Table 1.
Case | Control | |||||||
---|---|---|---|---|---|---|---|---|
Author | Population | Menses | Arg/Arg | Arg/His | His/His | Arg/Arg | Arg/His | His/His |
MARIE-GENICA | Caucasian | postmenopausal | 1381 | 1332 | 426 | 2338 | 2430 | 658 |
Gulyaeva | Caucasian | NM | 23 | 40 | 19 | 63 | 61 | 56 |
Rebbeck | Caucasian | postmenopausal | 199 | 226 | 297 | 259 | ||
Rebbeck | African | postmenopausal | 85 | 59 | 193 | 153 | ||
Yang | Asian | premenopausal | 622 | 116 | 0 | 614 | 112 | 0 |
Yang | Asian | postmenopausal | 299 | 65 | 0 | 363 | 58 | 0 |
Lilla | Caucasian | NM | 198 | 169 | 52 | 374 | 403 | 107 |
Le Marchand | Others | NM | 801 | 424 | 114 | 782 | 484 | 104 |
Jerevall | Caucasian | postmenopausal | 80 | 121 | 28 | 84 | 106 | 38 |
Han | Asian | premenopausal | 92 | 21 | 3 | 136 | 23 | 4 |
Han | Asian | postmenopausal | 68 | 20 | 5 | 219 | 38 | 6 |
Choi | Asian | NM | 796 | 190 | 0 | 830 | 215 | 0 |
Cheng | Asian | NM | 439 | 27 | 2 | 693 | 47 | 0 |
Sillanpaa | Caucasian | premenopausal | 145 | 229 | 106 | 147 | 221 | 110 |
Langsenlehner | Caucasian | NM | 201 | 250 | 47 | 224 | 212 | 63 |
Chacko | Asian | 76 | 56 | 8 | 95 | 41 | 4 | |
Chacko | Asian | premenopausa | 39 | 27 | 42 | 24 | ||
Chacko | Asian | postmenopausa | 37 | 37 | 53 | 21 | ||
Tang | Others | NM | 50 | 42 | 11 | 134 | 83 | 13 |
Zheng | Others | postmenopausal | 55 | 71 | 29 | 148 | 136 | 44 |
Seth | Caucasian | NM | 229 | 176 | 39 | 110 | 94 | 23 |
aNM: not mention