Copyright
©The Author(s) 2019.
World J Clin Cases. Mar 6, 2019; 7(5): 572-584
Published online Mar 6, 2019. doi: 10.12998/wjcc.v7.i5.572
Published online Mar 6, 2019. doi: 10.12998/wjcc.v7.i5.572
Author | Yr | Selection | Comparability | Exposure | Score | ||||||
Case definition | Case representativeness | Control selection | Control definition | Important confounders | Every confounders | Ascertainment | Consistency | Non-response rate | |||
Low et al[7] | 2011 | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 1 | 1 | 7 |
Takhshid et al[2] | 2015 | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 7 |
Daher et al[8] | 2011 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 8 |
Han et al[4] | 2012 | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 1 | 1 | 7 |
Gao et al[10] | 2016 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 8 |
Luan et al[13] | 2015 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 8 |
Li et al[12] | 2017 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 8 |
Li et al[11] | 2013 | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 7 |
Zhang et al[14] | 2014 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 8 |
Beltcheva et al[1] | 2014 | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 1 | 1 | 7 |
Pawlik et al[3] | 2017 | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 7 |
Chen et al[15] | 2011 | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 7 |
Wang et al[16] | 2016 | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 7 |
SNP | Author | Yr | Country | Ethnicity | Matching criteria | Method | Sample size | Genotype1 | HWE | ||
Case | Control | Case | Control | ||||||||
+45T/G | Low et al[7] | 2011 | Malaysia | Asian | NR | Taq PCR | 26 | 53 | 11/13/2 | 35/17/1 | 0.51 |
Takhshid et al[2] | 2015 | Iran | Asian | Age | PCR-RELF | 65 | 70 | 37/28/0 | 54/16/0 | 0.28 | |
Daher et al[8] | 2011 | Brazil | SA | Race | PCR-RELF | 79 | 169 | 61/15/3 | 134/32/3 | 0.51 | |
Han et al[4] | 2012 | China | Asian | NR | PCR-RELF | 152 | 120 | 63/71/18 | 64/50/6 | 0.34 | |
Gao et al[10] | 2016 | China | Asian | Age, GW | PCR-RELF | 150 | 150 | 59/66/25 | 81/57/12 | 0.66 | |
Luan et al[13] | 2015 | China | Asian | Age, GW | NR | 60 | 60 | 33/21/6 | 29/26/5 | 0.81 | |
Li et al[12] | 2017 | China | Asian | Age, GW | PCR-RELF | 130 | 130 | 53/63/14 | 63/60/7 | 0.13 | |
Li et al[11] | 2013 | China | Asian | NR | Sequencing | 264 | 172 | 134/113/17 | 97/66/9 | 0.6 | |
Zhang et al[14] | 2014 | China | Asian | Age, BMI, GW | PCR-RELF | 98 | 135 | 38/43/17 | 73/51/11 | 0.62 | |
+276G/T | Han et al[4] | 2012 | China | Asian | NR | PCR-RELF | 152 | 120 | 12/66/74 | 11/53/56 | 0.34 |
Gao et al[10] | 2016 | China | Asian | Age, GW | PCR-RELF | 150 | 150 | 15/69/66 | 15/60/75 | 0.66 | |
Luan et al[13] | 2015 | China | Asian | Age, GW | NR | 60 | 60 | 7/26/27 | 3/25/32 | 0.81 | |
Li et al[12] | 2017 | China | Asian | Age, GW | PCR-RELF | 130 | 130 | 64/58/8 | 60/56/14 | 0.13 | |
Zhang et al[14] | 2014 | China | Asian | Age, BMI, GW | PCR-RELF | 98 | 135 | 10/45/43 | 13/54/68 | 0.62 | |
-11377C/G | Beltcheva et al[1] | 2014 | Bulgaria | European | Age, BMI | TaqMan | 130 | 130 | 80/44/6 | 66/50/14 | 0.34 |
Pawlik et al[3] | 2017 | Poland | European | NR | TaqMan | 204 | 207 | 92/91/21 | 115/75/17 | 0.34 | |
Daher et al[8] | 2011 | Brazil | SA | race | PCR-RELF | 79 | 169 | 54/20/5 | 105/50/13 | 0.05 | |
Chen et al[15] | 2011 | China | Asian | NR | PCR-RELF | 103 | 97 | 55/43/5 | 50/38/9 | 0.65 | |
Wang et al[16] | 2016 | China | Asian | NR | PCR-RELF | 206 | 189 | 107/84/15 | 106/73/10 | 0.57 |
SNP | N | Sample size | Allelic model | Dominant model | Recessive model | ||||
Case | Control | OR (95%CI) | P | OR (95%CI) | P | OR (95%CI) | P | ||
+45T/G | |||||||||
Total | 10 | 1024 | 1059 | 1.45 (1.26-1.67) | 0.000a | 1.50 (1.25-1.79) | 0.000a | 2.00 (1.42-2.84) | 0.000a |
Subgroup | |||||||||
Ethnicity | |||||||||
Asian | 8 | 945 | 890 | 1.47 (1.27-1.70) | 0.000a | 1.54 (1.27-1.85) | 0.000a | 2.00 (1.43-2.85) | 0.000a |
SA | 1 | 79 | 169 | 1.21 (0.68-2.41) | 0.510 | 1.13 (0.59-2.15) | 0.710 | 2.18 (0.43-11.07) | 0.350 |
+276G/T | |||||||||
Total | 5 | 590 | 595 | 0.88 (0.74-1.05) | 0.158 | 0.91 (0.65-1.26) | 0.561 | 0.82 (0.64-1.05) | 0.118 |
-11377C/G | |||||||||
Total | 5 | 722 | 791 | 0.96 (0.72-1.26) | 0.750 | 1.00 (0.73-1.37) | 0.980 | 0.90 (0.61-1.32) | 0.570 |
Subgroup | |||||||||
Ethnicity | |||||||||
Asian | 2 | 309 | 286 | 1.04 (0.77-1.41) | 0.800 | 1.09 (0.79-1.50) | 0.600 | 0.97 (0.51-1.86) | 0.930 |
SA | 1 | 79 | 168 | 0.80 (0.50-1.29) | 0.360 | 0.77 (0.44-1.36) | 0.370 | 0.81 (0.28-2.34) | 0.690 |
European | 2 | 334 | 337 | 0.94 (0.45-1.96) | 0.870 | 1.00 (0.42-2.33) | 0.990 | 0.87 (0.51-1.49) | 0.610 |
- Citation: Huang LT, Wu SL, Liao X, Ma SJ, Tan HZ. Adiponectin gene polymorphisms and risk of gestational diabetes mellitus: A meta-analysis. World J Clin Cases 2019; 7(5): 572-584
- URL: https://www.wjgnet.com/2307-8960/full/v7/i5/572.htm
- DOI: https://dx.doi.org/10.12998/wjcc.v7.i5.572