Targeted proteomic profiling of cardiogenic shock in the cardiac intensive care unit

Siddharth M Patel1, Mathew S Lopes1, David A Morrow1

  • 1Levine Cardiac Intensive Care Unit, Cardiovascular Division, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, 75 Francis St., Boston, MA 02115, USA.

Insights

Researchers identified nine protein biomarkers linked to cardiogenic shock (CS) using proteomic profiling. These markers, including soluble ST2 (sST2) and growth differentiation factor (GDF)-15, may aid in diagnosing CS, especially in heart failure patients.

Area of Science:

  • Cardiology
  • Proteomics
  • Biomarker Discovery

Background:

  • Cardiogenic shock (CS) is a life-threatening condition requiring timely diagnosis.
  • Current diagnostic methods may benefit from novel biomarkers.
  • Proteomic profiling offers a powerful approach to identify such biomarkers.

Purpose of the Study:

  • To characterize circulating protein biomarkers associated with cardiogenic shock (CS).
  • To utilize highly multiplex proteomic profiling for biomarker discovery in CS.
  • To identify potential diagnostic biomarkers for CS using a case-control study.

Main Methods:

  • A cross-sectional case-control study design was employed.
  • A biorepository of cardiac intensive care unit patients (2017-2020) was used.
  • Olink proteomic platform analyzed 359 biomarkers in 239 patients (69 CS cases, 170 controls).

Main Results:

  • Sixty-three biomarkers were significantly associated with CS after Bonferroni correction.
  • Nine biomarkers remained significant when cross-validated in heart failure (HF) and hypotension subsets.
  • Key biomarkers included cathepsin D (CTSD), FGF-21, FGF-23, GDF-15, IGFBP1, NT-proBNP, osteopontin, OSMR, and sST2.
  • A multi-marker model using sST2, FGF-23, CTSD, and GDF-15 showed complementary diagnostic information.

Conclusions:

  • Targeted proteomic profiling can identify novel candidate biomarkers for CS.
  • Nine validated biomarkers show significant association with CS.
  • These findings support the potential of proteomic approaches for improving CS diagnosis.
Abstract

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