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Area of Science:

  • Genetics
  • Cardiovascular Disease Research
  • Statistical Modeling

Background:

  • Systolic blood pressure (SBP) is a critical cardiovascular risk factor.
  • Understanding the genetic basis of SBP variability is essential for personalized medicine.
  • Existing models may not fully capture the joint effects of multiple genetic variants on longitudinal SBP changes.

Purpose of the Study:

  • To develop and validate a novel mixed-effects model for analyzing longitudinal SBP data.
  • To estimate the joint effect of multiple sequence variants on SBP, considering familial correlations and time dependencies.
  • To identify specific multilocus genotypes associated with SBP levels.

Main Methods:

  • Conducted a genome-wide association study (GWAS) using chromosome 3 single-nucleotide polymorphisms (SNPs).
  • Fine-mapped additional variants in identified regions associated with SBP.
  • Employed a linear mixed-effects model with multilocus genotypes as random effects to assess joint effects.

Main Results:

  • Identified four significant SNPs in intergenic regions (PLXNA1-TPRA1, BPESC1-PISTR1) and the gene NLGN1 associated with SBP.
  • Determined specific multilocus genotypes (e.g., GG,TT,AG,GG) linked to elevated SBP.
  • Identified other multilocus genotypes (e.g., GG,CT,AA,AA) associated with reduced SBP.

Conclusions:

  • The proposed linear mixed-effects model is a powerful tool for GWAS and joint modeling of multilocus genotypes.
  • This approach enhances the understanding of genetic contributions to longitudinal SBP changes.
  • Findings provide insights into genetic risk factors for hypertension and potential therapeutic targets.