CoChat
Sign Up
Cited by 44

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Tandem mass tag-based quantitative proteomic profiling identifies candidate serum biomarkers of drug-induced liver injury in humans

Ravindra, Kodihalli C., Vaidya, Vishal S., Wang, Zhenyu, Federspiel, Joel D., Virgen-Slane, Richard, Everley, Robert A., Grove, Jane I., Stephens, Camilla, Ocana, Mireia F., Robles-Díaz, Mercedes, Isabel Lucena, M., Andrade, Raul J., Atallah, Edmond, Gerbes, Alexander L., Weber, Sabine, Cortez-Pinto, Helena, Fowell, Andrew J., Hussaini, Hyder, Bjornsson, Einar S., Patel, Janisha, Stirnimann, Guido, Verma, Sumita, Elsharkawy, Ahmed M., Griffiths, William J. H., Hyde, Craig, Dear, James W., Aithal, Guruprasad P., Ramaiah, Shashi K.·2023·Nature Communications
DOI 10.1038/s41467-023-36858-6PMC PMC9984368
Open this paper in CoChat — free account

Abstract

Diagnosis of drug-induced liver injury (DILI) and its distinction from other liver diseases are significant challenges in drug development and clinical practice. Here, we identify, confirm, and replicate the biomarker performance characteristics of candidate proteins in patients with DILI at onset (DO; n = 133) and follow-up ( n = 120), acute non-DILI at onset (NDO; n = 63) and follow-up ( n = 42), and healthy volunteers (HV; n = 104). Area under the receiver operating characteristic curve (AUC) for cytoplasmic aconitate hydratase, argininosuccinate synthase, carbamoylphosphate synthase, fumarylacetoacetase, fructose-1,6-bisphosphatase 1 (FBP1) across cohorts achieved near complete separation (range: 0.94–0.99) of DO and HV. In addition, we show that FBP1, alone or in combination with glutathione S-transferase A1 and leukocyte cell-derived chemotaxin 2, could potentially assist in clinical diagnosis by distinguishing NDO from DO (AUC range: 0.65–0.78), but further technical and clinical validation of these candidate biomarkers is needed.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/s41467-023-36858-6

Cites

3 of 3 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Show all 3 references

Research works printed but not linked: 52

  1. Fontana, R. J. et al. Persistent liver biochemistry abnormalities are more common in older patients and those with cholestatic drug induced liver injury. Am. J. Gastroenterol. 110, 1450–1459 (2015). · DOI
  2. Bjornsson, E. S. Clinical management of patients with drug-induced liver injury (DILI). United European Gastroenterol. J. 9, 781–786 (2021). · DOI
  3. Hayashi, P. H. et al. Death and liver transplantation within 2 years of onset of drug-induced liver injury. Hepatology 66, 1275–1285 (2017). · DOI · Paper page
  4. Kullak-Ublick, G. A. et al. Drug-induced liver injury: recent advances in diagnosis and risk assessment. Gut 66, 1154–1164 (2017). · DOI · Paper page
  5. Onakpoya, I. J., Heneghan, C. J. & Aronson, J. K. Post-marketing withdrawal of 462 medicinal products because of adverse drug reactions: a systematic review of the world literature. BMC Med. 14, 10 (2016). · DOI
  6. Pettersson, J. et al. Muscular exercise can cause highly pathological liver function tests in healthy men. Br. J. Clin. Pharmacol. 65, 253–259 (2008). · DOI
  7. Lewis, J. H. ‘Hy’s law,’ the ‘Rezulin Rule,’ and other predictors of severe drug-induced hepatotoxicity: putting risk-benefit into perspective. Pharmacoepidemiol. Drug Saf. 15, 221–229 (2006). · DOI
  8. Robles-Diaz, M. et al. Use of Hy’s law and a new composite algorithm to predict acute liver failure in patients with drug-induced liver injury. Gastroenterology 147, 109–118 (2014). · DOI · Paper page
  9. Senior, J. R. Alanine aminotransferase: a clinical and regulatory tool for detecting liver injury-past, present, and future. Clin. Pharmacol. Ther. 92, 332–339 (2012). · DOI
  10. Matheis, K. et al. A generic operational strategy to qualify translational safety biomarkers. Drug Discov. Today 16, 600–608 (2011). · DOI
  11. Church, R. J. et al. Candidate biomarkers for the diagnosis and prognosis of drug-induced liver injury: an international collaborative effort. Hepatology 69, 760–773 (2019). · DOI · Paper page
  12. Uhlen, M. et al. Proteomics. Tissue-based map of the human proteome. Science 347, 1260419 (2015). · DOI · Paper page
  13. MacParland, S. A. et al. Single cell RNA sequencing of human liver reveals distinct intrahepatic macrophage populations. Nat. Commun. 9, 4383 (2018). · DOI · Paper page
  14. Atallah, E. et al. Biomarkers of idiosyncratic drug-induced liver injury (DILI) - a systematic review. Expert Opin. Drug Metab. Toxicol. 17, 1327–1343 (2021). · DOI
  15. Vazquez, J. H. & McGill, M. R. Redrawing the map to novel DILI biomarkers in circulation: where are we, where should we go, and how can we get there? Livers 1, 286–293 (2021). · DOI
  16. Breu, A. C. et al. A Multicenter study into causes of severe acute liver injury. Clin. Gastroenterol. Hepatol. 17, 1201–1203 (2019). · DOI
  17. Donaghy, L. et al. Clinical and laboratory features and natural history of seronegative hepatitis in a nontransplant centre. Eur. J. Gastroenterol. Hepatol. 25, 1159–1164 (2013).
  18. Suzuki, A. et al. Assessment of the frequency, phenotypes, and outcomes of acute liver injury associated with amoxicillin/clavulanate in 1.4 million patients in the veterans health administration. Drug Saf. 46, 129–143 (2022). · DOI
  19. Wang, B., Hsu, S. H., Frankel, W., Ghoshal, K. & Jacob, S. T. Stat3-mediated activation of microRNA-23a suppresses gluconeogenesis in hepatocellular carcinoma by down-regulating glucose-6-phosphatase and peroxisome proliferator-activated receptor gamma, coactivator 1 alpha. Hepatology 56, 186–197 (2012). · DOI
  20. Wang, J. et al. Proteomic signature of acute liver failure: from discovery and verification in a pig model to confirmation in humans. Mol. Cell Proteomics 16, 1188–1199 (2017). · DOI
  21. Paris, J. & Henderson, N. C. Liver zonation, revisited. Hepatology 76, 1219–1230 (2022). · DOI
  22. Takata, N. et al. LECT2 as a hepatokine links liver steatosis to inflammation via activating tissue macrophages in NASH. Sci. Rep. 11, 555 (2021). · DOI
  23. Shaw, P. J., Ganey, P. E. & Roth, R. A. Idiosyncratic drug-induced liver injury and the role of inflammatory stress with an emphasis on an animal model of trovafloxacin hepatotoxicity. Toxicol. Sci. 118, 7–18 (2010). · DOI · Paper page
  24. Sato, Y. et al. Serum LECT2 level as a prognostic indicator in acute liver failure. Transplant Proc. 36, 2359–2361 (2004). · DOI
  25. Li, R. et al. Glutathione S-transferase A1 (GSTA1) as a marker of acetaminophen-induced hepatocyte injury in vitro. Toxicol. Mech. Methods 27, 401–407 (2017). · DOI
  26. Liu, F. et al. Glutathione S-transferase A1 (GSTA1) release, an early indicator of acute hepatic injury in mice. Food Chem. Toxicol. 71, 225–230 (2014). · DOI
  27. McGill, M. R. et al. Argininosuccinate synthetase as a plasma biomarker of liver injury after acetaminophen overdose in rodents and humans. Biomarkers 19, 222–230 (2014). · DOI
  28. Weerasinghe, S. V., Jang, Y. J., Fontana, R. J. & Omary, M. B. Carbamoyl phosphate synthetase-1 is a rapid turnover biomarker in mouse and human acute liver injury. Am. J. Physiol. Gastrointest. Liver Physiol. 307, G355–G364 (2014). · DOI
  29. Vazquez, J. H. et al. Identification of serum biomarkers to distinguish hazardous and benign aminotransferase elevations. Toxicol. Sci. 173, 244–254 (2020). · DOI
  30. Svetlov, S. I. et al. Identification and preliminary validation of novel biomarkers of acute hepatic ischaemia/reperfusion injury using dual-platform proteomic/degradomic approaches. Biomarkers 11, 355–369 (2006). · DOI
  31. Bailey, W. J. et al. A performance evaluation of three drug-induced liver injury biomarkers in the rat: alpha-glutathione S-transferase, arginase 1, and 4-hydroxyphenyl-pyruvate dioxygenase. Toxicol. Sci. 130, 229–244 (2012). · DOI
  32. Bell, L. N. et al. Serum proteomic profiling in patients with drug-induced liver injury. Aliment Pharmacol. Ther. 35, 600–612 (2012). · DOI
  33. Vickers, A. E., Ulyanov, A. V. & Fisher, R. L. Liver effects of clinical drugs differentiated in human liver slices. Int. J. Mol. Sci. 18, 574–606 (2017). · DOI
  34. Tegeris, A. S., Smalley, H. E. Jr., Earl, F. L. & Curtis, J. M. Ornithine carbamyl transferase as a liver function test comparative studies in the dog, swine, and man. Toxicol. Appl. Pharmacol. 14, 54–66 (1969). · DOI
  35. Fu, S. et al. Molecular biomarkers in drug-induced liver injury: Challenges and future perspectives. Front. Pharmacol. 10, 1667 (2019). · DOI
  36. Flanigan, K. M. et al. Pharmacokinetics and safety of single doses of drisapersen in non-ambulant subjects with Duchenne muscular dystrophy: results of a double-blind randomized clinical trial. Neuromuscul. Disord. 24, 16–24 (2014). · DOI
  37. Maniratanachote, R. et al. Detection of autoantibody to aldolase B in sera from patients with troglitazone-induced liver dysfunction. Toxicology 216, 15–23 (2005). · DOI
  38. Hu, Z. et al. Quantitative liver-specific protein fingerprint in blood: a signature for hepatotoxicity. Theranostics 4, 215–228 (2014). · DOI
  39. Murayama, H., Ikemoto, M., Fukuda, Y. & Nagata, A. Superiority of serum type-I arginase and ornithine carbamyltransferase in the detection of toxicant-induced acute hepatic injury in rats. Clin. Chim. Acta 391, 31–35 (2008). · DOI
  40. Furihata, T. et al. Characterization of release profile of ornithine carbamoyltransferase from primary rat hepatocytes treated with hepatotoxic drugs: Implications for its unique potential as a drug-induced liver injury biomarker. Drug Metab. Pharmacokinet. 31, 102–105 (2016). · DOI
  41. Danan, G. & Benichou, C. Causality assessment of adverse reactions to drugs–I. A novel method based on the conclusions of international consensus meetings: application to drug-induced liver injuries. J. Clin. Epidemiol. 46, 1323–1330 (1993). · DOI · Paper page
  42. Soga, T. et al. Serum metabolomics reveals gamma-glutamyl dipeptides as biomarkers for discrimination among different forms of liver disease. J. Hepatol. 55, 896–905 (2011). · DOI
  43. Huang, Y. et al. Metabolomics profiling and diagnosis biomarkers searching for drug-induced liver injury implicated to polygonum multiflorum: A cross-sectional cohort study. Front. Med. 7, 592434 (2020). · DOI
  44. Bjornsson, E. S. et al. A new framework for advancing in drug-induced liver injury research. The Prospective European DILI Registry. Liver Int. 43, 115–126 (2023). · DOI · Paper page
  45. Aithal, G. P. et al. Case definition and phenotype standardization in drug-induced liver injury. Clin. Pharmacol. Ther. 89, 806–815 (2011). · DOI · Paper page
  46. Eng, J. K., McCormack, A. L. & Yates, J. R. An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. J. Am. Soc. Mass Spectrom. 5, 976–989 (1994). · DOI · Paper page
  47. Huttlin, E. L. et al. A tissue-specific atlas of mouse protein phosphorylation and expression. Cell 143, 1174–1189 (2010). · DOI · Paper page
  48. Elias, J. E. & Gygi, S. P. Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry. Nat. Methods 4, 207–214 (2007). · DOI · Paper page
  49. Gallien, S., Kim, S. Y. & Domon, B. Large-scale targeted proteomics using internal standard triggered-parallel reaction monitoring (IS-PRM). Mol. Cell Proteomics 14, 1630–1644 (2015). · DOI
  50. MacLean, B. et al. Skyline: an open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics 26, 966–968 (2010). · DOI · Paper page
  51. Llewellyn, H. P. et al. Evaluating the sensitivity and specificity of promising circulating biomarkers to diagnose liver injury in humans. Toxicol. Sci. 181, 23–34 (2021). · DOI
  52. Ritchie, M. E. et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43, e47 (2015). · DOI · Paper page

Cited by

Sorted by citations

See all 44

Metadata

Authors
Ravindra, K. C., Vaidya, V. S., Wang, Z., Federspiel, J. D., Virgen-Slane, R., Everley, R. A., Grove, J. I., Stephens, C., Ocana, M. F., Robles-Díaz, M., Isabel Lucena, M., Andrade, R. J., Atallah, E., Gerbes, A. L., Weber, S., Cortez-Pinto, H., Fowell, A. J., Hussaini, H., Bjornsson, E. S., Patel, J., Stirnimann, G., Verma, S., Elsharkawy, A. M., Griffiths, W. J. H., Hyde, C., Dear, J. W., Aithal, G. P., & Ramaiah, S. K.
ORCID
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2023-03-03
Volume
14
Issue
1
ISSN
2041-1723
DOI
10.1038/s41467-023-36858-6
PMC
PMC9984368
Cited by
44
References
3
Language
en
Licence

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review