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Peer-reviewedCC BYJournal of medical virology

Deciphering Host Genomic Pathway Landscapes in Severe COVID-19 by Exome Sequencing of a Large Admixed Brazilian Cohort.

  • Aléxia Stefani Siqueira Zetum1
  • Danielle Ribeiro Campos da Silva1,2
  • Vinícius do Prado Ventorim1
  • Felipe Ataides Mion1
  • Felipe Dos Santos Passarela1
  • Patrícia Brasil3
  • Túlio de Lima Campos4
  • Bartolomeu Acioli-Santos5
  • Flávio Rosendo da Silva Oliveira6
  • Raquel Silva Dos Reis Trabach1
  • Lorena Souza Castro Altoé1
  • Débora Dummer Meira1
1 more authors
  • Iúri Drumond Louro1
6 affiliations
  1. 1Science Biology Department, Federal University of Espírito Santo, Vitória, Espírito Santo, Brazil.
  2. 2Haemostasis Laboratory, Hemotherapy and Hematology Center of Espírito Santo, Vitória, Espírito Santo, Brazil.
  3. 3Oswaldo Cruz Foundation, Rio de Janeiro, Rio de Janeiro, Brazil.
  4. 4Bioinformatics Center, Aggeu Magalhães Institute, Oswaldo Cruz Foundation, Recife, Pernambuco, Brazil.
  5. 5Department of Virology, Aggeu Magalhães Institute, Oswaldo Cruz Foundation, Recife, Pernambuco, Brazil.
  6. 6Federal Institute of Education, Science and Technology of Pernambuco, Recife, Pernambuco, Brazil.
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Abstract

The host genetic factors that resulted in the heterogeneous clinical outcomes of COVID-19 remained poorly understood, especially in admixed populations that are underrepresented in global genomic studies. In this study, we investigated the genetic landscape associated with COVID-19 severity using whole-exome sequencing data from 325 Brazilian individuals recruited between 2020 and 2023. To prioritize variants related to disease severity, we applied a machine learning framework combining Support Vector Machine - Recursive Feature Elimination and SHAP interpretation. This approach encompasses 25 variants that contributed to the model's discrimination between severe and non-severe cases (AUC = 0.94) in our cohort. Subsequently, logistic regression analyses adjusted for age, sex, principal components of ancestry, and significant comorbidities confirmed several loci associated with severity after correction for multiple testing (FDR < 0.05). The prioritized genes were grouped into biological axes, including mitochondrial bioenergetics, neuroimmune signaling, complement activation, and epithelial structural integrity. Variants in genes such as MUC16, SLC4A2, LAPS1, ARRDC2, and CCSER1 showed associations with disease severity. Furthermore, functional annotation using CADD and regulatory exploration using GTEx suggested that several loci may influence gene regulation in lung, immune, and neural tissues. Instead of implicating single causal variants, our findings highlight pathway-level genetic architectures that may contribute to the variability of the host response to COVID-19. These findings provide exploratory insights into potential host genetic pathways that may be involved in disease variability in admixed environments. However, replication in independent cohorts and functional validation are still needed.

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Cite

BibTeXRIS
BibTeX
@article{zetum2026deciphering,
  title = {{Deciphering Host Genomic Pathway Landscapes in Severe COVID-19 by Exome Sequencing of a Large Admixed Brazilian Cohort.}},
  author = {Aléxia Stefani Siqueira Zetum and Danielle Ribeiro Campos da Silva and Vinícius do Prado Ventorim and Felipe Ataides Mion and Felipe Dos Santos Passarela and Patrícia Brasil and Túlio de Lima Campos and Bartolomeu Acioli-Santos and Flávio Rosendo da Silva Oliveira and Raquel Silva Dos Reis Trabach and Lorena Souza Castro Altoé and Débora Dummer Meira and Iúri Drumond Louro},
  journal = {Journal of medical virology},
  year = {2026},
  month = nov,
  doi = {10.1002/jmv.71193},
  url = {https://europepmc.org/article/MED/42969658},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Deciphering Host Genomic Pathway Landscapes in Severe COVID-19 by Exome Sequencing of a Large Admixed Brazilian Cohort.
AU  - Aléxia Stefani Siqueira Zetum
AU  - Danielle Ribeiro Campos da Silva
AU  - Vinícius do Prado Ventorim
AU  - Felipe Ataides Mion
AU  - Felipe Dos Santos Passarela
AU  - Patrícia Brasil
AU  - Túlio de Lima Campos
AU  - Bartolomeu Acioli-Santos
AU  - Flávio Rosendo da Silva Oliveira
AU  - Raquel Silva Dos Reis Trabach
AU  - Lorena Souza Castro Altoé
AU  - Débora Dummer Meira
AU  - Iúri Drumond Louro
PY  - 2026
DA  - 2026/11/01
JO  - Journal of medical virology
DO  - 10.1002/jmv.71193
UR  - https://europepmc.org/article/MED/42969658
AB  - The host genetic factors that resulted in the heterogeneous clinical outcomes of COVID-19 remained poorly understood, especially in admixed populations that are underrepresented in global genomic studies. In this study, we investigated the genetic landscape associated with COVID-19 severity using whole-exome sequencing data from 325 Brazilian individuals recruited between 2020 and 2023. To prioritize variants related to disease severity, we applied a machine learning framework combining Support Vector Machine - Recursive Feature Elimination and SHAP interpretation. This approach encompasses 25 variants that contributed to the model's discrimination between severe and non-severe cases (AUC = 0.94) in our cohort. Subsequently, logistic regression analyses adjusted for age, sex, principal components of ancestry, and significant comorbidities confirmed several loci associated with severity after correction for multiple testing (FDR < 0.05). The prioritized genes were grouped into biological axes, including mitochondrial bioenergetics, neuroimmune signaling, complement activation, and epithelial structural integrity. Variants in genes such as MUC16, SLC4A2, LAPS1, ARRDC2, and CCSER1 showed associations with disease severity. Furthermore, functional annotation using CADD and regulatory exploration using GTEx suggested that several loci may influence gene regulation in lung, immune, and neural tissues. Instead of implicating single causal variants, our findings highlight pathway-level genetic architectures that may contribute to the variability of the host response to COVID-19. These findings provide exploratory insights into potential host genetic pathways that may be involved in disease variability in admixed environments. However, replication in independent cohorts and functional validation are still needed.
SN  - 0146-6615
SN  - 1096-9071
ER  -