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Genetic polymorphism in the pregnancy-associated plasma protein-A associated with acute myocardial infarction

Authors
 Sungha Park  ;  Jong-Chan Youn  ;  Namsik Chung  ;  Yangsoo Jang  ;  Jong-Won Ha  ;  Donghoon Choi  ;  Young-Guk Ko  ;  Jung-Sun Kim  ;  Chan-Mi Park  ;  Dong-Jik Shin 
Citation
 CORONARY ARTERY DISEASE, Vol.18(6) : 417-422, 2007 
Journal Title
CORONARY ARTERY DISEASE
ISSN
 0954-6928 
Issue Date
2007
Abstract
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.
Full Text
http://ovidsp.ovid.com/ovidweb.cgi?T=JS&CSC=Y&NEWS=N&PAGE=fulltext&AN=00019501-200709000-00001&LSLINK=80&D=ovft
DOI
10.1097/MCA.0b013e328241d967
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Biomedical Systems Informatics (의생명시스템정보학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Internal Medicine (내과학교실) > 1. Journal Papers
Yonsei Authors
Ko, Young Guk(고영국) ORCID logo https://orcid.org/0000-0001-7748-5788
Kim, Jung Sun(김중선) ORCID logo https://orcid.org/0000-0003-2263-3274
Park, Sung Ha(박성하) ORCID logo https://orcid.org/0000-0001-5362-478X
Park, Chan Mi(박찬미)
Jang, Yang Soo(장양수) ORCID logo https://orcid.org/0000-0002-2169-3112
Chung, Nam Sik(정남식)
Choi, Dong Hoon(최동훈) ORCID logo https://orcid.org/0000-0002-2009-9760
Ha, Jong Won(하종원) ORCID logo https://orcid.org/0000-0002-8260-2958
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/95922
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