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Novel urinary protein panels for the non-invasive diagnosis of non-alcoholic fatty liver disease and fibrosis stages

Novel urinary protein panels for the non-invasive diagnosis of non-alcoholic fatty liver disease and fibrosis stages
Novel urinary protein panels for the non-invasive diagnosis of non-alcoholic fatty liver disease and fibrosis stages
Background & aims: there is an unmet clinical need for non-invasive tests to diagnose non-alcoholic fatty liver disease (NAFLD) and individual fibrosis stages. We aimed to test whether urine protein panels could be used to identify NAFLD, NAFLD with fibrosis (stage F ≥ 1) and NAFLD with significant fibrosis (stage F ≥ 2).

Methods: we collected urine samples from 100 patients with biopsy-confirmed NAFLD and 40 healthy volunteers, and proteomics and bioinformatics analyses were performed in this derivation cohort. Diagnostic models were developed for detecting NAFLD (UPNAFLD model), NAFLD with fibrosis (UPfibrosis model), or NAFLD with significant fibrosis (UPsignificant fibrosis model). Subsequently, the derivation cohort was divided into training and testing sets to evaluate the efficacy of these diagnostic models. Finally, in a separate independent validation cohort of 100 patients with biopsy-confirmed NAFLD and 45 healthy controls, urinary enzyme-linked immunosorbent assay analyses were undertaken to validate the accuracy of these new diagnostic models.

Results: the UPfibrosis model and the UPsignificant fibrosis model showed an AUROC of .863 (95% CI: .725–1.000) and 0.858 (95% CI: .712–1.000) in the training set; and .837 (95% CI: .711–.963) and .916 (95% CI: .825–1.000) in the testing set respectively. The UPNAFLD model showed an excellent diagnostic performance and the area under the receiver operator characteristic curve (AUROC) exceeded .90 in the derivation cohort. In the independent validation cohort, the AUROC for all three of the above diagnostic models exceeded .80.

Conclusions: our newly developed models constructed from urine protein biomarkers have good accuracy for non-invasively diagnosing liver fibrosis in NAFLD.
NAFLD, diagnosis, fibrosis, liver biopsy, urinary proteomics
1478-3223
1234-1246
Feng, Gong
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Zhang, Xiaoxun
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Zhang, Liangjun
39206baa-8f40-41e6-b24d-af42c44bd485
Liu, Wen-Yue
117b3e15-59dd-4451-a06f-3250420a2e86
Geng, Shi
921b5a46-507b-4b04-b0b9-2e4c30ca4090
Yuan, Hai-Yang
02561bb7-5a54-4ec1-9e99-00e701364981
Sha, Jun-Cheng
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Wang, Xiao-Dong
bc16007a-52f6-4df6-af2b-454cfd65e054
Sun, Dan-Qin
50ecf2c0-6667-4a2a-a65a-35f45625f568
Targher, Giovanni
f257117e-c087-410b-bd95-01223382897c
Byrne, Christopher
1370b997-cead-4229-83a7-53301ed2a43c
Zheng, Tian-Lei
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Ye, Feng
bfb1e5b8-a561-4059-be84-be8d55aefdd3
Zheng, Ming-Hua
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Chai, Jin
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CHESS-MAFLD consortium
Feng, Gong
d1a23667-befc-4d07-814a-f35bf4d21a81
Zhang, Xiaoxun
e2351cea-bc58-4d9c-abf7-38e69a133ef5
Zhang, Liangjun
39206baa-8f40-41e6-b24d-af42c44bd485
Liu, Wen-Yue
117b3e15-59dd-4451-a06f-3250420a2e86
Geng, Shi
921b5a46-507b-4b04-b0b9-2e4c30ca4090
Yuan, Hai-Yang
02561bb7-5a54-4ec1-9e99-00e701364981
Sha, Jun-Cheng
834194e8-0ea4-42e4-9805-5446bb1c281a
Wang, Xiao-Dong
bc16007a-52f6-4df6-af2b-454cfd65e054
Sun, Dan-Qin
50ecf2c0-6667-4a2a-a65a-35f45625f568
Targher, Giovanni
f257117e-c087-410b-bd95-01223382897c
Byrne, Christopher
1370b997-cead-4229-83a7-53301ed2a43c
Zheng, Tian-Lei
6c92a484-eade-4b1f-b65b-81a5835c64a4
Ye, Feng
bfb1e5b8-a561-4059-be84-be8d55aefdd3
Zheng, Ming-Hua
6e34ff74-9a5f-4039-8e9c-3a1243ac93bd
Chai, Jin
75e7f818-7d6e-4e1d-be78-c0fc7a6be9c4

CHESS-MAFLD consortium (2023) Novel urinary protein panels for the non-invasive diagnosis of non-alcoholic fatty liver disease and fibrosis stages. Liver International, 43 (6), 1234-1246. (doi:10.1111/liv.15565).

Record type: Article

Abstract

Background & aims: there is an unmet clinical need for non-invasive tests to diagnose non-alcoholic fatty liver disease (NAFLD) and individual fibrosis stages. We aimed to test whether urine protein panels could be used to identify NAFLD, NAFLD with fibrosis (stage F ≥ 1) and NAFLD with significant fibrosis (stage F ≥ 2).

Methods: we collected urine samples from 100 patients with biopsy-confirmed NAFLD and 40 healthy volunteers, and proteomics and bioinformatics analyses were performed in this derivation cohort. Diagnostic models were developed for detecting NAFLD (UPNAFLD model), NAFLD with fibrosis (UPfibrosis model), or NAFLD with significant fibrosis (UPsignificant fibrosis model). Subsequently, the derivation cohort was divided into training and testing sets to evaluate the efficacy of these diagnostic models. Finally, in a separate independent validation cohort of 100 patients with biopsy-confirmed NAFLD and 45 healthy controls, urinary enzyme-linked immunosorbent assay analyses were undertaken to validate the accuracy of these new diagnostic models.

Results: the UPfibrosis model and the UPsignificant fibrosis model showed an AUROC of .863 (95% CI: .725–1.000) and 0.858 (95% CI: .712–1.000) in the training set; and .837 (95% CI: .711–.963) and .916 (95% CI: .825–1.000) in the testing set respectively. The UPNAFLD model showed an excellent diagnostic performance and the area under the receiver operator characteristic curve (AUROC) exceeded .90 in the derivation cohort. In the independent validation cohort, the AUROC for all three of the above diagnostic models exceeded .80.

Conclusions: our newly developed models constructed from urine protein biomarkers have good accuracy for non-invasively diagnosing liver fibrosis in NAFLD.

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Accepted/In Press date: 10 March 2023
e-pub ahead of print date: 16 March 2023
Published date: 1 June 2023
Additional Information: Funding Information: This work was supported by grants from the National Natural Science Foundation of China ( 92268110 and 82 070 588), the Outstanding Youth Foundation of Chongqing (cstc2021jcyj‐jqX0005) and the Project of Chongqing University Innovation Research Group (2021cqspt01). GT is supported in part by grants from the School of Medicine, University of Verona, Verona, Italy. CDB is supported in part by the Southampton NIHR Biomedical Research Centre (NIHR203319), UK. Publisher Copyright: © 2023 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Keywords: NAFLD, diagnosis, fibrosis, liver biopsy, urinary proteomics

Identifiers

Local EPrints ID: 477155
URI: http://eprints.soton.ac.uk/id/eprint/477155
ISSN: 1478-3223
PURE UUID: cef14e5a-e980-4505-9cb9-4df6a0c3904d
ORCID for Christopher Byrne: ORCID iD orcid.org/0000-0001-6322-7753

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Date deposited: 30 May 2023 16:41
Last modified: 18 Mar 2024 05:30

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Contributors

Author: Gong Feng
Author: Xiaoxun Zhang
Author: Liangjun Zhang
Author: Wen-Yue Liu
Author: Shi Geng
Author: Hai-Yang Yuan
Author: Jun-Cheng Sha
Author: Xiao-Dong Wang
Author: Dan-Qin Sun
Author: Giovanni Targher
Author: Tian-Lei Zheng
Author: Feng Ye
Author: Ming-Hua Zheng
Author: Jin Chai
Corporate Author: CHESS-MAFLD consortium

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