Proteome profile of stress test assessed cardiovascular disease risk-prone diabetic subjects

TitleProteome profile of stress test assessed cardiovascular disease risk-prone diabetic subjects
Publication TypeJournal Article
Year of Publication2025
AuthorsPatil, YR, Tiwari, S, Unnikrishnan, AG, Kulkarni, MJ
JournalJournal of Cardiovascular Translational Research
Volume18
Issue4
Pagination960-969
Date PublishedAUG
Type of ArticleArticle
ISSN1937-5387
Keywordscardiovascular disease, Diabetes, Multiple reaction monitoring, Plasma markers, Proteome profile, Quantitative mass spectrometry
Abstract

Cardiovascular disease (CVD) is the leading cause of death in the diabetic population. There is a need for specific predictive markers to assess CVD risk. The present study explored the plasma proteome profile of treadmill test (TMT) assessed diabetic stress test positive (DSTP) and diabetic stress test negative (DSTN) subjects by performing a SWATH-MS-based label-free quantitative mass spectrometry approach to identify differentially expressed proteins (DEPs). CVD-relevant DEPs were further validated using a targeted mass spectrometry approach (MRM-HR). It was observed that CO4B, PON1 and LUM exhibited considerable differential expression in both the MS approaches, and ROC analysis showed significant AUC (0.97, 0.79 and 0.77, respectively). Overall, the present study reports these proteins as potential alternative markers for TMT in assessing CVD risk. These markers can possibly overcome the limitations of TMT with further validation in the large cohort.Graphical AbstractAn overview of experimental approaches used in the current study. The study design depicts diabetic subjects assessed for cardiovascular risk by TMT or stress test. The experimental design shows the use of the SWATH-MS approach to identify differentially expressed proteins and validate CVD-related proteins with targeted MS approaches such as MRM-HR. Finally, CO4B, PON1 and LUM exhibited significant AUC in ROC analysis, indicating their potential marker capabilities to predict CVD in diabetic subjects.

DOI10.1007/s12265-025-10651-w
Type of Journal (Indian or Foreign)

Foreign

Impact Factor (IF)

2.9

Divison category: 
Biochemical Sciences
Database: 
Web of Science (WoS)

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