Top-Down Proteomics Identifies Plasma Proteoform Signatures of Liver Cirrhosis Progression
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Abstract
Abstract Cirrhosis, advanced liver disease, affects 2-5 million Americans. While most patients have compensated cirrhosis and may be fairly asymptomatic, many decompensate and experience life-threatening complications such as gastrointestinal bleeding, confusion (hepatic encephalopathy), and ascites, reducing life expectancy from 12 to less than 2 years. Among patients with compensated cirrhosis, identifying patients at high risk of decompensation is critical to optimize care and reduce morbidity and mortality. Therefore, it is important to preferentially direct them towards specialty care which cannot be provided to all patients with cirrhosis. We used discovery Top-down Proteomics (TDP) to identify differentially expressed proteoforms (DEPs) in the plasma of patients with progressive stages of liver cirrhosis with the ultimate goal to identify candidate biomarkers of disease progression. In this pilot study, we identified 209 DEPs across three stages of cirrhosis (compensated, compensated with portal hypertension, and decompensated), of which 115 derived from proteins enriched in the liver at a transcriptional level and discriminated the three stages of cirrhosis. Enrichment analyses demonstrated DEPs are involved in several metabolic and immunological processes known to be impacted by cirrhosis progression. We have preliminarily defined the plasma proteoform signatures of cirrhosis patients, setting the stage for ongoing discovery and validation of biomarkers for early diagnosis, risk stratification, and disease monitoring. Graphical Abstract Highlights Performed a pilot top-down LC-MS/MS analysis to identify proteoforms (PFRs) in the plasma of patients with 3 progressive stages of liver cirrhosis. Identified 2867 proteoforms (PFRs) and 209 differentially regulated proteoforms (DRPs) in the different stages of the disease. Identified DRP profiles able to potentially distinguish early from late stages of the disease, including 115 liver-derived DRPs. Fibrinogen alpha chain, haptoglobin, and Apo A-I are the proteins with the highest number of DRPs and represent potential candidate biomarkers of liver cirrhosis progression.
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Cites
Proteoform: a single term describing protein complexity
The Consortium for Top Down Proteomics, Smith, L. M., & Kelleher, N. L. (2013) · Nature Methods · doi:10.1038/nmeth.2369 · Cited by 1,528 · see citing works
Self-citationHow many human proteoforms are there?
Aebersold, R., Agar, J. N., Amster, I. J., Baker, M. S., Bertozzi, C. R., Boja, E. S., Costello, C. E., Cravatt, B. F., Fenselau, C., Garcia, B. A., et al. (2018) · Nature Chemical Biology · doi:10.1038/nchembio.2576 · Cited by 907 · see citing works
Self-citationThe Human Proteoform Project: Defining the human proteome
Smith, L. M., Agar, J. N., Chamot-Rooke, J., Danis, P. O., Ge, Y., Loo, J. A., Paša-Tolić, L., Tsybin, Y. O., Kelleher, N. L., & The Consortium for Top-Down Proteomics (2021) · Science Advances · doi:10.1126/sciadv.abk0734 · Cited by 242 · see citing works
Self-citationProton Transfer Charge Reduction Enables High-Throughput Top-Down Analysis of Large Proteoforms
Huguet, R., Mullen, C., Srzentić, K., Greer, J. B., Fellers, R. T., Zabrouskov, V., Syka, J. E. P., Kelleher, N. L., & Fornelli, L. (2019) · Analytical Chemistry · doi:10.1021/acs.analchem.9b03925 · Cited by 94 · see citing works
Self-citationTakemori, A., Butcher, D. S., Harman, V. M., Brownridge, P., Shima, K., Higo, D., Ishizaki, J., Hasegawa, H., Suzuki, J., Yamashita, M., et al. (2020) · Journal of Proteome Research · doi:10.1021/acs.jproteome.0c00303 · Cited by 90 · see citing works
Measurement of Individual Ions Sharply Increases the Resolution of Orbitrap Mass Spectra of Proteins
Kafader, J. O., Melani, R. D., Senko, M. W., Makarov, A. A., Kelleher, N. L., & Compton, P. D. (2019) · Analytical Chemistry · doi:10.1021/acs.analchem.8b04519 · Cited by 87 · see citing works
Self-citationChou, C. M., Nelson, C., Tarlé, S. A., Pribila, J. T., Bardakjian, T., Woods, S., Schneider, A., & Glaser, T. (2015) · Cell · doi:10.1016/j.cell.2015.03.006 · Cited by 76 · see citing works
Accurate Estimation of Context-Dependent False Discovery Rates in Top-Down Proteomics
LeDuc, R. D., Fellers, R. T., Early, B. P., Greer, J. B., Shams, D. P., Thomas, P. M., & Kelleher, N. L. (2019) · Molecular & Cellular Proteomics · doi:10.1074/mcp.ra118.000993 · Cited by 44 · see citing works
Self-citationMunteanu, M., Pais, R., Peta, V., Deckmyn, O., Moussalli, J., Ngo, Y., Rudler, M., Lebray, P., Charlotte, F., Thibault, V., et al. (2018) · Alimentary Pharmacology & Therapeutics · doi:10.1111/apt.14990 · Cited by 42 · see citing works
Intact-Mass Analysis Facilitating the Identification of Large Human Heart Proteoforms
Schaffer, L. V., Tucholski, T., Shortreed, M. R., Ge, Y., & Smith, L. M. (2019) · Analytical Chemistry · doi:10.1021/acs.analchem.9b02343 · Cited by 17 · see citing works
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- Authors
- Forte, E., Sanders, J. M., Pla, I., Kanchustambham, V. L., Hollas, M. A. R., Huang, C.-F., Sanchez, A., Peterson, K. N., Melani, R. D., Huang, A., Polineni, P., Doll, J. M., Dietch, Z., Kelleher, N. L., & Ladner, D. P.
- Affiliations
- Northwestern University (US)
- Corresponding author
- Kelleher, Neil L.
- Ladner, Daniela P.
- ORCID
- Venue
- Molecular & Cellular Proteomics
- Publisher
- Elsevier BV
- Published
- 2024-12
- Volume
- 23
- Issue
- 12
- Pages
- 100876
- ISSN
- 1535-9476 (ISSN-L)
- PMC
- PMC11664408
- OpenAlex
- W4404169112
- Cited by
- 22
- References
- 10
- Citations by year
- 2026: 12 · 2025: 9 · 2024: 1
- FWCI
- 5.76
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Molecular & Cellular Proteomics (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- PubMed Central (submittedVersion, cc-by-nc-nd)
- Funders
- National Institute of General Medical Sciences (P41GM108569)
- National Institute of Diabetes and Digestive and Kidney Diseases (T32DK077662)
- National Institutes of Health
- Northwestern University Feinberg School of Medicine
- Topics
- Health Sciences › Medicine › Hepatology › Liver Disease and Transplantation
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Health Sciences › Medicine › Epidemiology › Liver Disease Diagnosis and Treatment
- Keywords
- liver cirrhosis, disease progression, top-down proteomics, biomarkers, decompensated cirrhosis, compensated cirrhosis, portal hypertension, risk stratification, early diagnosis, liver disease
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