TY - JOUR
T1 - Identification of an interaction between VWF rs7965413 and platelet count as a novel risk marker for metabolic syndrome
T2 - An extensive search of candidate polymorphisms in a case-control study
AU - Nakatochi, Masahiro
AU - Ushida, Yasunori
AU - Yasuda, Yoshinari
AU - Yoshida, Yasuko
AU - Kawai, Shun
AU - Kato, Ryuji
AU - Nakashima, Toru
AU - Iwata, Masamitsu
AU - Kuwatsuka, Yachiyo
AU - Ando, Masahiko
AU - Hamajima, Nobuyuki
AU - Kondo, Takaaki
AU - Oda, Hiroaki
AU - Hayashi, Mutsuharu
AU - Kato, Sawako
AU - Yamaguchi, Makoto
AU - Maruyama, Shoichi
AU - Matsuo, Seiichi
AU - Honda, Hiroyuki
N1 - Publisher Copyright:
© 2015 Nakatochi et al.
PY - 2015/2/3
Y1 - 2015/2/3
N2 - Although many single nucleotide polymorphisms (SNPs) have been identified to be associated with metabolic syndrome (MetS), there was only a slight improvement in the ability to predict future MetS by the simply addition of SNPs to clinical risk markers. To improve the ability to predict future MetS, combinational effects, such as SNP - SNP interaction, SNP - environment interaction, and SNP - clinical parameter (SNP × CP) interaction should be also considered. We performed a case-control study to explore novel SNP × CP interactions as risk markers for MetS based on health check-up data of Japanese male employees. We selected 99 SNPs that were previously reported to be associated with MetS and components of MetS; subsequently, we genotyped these SNPs from 360 cases and 1983 control subjects. First, we performed logistic regression analyses to assess the association of each SNP with MetS. Of these SNPs, five SNPs were significantly associated with MetS (P < 0.05): LRP2 rs2544390, rs1800592 between UCP1 and TBC1D9, APOA5 rs662799, VWF rs7965413, and rs1411766 between MYO16 and IRS2. Furthermore, we performed multiple logistic regression analyses, including an SNP term, a CP term, and an SNP × CP interaction term for each CP and SNP that was significantly associated with MetS. We identified a novel SNP × CP interaction between rs7965413 and platelet count that was significantly associated with MetS [SNP term: odds ratio (OR) = 0.78, P = 0.004; SNP × CP interaction term: OR = 1.33, P = 0.001]. This association of the SNP × CP interaction with MetS remained nominally significant in multiple logistic regression analysis after adjustment for either the number of MetS components or MetS components excluding obesity. Our results reveal new insight into platelet count as a risk marker for MetS.
AB - Although many single nucleotide polymorphisms (SNPs) have been identified to be associated with metabolic syndrome (MetS), there was only a slight improvement in the ability to predict future MetS by the simply addition of SNPs to clinical risk markers. To improve the ability to predict future MetS, combinational effects, such as SNP - SNP interaction, SNP - environment interaction, and SNP - clinical parameter (SNP × CP) interaction should be also considered. We performed a case-control study to explore novel SNP × CP interactions as risk markers for MetS based on health check-up data of Japanese male employees. We selected 99 SNPs that were previously reported to be associated with MetS and components of MetS; subsequently, we genotyped these SNPs from 360 cases and 1983 control subjects. First, we performed logistic regression analyses to assess the association of each SNP with MetS. Of these SNPs, five SNPs were significantly associated with MetS (P < 0.05): LRP2 rs2544390, rs1800592 between UCP1 and TBC1D9, APOA5 rs662799, VWF rs7965413, and rs1411766 between MYO16 and IRS2. Furthermore, we performed multiple logistic regression analyses, including an SNP term, a CP term, and an SNP × CP interaction term for each CP and SNP that was significantly associated with MetS. We identified a novel SNP × CP interaction between rs7965413 and platelet count that was significantly associated with MetS [SNP term: odds ratio (OR) = 0.78, P = 0.004; SNP × CP interaction term: OR = 1.33, P = 0.001]. This association of the SNP × CP interaction with MetS remained nominally significant in multiple logistic regression analysis after adjustment for either the number of MetS components or MetS components excluding obesity. Our results reveal new insight into platelet count as a risk marker for MetS.
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U2 - 10.1371/journal.pone.0117591
DO - 10.1371/journal.pone.0117591
M3 - Article
C2 - 25646961
AN - SCOPUS:84922358051
SN - 1932-6203
VL - 10
JO - PloS one
JF - PloS one
IS - 2
M1 - e0117591
ER -