Your browser doesn't support javascript.
loading
Integrated metabolomics and proteomics reveal biomarkers associated with hemodialysis in end-stage kidney disease.
Lin, Weiwei; Mousavi, Fatemeh; Blum, Benjamin C; Heckendorf, Christian F; Moore, Jarrod; Lampl, Noah; McComb, Mark; Kotelnikov, Sergei; Yin, Wenqing; Rabhi, Nabil; Layne, Matthew D; Kozakov, Dima; Chitalia, Vipul C; Emili, Andrew.
Afiliação
  • Lin W; Center for Network Systems Biology, Boston University, Boston, MA, United States.
  • Mousavi F; Department of Biochemistry, Boston University School of Medicine, Boston, MA, United States.
  • Blum BC; Center for Network Systems Biology, Boston University, Boston, MA, United States.
  • Heckendorf CF; Center for Network Systems Biology, Boston University, Boston, MA, United States.
  • Moore J; Department of Biochemistry, Boston University School of Medicine, Boston, MA, United States.
  • Lampl N; Center for Network Systems Biology, Boston University, Boston, MA, United States.
  • McComb M; Department of Biochemistry, Boston University School of Medicine, Boston, MA, United States.
  • Kotelnikov S; Center for Network Systems Biology, Boston University, Boston, MA, United States.
  • Yin W; Department of Biochemistry, Boston University School of Medicine, Boston, MA, United States.
  • Rabhi N; Center for Network Systems Biology, Boston University, Boston, MA, United States.
  • Layne MD; Department of Biochemistry, Boston University School of Medicine, Boston, MA, United States.
  • Kozakov D; Center for Network Systems Biology, Boston University, Boston, MA, United States.
  • Chitalia VC; Department of Biochemistry, Boston University School of Medicine, Boston, MA, United States.
  • Emili A; Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, United States.
Front Pharmacol ; 14: 1243505, 2023.
Article em En | MEDLINE | ID: mdl-38089059
ABSTRACT

Background:

We hypothesize that the poor survival outcomes of end-stage kidney disease (ESKD) patients undergoing hemodialysis are associated with a low filtering efficiency and selectivity. The current gold standard criteria using single or several markers show an inability to predict or disclose the treatment effect and disease progression accurately.

Methods:

We performed an integrated mass spectrometry-based metabolomic and proteomic workflow capable of detecting and quantifying circulating small molecules and proteins in the serum of ESKD patients. Markers linked to cardiovascular disease (CVD) were validated on human induced pluripotent stem cell (iPSC)-derived cardiomyocytes.

Results:

We identified dozens of elevated molecules in the serum of patients compared with healthy controls. Surprisingly, many metabolites, including lipids, remained at an elevated blood concentration despite dialysis. These molecules and their associated physical interaction networks are correlated with clinical complications in chronic kidney disease. This study confirmed two uremic toxins associated with CVD, a major risk for patients with ESKD.

Conclusion:

The retained molecules and metabolite-protein interaction network address a knowledge gap of candidate uremic toxins associated with clinical complications in patients undergoing dialysis, providing mechanistic insights and potential drug discovery strategies for ESKD.
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Front Pharmacol Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Front Pharmacol Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos