Toll-like receptor and matrix metalloproteinase single-nucleotide polymorphisms, haplotypes, and polygenic risk score

Meng-Rui Lee1, Yen-Lin Chen2, Chang-Wei Wu1

  • 1Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan; Department of Internal Medicine, National Taiwan University Hospital Hsin-Chu Branch, Hsin-Chu, Taiwan.

Abstract

Insights

Single-nucleotide polymorphisms (SNPs) in toll-like receptors (TLRs) and matrix metalloproteinases (MMPs) are linked to tuberculosis (TB) risk. Specific TLR1, TLR2, and MMP8 variants, along with haplotypes and a polygenic risk score, may help predict active TB disease.

Area of Science:

  • Immunogenetics
  • Tuberculosis Research

Background:

  • Toll-like receptors (TLRs) and matrix metalloproteinases (MMPs) play roles in immune responses.
  • The genetic associations of TLR and MMP single-nucleotide polymorphisms (SNPs) with tuberculosis (TB) infection and disease are not fully understood.

Purpose of the Study:

  • To investigate the association between SNPs in TLR and MMP genes and the risk of latent TB infection versus active TB disease.
  • To evaluate the predictive potential of genetic variants, haplotypes, and polygenic risk scores for TB disease status.

Main Methods:

  • Genotyping of SNPs in TLR1, TLR2, TLR4, MMP1, MMP8, MMP9, MMP12, and tissue inhibitor of MMP2 in 400 active TB patients and 203 latent TB individuals.
  • Performed single-variant analysis, haplotype analysis, and created a polygenic risk score (PRS).

Main Results:

  • SNPs in TLR1 (rs5743580, rs5743551), TLR2 (rs3804100), and MMP8 (rs2508383) were associated with TB disease risk.
  • TLR1 rs5743580 and TLR2 rs3804100 showed significant associations with TB disease status across multiple models.
  • TLR1 haplotype increased TB disease risk, while MMP12 haplotype decreased it. A PRS of 3 SNPs was linked to higher TB disease risk.

Conclusions:

  • Specific SNP variants in TLR1, TLR2, and MMP8 differentiate between TB infection and disease.
  • Haplotype and PRS analyses suggest potential utility in predicting active TB disease status.

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