Multiomic analyses uncover immunological signatures in acute and chronic coronary syndromes
- Nat Med. 2024 May 21. doi: 10.1038/s41591-024-02953-4.
- 1. Medizinische Klinik und Poliklinik I, LMU University Hospital, Munich, Germany. [email protected].
- 2. DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, Munich, Germany. [email protected].
- 3. Institute of Computational Biology, German Research Center for Environmental Health, Helmholtz Zentrum München, Neuherberg, Germany.
- 4. Department of Computer Science, TUM School of Computation, Information and Technology, Technical University of Munich, Garching, Germany.
- 5. Medizinische Klinik und Poliklinik I, LMU University Hospital, Munich, Germany.
- 6. DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, Munich, Germany.
- 7. Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
- 8. Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
- 9. Department of Medicine III, LMU University Hospital, Munich, Germany.
- 10. Division of Clinical Pharmacology, LMU University Hospital, Member of the German Center for Lung Research (DZL), Munich, Germany.
- 11. Department of Informatics, Ludwig-Maximilian University, Munich, Germany.
- 12. Anthropology and Human Genomics, Faculty of Biology, Ludwig-Maximilian University, Munich, Germany.
- 13. Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany.
- 14. German Cancer Consortium (DKTK), a partnership between DKFZ and LMU University Hospital, Partner Site Munich, Munich, Germany.
- 15. Einheit für Klinische Pharmakologie (EKLiP), Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany.
- 16. Department of Cardiology, Angiology and Intensive Care Medicine, Deutsches Herzzentrum der Charité (DHZC), Berlin, Germany.
- 17. German Center for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany.
- 18. Charite-Universitätsmedizin Berlin, Berlin, Germany.
- 19. Department of Cardiology, University Medical Center Utrecht, Utrecht, The Netherlands.
- 20. DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, Munich, Germany. [email protected].
- 21. Institute of Computational Biology, German Research Center for Environmental Health, Helmholtz Zentrum München, Neuherberg, Germany. [email protected].
- 22. Department of Computer Science, TUM School of Computation, Information and Technology, Technical University of Munich, Garching, Germany. [email protected].
- 23. Medizinische Klinik und Poliklinik I, LMU University Hospital, Munich, Germany. [email protected].
- 24. DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, Munich, Germany. [email protected].
- 25. Medizinische Klinik und Poliklinik I, LMU University Hospital, Munich, Germany. [email protected].
- 26. DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, Munich, Germany. [email protected].
- # Contributed equally.
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.
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Research Areas: Cancer