Table 2.
Genotype distributions of miR-27a rs895819.
| No. of cases | Allele frequencies in cases | No. of controls | Allele frequencies in controls | |||||||||||
| First author | Year | Ethnicity | Country | Sample size (cases/controls) | AA | AG | GG | A | G | AA | AG | GG | A | G |
| Hoffman[7] | 2009 | Caucasian | USA | 434/477 | 184 | 200 | 50 | 568 | 300 | 220 | 211 | 46 | 651 | 303 |
| Kontorovich[8] | 2010 | Caucasian | Israel | 132/149 | 98 | 78 | 11 | 274 | 100 | 101 | 82 | 15 | 284 | 112 |
| Yang[9] | 2010 | Caucasian | German | 1189/1416 | 576 | 486 | 127 | 1638 | 740 | 605 | 660 | 151 | 1870 | 962 |
| Zhang[10] | 2011 | Asian | China | 376/190 | 196 | 150 | 30 | 542 | 210 | 106 | 70 | 14 | 282 | 98 |
| Zhang[11] | 2012 | Asian | China | 245/243 | 60 | 144 | 41 | 264 | 226 | 75 | 109 | 59 | 259 | 227 |
| Catucci[12] | 2012 | Caucasian | Italy | 1025/1593 | 547 | 388 | 90 | 1432 | 518 | 803 | 633 | 157 | 2239 | 947 |
| Ma[13] | 2013 | Asian | China | 189/190 | 97 | 76 | 16 | 270 | 108 | 106 | 70 | 14 | 282 | 98 |
| Zhang[14] | 2013 | Asian | China | 264/255 | 152 | 96 | 16 | 400 | 128 | 137 | 103 | 15 | 377 | 133 |
| Wang[15] | 2014 | Asian | China | 107/219 | 78 | 18 | 11 | 174 | 40 | 129 | 76 | 14 | 334 | 104 |
| He[16] | 2015 | Asian | China | 450/450 | 251 | 165 | 34 | 667 | 233 | 232 | 181 | 37 | 645 | 255 |
| Qi[17] | 2015 | Asian | China | 321/290 | 101 | 159 | 61 | 361 | 281 | 95 | 139 | 56 | 329 | 251 |
| Zhang[18] | 2015 | Asian | China | 376/190 | 196 | 150 | 30 | 542 | 210 | 106 | 70 | 14 | 282 | 98 |
| Morales[19] | 2016 | Caucasian | Chile | 440/807 | 245 | 166 | 29 | 656 | 224 | 432 | 298 | 77 | 1162 | 452 |
| Nguyen[20] | 2016 | Asian | Vietnam | 97/100 | 40 | 45 | 12 | 125 | 69 | 49 | 38 | 13 | 136 | 64 |
| Shekari[21] | 2017 | Asian | Iran | 120/120 | 78 | 34 | 8 | 190 | 50 | 58 | 52 | 10 | 168 | 72 |
| Mashayekhi[22] | 2018 | Asian | Iran | 353/353 | 167 | 156 | 30 | 490 | 216 | 127 | 155 | 71 | 409 | 297 |
HWE = Hardy–Weinberg equilibrium.