Characterization of myocardial injury phenotype by thermal liquid biopsy - Lidani, Karita C. F.; Buscaglia, Robert; Trainor, Patrick J.; Tomar, Shubham; Kaliappan, Alagammai; DeFilippis, Andrew P.; Garbett, Nichola C. (Frontiers in Cardiovascular Medicine, 2024)
Background and aims: With the advent and implementation of high-sensitivity cardiac troponin assays, differentiation of distinct types of myocardial injury patients, including acute thrombotic myocardial infarction (TMI), acute non-thrombotic myocardial injury (nTMi), and chronic coronary atherosclerotic disease (cCAD), is of pressing clinical importance. Thermal Liquid Biopsy (TLB) emerges as a valuable diagnostic tool, relying on identifying thermally-induced conformational changes of biomolecules in blood plasma. While TLB has proven useful in detecting and monitoring several cancers and autoimmune diseases, its application in cardiovascular diseases remains unexplored. In this proof-of-concept study, we sought to determine and characterize TLB profiles in TMI, nTMi, and cCAD patients at multiple acute-phase time points (T 0h, T 2h, T 4h, T 24h, T 48h) as well as a follow-up time point (Tfu) when the patient was in a stable state. Methods: TLB profiles were collected for 115 patients (60 with TMI, 35 with nTMi, and 20 with cCAD) who underwent coronary angiography at the event presentation and had subsequent follow-up. Medical history, physical, electrocardiographic, histological, biochemical, and angiographic data were gathered through medical records, standardized patient interviews, and core laboratory measurements. Results: Distinctive signatures were noted in the median TLB profiles across the three patient types. TLB profiles for TMI and nTMi patients exhibited gradual changes from T0 to Tfu, with significant differences during the acute and quiescent phases. During the quiescent phase, all three patient types demonstrated similar TLB signatures. An unsupervised clustering analysis revealed a unique TLB signature for the TMI patients. TLB metrics generated from specific features of TLB profiles were tested for differences between patient groups. The first moment temperature (TFM) metric distinguished all three groups at time of presentation (T0). Additionally, 13 other TLB derived metrics were shown to have distinct distributions between TMI and cCAD patients. Conclusion: Our findings demonstrated the use of TLB as a sensitive and data-rich technique to be explored in cardiovascular diseases, thus providing valuable insight into acute myocardial injury events.