Abstract Background Long-COVID (also known as post-acute sequelae of SARS-CoV-2 infection, PASC), is defined as the persistence, or the new onset, of symptoms after recovery from the acute phase of COVID-19. It consists of a multiorgan syndrome expressing itself with a wide variety of cardiovascular and non-cardiovascular symptoms such us chest pain, fatigue, shortness of breath, autonomic dysfunction, cognitive impairment and sleep disorders even in the absence of a clear evidence of organ dysfunction. Some previous studies have suggested the potential role of an abnormal inflammatory response after SARS-CoV-2 infection, however the specific underlying mechanisms remain unclear. In this study we performed a proteomic analysis of the serum of 80 long-COVID patients to identify potential biomarkers that may act as indicators or therapeutic targets for long COVID. Methods and results We compared the levels of the proteins in both long-COVID group and a control group using multivariate and univariate analysis. Both PLS-DA and PCA analysis showed a clear distinction between the two groups; clustering analysis also clearly separated control from long-COVID patients. Proteins were then filtered based on (a) statistical analysis, considering proteins with a VIP>1 (PLSDA) and p<0.05 (t-test); (b) coefficient of variation (CV), where only proteins with CV<10 were considered; (c) and fold change (FC), for which proteins with FC<0.67 or FC>1.5 were selected for further analysis. The selected proteins were then subjected to a ROC curve analysis to identify antithrombin as a potential biomarker with an area under the curve (AUC) near 1. Other proteins, displaying an AUC > 0.98, were also identified as potential biomarkers (Sirtuin 1, NatriureticPeptide B, Hemopexin Arachidonate 5-Lipoxygenase). In addition, a multivariate ROC method, using linear SVM as classification method, identified that a combination of ten proteins would also result in an AUC near 1. Finally, a correlation analysis between the proteins of interest and the clinical manifestations was performed. A positive correlation (above 0.5) was found between dyspnea and Glucocorticoid Receptor and between memory deficit and Antithrombin. Arachidonate 5-Lipoxygenase was negatively correlated (below -0.5) with tremors and hair loss, MannoseBinding Lectin 2 was found to be positively linked to asthenia, Antithrombin with concentration deficit and Endothelin-2 with muscles aches. Conclusions The identified biomarkers are associated with inflammatory processes, corroborating literature evidence that long-COVID patients develop an inflammatory state that damages many tissues. Further studies are needed to validate this data in larger cohorts to identify specific biomarkers, and guide future preventive strategies or treatments to address long COVID and its cardiovascular and non-cardiovascular sequelae.