Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts; Department of Psychiatry, University of Toronto Faculty of Medicine, Toronto, Ontario, Canada.
Am J Med Genet B Neuropsychiatr Genet. 2013 Oct;162B(7):770-8. doi: 10.1002/ajmg.b.32151. Epub 2013 May 6.
Genetic association studies of longitudinal cognitive phenotypes are an alternate approach to discovering genetic risk factors for Alzheimer's disease (AD). However, the standard linear mixed model approach is limited in the face of multidimensional longitudinal data and multiple genotypes. In this setting, the principal components of heritability (PCH) approach may increase efficiency by deriving a linear combination of phenotypes to maximize the heritability attributable to a particular genetic locus. The current study investigated the performance of two PCH methods, the Principal Components of Heritability Association Test (PCHAT) and C2BAT, in detecting association of the known AD susceptibility allele APOE-ϵ4 with cognitive function at baseline and decline in cognition over time.
PCHAT, C2BAT, and standard linear mixed models were used to test for association between APOE-ϵ4 allele and performance on 19 neuropsychological tests using subjects without dementia at baseline from the Religious Orders Study (ROS) (n = 693) and Memory and Aging Project (MAP) (n = 778). Analyses were conducted across the three methods for three nested phenotype definitions (all 19 measures, executive function and episodic memory measures, and episodic memory only), and for baseline data only versus longitudinal change.
In all cases, APOE-ϵ4 was significantly associated with baseline level of and change over time in cognitive function, and PCHAT and C2BAT yielded evidence of association comparable to or stronger than conventional methods.
PCHAT, C2BAT, and other PCH methods may have utility for genetic association studies of multidimensional cognitive and other phenotypes by maximizing genetic information while limiting multiple comparisons.
纵向认知表型的遗传关联研究是发现阿尔茨海默病（AD）遗传风险因素的另一种方法。然而，标准线性混合模型方法在面对多维纵向数据和多个基因型时受到限制。在这种情况下，遗传力主成分（PCH）方法可以通过推导表型的线性组合来最大化归因于特定遗传位点的遗传力，从而提高效率。本研究探讨了两种 PCH 方法，即遗传力主成分关联测试（PCHAT）和 C2BAT，在检测已知的 AD 易感性等位基因 APOE-ε4 与基线认知功能和随时间认知下降的关联中的性能。
使用 PCHAT、C2BAT 和标准线性混合模型，对基线时无痴呆的宗教秩序研究（ROS）（n=693）和记忆与衰老项目（MAP）（n=778）受试者的 19 项神经心理学测试的表现与 APOE-ε4 等位基因之间的关联进行了测试。对三个嵌套表型定义（所有 19 项测量、执行功能和情景记忆测量、仅情景记忆）和基线数据与纵向变化的所有三种方法进行了分析。
在所有情况下，APOE-ε4 与认知功能的基线水平和随时间的变化均显著相关，PCHAT 和 C2BAT 提供的关联证据与传统方法相当或更强。
PCHAT、C2BAT 和其他 PCH 方法可用于多维认知和其他表型的遗传关联研究，通过最大化遗传信息，同时限制多次比较，从而具有实用性。
