Fatores genéticos de risco e proteção para sequelas neurológicas da COVID-19

• Ano de defesa: 2025
• Autor(a) principal: Guaitolini, Yasmin Moreto
• Orientador(a): Louro, Iuri Drumond
• Banca de defesa: Paula, Flavia de , Carvalho, Elizeu Fagundes de
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal do Espírito Santo; Mestrado em Biotecnologia
• Programa de Pós-Graduação: Programa de Pós-Graduação em Biotecnologia
• Departamento: Centro de Ciências da Saúde
• País: BR
• Palavras-chave em Português: SARS-CoV-2; COVID longa; Sequelas neurológicas; Aprendizado de máquina; Biomarcadores genéticos; Long COVID; Neurological sequelae; Machine learning; Genetic biomarkers
• Área do conhecimento CNPq: Biotecnologia
• Link de acesso: http://repositorio.ufes.br/handle/10/20249

COVID-19, caused by SARS-CoV-2, has triggered a global crisis with significant health, social, and economic impacts. Although most infected individuals recover, some develop persistent sequelae known as post-COVID conditions, including neurological manifestations affecting the peripheral nervous system (PNS). Recent evidence suggests that host genetics may influence the susceptibility and severity of these sequelae, highlighting the importance of investigating genetic biomarkers associated with their occurrence. This is a case-control study aiming to identify genetic variants linked to the development of PNS sequelae following COVID-19, using whole-exome sequencing (WES) data. The cohort comprises 312 individuals without a complete vaccination scheme prior to infection, including 161 with sequelae (case group) and 151 without sequelae (control group). Clinical, sociodemographic, and genetic characteristics were analyzed. For genetic risk prediction, a machine learning (ML) model was implemented, testing different classifiers. The logistic regression (LR) model showed the best performance (AUC-ROC = 0.90, accuracy = 82%, and F1-score = 0.83), highlighting 20 SNPs most influential in predicting the risk of neurological sequelae. Analyses predominantly revealed pathways related to immune regulation, with the HLA-A (Antigen Peptide Transporter) gene playing a prominent role in this context. The PAQR5 gene (Progestin and AdipoQ Receptor Family Member 5), associated with steroid hormone signaling, was also identified. Additionally, other genes with undefined or poorly characterized functions, such as NPIPB15 (Nuclear Pore Complex Interacting Protein Family Member B15), possibly involved in nuclear transport, were observed. These findings suggest that immune response, inflammation, and alterations in lipid and hormonal metabolism may play a relevant role in the predisposition to neurological sequelae. The results obtained thus far provide important evidence on the genetic basis of these sequelae, contributing to the identification of susceptibility biomarkers and potential therapeutic targets, which may support advances, particularly in the clinical management of post-COVID-19 conditions