolo, J., Papa, L., Marini, P. L., Rubino, F., Le Roux, C. W., ... Mingrone, G. (2022). Accurate liquid biopsy for the diagnosis of non-Alcoholic steatohepatitis and liver fibrosis. Gut, [327498]. https://doi.org/10.1136/gutjnl-2022-327498

@article{46f0388f8d0d46e3bddcc854d2f24f80,

title = "Accurate liquid biopsy for the diagnosis of non-Alcoholic steatohepatitis and liver fibrosis",

abstract = "Objective: Clinical diagnosis and approval of new medications for non-Alcoholic steatohepatitis (NASH) require invasive liver biopsies. The aim of our study was to identify non-invasive biomarkers of NASH and/or liver fibrosis. Design: This multicentre study includes 250 patients (discovery cohort, n=100 subjects (Bariatric Surgery Versus Non-Alcoholic Steato-hepatitis-BRAVES trial); validation cohort, n=150 (Liquid Biopsy for NASH and Liver Fibrosis-LIBRA trial)) with histologically proven non-Alcoholic fatty liver (NAFL) or NASH with or without fibrosis. Proteomics was performed in monocytes and hepatic stellate cells (HSCs) with iTRAQ-nano-Liquid Chromatography-Mass Spectrometry/Mass Spectrometry (LC-MS/MS), while flow cytometry measured perilipin-2 (PLIN2) and RAB14 in peripheral blood CD14+CD16- monocytes. Neural network classifiers were used to predict presence/absence of NASH and NASH stages. Logistic bootstrap-based regression was used to measure the accuracy of predicting liver fibrosis. Results: The algorithm for NASH using PLIN2 mean florescence intensity (MFI) combined with waist circumference, triglyceride, alanine aminotransferase (ALT) and presence/absence of diabetes as covariates had an accuracy of 93% in the discovery cohort and of 92% in the validation cohort. Sensitivity and specificity were 95% and 90% in the discovery cohort and 88% and 100% in the validation cohort, respectively. The area under the receiver operating characteristic (AUROC) for NAS level prediction ranged from 83.7% (CI 75.6% to 91.8%) in the discovery cohort to 97.8% (CI 95.8% to 99.8%) in the validation cohort. The algorithm including RAB14 MFI, age, waist circumference, high-density lipoprotein cholesterol, plasma glucose and ALT levels as covariates to predict the presence of liver fibrosis yielded an AUROC of 95.9% (CI 87.9% to 100%) in the discovery cohort and 99.3% (CI 98.1% to 100%) in the validation cohort, respectively. Accuracy was 99.25%, sensitivity 100% and specificity 95.8% in the discovery cohort and 97.6%, 99% and 89.6% in the validation cohort. This novel biomarker was superior to currently used FIB4, non-Alcoholic fatty liver disease fibrosis score and aspartate aminotransferase (AST)-To-platelet ratio and was comparable to ultrasound two-dimensional shear wave elastography. Conclusions: The proposed novel liquid biopsy is accurate, sensitive and specific in diagnosing the presence and severity of NASH or liver fibrosis and is more reliable than currently used biomarkers. Clinical trials: Discovery multicentre cohort: Bariatric Surgery versus Non-Alcoholic Steatohepatitis, BRAVES, ClinicalTrials.gov identifier: NCT03524365. Validation multicentre cohort: Liquid Biopsy for NASH and Fibrosis, LIBRA, ClinicalTrials.gov identifier: NCT04677101.",

keywords = "HEPATIC FIBROSIS, NONALCOHOLIC STEATOHEPATITIS",

author = "Giulia Angelini and Simona Panunzi and Lidia Castagneto-Gissey and Francesca Pellican{\`o} and {De Gaetano}, Andrea and Maurizio Pompili and Laura Riccardi and Matteo Garcovich and Marco Raffaelli and Luigi Ciccoritti and Ornella Verrastro and Russo, {Maria Francesca} and Vecchio, {Fabio Maria} and Giovanni Casella and James Casella-Mariolo and Luigi Papa and Marini, {Pier Luigi} and Francesco Rubino and {Le Roux}, {Carel W.} and Stefan Bornstein and Geltrude Mingrone",

note = "Funding Information: Microbesomics: effect of gut microbiome on 'obesitypes' in human subjects (PRIN 2017 n. 2017FM74HK_004), Elucidating Pathways of Steatohepatitis (EPoS) (EPOS Horizon 2020 n. MIN-EPO-17-013), Stratification of Obese Phenotypes to Optimize Future Obesity Therapy (SOPHIA IMI n. 875534). Metadeq Inc. GM and SB acknowledge support from the Transcampus Initiative. Publisher Copyright: {\textcopyright} Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.",

year = "2022",

month = jul,

day = "12",

doi = "10.1136/gutjnl-2022-327498",

language = "English",

journal = "Gut",

issn = "0017-5749",

publisher = "BMJ Publishing Group",

}

Angelini, G, Panunzi, S, Castagneto-Gissey, L, Pellicanò, F, De Gaetano, A, Pompili, M, Riccardi, L, Garcovich, M, Raffaelli, M, Ciccoritti, L, Verrastro, O, Russo, MF, Vecchio, FM, Casella, G, Casella-Mariolo, J, Papa, L, Marini, PL, Rubino, F, Le Roux, CW, Bornstein, S & Mingrone, G 2022, 'Accurate liquid biopsy for the diagnosis of non-Alcoholic steatohepatitis and liver fibrosis', Gut. https://doi.org/10.1136/gutjnl-2022-327498

TY - JOUR

T1 - Accurate liquid biopsy for the diagnosis of non-Alcoholic steatohepatitis and liver fibrosis

AU - Angelini, Giulia

AU - Panunzi, Simona

AU - Castagneto-Gissey, Lidia

AU - Pellicanò, Francesca

AU - De Gaetano, Andrea

AU - Pompili, Maurizio

AU - Riccardi, Laura

AU - Garcovich, Matteo

AU - Raffaelli, Marco

AU - Ciccoritti, Luigi

AU - Verrastro, Ornella

AU - Russo, Maria Francesca

AU - Vecchio, Fabio Maria

AU - Casella, Giovanni

AU - Casella-Mariolo, James

AU - Papa, Luigi

AU - Marini, Pier Luigi

AU - Rubino, Francesco

AU - Le Roux, Carel W.

AU - Bornstein, Stefan

AU - Mingrone, Geltrude

N1 - Funding Information: Microbesomics: effect of gut microbiome on 'obesitypes' in human subjects (PRIN 2017 n. 2017FM74HK_004), Elucidating Pathways of Steatohepatitis (EPoS) (EPOS Horizon 2020 n. MIN-EPO-17-013), Stratification of Obese Phenotypes to Optimize Future Obesity Therapy (SOPHIA IMI n. 875534). Metadeq Inc. GM and SB acknowledge support from the Transcampus Initiative. Publisher Copyright: © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

PY - 2022/7/12

Y1 - 2022/7/12

N2 - Objective: Clinical diagnosis and approval of new medications for non-Alcoholic steatohepatitis (NASH) require invasive liver biopsies. The aim of our study was to identify non-invasive biomarkers of NASH and/or liver fibrosis. Design: This multicentre study includes 250 patients (discovery cohort, n=100 subjects (Bariatric Surgery Versus Non-Alcoholic Steato-hepatitis-BRAVES trial); validation cohort, n=150 (Liquid Biopsy for NASH and Liver Fibrosis-LIBRA trial)) with histologically proven non-Alcoholic fatty liver (NAFL) or NASH with or without fibrosis. Proteomics was performed in monocytes and hepatic stellate cells (HSCs) with iTRAQ-nano-Liquid Chromatography-Mass Spectrometry/Mass Spectrometry (LC-MS/MS), while flow cytometry measured perilipin-2 (PLIN2) and RAB14 in peripheral blood CD14+CD16- monocytes. Neural network classifiers were used to predict presence/absence of NASH and NASH stages. Logistic bootstrap-based regression was used to measure the accuracy of predicting liver fibrosis. Results: The algorithm for NASH using PLIN2 mean florescence intensity (MFI) combined with waist circumference, triglyceride, alanine aminotransferase (ALT) and presence/absence of diabetes as covariates had an accuracy of 93% in the discovery cohort and of 92% in the validation cohort. Sensitivity and specificity were 95% and 90% in the discovery cohort and 88% and 100% in the validation cohort, respectively. The area under the receiver operating characteristic (AUROC) for NAS level prediction ranged from 83.7% (CI 75.6% to 91.8%) in the discovery cohort to 97.8% (CI 95.8% to 99.8%) in the validation cohort. The algorithm including RAB14 MFI, age, waist circumference, high-density lipoprotein cholesterol, plasma glucose and ALT levels as covariates to predict the presence of liver fibrosis yielded an AUROC of 95.9% (CI 87.9% to 100%) in the discovery cohort and 99.3% (CI 98.1% to 100%) in the validation cohort, respectively. Accuracy was 99.25%, sensitivity 100% and specificity 95.8% in the discovery cohort and 97.6%, 99% and 89.6% in the validation cohort. This novel biomarker was superior to currently used FIB4, non-Alcoholic fatty liver disease fibrosis score and aspartate aminotransferase (AST)-To-platelet ratio and was comparable to ultrasound two-dimensional shear wave elastography. Conclusions: The proposed novel liquid biopsy is accurate, sensitive and specific in diagnosing the presence and severity of NASH or liver fibrosis and is more reliable than currently used biomarkers. Clinical trials: Discovery multicentre cohort: Bariatric Surgery versus Non-Alcoholic Steatohepatitis, BRAVES, ClinicalTrials.gov identifier: NCT03524365. Validation multicentre cohort: Liquid Biopsy for NASH and Fibrosis, LIBRA, ClinicalTrials.gov identifier: NCT04677101.

AB - Objective: Clinical diagnosis and approval of new medications for non-Alcoholic steatohepatitis (NASH) require invasive liver biopsies. The aim of our study was to identify non-invasive biomarkers of NASH and/or liver fibrosis. Design: This multicentre study includes 250 patients (discovery cohort, n=100 subjects (Bariatric Surgery Versus Non-Alcoholic Steato-hepatitis-BRAVES trial); validation cohort, n=150 (Liquid Biopsy for NASH and Liver Fibrosis-LIBRA trial)) with histologically proven non-Alcoholic fatty liver (NAFL) or NASH with or without fibrosis. Proteomics was performed in monocytes and hepatic stellate cells (HSCs) with iTRAQ-nano-Liquid Chromatography-Mass Spectrometry/Mass Spectrometry (LC-MS/MS), while flow cytometry measured perilipin-2 (PLIN2) and RAB14 in peripheral blood CD14+CD16- monocytes. Neural network classifiers were used to predict presence/absence of NASH and NASH stages. Logistic bootstrap-based regression was used to measure the accuracy of predicting liver fibrosis. Results: The algorithm for NASH using PLIN2 mean florescence intensity (MFI) combined with waist circumference, triglyceride, alanine aminotransferase (ALT) and presence/absence of diabetes as covariates had an accuracy of 93% in the discovery cohort and of 92% in the validation cohort. Sensitivity and specificity were 95% and 90% in the discovery cohort and 88% and 100% in the validation cohort, respectively. The area under the receiver operating characteristic (AUROC) for NAS level prediction ranged from 83.7% (CI 75.6% to 91.8%) in the discovery cohort to 97.8% (CI 95.8% to 99.8%) in the validation cohort. The algorithm including RAB14 MFI, age, waist circumference, high-density lipoprotein cholesterol, plasma glucose and ALT levels as covariates to predict the presence of liver fibrosis yielded an AUROC of 95.9% (CI 87.9% to 100%) in the discovery cohort and 99.3% (CI 98.1% to 100%) in the validation cohort, respectively. Accuracy was 99.25%, sensitivity 100% and specificity 95.8% in the discovery cohort and 97.6%, 99% and 89.6% in the validation cohort. This novel biomarker was superior to currently used FIB4, non-Alcoholic fatty liver disease fibrosis score and aspartate aminotransferase (AST)-To-platelet ratio and was comparable to ultrasound two-dimensional shear wave elastography. Conclusions: The proposed novel liquid biopsy is accurate, sensitive and specific in diagnosing the presence and severity of NASH or liver fibrosis and is more reliable than currently used biomarkers. Clinical trials: Discovery multicentre cohort: Bariatric Surgery versus Non-Alcoholic Steatohepatitis, BRAVES, ClinicalTrials.gov identifier: NCT03524365. Validation multicentre cohort: Liquid Biopsy for NASH and Fibrosis, LIBRA, ClinicalTrials.gov identifier: NCT04677101.

KW - HEPATIC FIBROSIS

KW - NONALCOHOLIC STEATOHEPATITIS

UR - http://www.scopus.com/inward/record.url?scp=85134754072&partnerID=8YFLogxK

U2 - 10.1136/gutjnl-2022-327498

DO - 10.1136/gutjnl-2022-327498

M3 - Article

C2 - 35820779

AN - SCOPUS:85134754072

SN - 0017-5749

JO - Gut

JF - Gut

M1 - 327498

ER -

Accurate liquid biopsy for the diagnosis of non-Alcoholic steatohepatitis and liver fibrosis

Abstract

Keywords

UN SDGs

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