Guo et al. developed a random forest machine learning model based on proteomic and metabolomic data from COVID-19 patients, which incorporated genes such as SAA2,ALB,CRP,SAA1,HABP2, and HP, and was able to discriminate well between non-severe and severe COVID-19 patients (AUC = 0.957) [36]. This evidence concerns the gene SAA2 and COVID-19.