Integrating genomic architecture and tuberculosis (TB) immunity in Africa

University Of Colorado Denver, Aurora CO

Investigators

Abstract

Modified Project Summary/Abstract Section The human obligate bacterium Mycobacterium tuberculosis (M.tb) infects approximately a quarter of the world's population, leading to chronic disease with an annual death toll exceeding 1.6 million. The disruption of services during the COVID-19 pandemic resulted in a 4.5% increase in cases, exceeding 6 million new cases in 2021, with Africa bearing a critical burden. The incidence in USA is increasing by 16% per year. Not all infected individuals progress to active disease, and we have shown in genome-wide association studies (GWAS) that human host genetic factors contribute to disease outcome. To identify new ways to improve disease outcome, human studies to characterize the genetic factors involved in TB and its interaction with the immune system are urgently needed. Here, we focus on the genetic susceptibility to active TB, focusing on HLA and its interactions with the KIR genes of natural killer (NK) cells, critical in shaping the immune response against TB. In this study, we propose to uniquely leverage the diversity of South African populations (sub-Saharan African, European, and South-East Asian ancestries) to perform multi-ethnic associations with broad applicability. Specifically, we aim to: 1) Generate population-level data (HLA, KIR, and SNP array) on 5,000 case/control samples, characterizing genetic diversity across multi-ancestry individuals from South Africa; 2) Perform binding and cytotoxic assays to functionally test/develop interaction scores for newly discovered alleles, and determine their specific NK impact on NK cell function 3) Develop appropriate, well-powered statistical models for association of HLA/KIR variation and HLA/KIR interaction with disease susceptibility. The Northern Cape Province, South Africa provides an ideal location to perform this study; the extremely high community TB incidence results in lower misclassification bias introduced by unknown or low infectious disease exposure. Outcomes include: a) studying a large TB case-control dataset of DNA, clinically-active cases and epidemiological variables of 5,000 participants; b) clarifying the role of NK cells in TB pathogenesis; c) appropriately calibrated statistical models of HLA/KIR association in admixed populations. We have an outstanding track record of collaboration, including ≥ 40 co-authored publications, as well as expertise in clinical epidemiology, statistical and population genetics, and immunogenetics, uniquely positioning us to address this critical research question using innovative methods -- including direct HLA and KIR allele sequencing and functional validation of their interactions. Through direct genetic assays, complex interaction analyses, and advanced statistical approaches, this study aims to shed light on the genetic risk factors and the immunogenetic landscape critical for understanding and combatting TB.