Abstract
In the post-large era, various COVID-19 sequelae are getting more and more attention to health problems. Although the mortality rate of the COVID-19 infection is now declining, it is often accompanied by new clinical sequelae with different symptoms such as fatigue after infection, loss of smell. The degree of age, gender, virus infection seems to be weakly correlated with clinical symptoms. Human genetic variation plays a significant role in the sequelae of the COVID-19 infection. This study aims to analyze the genomic differences between individuals with different COVID-19 sequelae. In this study, the exomes of 97 patients with Omicron with 8 unique clinical manifestations are sequenced, and conducted a systematic analysis. Based on non-negative matrix factorization algorithms, the trinucleotide mutation spectrum of four long-term COVID-19 genomes is summarized and found that individuals with different clinical symptoms have unique DNA mutation patterns and indel patterns. By constructing a Genomic Fingerprinting Framework, the driver genes of variation in each symptomatic population are deciphered and analyzed. This study showed that population-specific mutational fingerprint differences are the main cause of heterogeneity in long-term COVID-19 sequelae. This study provides new ideas and insights into the causes of the long-term COVID-19 sequelae.