Introduction
Material and methodology
Search strategy
Inclusion/ exclusion criteria
Data search and quality assessment
Statistical analysis
Results
Studies included in the meta-analysis
Sr. No | Study | Year | Country | PCOS diagnostic criteria | Variants Studied | Genotyping method | Sample size (Cases/Controls) |
---|---|---|---|---|---|---|---|
1) | Conway et al. [27] | 1999 | UK | PCO + OA + MD | rs6165, rs6166 | PCR-SSCP | 93/51 |
2) | Tong et al. [28] | 2001 | China | HA + PCO + MD | rs6165 | PCR–RFLP | 124/236 |
3) | Sudo et al. [29] | 2002 | Japan | Rotterdam Criteria | rs6165, rs6166 | PCR–RFLP | 18/168 |
4) | Unsal et al. [30] | 2009 | Turkish | Rotterdam Criteria | rs6165, rs6166 | PCR–RFLP | 44/50 |
5) | Valkenburg et al. [17] | 2009 | Netherlands | Rotterdam Criteria | rs6166 | PCR-SSP | 495/2912 |
6) | Du et al. [31] | 2010 | China | Rotterdam Criteria | rs6165, rs6166 | PCR-SSP | 55/92 |
7) | Gu et al. [16] | 2010 | Korea | Rotterdam Criteria | rs6165, rs6166 | PCR–RFLP | 235/128 |
8) | Mohiyiddeen et al. [32] | 2012 | UK | Rotterdam Criteria | rs6166 | Taq man assay | 58/83 |
9) | Fu et al. [33] | 2013 | China | Rotterdam Criteria | rs6165, rs6166 | Sequencing | 384/768 |
10) | Kambalachenu et al. [34] | 2013 | India | Rotterdam Criteria | rs6166 | PCR–RFLP | 97/101 |
11) | Liaqat et al. [35] | 2013 | Pakistan | Rotterdam Criteria | rs6165, rs6166 | PCR-SSP | 96/96 |
12) | Singhasena et al. [36] | 2014 | Thailand | Rotterdam Criteria | rs6165, rs6166 | PCR–RFLP | 133/132 |
13) | Wu et al. [37] | 2014 | China | Rotterdam Criteria | rs6165, rs6166 | PCR–RFLP | 215/205 |
14) | Almawi et al. [38] | 2015 | Bahrain | Rotterdam Criteria | rs6166 | Real-time PCR | 203/211 |
15) | Thathapudi et al. [39] | 2016 | India | AES | rs6166 | PCR–RFLP | 204/204 |
16) | Kim et al. [4] | 2017 | Japan | Rotterdam Criteria | rs6165, rs6166 | Sequencing | 377/388 |
17) | Branavan et al. [40] | 2018 | Sri Lanka | Rotterdam Criteria | rs6165, rs6166 | Real-time PCR | 55/110 |
18) | Wan et al. [23] | 2021 | China | Rotterdam Criteria | rs6165, rs6166 | Sanger sequencing | 400/480 |
19) | Kaur et al. [24] | 2023 | India | Rotterdam Criteria | rs6165, rs6166 | PCR–RFLP | 421/322 |
20) | Vieira et al. [25] | 2023 | Portugal | Rotterdam Criteria | rs6166 | PCR–RFLP | 88/80 |
rs6165 | HWE p- value | rs6166 | HWE p- value | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Cases | Controls | Cases | Controls | |||||||||||
Thr/Thr | Thr/Ala | Ala/Ala | Thr/Thr | Thr/Ala | Ala/Ala | Asn/Asn | Asn/Ser | Ser/Ser | Asn/Asn | Asn/Ser | Ser/Ser | |||
Conway et al. [27] | 22 | 47 | 24 | 8 | 25 | 18 | 0.88 | 23 | 48 | 22 | 18 | 25 | 8 | 0.88 |
Tong et al. [28] | 53 | 56 | 15 | 102 | 110 | 24 | 0.47 | - | - | - | - | - | - | |
Sudo et al. [29] | 3 | 12 | 3 | 73 | 73 | 22 | 0.57 | 3 | 12 | 3 | 73 | 73 | 22 | 0.57 |
Unsal et al. [30] | 16 | 19 | 9 | 16 | 25 | 9 | 0.88 | 13 | 20 | 11 | 14 | 27 | 9 | 0.2 |
Valkenburg et al. [17] | - | - | - | - | - | - | - | 123 | 248 | 124 | 782 | 1500 | 630 | 0.07 |
Du et al. [31] | 26 | 20 | 9 | 40 | 37 | 15 | 0.2 | 26 | 26 | 3 | 40 | 34 | 16 | 0.07 |
Gu et al. [16] | 81 | 116 | 38 | 50 | 56 | 22 | 0.35 | 138 | 91 | 6 | 92 | 35 | 1 | 0.23 |
Mohiyiddeen et al. [32] | - | - | - | - | - | - | - | 14 | 34 | 10 | 20 | 47 | 16 | 0.21 |
Fu et al. [33] | 192 | 156 | 36 | 362 | 329 | 77 | 0.86 | 187 | 162 | 35 | 357 | 334 | 77 | 0.93 |
Kambalachenu et al. [34] | - | - | - | - | - | - | - | 25 | 64 | 8 | 31 | 52 | 18 | 0.63 |
Liaqat et al. [35] | 27 | 47 | 22 | 22 | 49 | 25 | 0.83 | 29 | 47 | 20 | 24 | 47 | 25 | 0.83 |
Singhasena et al. [36] | 70 | 53 | 10 | 70 | 56 | 6 | 0.20 | 69 | 59 | 5 | 72 | 54 | 6 | 0.29 |
Wu et al. [37] | 93 | 95 | 27 | 91 | 100 | 14 | 0.052 | 93 | 94 | 28 | 94 | 98 | 13 | 0.057 |
Almawi et al. [38] | - | - | - | - | - | - | - | 64 | 92 | 47 | 52 | 107 | 52 | 0.83 |
Thathapudi et al. [39] | - | - | - | - | - | - | - | 74 | 99 | 31 | 44 | 90 | 70 | 0.14 |
Kim et al. [4] | 145 | 176 | 56 | 181 | 176 | 31 | 0.18 | 149 | 178 | 50 | 180 | 176 | 32 | 0.22 |
Branavan et al. [40] | 16 | 26 | 13 | 28 | 53 | 29 | 0.7 | 16 | 26 | 13 | 28 | 53 | 29 | 0.7 |
Wan et al. [23] | 175 | 175 | 50 | 210 | 222 | 48 | 0.33 | 176 | 178 | 46 | 218 | 215 | 47 | 0.56 |
Kaur et al. [24] | 93 | 175 | 153 | 76 | 146 | 100 | 0.11 | 119 | 198 | 104 | 92 | 156 | 74 | 0.6 |
Vieira et al. [25] | - | - | - | - | - | - | - | 28 | 43 | 17 | 30 | 32 | 18 | 0.104 |
Pooled analysis
Overall Analysis | Asian Studies Meta-analysis | Indian Studies Meta-analysis | Other studies Meta-analysis | |||
---|---|---|---|---|---|---|
FEM | REM | I2 | ||||
rs6165 | OR (CI), p-value | |||||
Dominant Model | 1.04(0.93–1.16), 0.49 | 1.19 (0.92–1.16), 0.54 | 4% | 1.04(0.92–1.18), 0.53 | 1.09(0.77–1.54), 0.63 | 0.6(0.25–1.47), 0.26 |
Recessive Model | 1.19(1.03–1.3), 0.02 | 1.2 (1.01–1.4), 0.04 | 10% | 1.22(1.02–1.46), 0.03 | 1.27(0.93–1.73), 0.13 | 0.64(0.3–1.33), 0.23 |
Additive Model | 1.2(1.02–1.42), 0.03 | 1.19(0.96–1.47), 0.11 | 27% | 1.23(1.02–1.49), 0.03 | 1.25(0.84–1.85), 0.16 | 0.48(0.18–1.34), 0.16 |
Allele Model | 1.07(0.99–1.18), 0.08 | 1.07(0.97–1.17), 0.19 | 25% | 1.07(0.97–1.19), 0.18 | 1.15(0.93–1.41), 0.19 | 0.7(0.43–1.14), 0.16 |
rs6166 | ||||||
Dominant Model | 1.05(0.95–1.15), 0.34 | 1.04 (0.91–1.2) 0.56 | 44% | 1.07 (0.95–1.2), 0.28 | 0.84 (0.66–1.06), 0.15 | 1.15 (0.95–1.39), 0.16 |
Recessive Model | 1.02(0.91–1.15), 0.72 | 0.97 (0.78–1.22), 0.82 | 61% | 1.11 (0.92–1.32), 0.27 | 0.7 (0.54–0.9), 0.006* | 1.02 (0.91–1.15), 0.11 |
Additive Model | 1.03 (0.90–1.2), 0.67 | 0.99 (0.76–1.29), 0.94 | 64% | 1.1 (0.91–1.34), 0.33 | 0.65 (0.48–0.89), 0.006* | 1.25 (0.98–1.59), 0.07 |
Allele Model | 1.03(0.96–1.10), 0.4 | 1.02 (0.90–1.15), 0.78 | 64% | 1.06 (0.95–1.15), 0.19 | 0.82 (0.7–0.95), 0.01* | 1.17 (1.04–1.32), 0.01* |