Table 1.
SNP | First author | Year | Area | Sample size | Age (y) | Source of control | Genotyping method | Cases | Controls | NOS | HWE | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Case | Control | Case | Control | TT/GG/CC | CT/GA/CT | CC/AA/TT | TT/GG/CC | CT/GA/CT | CC/AA/TT | χ2 | P | |||||||
APOA5–1131 T>C |
Zhao DD [11] | 2007 | Beijing, China | 172 | 80 | NR | NR | HB | PCR-RFLP | 63 | 86 | 23 | 39 | 36 | 5 | 7 | 0.77 | 0.37 |
Niu ZB [12] | 2016 | Shanghai, China | 156 | 262 | NR | NR | PB | MALDI-TOF | 68 | 68 | 20 | 153 | 94 | 15 | 9 | 0.01 | 0.91 | |
Huang M [13] | 2008 | Taiwan, China | 76 | 240 | 59.57 ± 10.2 | 60.98 ± 13.58 | PB | PCR-RFLP | 15 | 41 | 20 | 99 | 111 | 30 | 8 | 0.02 | 0.9 | |
Long SY [14] | 2013 | Hunan, China | 95 | 102 | 61 ± 12 | 62 ± 12 | HB | PCR-RFLP | 46 | 36 | 13 | 50 | 45 | 7 | 7 | 0.54 | 0.46 | |
Maria [15] | 2014 | Napoli, Italian | 165 | 142 | 47.5 ± 12.2 | 43.9 ± 9.6 | HB | TaqMan | 111 | 49 | 5 | 117 | 23 | 2 | 7 | 0.49 | 0.48 | |
Cláudia [16] | 2012 | Minas Gerais, Brazil | 108 | 107 | 48.4 ± 6.8 | 46.7 ± 6.6 | PB | PCR-RFLP | 52 | 52 | 4 | 71 | 33 | 3 | 7 | 0.13 | 72 | |
Brito [17] | 2010 | Belo Horizonte, Brazil | 53 | 77 | 10.4 ± 2.7 | 11.2 ± 3.4 | HB | PCR-RFLP | 34 | 14 | 5 | 62 | 13 | 2 | 6 | 1.52 | 0.22 | |
ZK Liu [18] | 2009 | Hongkong, China | 56 | 176 | 49.6 ± 12.3 | 50.1 ± 9.4 | HB | PCR | 9 | 27 | 20 | 101 | 61 | 11 | 7 | 0.19 | 0.66 | |
Peter H [19] | 2008 | Netherlands | 254 | 240 | NR | NR | HB | PCR | 142 | 72 | 7 | 172 | 22 | 1 | 6 | 0.11 | 0.75 | |
Han Y [8] | 2012 |
Hunan, China |
109 | 117 | 60.3 ± 12.1 | 62.9 ± 12.0 | HB | PCR-RFLP | 52 | 43 | 14 | 59 | 50 | 8 | 7 | 0.36 | 0.55 | |
APOA1-75 bp | Huang G [20] | 2011 |
Xinjiang, China |
275 | 252 | 47.7 ± 7.9 | 48.23 ± 7.6 | HB | PCR-RFLP | 135 | 102 | 38 | 136 | 95 | 21 | 8 | 0.57 | 0.49 |
Feng DW [7] | 2016 |
Xinjiang, China |
365 | 370 | 46.8 ± 15.9 | 45.21 ± 16.4 | PB | PCR | 248 | 104 | 13 | 280 | 83 | 7 | 9 | 0.09 | 0.77 | |
Feng DW [7] | 2016 |
Xinjiang, China |
345 | 391 | 43.9 ± 14.3 | 41.5 ± 13.3 | PB | PCR | 250 | 87 | 7 | 299 | 86 | 5 | 9 | 0.18 | 0.67 | |
Chi YH [21] | 2012 | Xinjiang,China | 200 | 200 | 58.5 ± 11.8 | 58.3 ± 11.5 | PB | PCR-RFLP | 116 | 82 | 2 | 124 | 73 | 5 | 7 | 2.31 | 1.29 | |
Bora K [2] | 2017 | Assam, India | 100 | 100 | 43.1 ± 11.6 | 43.0 ± 11.6 | PB | PCR-RFLP | 62 | 35 | 3 | 60 | 33 | 7 | 8 | 0.68 | 0.41 | |
APOA1+83 bp | Xie YJ [22] | 2011 |
Xinjiang, China |
150 | 150 | 56.8 ± 10.8 | 58.1 ± 10.5 | HB | PCR-RFLP | 126 | 24 | 0 | 130 | 20 | 0 | 7 | 0.77 | 0.38 |
Ou HJ [5] | 2015 |
Xinjiang, China |
241 | 246 | 49.1 ± 0.7 | 48.3 ± 0.8 | HB | MALDI-TOF | 160 | 80 | 1 | 171 | 73 | 2 | 7 | 3.78 | 0.05 | |
Feng DW [7] | 2016 |
Xinjiang, China |
365 | 370 | 46.8 ± 15.9 | 45.2 ± 16.4 | PB | PCR | 317 | 48 | 0 | 304 | 63 | 3 | 9 | 0.02 | 0.89 | |
Feng DW [7] | 2016 | Xinjiang,China | 345 | 391 | 43.91 ± 14.27 | 41.51 ± 13.28 | PB | PCR | 299 | 44 | 1 | 330 | 57 | 3 | 9 | 0.1 | 0.76 | |
Zhu H [23] | 2001 |
Sichuan, China |
134 | 255 | 54.7 ± 12.6 | 51.7 ± 10.9 | PB | PCR | 123 | 11 | 0 | 238 | 17 | 0 | 7 | 0.3 | 0.58 | |
Jia LQ [24] | 2005 |
Sichuan, China |
118 | 109 | 58.1 ± 8.9 | 54.5 ± 9.6 | NR | PCR | 105 | 13 | 0 | 99 | 10 | 0 | 6 | 0.25 | 0.62 | |
Bora K [2] | 2017 | Assam, India | 100 | 100 | 43.12 ± 11.64 | 42.95 ± 11.60 | PB | PCR-RFLP | 89 | 11 | 0 | 87 | 13 | 0 | 8 | 0.48 | 0.49 |
SNP single nucleotide polymorphism, PB population-based; HB: hospital-based, HWE Hardy-Weinberg equilibrium, NR not reported