| Literature DB >> 23049772 |
Zhengting Wang1, Jiajia Hu, Rong Fan, Jie Zhou, Jie Zhong.
Abstract
BACKGROUND: The gene encoding CD14 has been proposed as an IBD-susceptibility gene with its polymorphism C-260T being widely evaluated, yet with conflicting results. The aim of this study was to investigate the association between this polymorphism and IBD by conducting a meta-analysis. METHODOLOGY/PRINCIPALEntities:
Mesh:
Substances:
Year: 2012 PMID: 23049772 PMCID: PMC3458839 DOI: 10.1371/journal.pone.0045144
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Figure 1Flow diagram of search strategy and study selection.
The baseline characteristics of all eligible studies.
| First author | Year | Ethnicity | Study design | Genotyping method | Numbers | T freq. (%) | HWE | ||||
| Cases | Controls | Cases | Controls | ||||||||
| CD | UC | CD | UC | ||||||||
| Klein W et al. | 2002 | Germany (C) | NA | PCR-RFLP | 219 | 142 | 410 | 51.1 | 43.7 | 44.5 | 0.9006 |
| Obana N et al. | 2002 | Japan (A) | NA | PCR-RFLP | 82 | 101 | 123 | 48.2 | 57.4 | 44.7 | 0.5234 |
| Klein W et al. | 2003 | Germany (C) | HB | PCR-RFLP | 253 | / | 650 | 51.0 | / | 44.5 | 0.993 |
| Torok HP et al. | 2004 | Germany (C) | PB | PCR-RFLP | 102 | 98 | 145 | 48.5 | 43.4 | 50.0 | 0.9983 |
| Arnott IDR et al. | 2004 | UK (C) | PB | PCR-RFLP | 242 | 233 | 189 | 49.0 | 52.8 | 51.9 | 0.6105 |
| Klausz G et al. | 2005 | Hungary (C) | NA | Probe | 133 | / | 75 | 48.5 | / | 46.0 | 0.9599 |
| Guo QS et al. | 2005 | Chinese (A) | PB | PCR-RFLP | / | 114 | 160 | / | 64.0 | 60.3 | 0.9989 |
| Gazouli M et al. | 2005 | Greece (C) | HB | PCR-RFLP | 120 | 85 | 100 | 50.4 | 40.0 | 37.0 | 0.6079 |
| Leung E et al. | 2005 | New Zealand (C) | PB | PCR-RFLP | 185 | / | 187 | 51.4 | / | 50.3 | 0.7974 |
| Peters KE et al. | 2005 | Australia (C) | PB | PCR-RFLP | 235 | 81 | 189 | 49.6 | 56.8 | 49.2 | 0.5584 |
| Ouburg S et al. | 2005 | Netherlands (C) | HB | PCR-RFLP | 112 | / | 170 | 44.6 | / | 47.7 | 0.9544 |
| XUE H et al. | 2007 | Chinese (A) | HB | PCR-RFLP | 41 | 43 | 135 | 61.0 | 60.5 | 59.3 | 0.6887 |
| Wang F et al. | 2007 | Japanese (A) | HB | PCR-RFLP | / | 97 | 135 | / | 66.0 | 48.5 | 0.5882 |
| Baumgart DC et al. | 2007 | Hungary (C) | NA | Probe | 144 | 118 | 202 | 42.7 | 44.1 | 52.7 | 0.7091 |
| Baumgart DC et al. | 2007 | Germany (C) | NA | Probe | 235 | 145 | 403 | 45.3 | 53.8 | 45.5 | 0.9415 |
| Petermann I et al. | 2009 | New Zealand (C) | PB | Taqman | 387 | 405 | 377 | 49.6 | 48.4 | 49.3 | 0.984 |
| Sivaram G et al. | 2012 | India (A) | NA | PCR-RFLP | / | 139 | 176 | / | 53.2 | 41.8 | 0.3855 |
| Kim EJ et al. | 2012 | Korea (A) | HB | PCR-RFLP | 45 | 99 | 178 | 61.1 | 54.6 | 36.5 | 0.8755 |
Abbreviations: HB = hospital-based design; PB = population-based design; NA = not available; CD = Crohn's disase; UC = ulcerative colitis.
Figure 2Begg's funnel plots of publication bias test for CD14 C-260T polymorphism with UC (a. -260T vs.-260C allele; b. -260TT vs. -260CC; c. dominant model; d. recessive model).
Vertical axis represents the log of OR; horizontal axis represents the SE of log(OR). Funnel plots are drawn with 95% confidence limits. OR, odds ratio; SE, standard error. The graphic symbols represents the data in the plot be sized proportional to the inverse variance.
Subgroup analysis of CD14 C-260T gene polymorphisms and IBD (CD and UC).
| Variables | Allele contrast | Homozygote model | Dominant model | Recessive model | ||||
| OR (95% CI) |
| OR (95% CI) |
| OR (95% CI) |
| OR (95% CI) |
| |
|
| ||||||||
|
| 1.10(0.96,1.25) | 0.167 | 1.18(0.92,1.52) | 0.201 | 1.05(0.88,1.23) | 0.603 | 1.20(0.97,1.49) | 0.090 |
|
| ||||||||
| Caucasians | 1.05(0.93,1.18) | 0.479 | 1.08(0.85,1.38) | 0.510 | 1.00(0.85,1.18) | 0.991 | 1.12(0.91,1.38) | 0.265 |
| Asians | 1.49(0.84,2.66) | 0.171 | 2.03(0.70,5.91) | 0.193 | 1.53(0.83,2.82) | 0.169 | 1.77(0.76,4.13) | 0.185 |
|
| ||||||||
| HB | 1.40(1.01,1.94) | 0.046 | 1.82(1.00,3.32) | 0.050 | 1.36(0.92,2.01) | 0.127 | 1.67(1.05,2.65) | 0.030 |
| PB | 0.99(0.88,1.11) | 0.808 | 0.97(0.77,1.23) | 0.801 | 0.96(0.79,1.16) | 0.669 | 1.00(0.83,1.22) | 0.970 |
| NA | 1.02(0.81,1.29) | 0.879 | 1.03(0.64,1.65) | 0.914 | 0.95(0.69,1.31) | 0.761 | 1.10(0.72,1.69) | 0.663 |
|
| ||||||||
| PCR-based | 1.18(1.00,1.38) | 0.045 | 1.35(1.00,1.81) | 0.049 | 1.12(0.93,1.36) | 0.225 | 1.33(1.03,1.71) | 0.027 |
| Probe or Taqman | 0.93(0.77,1.13) | 0.459 | 0.86(0.58,1.26) | 0.430 | 0.87(0.62,1.23) | 0.444 | 0.93(0.69,1.24) | 0.607 |
|
| ||||||||
|
| 1.21(1.02,1.43) | 0.027 | 1.44(1.03,2.01) | 0.033 | 1.36(1.06,1.75) | 0.016 | 1.19(0.96,1.48) | 0.112 |
|
| ||||||||
| Caucasians | 1.01(0.87,1.19) | 0.866 | 1.01(0.73,1.41) | 0.938 | 1.09(0.83,1.43) | 0.538 | 0.95(0.79,1.15) | 0.626 |
| Asians | 1.58(1.28,1.95) | 0.000 | 2.51(1.77,3.55) | 0.000 | 1.97(1.46,2.65) | 0.000 | 1.69(1.27,2.25) | 0.000 |
|
| ||||||||
| HB | 1.54(1.08,2.20) | 0.017 | 2.27(1.11,4.66) | 0.025 | 1.92(1.12,3.31) | 0.018 | 1.65(1.10,2.48) | 0.016 |
| PB | 1.03(0.88,1.20) | 0.754 | 1.09(0.73,1.61) | 0.679 | 1.16(0.85,1.58) | 0.354 | 0.95(0.75,1.20) | 0.674 |
| NA | 1.20(0.88,1.63) | 0.251 | 1.37(0.77,2.45) | 0.287 | 1.24(0.80,1.91) | 0.336 | 1.25(0.85,1.85) | 0.258 |
|
| ||||||||
| PCR-based | 1.29(1.06,1.56) | 0.009 | 1.63(1.12,2.36) | 0.010 | 1.48(1.13,1.94) | 0.005 | 1.30(1.01,1.68) | 0.044 |
| Probe or Taqman | 0.99(0.70,1.39) | 0.956 | 0.98(0.48,2.00) | 0.954 | 1.06(0.57,1.95) | 0.863 | 0.93(0.68,1.28) | 0.668 |
Abbreviations: OR = odds ratio; CI = confidence interval; HB = Hospital based; PB = Population based; NA = Not available.
Figure 3Subgroup analyses of CD14 C-260T polymorphism to UC by ethnicity ( a. -260T vs. -260C allele; b. -260TT vs. -260CC; c. dominant model; d. recessive model).
There was significant association among Asian populations, whereas no substantive changes was observed in Caucasians in any kind of comparisons.