Toll-like receptor and matrix metalloproteinase single-nucleotide polymorphisms, haplotypes, and polygenic risk score differentiated between tuberculosis disease and infection

Single-nucleotide polymorphism 0301 basic medicine Toll-Like Receptors Infectious and parasitic diseases RC109-216 Polymorphism, Single Nucleotide Toll-Like Receptor 1 Toll-Like Receptor 2 Matrix Metalloproteinases 3. Good health Matrix metalloproteinase 03 medical and health sciences Matrix Metalloproteinase 8 Haplotypes Toll-like receptor Latent Tuberculosis Risk Factors Case-Control Studies Matrix Metalloproteinase 12 Humans Tuberculosis Latent tuberculosis infection Genetic Predisposition to Disease
DOI: 10.1016/j.ijid.2022.10.020 Publication Date: 2022-10-19T16:33:12Z
ABSTRACT
The association of toll-like receptors (TLRs) and matrix metalloproteinases (MMPs) single-nucleotide polymorphisms (SNPs) among latent tuberculosis (TB) infection and active TB remained less studied.We recruited participants with TB disease (active TB) (n = 400) and TB infection (latent TB infection) (n = 203) in this study. We genotyped SNPs in TLR1, TLR2, TLR4, MMP1, MMP8, MMP9, MMP12, and tissue inhibitor of MMP2. Single-variant analysis and haplotype analysis were performed, and a polygenic risk score (PRS) was created.We found that SNPs in TLR1 (rs5743580, rs5743551), TLR2 (rs3804100), and MMP8 (rs2508383) were associated with different TB disease status risks. TLR1 rs5743580 was associated with a higher risk of TB disease status in genotypic, recessive, and additive models. TLR2 rs3804100 polymorphisms demonstrated significant association with TB disease status in genotypic, dominant, and additive models. In the haplotype analysis, the TLR1 haplotype was associated with a higher risk of TB disease, and the MMP12 haplotype was associated with a lower risk of TB disease. A PRS using 3 SNPs was associated with a higher risk of TB disease.This study revealed that SNP variants in TLR1, TLR2, and MMP8 differed among TB infection and disease. Haplotypes and PRS could potentially help predict TB disease status.
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