Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America.
PLoS One. 2012;7(1):e29848. doi: 10.1371/journal.pone.0029848. Epub 2012 Jan 18.
Like most complex phenotypes, exceptional longevity is thought to reflect a combined influence of environmental (e.g., lifestyle choices, where we live) and genetic factors. To explore the genetic contribution, we undertook a genome-wide association study of exceptional longevity in 801 centenarians (median age at death 104 years) and 914 genetically matched healthy controls. Using these data, we built a genetic model that includes 281 single nucleotide polymorphisms (SNPs) and discriminated between cases and controls of the discovery set with 89% sensitivity and specificity, and with 58% specificity and 60% sensitivity in an independent cohort of 341 controls and 253 genetically matched nonagenarians and centenarians (median age 100 years). Consistent with the hypothesis that the genetic contribution is largest with the oldest ages, the sensitivity of the model increased in the independent cohort with older and older ages (71% to classify subjects with an age at death>102 and 85% to classify subjects with an age at death>105). For further validation, we applied the model to an additional, unmatched 60 centenarians (median age 107 years) resulting in 78% sensitivity, and 2863 unmatched controls with 61% specificity. The 281 SNPs include the SNP rs2075650 in TOMM40/APOE that reached irrefutable genome wide significance (posterior probability of association = 1) and replicated in the independent cohort. Removal of this SNP from the model reduced the accuracy by only 1%. Further in-silico analysis suggests that 90% of centenarians can be grouped into clusters characterized by different "genetic signatures" of varying predictive values for exceptional longevity. The correlation between 3 signatures and 3 different life spans was replicated in the combined replication sets. The different signatures may help dissect this complex phenotype into sub-phenotypes of exceptional longevity.
与大多数复杂的表型一样，超长寿命被认为反映了环境（例如生活方式选择、生活地点）和遗传因素的综合影响。为了探究遗传因素的贡献，我们对 801 名百岁老人（死亡时的中位年龄为 104 岁）和 914 名基因匹配的健康对照者进行了全基因组关联研究。利用这些数据，我们构建了一个遗传模型，其中包含 281 个单核苷酸多态性（SNP），在发现集的病例和对照者中，该模型的敏感性和特异性分别为 89%和 58%，在另外 341 名对照者和 253 名基因匹配的非百岁和百岁老人（中位年龄 100 岁）的独立队列中，特异性和敏感性分别为 60%和 71%。与遗传贡献随着年龄最大而最大的假设一致，该模型在独立队列中的敏感性随着年龄的增长而增加（将年龄在 102 岁以上的受试者分类的敏感性为 71%，将年龄在 105 岁以上的受试者分类的敏感性为 85%）。为了进一步验证，我们将该模型应用于另外 60 名无匹配的百岁老人（中位年龄 107 岁），结果敏感性为 78%，并对 2863 名无匹配的对照者进行了分析，特异性为 61%。这 281 个 SNP 包括 TOMM40/APOE 中的 SNP rs2075650，该 SNP 达到了不可置疑的全基因组显著水平（关联的后验概率为 1），并在独立队列中得到了复制。从模型中去除这个 SNP 只会使准确性降低 1%。进一步的计算机分析表明，90%的百岁老人可以分为不同的群组，这些群组具有不同的“遗传特征”，对超长寿命的预测值也不同。3 个特征与 3 个不同的寿命之间的相关性在综合复制集中得到了复制。不同的特征可能有助于将这种复杂的表型分解为超长寿命的亚表型。
