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Author Spotlight: Advancing the Analysis of Plasma Extracellular Vesicle Proteome for Cardiovascular Biomarker Studies
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Quantitative Data-Independent Acquisition Mass Spectrometry Proteomics and Weighted Correlation Network Analysis of

Daopeng Dai1, Zhiwei Cheng2, Shuo Feng1

  • 1Department of Cardiovascular Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

DNA and Cell Biology
|October 18, 2022
PubMed

Insights

This study identified novel protein biomarkers linked to atherosclerosis in chronic kidney disease (CKD) patients. These findings illuminate CKD-specific risk factors, potentially guiding new therapeutic strategies for cardiovascular complications.

Area of Science:

  • Cardiovascular Medicine
  • Nephrology
  • Proteomics

Background:

  • Chronic kidney disease (CKD) significantly accelerates atherosclerosis.
  • CKD introduces unique risk factors beyond traditional ones like hypertension and diabetes.
  • Understanding these CKD-specific factors is crucial for managing cardiovascular complications.

Purpose of the Study:

  • To identify novel, CKD-specific risk factors for atherosclerosis.
  • To elucidate the molecular mechanisms underlying CKD-accelerated atherosclerosis.
  • To discover potential protein biomarkers for CKD-related cardiovascular disease.

Main Methods:

  • Enrolled 62 patients with varying kidney function and assessed coronary atherosclerosis severity using SYNTAX scores.
  • Utilized data-independent acquisition mass spectrometry to identify differentially expressed proteins (DEPs) in plasma.
  • Applied weighted gene co-expression network analysis (WGCNA) to find protein modules and hub proteins associated with CKD and atherosclerosis.

Main Results:

  • Identified 10 DEPs associated with atherosclerosis in patients with moderate to severe CKD.
  • WGCNA revealed 1768 proteins and 8 significant protein modules.
  • Enrichment analysis highlighted inflammation, complement, and coagulation cascades as key pathways in CKD-related atherosclerosis.

Conclusions:

  • The study identified specific protein signatures and pathways involved in CKD-accelerated atherosclerosis.
  • Findings provide insights into the complex mechanisms of atherosclerosis in CKD patients.
  • Results may inform the development of targeted treatments for cardiovascular disease in CKD.

Keywords:
atherosclerosischronic kidney diseasedata-independent acquisitionproteomicsweighted gene coexpression network analysis

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