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Association of CETP Gene Polymorphisms and Haplotypes with Cardiovascular Risk.

Peter PikoTibor JeneiZsigmond KosaJanos SandorNora KovacsIldiko SeresGyorgy ParaghRoza Adany
Published in: International journal of molecular sciences (2023)
Cholesteryl ester transfer protein ( CETP ) is known to influence HDL-C levels, potentially altering the profile of HDL subfractions and consequently cardiovascular risk (CVR). This study aimed to investigate the effect of five single-nucleotide polymorphisms (SNPs; rs1532624, rs5882, rs708272, rs7499892, and rs9989419) and their haplotypes (H) in the CETP gene on 10-year CVR estimated by the Systematic Coronary Risk Evaluation (SCORE), the Framingham Risk Score for Coronary Heart Disease (FRS CHD ) and Cardiovascular Disease (FRS CVD ) algorithms. Adjusted linear and logistic regression analyses were used to investigate the association of SNPs and 10 haplotypes (H1-H10) on 368 samples from the Hungarian general and Roma populations. The T allele of rs7499892 showed a significant association with increased CVR estimated by FRS. H5, H7, and H8 showed a significant association with increased CVR based on at least one of the algorithms. The impact of H5 was due to its effect on TG and HDL-C levels, while H7 showed a significant association with FRS CHD and H8 with FRS CVD mediated by a mechanism affecting neither TG nor HDL-C levels. Our results suggest that polymorphisms in the CETP gene may have a significant effect on CVR and that this is not mediated exclusively by their effect on TG and HDL-C levels but also by presently unknown mechanisms.
Keyphrases
  • cardiovascular disease
  • machine learning
  • genome wide
  • coronary artery
  • heart failure
  • deep learning
  • protein protein
  • transcatheter aortic valve replacement
  • cardiovascular risk factors