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目的研究遗传因素作用于空腹血糖(FPG)水平的模式,为探讨复杂性疾病的遗传方式、寻找疾病主效基因提供依据。方法本研究采用家系研究设计,在课题组前期收集的慢性病家系队列中,选取符合条件的非糖尿病家系285个,其中核心家系17个,同胞对387对。采用S.A.G.E.6.3软件分析家系中不同亲属间FPG水平的相关性,并对家系中FPG水平进行分离分析,筛选出家系中FPG水平传递的最佳模型。结果研究共纳入686名研究对象,其FPG水平的中位数(四分位数间距)为5.0(1.0)mmol/L,其中,先证者的FPG水平为5.0(1.1)mmol/L。家系中母-子(n=54,相关性系数为0.422 4,P<0.01)、母-女(n=41,相关性系数为0.435 7,P<0.01)、姐妹间(n=91,相关性系数为0.341 3,P<0.01)的相关性有统计学意义,而配偶(n=17)、父-女(n=26)、父-子(n=29)、兄弟间(n=119)以及异性同胞间(n=177)FPG水平的相关性均无统计学意义(P>0.05),提示,性别可能影响家系中FPG的水平。混合分离分析显示,三均值模型的赤池信息量准则(Akaike’s Information Criteria,AIC)值(1 664.728)最小,此模型最佳,提示在该家系中存在影响FPG水平的主效应因素。进一步复杂分离分析显示,与一般模型相比,孟德尔遗传模型和共显性模型均被拒绝(P<0.01);而环境模型与一般模型无统计学差异(P>0.05),且其AIC值最小,为最佳模型。结论家系中FPG水平的分布不存在主效基因效应,FPG的水平主要受环境因素影响。
Objective To study the effect of genetic factors on the level of fasting blood glucose (FPG) in order to provide basis for exploring the genetic mode of complex diseases and searching for the major genes of diseases. Methods A pedigree study was designed in this study. Of the 285 pediatric non-diabetic pedigrees selected from the chronic disease pedigrees cohort collected in the previous study group, there were 17 core family members and 387 pairs of siblings. Using S.A.G.E.6.3 software to analyze the relationship between FPG levels of different relatives in pedigree, and to separate and analyze the FPG level of the pedigree, we screened out the best model of FPG transmission in pedigrees. Results A total of 686 subjects were enrolled. The median FPG level (interquartile range) was 5.0 (1.0) mmol / L, with a proband’s FPG level of 5.0 (1.1) mmol / L. There was no significant difference between maternal and females (n = 54, correlation coefficient of 0.422 4, P <0.01), mother-female (n = 41, correlation coefficient of 0.435 7, P <0.01) (N = 17), father-daughter (n = 26), father-daughter (n = 29), brother (n = 119), sex = 0.341 3, P <0.01) ) And FPG (n = 177) were not statistically significant (P> 0.05), suggesting that sex may affect the level of FPG in the family. The mixed segregation analysis showed that Akaike’s Information Criteria (AIC) value (1 664.728) was the smallest in the three-mean model, and this model was the best, suggesting that there are main effect factors affecting FPG in this family. Further complicated segregation analysis showed that compared with the general model, Mendelian genetic model and co-dominant model were rejected (P <0.01), while there was no significant difference between the environmental model and the general model (P> 0.05), and the AIC value The smallest, best model. Conclusion The distribution of FPG in pedigrees does not have the main effect of genomic effect. The level of FPG is mainly affected by environmental factors.