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 significa...

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Veröffentlicht in:Liver international 2023-06, Vol.43 (6), p.1234-1246
Hauptverfasser: Feng, Gong, Zhang, Xiaoxun, Zhang, Liangjun, Liu, Wen‐Yue, Geng, Shi, Yuan, Hai‐Yang, Sha, Jun‐Cheng, Wang, Xiao‐Dong, Sun, Dan‐Qin, Targher, Giovanni, Byrne, Christopher D., Zheng, Tian‐Lei, Ye, Feng, Zheng, Ming‐Hua, Chai, Jin
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container_end_page 1246
container_issue 6
container_start_page 1234
container_title Liver international
container_volume 43
creator Feng, Gong
Zhang, Xiaoxun
Zhang, Liangjun
Liu, Wen‐Yue
Geng, Shi
Yuan, Hai‐Yang
Sha, Jun‐Cheng
Wang, Xiao‐Dong
Sun, Dan‐Qin
Targher, Giovanni
Byrne, Christopher D.
Zheng, Tian‐Lei
Ye, Feng
Zheng, Ming‐Hua
Chai, Jin
description 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.
doi_str_mv 10.1111/liv.15565
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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.</description><identifier>ISSN: 1478-3223</identifier><identifier>EISSN: 1478-3231</identifier><identifier>DOI: 10.1111/liv.15565</identifier><identifier>PMID: 36924436</identifier><language>eng</language><publisher>United States: Wiley Subscription Services, Inc</publisher><subject>Accuracy ; Bioinformatics ; Biomarkers ; Biomarkers - metabolism ; Biopsy ; Derivation ; diagnosis ; Diagnostic systems ; Fatty liver ; Fibrosis ; Humans ; Liver ; Liver - pathology ; liver biopsy ; Liver Cirrhosis - pathology ; Liver diseases ; NAFLD ; Non-alcoholic Fatty Liver Disease - pathology ; Panels ; Proteins ; Proteomics ; Training ; urinary proteomics ; Urine</subject><ispartof>Liver international, 2023-06, Vol.43 (6), p.1234-1246</ispartof><rights>2023 John Wiley &amp; Sons A/S. Published by John Wiley &amp; Sons Ltd.</rights><rights>2023 John Wiley &amp; Sons A/S</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3535-7c2d0ea9107853940981a2d3a26cc26b776781e7ec3479904b8c96b550098e5b3</citedby><cites>FETCH-LOGICAL-c3535-7c2d0ea9107853940981a2d3a26cc26b776781e7ec3479904b8c96b550098e5b3</cites><orcidid>0000-0003-4984-2631 ; 0000-0002-8543-4566 ; 0000-0002-3892-7464 ; 0000-0002-7053-8661 ; 0000-0002-4325-3900</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fliv.15565$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fliv.15565$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36924436$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Feng, Gong</creatorcontrib><creatorcontrib>Zhang, Xiaoxun</creatorcontrib><creatorcontrib>Zhang, Liangjun</creatorcontrib><creatorcontrib>Liu, Wen‐Yue</creatorcontrib><creatorcontrib>Geng, Shi</creatorcontrib><creatorcontrib>Yuan, Hai‐Yang</creatorcontrib><creatorcontrib>Sha, Jun‐Cheng</creatorcontrib><creatorcontrib>Wang, Xiao‐Dong</creatorcontrib><creatorcontrib>Sun, Dan‐Qin</creatorcontrib><creatorcontrib>Targher, Giovanni</creatorcontrib><creatorcontrib>Byrne, Christopher D.</creatorcontrib><creatorcontrib>Zheng, Tian‐Lei</creatorcontrib><creatorcontrib>Ye, Feng</creatorcontrib><creatorcontrib>Zheng, Ming‐Hua</creatorcontrib><creatorcontrib>Chai, Jin</creatorcontrib><creatorcontrib>CHESS-MAFLD Consortium</creatorcontrib><creatorcontrib>CHESS‐MAFLD Consortium</creatorcontrib><title>Novel urinary protein panels for the non‐invasive diagnosis of non‐alcoholic fatty liver disease and fibrosis stages</title><title>Liver international</title><addtitle>Liver Int</addtitle><description>Background &amp; 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. 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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.</abstract><cop>United States</cop><pub>Wiley Subscription Services, Inc</pub><pmid>36924436</pmid><doi>10.1111/liv.15565</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0003-4984-2631</orcidid><orcidid>https://orcid.org/0000-0002-8543-4566</orcidid><orcidid>https://orcid.org/0000-0002-3892-7464</orcidid><orcidid>https://orcid.org/0000-0002-7053-8661</orcidid><orcidid>https://orcid.org/0000-0002-4325-3900</orcidid></addata></record>
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source MEDLINE; Wiley Online Library Journals Frontfile Complete
subjects Accuracy
Bioinformatics
Biomarkers
Biomarkers - metabolism
Biopsy
Derivation
diagnosis
Diagnostic systems
Fatty liver
Fibrosis
Humans
Liver
Liver - pathology
liver biopsy
Liver Cirrhosis - pathology
Liver diseases
NAFLD
Non-alcoholic Fatty Liver Disease - pathology
Panels
Proteins
Proteomics
Training
urinary proteomics
Urine
title Novel urinary protein panels for the non‐invasive diagnosis of non‐alcoholic fatty liver disease and fibrosis stages
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