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Aim The aim of our meta-analysis was to summarize quantitatively the association of genetic polymorphisms with cerebral palsy (CP). Method We identified 16 studies on the association of genetic polymorphisms with CP in Pubmed, Elsevier Science Direct, Chinese Biomedical Literature Database, Chinese National Knowledge Infrastructure, and Wanfang. Eleven of these studies (involving a total of 2533 cases and 4432 controls) were used in the current meta-analysis. A study was included if (1) it was published up to September 2010 and (2) it was a case–control study. We excluded one study of family members because the analysis was based on linkage considerations. Meta odds ratios and 95% confidence intervals based on fixed-effects models or random-effects models were dependent on Cochran’s Q statistic. We examined the relationship between alleles, as well as genotypes and susceptibility to CP. Results Meta-analysis was performed for 17 genetic polymorphisms: apolipoprotein E (e2,e3,e4), methylenetetrahydrofolate reductase (MTHFR) (rs1801133), coagulation factor II (rs1799963]), coagulation factor V (rs6025), coagulation factor VII (rs5742910/rs6046), interleukin-6 (IL-6) (rs1800795), endothelial nitric oxide (rs1800779/rs1799983/rs3918226), fibrinogen β-polypeptide (rs1800790), plasminogen activator inhibitor 1 (rs1799768/rs7242), TNF-β lymphotoxin α precursor (rs1041981), adducin 1 (α) (rs4961), ADRB2 (rs1042714), and tumour necrosis factor α (rs1800629). We found a significant association between CP and IL-6 (rs1800795) [C vs G: odds ratio (OR) 1.79, 95% confidence interval (CI) 1.44–2.22, p

BACKGROUND The results of recent published studies focusing on CYP17 polymorphisms in prostate cancer (PCa) susceptibility are often conflicting. We performed a meta-analysis based on 38 independent studies to evaluate the association. METHODS Data were collected from the following electronic databases: PubMed, Excerpta Medica Database, and Chinese Biomedical Literature Database, with the last report up to September 2010. Meta-analysis was conducted in a fixed/random effect model. RESULTS Thirty-eight independent studies including 34,782 cases and 38,626 controls on the association of CYP17 gene polymorphisms with PCa risk in different ethnic groups were identified. The meta-analysis was performed for five polymorphisms: rs743572 (A1/A2, 38 studies), rs6162 (C/T, 3 studies), rs619824 (C/A, 4 studies), rs2486758 (T/C, 4 studies), and rs10883782 (A/G, 4 studies). When all groups were pooled, we did not detect the association of rs743572 polymorphism with PCa risk. In the subgroup analysis, a significant association of rs743572 polymorphism and PCa was found in Black population (A2/A2 vs. A1/A1 + A2/A1: OR = 1.70, 95% CI = 1.08–2.69, P = 0.02), but not in Caucasian or Asian population. For other polymorphisms, we found that rs619824 polymorphism was associated with a significant decreased risk of PCa (A vs. C: OR = 0.95, 95% CI = 0.92–0.99, P = 0.01), and rs2486758 polymorphism was associated with a significant increased risk of PCa (C vs. T: OR = 1.07, 95% CI = 1.03–1.12, P = 0.002). CONCLUSION This meta-analysis suggests that rs743572 polymorphism is associated with PCa risk in Black population, but not in Caucasian or Asian population. Moreover, our study suggests that rs619824 and rs2486758 polymorphisms are associated with PCa risk. Prostate 71:1167–1177, 2011. © 2011 Wiley-Liss, Inc.

The aim of our study was to assess the association between FKBP5 gene polymorphisms and treatment response in patients with mood disorders using a meta-analysis. Eight separate studies that included data from 2199 subjects were identified. Meta-analysis was performed for three FKBP5 gene polymorphisms (rs1360780, rs3800373, and rs4713916). A significant association of FKBP5 gene rs4713916 polymorphism and response rate was found in patients with mood disorders (Overall: A versus G: OR = 1.28, 95%CI = 1.06–1.53, P = 0.01; GA + AA versus GG: OR = 1.32, 95%CI = 1.05–1.67, P = 0.02. Caucasian: A versus G: OR = 1.28, 95%CI = 1.06–1.55, P = 0.01; GA + AA versus GG: OR = 1.33, 95%CI = 1.04–1.70, P = 0.02). However, we did not detect the association between FKBP5 gene rs1360780 and rs3800373 polymorphisms and treatment response in patients with mood disorders (P > 0.05). This meta-analysis demonstrates that treatment response in patients with mood disorders is associated with FKBP5 gene rs4713916 polymorphism, but not rs1360780 and rs3800373.

Summary The purpose of this study was to generate large-scale evidence on whether SUMO4 M55V polymorphism is associated with autoimmune and inflammatory diseases using a meta-analysis. We surveyed studies on the association of SUMO4 M55V polymorphism with autoimmune and inflammatory diseases in PubMed. Meta-analysis was performed for genotypes AG versus AA, GG versus AA, GG versus AA + AG, AG + GG versus AA and G allele versus A allele in a fixed/random effect model. We identified 16 studies (11 407 cases and 10 679 controls) using PubMed search. When all groups were pooled, we detected the association of SUMO4 M55V polymorphism with autoimmune and inflammatory diseases (G versus A: OR = 1.11, 95%CI = 1.03–1.19, P = 0.005; AG + GG versus AA: OR = 1.17, 95%CI = 1.06–1.28, P = 0.001; GG versus AA + AG: OR = 1.07, 95%CI = 0.94–1.21, P = 0.29; GG versus AA: OR = 1.15, 95%CI = 1.00–1.34, P = 0.06; AG versus AA: OR = 1.15, 95%CI = 1.08–1.23, P

To quantitatively summarize the association of NFKBIA gene polymorphisms with autoimmune and inflammatory diseases. We surveyed studies on the association of NFKBIA gene polymorphisms with autoimmune and inflammatory diseases in PubMed. Meta-analysis was performed in a fixed/random effect model. We identified 14 studies using a PubMed search. Meta-analysis was performed for NFKBIA gene polymorphisms at positions 2758 (A/G, 5 studies), −881 (A/G, 3 studies), −826 (C/T, 3 studies), and −297 (C/T, 3 studies). We did not detect associations of NFKBIA gene polymorphisms at positions 2758, −881, −297 with autoimmune and inflammatory diseases. An association of NFKBIA gene −826C/T polymorphism with autoimmune and inflammatory diseases was found (C vs. T: OR = 1.81, 95% CI = 0.97–3.36, P = 0.06; CT + TT vs. CC: OR = 2.11, 95% CI = 1.07–4.19, P = 0.03; TT vs. CC + CT: OR = 2.20, 95% CI = 0.78–6.21, P = 0.06; TT vs. CC: OR = 2.87, 95% CI = 0.78–10.62, P = 0.11; CT vs. CC: OR = 2.02, 95% CI = 1.22–3.36, P = 0.006). This meta-analysis demonstrates that autoimmune and inflammatory diseases are associated with NFKBIA gene −826C/T polymorphism, but not with 2758A/G, −881A/G, and −279C/T.

Objective To explore the association of brain-derived neurotrophic-factor (BDNF) Val66Met polymorphism with both baseline health related quality of life (HRQOL) scores and improvement in HRQOL scores in Chinese major depressive patients treated with fluoxetine. Methods Patientswithmajordepressivedisorder(MDD)tookfluoxetine(20mg/day)for6 weeks.TheHRQOL was measuredwith theMedical Outcomes Study Short Form-36 (SF-36) at baseline and at 6th week. Patients were genotyped for Val66Met polymorphism of BDNF gene. Results There was a significant association between social function (SF) and BDNF Val66Met polymorphism, and patients with Met/Met genotype had better SF (compared with Val/Val P ¼0.004; compared with Val/Met P ¼0.005). A significant association was found between improvement in SF and BDNF Val66Met polymorphism, and patients with Met/Met genotype had poorer improvement in SF (compared with Val/Val P ¼0.010; compared with Val/Met P ¼0.001). Similar association was found between improvement in mental component summary (MCS) and BDNF Val66Met polymorphism, and patients with Met/Met genotype had poorer improvement in MCS (compared with Val/ Val P ¼0.066; compared with Val/Met P ¼0.006). Conclusions These results indicate that there may be association between BDNF Val66Met polymorphism and both baseline HRQOL (SF) scores and improvement in HRQOL (SF, MCS) scores in Chinese major depressive patients treated with fluoxetine. Copyright # 2010 John Wiley & Sons, Ltd. key words—health related quality of life; major depressive disorder; brain-derived neurotrophic factor; polymorphism; SSRIs

Background: Preclinical studies have shown that brain-derived neurotrophic factor (BDNF) may be involved in antidepressant action, and the BDNF gene has been suggested to be involved in the pharmacological treatment of major depressive disorder (MDD). In this study, the relationship between BDNF Val66Met polymorphism (Single Nucleotide Polymorphism Database ID: rs6265) and severity of depression, efficacy of fluoxetine and its side effects was tested in Chinese patients with MDD. Methods: Patients with MDD took the oral selective serotonin reuptake inhibitor (SSRI) fluoxetine (20 mg/day) for 6 weeks. Its clinical efficacy and side effects were measured by the 17-item Hamilton Rating Scale for Depression and the Treatment-Emergent Symptoms Scale (TESS), respectively. The patients were genotyped for Val66Met polymorphism of the BDNF gene. Results: In the multivariate regression analysis, there was no significant association between severity of depression and BDNF Val66Met polymorphism. There was no association between efficacy of fluoxetine and BDNF Val66Met polymorphism, but there was a marginal positive suggestion that heterozygous patients tended to have a better remission with fluoxetine in comparison with homozygous analogs. Insomnia and decreased sexual desire, side effects of fluoxetine, may have an association with the BDNF Val66Met polymorphism, and Met allele carriers showed a lower incidence of these side effects. Conclusions: These results indicate that there was a lack of association between severity of depression and BDNF Val66Met polymorphism in Chinese patients with MDD. The BDNF Val66Met polymorphism may play a major role in the efficacy and side effects of SSRI (fluoxetine) in Chinese patients with MDD.

Background: Several studies have investigated the association of FKBP5 gene polymorphisms with mood disorders, but findings are not always consistent. The aim of our study was to assess the association of FKBP5 gene polymorphisms with mood disorders using a meta-analysis.Methods: Data were collected from the following electronic databases: PubMed, Elsevier Science Direct, Cochrane Library, Chinese Biomedical Literature Database, China National Knowledge Infrastructure and Wanfang, with the last report up to March 2010. Meta-analysis was performed in a fixed/random effect model.Results: We identified six studies using search, and one study was excluded because of unavailable data. One study contained data on two different ethnicities and we treated them independently. Thus, six separate studies (2655 cases and 3593 controls) were included in the meta-analysis. Meta-analysis was performed for three FKBP5 gene polymorphisms (rs1360780, rs3800373 and rs4713916) in overall and Caucasian populations. We did not detect any association of FKBP5 gene rs1360780 and rs3800373 polymorphisms with mood disorders (p > 0.05). However, a significant association of FKBP5 gene rs4713916 polymorphism with mood disorders was found, and the heterozygous individual (GA genotype) was more susceptible to mood disorders in comparison to homozygous analogues (GG or AA genotype) [overall: GA vs. GG: OR (odds ratio) = 1.20, 95% CI (confidence interval) = 1.03–1.40, p = 0.02; GA vs. AA: OR = 1.44, 95% CI = 1.09–1.90, p = 0.009; Caucasian: GA vs. GG: OR = 1.22, 95% CI = 1.04–1.44, p = 0.01; GA vs. AA: OR = 1.43, 95% CI = 1.09–1.89, p = 0.01].Conclusion: This meta-analysis shows that mood disorders are associated with FKBP5 gene rs4713916 polymorphism, but not with rs1360780 and rs3800373.

Recently, we read with interest the article by Yu et al. [1]. They performed a meta-analysis to make an estimation of the association between two single-nucleotide polymorphisms (SNPs) in the interleukin-10 (IL-10) gene promoter, -1082A [ G (rs1800896) and -592C [ A (rs1800872), and breast cancer, and the results suggest that there was lack of association between the two SNPs and breast cancer. However, I have several concerns. First, they concluded that there was lack of association between the two SNPs and breast cancer. Only 3 of the 10 studies were conducted in non-Caucasians included in the meta-analysis. Especially, the study by Guzowski et al. [2] only included 50 cases and 25 controls, and the study by Gonullu et al. [3] only included 38 cases and 24 controls. Therefore, the results of the meta-analysis indicate that there was lack of association between the two SNPs and breast cancer, mainly in Caucasians. Further studies with larger sample size are needed to clarify the role of IL-10 in breast carcinogenesis in non-Caucasians. Secondly, in the discussion, they stated that ‘‘the total subject number of rs1800896 studies seemed to be insufficient (*1,600 cases and 1,600 controls) to reach a reliable conclusion.’’ However, we estimated the expected power of rs1800896 studies at the 0.05 level of significance, assuming that odds ratio (OR) was 1.5 for difference in allele frequency, as well as the minor (a) allele frequency was 0.2, and we found the expected power was 0.999. Thus, the total subject number of rs1800896 studies was sufficient to reach a reliable conclusion. Thirdly, in the article, though the genotype contrasts (Aa genotype vs. AA genotype, aa genotype vs. AA genotype, aa?Aa genotypes vs. AA genotype, and aa genotype vs. Aa?AA genotypes) were included, the allele (a allele vs. A allele) contrast was not included. It is needed to perform the allele contrast. In conclusion, the meta-analysis suggests that there was lack of association between the two SNPs in IL-10 gene promoter and breast cancer, mainly in Caucasians. Further studies with larger sample size are needed in non-Caucasians. Meanwhile, further gene–gene and gene–environment interactions studies stratified by ethnicity are still needed. We look forward to seeing the results from these interesting studies.

Published data on the association between interleukin-10 (IL-10) gene polymorphisms and prostate cancer (PCa) are inconclusive. To derive a more precise estimation of the association, we conducted a meta-analysis. Data were collected from the following electronic databases: PubMed, Elsevier Science Direct, Excerpta Medica Database and Chinese Biomedical Literature Database, with the last report up to September 2010. The odds ratio (OR) and its 95% confidence interval (95%CI) were used to assess the strength of association. A total of 13 separate studies including 5503 cases and 6078 controls based on the search criteria were involved in this meta-analysis. Meta-analysis was performed for three IL-10 gene polymorphisms (rs1800896, rs1800871, and rs1800872). We found no association between IL-10 gene rs1800896 polymorphism and PCa in overall population (G versus A: OR = 1.00, 95%CI = 0.91–1.10, P = 0.99; AG + GG versus AA: OR = 1.18, 95%CI = 0.97–1.43, P = 0.10; GG versus AA + AG: OR = 1.04, 95%CI = 0.86–1.26, P = 0.67). In subgroup analysis, similar results were found in Caucasian (G versus A: OR = 0.99, 95%CI = 0.84–1.18, P = 0.92; AG + GG versus AA: OR = 1.32, 95%CI = 0.90–1.94, P = 0.16; GG versus AA + AG: OR = 1.07, 95%CI = 0.89–1.28, P = 0.48), and Asian (G versus A: OR = 0.97, 95%CI = 0.78–1.20, P = 0.78; AG + GG versus AA: OR = 1.07, 95%CI = 0.79–1.45, P = 0.65; GG versus AA + AG: OR = 1.24, 95%CI = 0.38–4.07, P = 0.73) populations. We did not detect an association between IL-10 gene rs1800871 polymorphism and PCa in overall population (T versus C: OR = 0.96, 95%CI = 0.85–1.08, P = 0.51; CT + TT versus CC: OR = 0.94, 95%CI = 0.80–1.11, P = 0.48; TT versus CC + CT: OR = 0.94, 95%CI = 0.81–1.10, P = 0.44). Similar results were found in Asian population (T versus C: OR = 0.85, 95%CI = 0.71–1.09, P = 0.09; CT + TT versus CC: OR = 0.72, 95%CI = 0.52–1.17, P = 0.05; TT versus CC + CT: OR = 0.89, 95%CI = 0.68–1.17, P = 0.39). We found no association between IL-10 gene rs1800872 polymorphism and PCa in overall population (A versus C: OR=1.03, 95%CI = 0.96–1.11, P = 0.41; CA + AA versus CC: OR = 1.04, 95%CI = 0.92–1.17, P = 0.56; AA versus CC + CA: OR = 1.02, 95%CI = 0.85–1.22, P = 0.87). Similar results were found in Caucasian population (A versus C: OR = 1.06, 95%CI = 0.98–1.16, P = 0.16; CA + AA versus CC: OR = 1.07, 95%CI = 0.85–1.35, P = 0.57; AA versus CC + CA: OR = 1.23, 95%CI = 0.92–1.64, P = 0.17). This meta-analysis suggests that there is no association between IL-10 gene rs1800896, rs1800871 and rs1800872 polymorphisms and PCa.

Background In the past few decades, a number of studies have investigated the association of dopamine D2 receptor (DRD2) gene polymorphisms with mood disorders, but the findings are not always consistent. The aim of our study was to assess the association between DRD2 gene polymorphisms and mood disorders by using a meta-analysis. Methods Data were collected from the following electronic databases: PubMed, Elsevier Science Direct, Cochrane Library, Chinese Biomedical Literature Database, China National Knowledge Infrastructure, and Wanfang, with the last report up to June 2010. Meta-analysis was performed in a fixed/random effect model by using the software Review Manager 4.2. Results We identified 19 separate studies using search, but only 14 separate studies (2157 cases and 3272 controls) were included in the current study. Meta-analysis was performed for three DRD2 gene polymorphisms (-141Cins/del, Ser311/Cys311, and TaqI A1). We performed meta-analysis in overall, Caucasian, and Asian populations. We also performed disease-specific meta-analysis in unipolar disorder and bipolar disorder. We found no association between DRD2 gene -141Cins/del polymorphism and mood disorders in overall and Caucasian populations ( P > 0.05). We also found no association between DRD2 gene Ser311/Cys311 polymorphism and mood disorders in overall, Caucasian, and Asian populations ( P > 0.05). An association of DRD2 gene TaqI A1 polymorphism with mood disorders was found in overall population, and the individuals with A1A1 genotype were more susceptible to mood disorders in comparison to those with A2A1 and A2A2 genotypes (OR = 1.84, 95% CI = 1.07–3.17, P = 0.03). Limitation Meta-analysis is retrospective research that is subject to the methodological deficiencies of the included studies. Conclusion This meta-analysis suggests that mood disorders may be associated with DRD2 gene TaqI A1 polymorphism, but not -141Cins/del and Ser311/Cys311.

The aim of our meta-analysis was to quantitatively summarize the association of TYK2 gene polymorphisms with autoimmune and inflammatory diseases. 11 studies that included data from 21497 cases and 22647 controls were identified. OR was used as a measure of the effect of the association in a fixed/random effect model. Meta-analysis was performed for six TYK2 gene polymorphisms (rs34536443, rs2304256, rs280523, rs280519, rs12720270 and rs12720356). Significant association was found in rs34536443 (C versus G: OR = 0.76, 95% CI = 0.69–0.84, P

To the Editor, Recently, we read with great interest the article by Wang et al. [1]. They performed a meta-analysis of 10 case– control studies (4,443 cases and 5,447 controls) to examine the association between thymidylate synthase (TYMS) gene polymorphisms and breast cancer (BC). Their metaanalysis suggests that the TSER polymorphism may increase susceptibility to BC in the Caucasian population, and the TS30-UTR polymorphism may be a genetic determinant for developing BC in the Asian population. However, the authors have several concerns related to the article. First, the results of the meta-analysis should be interpreted with caution. In the conclusion, they stated that ‘‘ethnic background should be carefully considered in further studies.’’ For the TSER polymorphism, the overall odds ratios (ORs) and the corresponding 95% confidence interval (CI) showed a statistical association between this polymorphism and BC risk under homozygote comparison, allele comparison and the recessive model. In the subgroup analysis by ethnicity, the association was detected in the Caucasian population, but not in the Asian population. While, only two studies were conducted in the Asian population, and null findings may be due to a lack of statistical power in the Asian population. Similarly, for the TS30-UTR polymorphism, the overall ORs and the corresponding 95%CI showed a statistical association between this polymorphism and BC risk under homozygote comparison. Subgroup analysis revealed that there was only a marginal association in the Asian population for homozygote comparison (P = 0.05). Nevertheless, the meta-analysis showed a modest association in the overall population (All in HWE) when the Caucasian study by Justenhoven et al. [2] was included in the analysis (P = 0.03). Furthermore, for the TS30-UTR polymorphism, only two studies were conducted in the Caucasian population under homozygote comparison, and, of the two studies, the genotype distributions of controls in one study were not in agreement with Hardy–Weinberg equilibrium (HWE) [3]. There may be no enough power to detect a significant association of the TS30-UTR polymorphism with BC in the Caucasian population. Therefore, the data included in the meta-analysis are insufficient to support the conclusion that ethnic background should be carefully considered in further studies. Second, there are some issues in the methods. In the results, they stated that ‘‘A total of 10 studies (4,443 cases and 5,447 controls) met the inclusion criteria.’’ However, in the methods, they stated that ‘‘The following criteria were used to select the eligible studies... (d) a genotype distribution among the control populations consistent with Hardy–Weinberg Equilibrium (HWE).’’ Of the ten studies, the genotype distributions among the control populations in two studies were not in agreement with HWE [3, 4]. Thus, the two studies did not meet the inclusion criteria and should be excluded. Poor reporting of meta-analysis diminishes their value to clinicians, policy makers, and other users. An international group that included experienced authors and methodologists developed PRISMA (preferred reporting items for systematic reviews and metaanalyses) as a guideline for systematic reviews and metaanalyses. The PRISMA statement consists of a 27-item Y.-F. Zou X.-L. Feng Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei 230032, Anhui, China

Dear editor, Complex diseases are caused by a combination of genetic, environmental, and lifestyle factors, most of which have not yet been identiWed. The vast majority of diseases, including several congenital defects and a number of adult-onset diseases, fall into complex diseases. Complex diseases do not obey the standard Mendelian patterns of inheritance [1]. In the past few decades, many studies have been performed to relate genetic polymorphisms to complex diseases. In these studies, researchers examined the association between the allele, genotype and complex diseases. They usually select a dominant genetic eVect and a recessive genetic eVect of the minor allele. However, the two genetic inheritance patterns may not be comprehensive for complex diseases, and there may be another genetic eVect of the minor allele. Recently, we investigated the association between the tumor necrosis factor- (TNF-) promoter i238A/G polymorphism (TNF- i238G>A, rs361525) and systemic lupus erythematosus (SLE) using a meta-analysis [2]. We