Noninvasive proteomic biomarkers for alcohol-related liver disease

Research output: Contribution to journalJournal articlepeer-review

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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.

In: Nature Medicine, Vol. 28, No. 6, 2022, p. 1277-1287.

Research output: Contribution to journalJournal articlepeer-review

Harvard

Niu, L, Thiele, M, Geyer, PE, Rasmussen, DN, Webel, HE, Santos, A, Gupta, R, Meier, F, Strauss, M, Kjaergaard, M, Lindvig, K, Jacobsen, S, Rasmussen, S, Hansen, T, Krag, A & Mann, M 2022, 'Noninvasive proteomic biomarkers for alcohol-related liver disease', Nature Medicine, vol. 28, no. 6, pp. 1277-1287. https://doi.org/10.1038/s41591-022-01850-y

APA

Niu, L., Thiele, M., Geyer, P. E., Rasmussen, D. N., Webel, H. E., Santos, A., Gupta, R., Meier, F., Strauss, M., Kjaergaard, M., Lindvig, K., Jacobsen, S., Rasmussen, S., Hansen, T., Krag, A., & Mann, M. (2022). Noninvasive proteomic biomarkers for alcohol-related liver disease. Nature Medicine, 28(6), 1277-1287. https://doi.org/10.1038/s41591-022-01850-y

Vancouver

Niu L, Thiele M, Geyer PE, Rasmussen DN, Webel HE, Santos A et al. Noninvasive proteomic biomarkers for alcohol-related liver disease. Nature Medicine. 2022;28(6):1277-1287. https://doi.org/10.1038/s41591-022-01850-y

Author

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. / Noninvasive proteomic biomarkers for alcohol-related liver disease. In: Nature Medicine. 2022 ; Vol. 28, No. 6. pp. 1277-1287.

Bibtex

@article{0838946ba9ba464299640137cb2b189b,
title = "Noninvasive proteomic biomarkers for alcohol-related liver disease",
abstract = "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.",
author = "Lili Niu and Maja Thiele and Geyer, {Philipp E.} and Rasmussen, {Ditlev Nytoft} and Webel, {Henry Emanuel} and Alberto Santos and Rajat Gupta and Florian Meier and Maximilian Strauss and Maria Kjaergaard and Katrine Lindvig and Suganya Jacobsen and Simon Rasmussen and Torben Hansen and Aleksander Krag and Matthias Mann",
note = "{\textcopyright} 2022. The Author(s).",
year = "2022",
doi = "10.1038/s41591-022-01850-y",
language = "English",
volume = "28",
pages = "1277--1287",
journal = "Nature Medicine",
issn = "1078-8956",
publisher = "nature publishing group",
number = "6",

}

RIS

TY - JOUR

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