Brehima Diakite, Yaya Kassogue, Guimogo Dolo, Jun Wang, Erin Neuschler, Oumar Kassogue, Mamadou L Keita, Cheick B Traore, Bakarou Kamate, Etienne Dembele, Sellama Nadifi, Robert L Murphy, Seydou Doumbia, Lifang Hou, Mamoudou Maiga
{"title":"p.Arg72Pro多态性与乳腺癌风险:病例对照研究的荟萃分析","authors":"Brehima Diakite, Yaya Kassogue, Guimogo Dolo, Jun Wang, Erin Neuschler, Oumar Kassogue, Mamadou L Keita, Cheick B Traore, Bakarou Kamate, Etienne Dembele, Sellama Nadifi, Robert L Murphy, Seydou Doumbia, Lifang Hou, Mamoudou Maiga","doi":"10.1186/s12881-020-01133-8","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The effect of the p.Arg72Pro variant of the P53 gene on the risk of development ofbreast cancer remains variable in populations. However, the use ofstrategies such aspoolingage-matched controls with disease may provide a consistent meta-analysis. Our goal was to perform a meta-analysis in order to assess the association of p.Arg72Pro variant of P53 gene with the risk of breast cancer.</p><p><strong>Methods: </strong>Databases such as PubMed, Genetics Medical Literature, Harvard University Library, Web of Science and Genesis Library were used to search articles. Case-control studies with age-matched on breast cancer havingevaluated the genotype frequencies of the TP53 p.Arg72Pro polymorphism were selected. The fixed and random effects (Mantel-Haenszel) were calculated using pooled odds ratio of 95% CI to determine the risk of disease. Inconsistency was calculated to determine heterogeneity among the studies. The publication bias was estimated using the funnel plot.</p><p><strong>Results: </strong>Twenty-one publications with 7841 cases and 8876 controls were evaluated in this meta-analysis. Overall, our results suggested that TP53 p.Arg72Pro was associated with the risk of breast cancer for the dominant model (OR = 1.09, 95% CI = 1.02-1.16, P = 0.01) and the additive model (OR = 1.09, 95% CI = 1.01-1.17, P = 0.03), but not for the recessive model (OR = 1.07, 95% CI = 0.97-1.18, P = 0.19). According to the ethnic group analysis, Pro allele was associated with the risk of breast cancer in Caucasians for the dominant model and additive model (P = 0.02), and Africans for the recessive model and additive model (P = 0.03).</p><p><strong>Conclusions: </strong>This meta-analysis found a significant association between TP53 p.Arg72Pro polymorphism and the risk of breast cancer. Individuals carrying at least one Pro allele were more likely to have breast cancer than individuals harboring the Arg allele.</p>","PeriodicalId":9015,"journal":{"name":"BMC Medical Genetics","volume":" ","pages":"206"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s12881-020-01133-8","citationCount":"9","resultStr":"{\"title\":\"p.Arg72Pro polymorphism of P53 and breast cancer risk: a meta-analysis of case-control studies.\",\"authors\":\"Brehima Diakite, Yaya Kassogue, Guimogo Dolo, Jun Wang, Erin Neuschler, Oumar Kassogue, Mamadou L Keita, Cheick B Traore, Bakarou Kamate, Etienne Dembele, Sellama Nadifi, Robert L Murphy, Seydou Doumbia, Lifang Hou, Mamoudou Maiga\",\"doi\":\"10.1186/s12881-020-01133-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The effect of the p.Arg72Pro variant of the P53 gene on the risk of development ofbreast cancer remains variable in populations. However, the use ofstrategies such aspoolingage-matched controls with disease may provide a consistent meta-analysis. Our goal was to perform a meta-analysis in order to assess the association of p.Arg72Pro variant of P53 gene with the risk of breast cancer.</p><p><strong>Methods: </strong>Databases such as PubMed, Genetics Medical Literature, Harvard University Library, Web of Science and Genesis Library were used to search articles. Case-control studies with age-matched on breast cancer havingevaluated the genotype frequencies of the TP53 p.Arg72Pro polymorphism were selected. The fixed and random effects (Mantel-Haenszel) were calculated using pooled odds ratio of 95% CI to determine the risk of disease. Inconsistency was calculated to determine heterogeneity among the studies. The publication bias was estimated using the funnel plot.</p><p><strong>Results: </strong>Twenty-one publications with 7841 cases and 8876 controls were evaluated in this meta-analysis. Overall, our results suggested that TP53 p.Arg72Pro was associated with the risk of breast cancer for the dominant model (OR = 1.09, 95% CI = 1.02-1.16, P = 0.01) and the additive model (OR = 1.09, 95% CI = 1.01-1.17, P = 0.03), but not for the recessive model (OR = 1.07, 95% CI = 0.97-1.18, P = 0.19). According to the ethnic group analysis, Pro allele was associated with the risk of breast cancer in Caucasians for the dominant model and additive model (P = 0.02), and Africans for the recessive model and additive model (P = 0.03).</p><p><strong>Conclusions: </strong>This meta-analysis found a significant association between TP53 p.Arg72Pro polymorphism and the risk of breast cancer. 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引用次数: 9
摘要
背景:P53基因p.a g72pro变异对乳腺癌发生风险的影响在人群中仍然存在差异。然而,使用诸如将年龄匹配的对照与疾病相结合的策略可能会提供一致的荟萃分析。我们的目标是进行一项荟萃分析,以评估P53基因p.a g72pro变异与乳腺癌风险的关系。方法:检索PubMed、Genetics Medical Literature、Harvard University Library、Web of Science、Genesis Library等数据库。选择年龄匹配的乳腺癌病例对照研究,评估TP53 p.a g72pro多态性的基因型频率。固定效应和随机效应(Mantel-Haenszel)采用95% CI的合并优势比计算,以确定疾病风险。计算不一致性以确定研究之间的异质性。用漏斗图估计发表偏倚。结果:本荟萃分析评估了21篇发表的7841例病例和8876例对照。总体而言,我们的结果表明,TP53 p.a g72pro与乳腺癌风险相关的显性模型(OR = 1.09, 95% CI = 1.02-1.16, P = 0.01)和加性模型(OR = 1.09, 95% CI = 1.01-1.17, P = 0.03),但与隐性模型无关(OR = 1.07, 95% CI = 0.97-1.18, P = 0.19)。根据族群分析,Pro等位基因与乳腺癌风险的相关性在高加索人中为显性模型和加性模型(P = 0.02),在非洲人中为隐性模型和加性模型(P = 0.03)。结论:该荟萃分析发现TP53 p.a g72pro多态性与乳腺癌风险之间存在显著关联。携带至少一个Pro等位基因的个体比携带Arg等位基因的个体更容易患乳腺癌。
p.Arg72Pro polymorphism of P53 and breast cancer risk: a meta-analysis of case-control studies.
Background: The effect of the p.Arg72Pro variant of the P53 gene on the risk of development ofbreast cancer remains variable in populations. However, the use ofstrategies such aspoolingage-matched controls with disease may provide a consistent meta-analysis. Our goal was to perform a meta-analysis in order to assess the association of p.Arg72Pro variant of P53 gene with the risk of breast cancer.
Methods: Databases such as PubMed, Genetics Medical Literature, Harvard University Library, Web of Science and Genesis Library were used to search articles. Case-control studies with age-matched on breast cancer havingevaluated the genotype frequencies of the TP53 p.Arg72Pro polymorphism were selected. The fixed and random effects (Mantel-Haenszel) were calculated using pooled odds ratio of 95% CI to determine the risk of disease. Inconsistency was calculated to determine heterogeneity among the studies. The publication bias was estimated using the funnel plot.
Results: Twenty-one publications with 7841 cases and 8876 controls were evaluated in this meta-analysis. Overall, our results suggested that TP53 p.Arg72Pro was associated with the risk of breast cancer for the dominant model (OR = 1.09, 95% CI = 1.02-1.16, P = 0.01) and the additive model (OR = 1.09, 95% CI = 1.01-1.17, P = 0.03), but not for the recessive model (OR = 1.07, 95% CI = 0.97-1.18, P = 0.19). According to the ethnic group analysis, Pro allele was associated with the risk of breast cancer in Caucasians for the dominant model and additive model (P = 0.02), and Africans for the recessive model and additive model (P = 0.03).
Conclusions: This meta-analysis found a significant association between TP53 p.Arg72Pro polymorphism and the risk of breast cancer. Individuals carrying at least one Pro allele were more likely to have breast cancer than individuals harboring the Arg allele.
期刊介绍:
BMC Medical Genetics is an open access journal publishing original peer-reviewed research articles in the effects of genetic variation in individuals, families and among populations in relation to human health and disease.
Note: BMC Medical Genetics is now closed. This journal has merged with BMC Medical Genomics, a broad-scope, open access community journal for all medical genetics and genomics research.