Post-acute COVID syndrome (PACS) /post-acute sequale of COVID-19 (PASC) / post-COVID is a novel clinical syndrome with unknown biological mechanisms, and to date no standard-of-care, routines for follow-up, or evidence-based treatments have been established. In this project, we will employ a systems medicine approach to identify pathways and networks of genes, proteins and metabolites that are critical in disease onset and progression, towards the goal of understanding specific mechanisms in the etiology of PASC. The objective of the project is to perform clinical and molecular characterization and sub-phenotyping of patients with PASC, (a.k.a. PACS, or post-COVID), into mechanistically relevant groups, with focus on sex differences in patients with lung involvement. Molecular pathways involved in disease etiology will be identified by correlating rigorous clinical phenotyping and longitudinal eHealth data (home-monitoring via App, home spirometer etc), with multi-molecular level omics profiling of samples collected from the lung, integrated with our systems medicine framework. Aim I involves longitudinal home-monitoring at baseline to investigate fluctuations in general wellbeing, and causes thereof, in PASC patients with lung involvement compared to healthy controls. In Aim II, a set of omics technologies will be employed to provide in-depth molecular characterization of samples from the lung, exhaled particles (PExA), blood and urine. In depth clinical characterizations including photon-counting CT will be performed. In Aim III, integrative statistical- and network modeling approaches will be utilized to: i) identify molecularly distinct sub-groups of obstructive lung diseases based on multi-molecular level network-integration, and ii) identify individual mediators and molecular pathways related to clinical phenotype including longitudinal home-monitoring data, prognosis, diagnosis, and disease etiology of the identified sub-groups. A variety of inflammation-regulating molecules from multiple anatomical locations in the lung will be quantified in patients with PASC (n=50) versus relevant controls (n=50), including proteins, eicosanoids, microRNA and mRNA. Both bulk and single-cell analyses will be applied. Initally, the main use of UPPMAX will be for the purpose of single cell seq analysis of immune cells from the lung (BAL cells) using the 10x platform, as well as bulk seq analysis of miRNA and mRNA from extracellular vesicles from the lung, from particles from exhaled air (PExA) samples, as well as airway epithelial samples.