التفاصيل البيبلوغرافية
| العنوان: |
Human Genome Polymorphisms and Computational Intelligence Approach Revealed a Complex Genomic Signature for COVID-19 Severity in Brazilian Patients. |
| المؤلفون: |
Pastor, André Filipe, Docena, Cássia, Rezende, Antônio Mauro, Oliveira, Flávio Rosendo da Silva, Sena, Marília de Albuquerque, Morais, Clarice Neuenschwander Lins de, Bresani-Salvi, Cristiane Campello, Vasconcelos, Luydson Richardson Silva, Valença, Kennya Danielle Campelo, Mariz, Carolline de Araújo, Brito, Carlos, Fonseca, Cláudio Duarte, Braga, Cynthia, Reis, Christian Robson de Souza, Marques, Ernesto Torres de Azevedo, Acioli-Santos, Bartolomeu |
| المصدر: |
Viruses (1999-4915); Mar2023, Vol. 15 Issue 3, p645, 15p |
| مصطلحات موضوعية: |
COMPUTATIONAL intelligence, HUMAN genome, COVID-19 pandemic, COVID-19, SUPPORT vector machines |
| مستخلص: |
We present a genome polymorphisms/machine learning approach for severe COVID-19 prognosis. Ninety-six Brazilian severe COVID-19 patients and controls were genotyped for 296 innate immunity loci. Our model used a feature selection algorithm, namely recursive feature elimination coupled with a support vector machine, to find the optimal loci classification subset, followed by a support vector machine with the linear kernel (SVM-LK) to classify patients into the severe COVID-19 group. The best features that were selected by the SVM-RFE method included 12 SNPs in 12 genes: PD-L1, PD-L2, IL10RA, JAK2, STAT1, IFIT1, IFIH1, DC-SIGNR, IFNB1, IRAK4, IRF1, and IL10. During the COVID-19 prognosis step by SVM-LK, the metrics were: 85% accuracy, 80% sensitivity, and 90% specificity. In comparison, univariate analysis under the 12 selected SNPs showed some highlights for individual variant alleles that represented risk (PD-L1 and IFIT1) or protection (JAK2 and IFIH1). Variant genotypes carrying risk effects were represented by PD-L2 and IFIT1 genes. The proposed complex classification method can be used to identify individuals who are at a high risk of developing severe COVID-19 outcomes even in uninfected conditions, which is a disruptive concept in COVID-19 prognosis. Our results suggest that the genetic context is an important factor in the development of severe COVID-19. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |
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