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LIVER

Proteomics and machine-learning models for alcohol-related liver disease biomarkers

Nature Reviews Gastroenterology & Hepatology volume 19, page 488 (2022)Cite this article

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Researchers have used paired liver-plasma proteomics and machine-learning models to identify biomarker panels for alcohol-related liver disease (ALD). Plasma samples from 596 individuals (459 patients with ALD and 137 control individuals) and liver biopsy samples were assessed by mass spectrometry-based proteomics. On the basis of these data, machine-learning models were able to generate biomarker panels to detect fibrosis, inflammation and steatosis. Such panels were used to predict liver-related events and mortality and were validated in an independent cohort.

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References

Original article

  • Niu, L. et al. Noninvasive proteomic biomarkers for alcohol-related liver disease. Nat. Med. 28, 1277–1287 (2022)

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  1. Nature Reviews Gastroenterology & Hepatology http://www.nature.com/nrgastro/

    Jordan Hindson

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  1. Jordan Hindson
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Correspondence to Jordan Hindson.

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Hindson, J. Proteomics and machine-learning models for alcohol-related liver disease biomarkers. Nat Rev Gastroenterol Hepatol 19, 488 (2022). https://doi.org/10.1038/s41575-022-00655-1

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  • DOI: https://doi.org/10.1038/s41575-022-00655-1

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