Local Ancestry Adjusted Allelic Association Analysis Robustly Captures Tuberculosis Susceptibility Loci

Abstract

Pulmonary tuberculosis (TB), caused by Mycobacterium tuberculosis, is a complex disease. The risk of developing active TB is in part determined by host genetic factors. Most genetic studies investigating TB susceptibility fail to replicate association signals particularly across diverse populations. South African populations arose because of multi-wave genetic admixture from the indigenous KhoeSan, Bantu-speaking Africans, Europeans, Southeast Asian-and East Asian populations. This has led to complex genetic admixture with heterogenous patterns of linkage disequilibrium and associated traits. As a result, precise estimation of both global and local ancestry is required to prevent both false positive and false-negative associations. Here, 820 individuals from South Africa were genotyped on the SNP-dense Illumina Multi-Ethnic Genotyping Array (∼1.7M SNPs) followed by local and global ancestry inference using RFMix. Local ancestry adjusted allelic association (LAAA) models were utilized owing to the extensive genetic heterogeneity present in this population. Hence, an interaction term, comprising the identification of the minor allele that corresponds to the ancestry present at the specific locus under investigation, was included as a covariate. One SNP (rs28647531) located on chromosome 4q22 was significantly associated with TB susceptibility and displayed a SNP minor allelic effect (G allele, frequency = 0.204) whilst correcting for local ancestry for Bantu-speaking African ancestry (p-value = 5.518 × 10−7; OR = 3.065; SE = 0.224). Although no other variants passed the significant threshold, clear differences were observed between the lead variants identified for each ancestry. Furthermore, the LAAA model robustly captured the source of association signals in multi-way admixed individuals from South Africa and allowed the identification of ancestry-specific disease risk alleles associated with TB susceptibility that have previously been missed.

cis-eQTL mapping of TB-T2D comorbidity elucidates the involvement of African ancestry in TB susceptibility

“…The local ancestry represented in karyograms indicates the ancestry of each genomic region from chromosome 1 to 22 (Fig S8). Noticeably, the local ancestry patterns appear to be highly heterogeneous, which is in line with previous studies [13,14]. The successful inference of both global and local ancestry allowed the efficient inclusion of this covariate in the subsequent statistical models.…”

Evolutionary Genetics and Admixture in African Populations

“…A greater understanding of the genetic architecture can help explain differences in disease risk between populations. One key example of this involves tuberculosis, a disease that has particularly severe infections in the SAC population ( Chimusa et al 2014 ; Swart et al 2021 ). Leveraging local ancestry and population-specific high-density genotype data, a novel SNP (rs28647531) on chromosome 4q22 was associated with tuberculosis susceptibility in the SAC population.…”

“…Leveraging local ancestry and population-specific high-density genotype data, a novel SNP (rs28647531) on chromosome 4q22 was associated with tuberculosis susceptibility in the SAC population. This displayed an SNP minor allelic effect while correcting for local ancestry for Bantu-speaking African ancestry ( Swart et al 2021 ). This example illustrates that admixed African populations are a promising opportunity to better understand ancestry-specific disease risk compared with homogeneous populations ( Patterson et al 2010 ).…”

Genome-wide host-pathogen analyses reveal genetic interaction points in tuberculosis disease

“…Both FSTL5 and DAP proteins were associated with a clade containing fifteen lineage 2.2.1 (Beijing) strains. SNPs in the FSTL5 gene, which codes for a protein involved in calcium binding, has been associated with susceptibility to TB in an ancestry-adjusted association analysis 29 . DAP codes for a protein involved in mediation of cell death induced by IFNγ.…”