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Next-generation sequencing of host genetics risk factors associated with COVID-19 severity and long-COVID in

Mariana Angulo-Aguado¹, Juan Camilo Carrillo-Martinez¹, Nora Constanza Contreras-Bravo¹

¹School of Medicine and Health Sciences, Center for Research in Genetics and Genomics (CIGGUR), Institute of Translational Medicine (IMT), Universidad Del Rosario, Bogotá, D.C, Colombia.

Scientific Reports

|April 11, 2024

Insights

This study identifies genetic markers associated with COVID-19 severity and long-COVID in a Latin American population. Integrating genetic and clinical data improves prediction models for better precision medicine in infectious diseases.

Area of Science:

Genetics
Infectious Diseases
Precision Medicine

Background:

Host genetic factors significantly influence COVID-19 severity and long-term symptoms.
Genetic factors in Latin American populations remain understudied.
Identifying genetic markers can aid in risk stratification and intervention development.

Purpose of the Study:

To investigate host genetic factors associated with COVID-19 severity and long-COVID in a Colombian population.
To develop and evaluate a predictive model for COVID-19 severity and long-COVID incorporating genetic and non-genetic variables.
To validate previously identified genetic variants in a Latin American cohort.

Main Methods:

Case-control study design analyzing 112 individuals (56 mild/asymptomatic, 56 severe/critical).
Next-generation sequencing (NGS) panel targeting 81 genetic variants in 74 genes.
Comparison of predictive models including clinical, genetic, and integrated (mixed) approaches.

Main Results:

Clinical variables like male sex, obesity, cough, and dyspnea were associated with severe COVID-19.
Thirteen genetic variants showed association with COVID-19 severity, notably rs11385942 (LZTFL1) and rs35775079 (CCR3).
The IL10RB variant rs8178521 was associated with long-COVID symptoms.
An integrated model combining genetic and non-genetic variables demonstrated superior predictive performance.

Conclusions:

This study is the first in Colombia and Latin America to propose a genomic-based predictive model for COVID-19 severity and long-COVID.
Genomic approaches are valuable for studying host genetic risk factors in diverse populations.
The findings underscore the importance of integrating genetic information into precision medicine strategies for infectious diseases.

Read full analysis

Abstract:

Coronavirus disease 2019 (COVID-19) was considered a major public health burden worldwide. Multiple studies have shown that susceptibility to severe infections and the development of long-term symptoms is significantly influenced by viral and host factors. These findings have highlighted the potential of host genetic markers to identify high-risk individuals and develop target interventions to reduce morbimortality. Despite its importance, genetic host factors remain largely understudied in Latin-American populations. Using a case-control design and a custom next-generation sequencing (NGS) panel encompassing 81 genetic variants and 74 genes previously associated with COVID-19 severity and long-COVID, we analyzed 56 individuals with asymptomatic or mild COVID-19 and 56 severe and critical cases. In agreement with previous studies, our results support the association between several clinical variables, including male sex, obesity and common symptoms like cough and dyspnea, and severe COVID-19. Remarkably, thirteen genetic variants showed an association with COVID-19 severity. Among these variants, rs11385942 (p < 0.01; OR = 10.88; 95% CI = 1.36-86.51) located in the LZTFL1 gene, and rs35775079 (p = 0.02; OR = 8.53; 95% CI = 1.05-69.45) located in CCR3 showed the strongest associations. Various respiratory and systemic symptoms, along with the rs8178521 variant (p < 0.01; OR = 2.51; 95% CI = 1.27-4.94) in the IL10RB gene, were significantly associated with the presence of long-COVID. The results of the predictive model comparison showed that the mixed model, which incorporates genetic and non-genetic variables, outperforms clinical and genetic models. To our knowledge, this is the first study in Colombia and Latin-America proposing a predictive model for COVID-19 severity and long-COVID based on genomic analysis. Our study highlights the usefulness of genomic approaches to studying host genetic risk factors in specific populations. The methodology used allowed us to validate several genetic variants previously associated with COVID-19 severity and long-COVID. Finally, the integrated model illustrates the importance of considering genetic factors in precision medicine of infectious diseases.

Keywords:

COVID-19 Long-COVID Next-generation sequencing Personalized medicine Predictive model

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