Abstract
Acute and chronic coronary syndromes (ACS and CCS) are leading causes of mortality. Inflammation is considered a key pathogenic driver of these diseases, but the underlying immune states and their clinical implications remain poorly understood. Multiomic factor analysis (MOFA) allows unsupervised data exploration across multiple data types, identifying major axes of variation and associating these with underlying molecular processes. We hypothesized that applying MOFA to multiomic data obtained from blood might uncover hidden sources of variance and provide pathophysiological insights linked to clinical needs. Here we compile a longitudinal multiomic dataset of the systemic immune landscape in both ACS and CCS (n = 62 patients in total, n = 15 women and n = 47 men) and validate this in an external cohort (n = 55 patients in total, n = 11 women and n = 44 men). MOFA reveals multicellular immune signatures characterized by distinct monocyte, natural killer and T cell substates and immune-communication pathways that explain a large proportion of inter-patient variance. We also identify specific factors that reflect disease state or associate with treatment outcome in ACS as measured using left ventricular ejection fraction. Hence, this study provides proof-of-concept evidence for the ability of MOFA to uncover multicellular immune programs in cardiovascular disease, opening new directions for mechanistic, biomarker and therapeutic studies.
Dokumententyp: | Zeitschriftenartikel |
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EU Funded Grant Agreement Number: | 833440 |
EU-Projekte: | Horizon 2020 > ERC Grants > ERC Advanced Grant > ERC Grant 833440: IMMUNOTHROMBOSIS - Cross-talk between platelets and immunity - implications for host homeostasis and defense |
Fakultät: | Medizin > Klinikum der LMU München > Medizinische Klinik und Poliklinik I (Kardiologie) |
Themengebiete: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit |
URN: | urn:nbn:de:bvb:19-epub-116927-4 |
ISSN: | 1078-8956 |
Bemerkung: | Online first |
Sprache: | Englisch |
Dokumenten ID: | 116927 |
Datum der Veröffentlichung auf Open Access LMU: | 05. Jun. 2024 05:45 |
Letzte Änderungen: | 05. Jun. 2024 05:45 |