A Genome-Wide Association Study of Resistance to Tuberculosis Infection in a Multi-Ancestry Brazilian Cohort Public

Fernandes Gyorfy, Matheus (Spring 2023)

Permanent URL: https://etd.library.emory.edu/concern/etds/j67315034?locale=fr
Published

Abstract

Background: Tuberculosis (TB) impacts over a quarter of world’s population. Although its global incidence rate has been steadily decreasing due to advancements in testing capabilities and novel drug regimens, the relationship between host genetic and molecular factors and infectious pathogen remains largely underexplored. Studies assessing resistance to Mycobacterium tuberculosis (Mtb) infection have been limited by a lack of consistent classification of infectious and exposure levels. Methods: Among household contacts of active TB patients, we used detailed measurements of exposure levels and TB infection to identify most likely resisters to Mtb infection. Using imputed single nucleotide polymorphisms (SNP) data from TOPMed imputation panel, we conducted a genome-wide association study (GWAS) of resistance to Mtb infection in 1,540 multi-ancestry Brazilian participants. Results: A total of 232 (15.1%) individuals whose Tuberculin Skin Test (TST) or Interferon-Gamma Release Assay (IGRA) results were negative and who experienced the highest-level exposure were categorized as resisters. This analysis identified SNPs significantly associated with resistance to Mtb infection, from four loci close to genes PARD3B (rs888091, OR = 2.93 [95%CI: 2.56, 3.30]; p = 9.99E-9]), AC073987.1 (rs117179998, OR = 2.81 [95%CI: 2.46, 3.16]; p = 1.02E-8), IQCA1 (rs35136956, OR = 2.10 [95%CI: 1.81, 2.39]; p = 3.88E-8) in chromosome 2, and COL18A1 (rs80327334, OR = 2.15 [95%CI: 1.88, 2.42]; p = 4.69E-8) in chromosome 21. However, we observed substantial inflation of low p-values (inflation factor of 1.17) which can be caused by relatedness among household contacts. Conclusion: Our findings demonstrated the role of human genetic factors in the resistance to Mtb infection. In the future, we will address the global inflation by adjustment of relatedness of study participants. To further validate our results, we will conduct replication and meta-analysis using similar household contact cohorts from India and South Africa.

Table of Contents

INTRODUCTION

METHODS

Study Design and Population Phenotype

Samples Genotyping, Quality Control, and Imputation

Statistical, Graphical, and Annotations Methods

Ethical Considerations

RESULTS

Primary Analysis

Preliminary Analysis

Previously Published Loci

DISCUSSION

LIMITATIONS AND FUTURE WORK

REFERENCES



TABLES AND FIGURES

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