Immune inhibitory receptor-mediated immune response, metabolic adaptation, and clinical characterization in COVID-19 patients

Abstract

Abstract Immune inhibitory receptors (IRs) have been demonstrated to play a critical role in the regulation of immune response to various respiratory viral infection. However, in COVID-19, the potential roles of the integrated effect of these IRs in immune modulation, metabolic reprogramming, and clinical characterization remains to be determined. Through the consensus clustering analysis of IR transcription in the peripheral blood of COVID-19 patients, we identified two distinct IR patterns in COVID-19 patients. And we demonstrated that IR_cluster2 patients characterized by lower expression of most IRs presented suppressed immune response, lower nutrient metabolism, and worse clinical manifestations or prognosis. To quantify and assess the IR patterns of individual COVID-19 patients, we established a scoring system named IRscore based on principal component analysis algorithms. Similar to IR_cluster2 patients, patients with high IRscore had a longer hospital-free days at day 45, required ICU admission and mechanical ventilatory support, and presented higher Charlson comorbidity index score and SOFA score. Moreover, high IRscore was also linked to high viral load, acute infection phase, and absence of drug intervention. Our investigation comprehensively elucidates the potential role of IR patterns in regulating immune response, modulating metabolic processes, and shaping clinical manifestations for COVID-19. All these evidences suggest the essential role of prognostic stratification and biomarker screening based on IR patterns in the clinical management and drug development of future emerging infectious diseases such as COVID-19.