Lonjou C, Clayton J, Cambon-Thomsen A, Raffoux C
Centre d'Immunopathologie et de Génétique Humaine UPR 8291, CHU Purpan, Toulouse, France.
Transplantation. 1995 Aug 27;60(4):375-83. doi: 10.1097/00007890-199508270-00013.
We have undertaken a study of the haplotypes among French potential bone marrow donors in order to define the geographical regions of France with the maximum of polymorphism and also to develop a strategy for optimal donor recruitment. A maximum likelihood estimator was used to calculate haplotype frequencies and their support limits for each region and for the whole of France. The observed differences between the regions were statistically significant. For each region, the minimum number of haplotypes necessary to explain 50% of the total frequency was calculated and compared with the equivalent values, and confidence intervals, obtained by repeated random samplings from the overall file. This approach shows that some regions (e.g., Provence) appear to be richer in terms of the numbers of haplotypes observed, and others (e.g., Bretagne) poorer. In the latter case, however, the frequencies of the most common haplotypes are greater. The haplotype frequencies of the whole sample were used to calculate the probability of finding a match for the next potential recipient for given sizes of the donor file, assuming random selection of donors. They were also used to calculate expected numbers of the major phenotypes, assuming Hardy-Weinberg equilibrium, and these were compared with those observed in the real data file. In this way, a large number of under-represented and nonrepresented phenotypes were identified. For each of these phenotypes, the most probable haplotypes and the regions in which these have the greatest frequencies have been identified. A search for donors with such particular phenotypes would be much more fruitful if directed towards these regions.
我们对法国潜在骨髓捐献者的单倍型进行了一项研究，目的是确定法国多态性最高的地理区域，并制定最佳捐献者招募策略。使用最大似然估计器来计算每个地区以及整个法国的单倍型频率及其支持限度。各地区之间观察到的差异具有统计学意义。计算每个地区解释总频率的50%所需的最少单倍型数量，并与通过从整个档案中重复随机抽样获得的等效值及置信区间进行比较。这种方法表明，有些地区（如普罗旺斯）观察到的单倍型数量似乎更丰富，而其他地区（如布列塔尼）则较少。然而，在后一种情况下，最常见单倍型的频率更高。假设随机选择捐献者，利用整个样本的单倍型频率来计算对于给定规模的捐献者档案，下一个潜在接受者找到匹配的概率。还利用这些频率在哈迪-温伯格平衡假设下计算主要表型的预期数量，并与实际数据档案中观察到的数量进行比较。通过这种方式，确定了大量代表性不足和未被代表的表型。对于每种此类表型，已确定了最可能的单倍型以及这些单倍型频率最高的地区。如果针对这些地区寻找具有此类特殊表型的捐献者，将会更有成效。
