Table 1.
Main characteristics of studies involved in this meta-analysis of PCSK9 E670G polymorphism and CAD risk
| First author | Year | Country | Ethnicity | Mean age (years) (case/control) | Type of study | Sample size (case/control) | Cases | Controls | Genotyping method | MAF (control, %) | HWE (P) | ||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| AA | AG | GG | AA | AG | GG | ||||||||||
| Salazar LA [16] | 2007 | Chile | Caucasian | -/ - | C-C | 110/108 | 105 | 5 | 0 | 103 | 5 | 0 | PCR-RFLP | 2.3 | >0.05 |
| Hsu LA [10] | 2009 | China | Asian | 55.6 + 10.5/ 45.9 + 10.4 | C-C | 202/614 | 182 | 20 | 0 | 541 | 72 | 1 | PCR-RFLP | 6.0 | >0.05 |
| Zeng J [19] | 2011 | China | Asian | 65.9 ± 10.2/ 57.0 ± 8.7 | C-C | 212/184 | 167 | 38 | 7 | 165 | 17 | 2 | PCR-RFLP | 5.7 | >0.05 |
| Meng YH [7] | 2011 | China | Asian | 66.49 ± 9.92/ 64.34 ± 15.35 | C-C | 165/180 | 146 | 19 | 0 | 166 | 14 | 0 | PCR-RFLP | 3.9 | >0.05 |
| Slimani A [8] | 2014 | Tunisian | African | 61[55–67]/ 49[45–55] | C-C | 192/232 | 148 | 37 | 7 | 199 | 32 | 1 | PCR-RFLP | 7.3 | >0.05 |
| Zhang L [23] | 2014 | China | Asian | 59.85 + 8.71/ 58.83 + 9.35 | C-C | 416/257 | 291 | 117 | 8 | 212 | 42 | 3 | PCR-RFLP | 15.3 | >0.05 |
| Mo YQ [26] | 2015 | China | Asian | 56.4 + 11.7/ 54.7 + 10.2 | C-C | 100/100 | 87 | 13 | 0 | 92 | 8 | 0 | DNA sequencing | 4.0 | >0.05 |
| Gao Y a [25] | 2015 | China | Asian | -/- | C-C | 60/60 | 19 | 21 | 20 | 20 | 22 | 18 | PCR-RFLP | 48.3 | <0.05 |
| Gao Y b [25] | 2015 | China | Asian | -/- | C-C | 60/60 | 15 | 21 | 24 | 23 | 18 | 19 | PCR-RFLP | 46.7 | <0.05 |
aChinese Han population
bMongols population
C-C case–control, PCR-RFLP polymerase chain reaction- restriction fragment length polymorphism, MAF minor allelic frequencies, HWE Hardy-Weinberg equilibrium