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. 2018 Sep 5;38(11):1853–1871. doi: 10.1177/0271678X18797958

Table 1.

Ischemic stroke.

Study Country(ies) of study Cases/ controls Gene Relevant function Reference SNP # Amino acid change Common name Associated population Inheritance model OR CI at 95% p
Variants associated with ischemic stroke
 He et al.20 China 500/600 MTHFR Endothelial and vascular health (homocysteine metabolism) rs868014 *in 3′-UTR* Chinese Han Recessive 1.99 1.29–3.88 0.001a
Dominant 1.71 1.33–3.56 <0.001a
 Wei et al.16 Iraq, India, China, Korea, Romania, Italy, Australia, China, Denmark, Germany, Belgium, Ireland, Japan, North America, Sweden, Austria, Poland, UK, Malaysia, Tunisia, USA, Turkey, Brazil, Hungary, Morocco, Croatia, Turkey, South Korea 29,637/ 30,880 rs1801133 229A > V 677C > T Multiethnic allelic 1.32 1.25–1.40 <0.001
Recessive 1.41 1.31–1.51 <0.001
Over-dominant 1.11 1.05–1.17 <0.001
Asian Allelic 1.43 1.34–1.52 <0.001
Recessive 1.47 1.35–1.59 <0.001
Over-dominant 1.18 1.11–1.25 <0.001
Caucasian Recessive 1.28 1.10–1.48 0.002
5674/6793 rs1801131 429E > A 1298A > C Multiethnic Allelic 1.21 1.05–1.38 0.006
Recessive 1.45 1.13–1.87 0.004
Allelic 1.38 1.26–1.53 <0.001
Recessive 1.86 1.42–2.43 <0.001
Over-dominant 1.27 1.10–1.48 0.002
29,506/ 32,628 ApoE Plasma lipid metabolism rs429358 130C > R ɛ4 Multiethnic Allelic 1.58 1.40–1.79 <0.001
Asian Allelic 1.7 1.47–1.97 <0.001
Caucasian Allelic 1.27 1.01–1.60 0.04
 Chen and Hu21 China 6190/6248 Chinese Additive 2.19 1.90–2.52 <0.001
Dominant 2.41 2.00–2.89 <0.001
 Wei et al.16 Iraq, India, China, Korea, Romania, Italy, Australia, China, Denmark, Germany, Belgium, Ireland, Japan, North America, Sweden, Austria, Poland, UK, Malaysia, Tunisia, USA, Turkey, Brazil, Hungary, Morocco, Croatia, Turkey, South Korea 10,198/ 10,821 eNOS Endothelial and vascular health rs1799983 298D > E +894G > T Multiethnic Allelic 1.25 1.13–1.38 0.003
Recessive 1.29 1.10–1.50 0.001
Over-dominant 1.15 1.03–1.29 0.01
Asian Allelic 1.45 1.23–1.69 <0.001
Recessive 1.56 1.16–2.08 0.003
Over-dominant 1.26 1.06–1.49 0.008
Caucasian Recessive 1.2 1.00–1.43 0.001
6501/ 14,101 AGT Blood pressure modulation rs699 235M > T Multiethnic allelic 1.33 1.17–1.50 <0.001
Recessive 1.41 1.22–1.64 <0.001
Asians Allelic 1.4 1.24–1.59 <0.001
Recessive 1.5 1.28–1.75 0.002
9022/ 9792 PON1 Plasma lipid metabolism rs662 192Q>R Multiethnic Allelic 1.14 1.06–1.23 <0.001
Recessive 1.15 1.02–1.29 0.02
Asian Allelic 1.15 1.04–1.28 0.005
Recessive 1.16 1.01–1.33 0.04
Dominant 0.81 0.70–0.94 0.005
 Casas et al.4 Various 4588/13,798 Factor V Coagulation rs6025 506R > Q Leiden Caucasian Dominant 1.33 1.12–1.58 0.03
 Au et al.26 Turkey, Hungary, China 945/464 APOA5 Plasma lipid modulation rs3135506 19S > W 56C > G Multiethnic Over-dominant 1.97 1.23–3.16 0.005
allelic 1.77 1.15–2.73 0.009
Brazil, Russia, Serbia, China 696/987 APOB rs1042031 4181E > K Multiethnic Over-dominant 1.88 1.46–2.42 <0.001
Allelic 1.66 1.35–2.05 <0.001
Germany, China, Russia, UK 2873/3146 ABCA1 rs2230806 219R > K Multiethnic Dominant 1.31 1.16–1.48 <0.001
2052/2106 Asian Dominant 1.37 1.19–1.57 <0.001
 Wang et al.27 China 895/883 APOC3 rs4520 *silent* Silent T-C Chinese Han Recessive 2.05 1.28–3.29 <0.01b
rs5128 *in 3′-UTR* Recessive 0.2 0.09–0.43 <0.01b
 Yamada et al.28 Japan 1575/9210 TMPRSS7 Blood pressure modulation rs147783135 *truncated protein* R692* Japanese Additive 1 0.38 0.17–0.74 0.0029c
Dominant 0.37 0.16–0.72 0.0024c
PDIA5 Coagulation rs2292661 391T > M Additive 1 0.35 0.14–0.76 0.0054c
Dominant 0.35 0.14–0.76 0.0054c
CYP4F12 Inflammation rs191885206 402C>R Additive 1 2.6 1.30–4.93 0.0082c
Dominant 2.6 1.30–4.93 0.0082c
 Ma et al.29 USA, China 2108/1924 RAGE rs2070600 82G>S Multiethnic Allelic 1.32 1.05–1.65 <0.05
Recessive 2.2 1.74–2.78 <0.05
Dominant 1.2 1.04–1.38 <0.05
 Misra et al.34 India, Germany, UK 713/948 PSMA6 rs1048990 *in 5′-UTR* 8C>G Multiethnic Recessive 0.25 0.08–0.72 0.01
 Kim et al.35 South Korea 523/400 miR-200b Coagulation rs7549819 *non-coding RNA* South Korean Recessive 0.475 0.239–0.944 0.034d
 Kovalevа et al.31 Russia 1200/500 HIF1a Erythropoiesis rs11549465 582P > S 1772C > T Russian Not specified 1.603 0.01
 Zhu et al.32 China 1102/1610 NLRP3 Inflammation rs10754558 *in 3′-UTR* Chinese Han Additive 1.60 1.41–1.73 <0.001
Dominant 1.81 1.57–2.11 <0.001
Recessive 2.01 1.65–2.45 <0.001
 Sung et al.33 Taiwan 914/746 ALDH2 Ethanol metabolism rs671 487E > K *2 allele Taiwanese Recessive 1.84 1.10–3.08 0.02
 Tong et al.36 China 648/648 PPARγ Plasma lipid modulation rs1801282 12P > A East Asian Additive 0.542 0.346–0.850 0.008e
Dominant 0.555 0.356–0.864 0.009e
Variants associated with large-vessel ischemic stroke
 Malik et al.30 Australia, Germany, UK, South Asia 3127/9778 SERPINA1 Inflammation rs6647 237V > A Multiethnic Not specified 1.22 1.13–1.31 <0.001
3127/9779 HDAC9 Epigenetics rs2023938 *in 3′-UTR* Multiethnic Not specified 1.28 1.16–1.40 <0.002
Monogenic disorders associated with ischemic stroke
 Christoffersen  et al.38 Denmark 2020/57,170 WRN DNA repair rs1346044 1367C > R Danish Recessive 1.14 1.04–1.25 0.02f
a

Adjusted for age, gender, parental smoking, and drinking.

b

Adjusted for age, gender, BMI, diabetes mellitus, hypertension, history of smoking, history of alcohol use, family history of stroke and hyperlipidemia.

c

Adjusted for age, sex, hypertension, and diabetes mellitus. Based on Bonferroni's correction.

d

Derived by multivariate logistic regression adjusted for age, sex, hypertension, diabetes mellitus, hyperlipidemia, and current smoking.

e

Multivariate logistic regression analysis adjusted for sex, age, hypertension, diabetes, smoking, alcohol drinking, tea drinking, BMI, and waist-hip ratio.

f

Adjusted for age, sex, total cholesterol, LDL cholesterol, HDL cholesterol, triglycerides, BMI, hypertension, diabetes, cumulated smoking exposure, heavy alcohol consumption, use of lipid lowering therapy, and physical activity.

OR: odds ratio; CI: confidence interval.