Neurology Service, Neurology Department and CIBERNED, Marqués de Valdecilla University Hospital University of Cantabria and IFIMAV, 39008 Santander, Spain.
J Neural Transm (Vienna). 2013 May;120(5):807-12. doi: 10.1007/s00702-012-0920-x. Epub 2012 Nov 20.
Aside from APOE, the genetic factors that influence the progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) remain largely unknown. We assessed whether a genetic risk score (GRS), based on eight non-APOE genetic variants previously associated with AD risk in genome-wide association studies, is associated with either risk of conversion or with rapid progression from MCI to AD. Among 288 subjects with MCI, follow-up (mean 26.3 months) identified 118 MCI-converters to AD and 170 MCI-nonconverters. We genotyped ABCA7 rs3764650, BIN1 rs744373, CD2AP rs9296559, CLU rs1113600, CR1 rs1408077, MS4A4E rs670139, MS4A6A rs610932, and PICALM rs3851179. For each subject we calculated a cumulative GRS, defined as the number of risk alleles (range 0-16) with each allele weighted by the AD risk odds ratio. GRS was not associated with risk of conversion from MCI to AD. However, MCI-converters to AD harboring six or more risk alleles (second and third GRS tertiles) progressed twofold more rapidly to AD when compared with those with less than six risk alleles (first GRS tertile). Our GRS is a first step toward development of prediction models for conversion from MCI to AD that incorporate aggregate genetic factors.
除了 APOE 之外,影响从轻度认知障碍 (MCI) 向阿尔茨海默病 (AD) 进展的遗传因素在很大程度上仍然未知。我们评估了基于之前与全基因组关联研究中 AD 风险相关的八个非 APOE 遗传变异的遗传风险评分 (GRS) 是否与转换风险或从 MCI 向 AD 的快速进展相关。在 288 名 MCI 患者中,随访(平均 26.3 个月)确定了 118 名 MCI 向 AD 转化者和 170 名 MCI 未转化者。我们对 ABCA7 rs3764650、BIN1 rs744373、CD2AP rs9296559、CLU rs1113600、CR1 rs1408077、MS4A4E rs670139、MS4A6A rs610932 和 PICALM rs3851179 进行了基因分型。对于每个受试者,我们计算了累积 GRS,定义为每个等位基因的风险等位基因数量(范围 0-16),每个等位基因的权重为 AD 风险比值比。GRS 与从 MCI 向 AD 的转换风险无关。然而,与携带少于六个风险等位基因(第一 GRS 三分位数)的 AD 相比,携带六个或更多风险等位基因(第二和第三 GRS 三分位数)的 MCI 向 AD 转化者向 AD 进展的速度快两倍。我们的 GRS 是开发从 MCI 向 AD 转化的预测模型的第一步,该模型包含综合遗传因素。