Xu J, Postma D S, Howard T D, Koppelman G H, Zheng S L, Stine O C, Bleecker E R, Meyers D A
Center for Human Genomics, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA.
Am J Hum Genet. 2000 Nov;67(5):1163-73. doi: 10.1086/321190. Epub 2000 Oct 6.
Immunoglobulin E (IgE) has a major role in the pathogenesis of allergic disorders and asthma. Previous data from 92 families, each identified through a proband with asthma, showed evidence for two major genes regulating total serum IgE levels. One of these genes mapped to 5q31-33. In the current study, the segregation analysis was extended by the addition of 108 probands and their families, ascertained in the same manner. A mixed recessive model (i.e., major recessive gene and residual genetic effect) was the best-fitting and most-parsimonious one-locus model of the segregation analysis. A mixed two-major-gene model (i.e., two major genes and residual genetic effect) fit the data significantly better than did the mixed recessive one-major-gene model. The second gene modified the effect of the first recessive gene. Individuals with the genotype aaBB (homozygous high-risk allele at the first gene and homozygous low-risk allele at the second locus) had normal IgE levels (mean 23 IU/ml), and only individuals with genotypes aaBb and aabb had high IgE levels (mean 282 IU/ml). A genomewide screening was performed using variance-component analysis. Significant evidence for linkage was found for a novel locus at 7q, with a multipoint LOD score of 3. 36 (P=.00004). A LOD score of 3.65 (P=.00002) was obtained after genotyping additional markers in this region. Evidence for linkage was also found for two previously reported regions, 5q and 12q, with LOD scores of 2.73 (P=.0002) and 2.46 (P=.0004), respectively. These results suggest that several major genes, plus residual genetic effects, regulate total serum IgE levels.
免疫球蛋白E（IgE）在过敏性疾病和哮喘的发病机制中起主要作用。先前来自92个家庭的数据（每个家庭通过一名哮喘先证者确定）显示，有证据表明存在两个调节血清总IgE水平的主要基因。其中一个基因定位于5q31 - 33。在当前研究中，通过以相同方式确定的另外108名先证者及其家庭扩展了分离分析。混合隐性模型（即主要隐性基因和残余遗传效应）是分离分析中拟合度最佳且最简约的单基因座模型。混合双主基因模型（即两个主要基因和残余遗传效应）对数据的拟合明显优于混合隐性单主基因模型。第二个基因改变了第一个隐性基因的效应。基因型为aaBB（第一个基因的纯合高危等位基因和第二个基因座的纯合低危等位基因）的个体IgE水平正常（平均23 IU/ml），只有基因型为aaBb和aabb的个体IgE水平高（平均282 IU/ml）。使用方差成分分析进行了全基因组筛选。在7q发现了一个新基因座存在显著的连锁证据，多点LOD得分为3.36（P = .00004）。在该区域对额外标记进行基因分型后，获得了3.65的LOD得分（P = .00002）。在两个先前报道的区域5q和12q也发现了连锁证据，LOD得分分别为2.73（P = .0002）和2.46（P = .0004）。这些结果表明，几个主要基因加上残余遗传效应调节血清总IgE水平。
