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白癜风遗传模式的复合分离分析 被引量:6

Genetic patterns of vitiligo in China
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摘要 目的 探讨中国汉族不同类型白癜风可能的遗传模式。方法 以调查表的形式收集患者的临床资料及家系资料 ,用EpiInfo 5 0及SPSS 10 0软件包进行统计学分析 ,用SAGE 3 1进行遗传模式的复合分离分析。结果 白癜风的平均发病年龄为 19岁左右 ,性别间差异无显著性 (P >0 0 5 ) ;患者一、二级亲属中白癜风患病率较一般人群显著增高 (P <0 0 5 )。局限型、面肢型及节段型白癜风符合多基因累加遗传模式 (P >0 0 5 ) ,泛发型白癜风可能的遗传模式为环境模式 (P >0 0 5 )。结论 白癜风的发生无性别差异 ,但存在明显的家族聚集性 ,不同类型的白癜风发病机制可能不尽相同。该病的发生可能是由多基因累加遗传效应及环境因素共同作用的结果。 Objective The aims were to analyze the clinical characteristics and to explore the potential genetic model of vitiligo in Chinese Han.Methods Information of the clinical feature and the familial history of a large cohort of patients with vitiligo was elicited by a uniform questionnaire.The set of data was analyzed by Epi Info 5.0 and SPSS 10.0 software packages.A complex segregation analysis was conducted using the REGTL program in SAGE 3.1 package in order to propose the putative genetic model of vitiligo.Results The mean onset age of vitiligo in the males was about 19 years old,the same to the females. The mean onset age of segmental vitiligo was earlier (P<0.05) than those of the other phenotypes of vitiligo. The prevalence rates of vitiligo among patients’first-and second-degree relatives were significantly higher (P<0.05) than that in the general population. A polygenic additive model was fit for focal vitiligo, acrofacial vitiligo and segmental vitiligo (P>0.05) according to the results obtained by the complex segregation analysis. For universal vitiligo, the best model was an environmental model.Conclusions Males and females are affected by vitiligo with an equal frequency and the same onset age. There is an obvious familial aggregation of vitiligo. This study indicates that different phenotypes of vitiligo have different pathogeneses and genetic backgrounds. Onset of vitiligo is probably determined by both genetic backgrounds and common environmental factors.
出处 《安徽医科大学学报》 CAS 2004年第6期415-418,共4页 Acta Universitatis Medicinalis Anhui
基金 国家 8 63计划课题资助项目 (编号 :2 0 0 1AA2 2 70 3 1)
关键词 白癜风 遗传模式 遗传流行病学 vitiligo genetic model genetic epidemiology
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