Background: Myocarditis, an inflammatory disease of the heart muscle, predominantly affects individuals under 40 and can result from diverse causes, including infections, autoimmune mechanisms, toxins, and cancer immunotherapies. Diagnosis is challenging, typically necessitating an endomyocardial biopsy, which is infrequently performed. The absence of specific treatments and the potential progression to dilated cardiomyopathy (DCM) or heart failure underscore the critical need for non-invasive biomarkers for early diagnosis and risk assessment. Objectives: This project aims to evaluate the prevalence and clinical presentation of myocarditis in a comprehensive patient cohort and to identify novel blood-based biomarkers that enhance diagnosis, prognostication, and individualized follow-up. We hypothesize that patients suffering from myocarditis may have an increased genetic susceptibility to develop myocarditis and/or cardiac complications following myocarditis. By investigating the patients' genomes, we seek to determine whether genetic screening should be offered to these patients. Additionally, we aim to elucidate the infectious, immunological, and metabolic factors contributing to disease progression. All data constitute sensitive personal data including sequencing and clinical information from patients; hence analyses require processing within secure UPPMAX Bianca environment. Methods: The study encompasses myocarditis patients of all ages, diagnosed in Sweden from 2009 onward, with ongoing inclusion of new cases. Blood samples are collected at multiple timepoints and analyzed using metagenomic sequencing, genetic profiling, metabolomics, immunological profiling and microRNA analysis. Clinical data, imaging, and long-term follow-up are used to assess cardiac outcomes, including the development of DCM and heart failure. Sequencing data will be processed within the secure environment using nf-core workflows such as nf-core/sarek, nf-core/smrnaseq, and appropriate workflows for viral genome assembly. Downstream analysis will be performed using R/Bioconductor and other statistical tools within secure interactive sessions. Significance: This study addresses the urgent need for improved diagnostics and risk assessment tools in myocarditis care. By identifying biomarkers for improved diagnostics, guiding treatment decisions, and predicting long-term complications, we aim to enable more personalized and effective patient management. Furthermore, we will explore the potential benefits of offering genetic screening to these patients, which could refine risk assessment and management strategies, ultimately leading to improved outcomes.