Serum protein profile study of myocardial infarction using a LED induced fluorescence based HPLC system

Area of Science:

• Biochemistry
• Analytical Chemistry
• Medical Diagnostics

Background:

• Cardiovascular diseases (CVDs) are leading causes of mortality and morbidity worldwide.
• Delayed diagnosis of CVDs, such as myocardial infarction (MI), negatively impacts patient health outcomes.
• Accurate and timely diagnosis is crucial for effective MI management and treatment.

Purpose of the Study:

• To develop and validate an in-house assembled UV-light emitting diode (LED) based fluorescence detector for high-performance liquid chromatography (HPLC) (HPLC-LED-IF) system.
• To assess the system's capability in discriminating between serum protein profiles of normal individuals, pre-medication MI patients, and post-medication MI patients.
• To evaluate the diagnostic reliability of the HPLC-LED-IF method for MI detection.

Main Methods:

• An in-house HPLC-LED-IF system was utilized to analyze serum chromatograms from three distinct sample groups: normal, pre-medication MI (B-MI), and post-medication MI (A-MI).
• System sensitivity and performance were validated using commercial serum proteins.
• Statistical analyses, including descriptive statistics, principal component analysis (PCA), and Match/No Match tests, were employed for sample group differentiation.

Main Results:

• The HPLC-LED-IF system demonstrated the ability to record distinct serum chromatograms for the three patient categories.
• Statistical analysis revealed significant variations in protein profiles, enabling fairly good discrimination among the normal, B-MI, and A-MI groups.
• Receiver operating characteristic (ROC) curve analysis confirmed the reliability of the developed method for diagnosing MI.

Conclusions:

• The developed HPLC-LED-IF system offers a reliable method for differentiating serum protein profiles in myocardial infarction patients.
• This technique shows promise for aiding in the early and accurate diagnosis of MI.
• The study highlights the potential of advanced analytical techniques in improving cardiovascular disease diagnostics.