Genomic Biomarker Heterogeneities between SARS-CoV-2 and COVID-19

  1. Zhengjun Zhang

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Abstract

Genes functionally associated with SARS-CoV-2 infection and genes functionally related to the COVID-19 disease can be different, whose distinction will become the first essential step for successfully fighting against the COVID-19 pandemic. Unfortunately, this first step has not been completed in all biological and medical research. Using a newly developed max-competing logistic classifier, two genes, ATP6V1B2 and IFI27, stand out to be critical in the transcriptional response to SARS-CoV-2 infection with differential expressions derived from NP/OP swab PCR. This finding is evidenced by combining these two genes with another gene in predicting disease status to achieve better-indicating accuracy than existing classifiers with the same number of genes. In addition, combining these two genes with three other genes to form a five-gene classifier outperforms existing classifiers with ten or more genes. These two genes can be critical in fighting against the COVID-19 pandemic as a new focus and direction with their exceptional predicting accuracy. Comparing the functional effects of these genes with a five-gene classifier with 100% accuracy identified and tested from blood samples in our earlier work, the genes and their transcriptional response and functional effects on SARS-CoV-2 infection, and the genes and their functional signature patterns on COVID-19 antibodies, are significantly different. We will use a total of fourteen cohort studies (including breakthrough infections and omicron variants) with 1481 samples to justify our results. Such significant findings can help explore the causal and pathological links between SARS-CoV-2 infection and the COVID-19 disease, and fight against the disease with more targeted genes, vaccines, antiviral drugs, and therapies.

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  1. Version published to 10.3390/vaccines10101657
  2. Version published to 10.1101/2022.01.13.476223v2 on bioRxiv
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  4. Version published to 10.1101/2022.01.13.476223v1 on bioRxiv