Noninvasive proteomic biomarkers for alcohol-related liver disease
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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Noninvasive proteomic biomarkers for alcohol-related liver disease. / Niu, Lili; Thiele, Maja; Geyer, Philipp E.; Rasmussen, Ditlev Nytoft; Webel, Henry Emanuel; Santos, Alberto; Gupta, Rajat; Meier, Florian; Strauss, Maximilian; Kjaergaard, Maria; Lindvig, Katrine; Jacobsen, Suganya; Rasmussen, Simon; Hansen, Torben; Krag, Aleksander; Mann, Matthias.
I: Nature Medicine, Bind 28, Nr. 6, 2022, s. 1277-1287.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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T1 - Noninvasive proteomic biomarkers for alcohol-related liver disease
AU - Niu, Lili
AU - Thiele, Maja
AU - Geyer, Philipp E.
AU - Rasmussen, Ditlev Nytoft
AU - Webel, Henry Emanuel
AU - Santos, Alberto
AU - Gupta, Rajat
AU - Meier, Florian
AU - Strauss, Maximilian
AU - Kjaergaard, Maria
AU - Lindvig, Katrine
AU - Jacobsen, Suganya
AU - Rasmussen, Simon
AU - Hansen, Torben
AU - Krag, Aleksander
AU - Mann, Matthias
N1 - © 2022. The Author(s).
PY - 2022
Y1 - 2022
N2 - Alcohol-related liver disease (ALD) is a major cause of liver-related death worldwide, yet understanding of the three key pathological features of the disease-fibrosis, inflammation and steatosis-remains incomplete. Here, we present a paired liver-plasma proteomics approach to infer molecular pathophysiology and to explore the diagnostic and prognostic capability of plasma proteomics in 596 individuals (137 controls and 459 individuals with ALD), 360 of whom had biopsy-based histological assessment. We analyzed all plasma samples and 79 liver biopsies using a mass spectrometry (MS)-based proteomics workflow with short gradient times and an enhanced, data-independent acquisition scheme in only 3 weeks of measurement time. In plasma and liver biopsy tissues, metabolic functions were downregulated whereas fibrosis-associated signaling and immune responses were upregulated. Machine learning models identified proteomics biomarker panels that detected significant fibrosis (receiver operating characteristic-area under the curve (ROC-AUC), 0.92, accuracy, 0.82) and mild inflammation (ROC-AUC, 0.87, accuracy, 0.79) more accurately than existing clinical assays (DeLong's test, P < 0.05). These biomarker panels were found to be accurate in prediction of future liver-related events and all-cause mortality, with a Harrell's C-index of 0.90 and 0.79, respectively. An independent validation cohort reproduced the diagnostic model performance, laying the foundation for routine MS-based liver disease testing.
AB - Alcohol-related liver disease (ALD) is a major cause of liver-related death worldwide, yet understanding of the three key pathological features of the disease-fibrosis, inflammation and steatosis-remains incomplete. Here, we present a paired liver-plasma proteomics approach to infer molecular pathophysiology and to explore the diagnostic and prognostic capability of plasma proteomics in 596 individuals (137 controls and 459 individuals with ALD), 360 of whom had biopsy-based histological assessment. We analyzed all plasma samples and 79 liver biopsies using a mass spectrometry (MS)-based proteomics workflow with short gradient times and an enhanced, data-independent acquisition scheme in only 3 weeks of measurement time. In plasma and liver biopsy tissues, metabolic functions were downregulated whereas fibrosis-associated signaling and immune responses were upregulated. Machine learning models identified proteomics biomarker panels that detected significant fibrosis (receiver operating characteristic-area under the curve (ROC-AUC), 0.92, accuracy, 0.82) and mild inflammation (ROC-AUC, 0.87, accuracy, 0.79) more accurately than existing clinical assays (DeLong's test, P < 0.05). These biomarker panels were found to be accurate in prediction of future liver-related events and all-cause mortality, with a Harrell's C-index of 0.90 and 0.79, respectively. An independent validation cohort reproduced the diagnostic model performance, laying the foundation for routine MS-based liver disease testing.
U2 - 10.1038/s41591-022-01850-y
DO - 10.1038/s41591-022-01850-y
M3 - Journal article
C2 - 35654907
VL - 28
SP - 1277
EP - 1287
JO - Nature Medicine
JF - Nature Medicine
SN - 1078-8956
IS - 6
ER -
ID: 310847140