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Updated: Jul 13, 2026

A Method to Study the C924T Polymorphism of the Thromboxane A2 Receptor Gene
Published on: April 1, 2019
Genetic polymorphism in the pregnancy-associated plasma protein-A associated with acute myocardial infarction
Sungha Park1, Jong-Chan Youn, Dong-Jik Shin
1Division of Cardiology, Yonsei Cardiovascular Center, Yonsei University College of Medicine, Shinchon-Dong, Seodaemun-Ku, Seoul, Republic of Korea.
Background:
Pregnancy-associated plasma protein-A (PAPP-A) is a high-molecular-weight, zinc-binding matrix metalloproteinase that is known to be abundantly expressed in ruptured plaques. Previous studies have shown PAPP-A to be a significant marker of plaque instability and cardiovascular events in patients with acute coronary syndromes. Because the activity of PAPP-A may be modulated by genetic variants in the PAPP-A genes, we tried to determine the association of PAPP-A gene with acute myocardial infarction (AMI).
Methods:
We analyzed four single nucleotide polymorphisms (SNPs) of PAPP-A gene variants and seven other polymorphisms of cytokine genes that have been reported to have functional significance (RANTES G-403A, MCP1 G-2518A, CRP A2147G, CRP G-717A, AGER G557A, LTA T26A, IL-6 G-572C) for possible association with AMI in 170 unrelated AMI patients and unrelated age-matched controls, respectively.
Results:
The average age of the study population was 62.2+/-11.4 years in AMI patients and 62.6+/-10.4 years in healthy controls. Multiple logistic regression analysis with risk factors such as age, male sex, smoking, hypertension, diabetes mellitus, and dyslipidemia revealed the PAPP-A IVS6+95 C allele to be associated with an increased risk of AMI (dominancy: odds ratio, 2.13; 95% confidence interval, 1.12-4.07; P=0.022; codominancy: odds ratio, 1.89; 95% confidence interval, 1.14-3.16; P=0.015).
Conclusions:
We found, for the first time, that PAPP-A IVS6+95 C allele is an independent risk factor for AMI even after adjustment for traditional risk factors. The determination of such genotype contributing to AMI could provide a new tool for identifying high-risk individuals.
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