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Genetic heterogeneity is a common problem for genome-wide association studies of complex human diseases. Ordered-subset analysis (OSA) reduces genetic heterogeneity and optimizes the use of phenotypic information, thus improving power under some disease models. We hypothesized that in a genetically heterogeneous disorder such as Alzheimer's disease (AD), utilizing OSA by age at onset (AAO) of AD may increase the power to detect relevant loci. Using this approach, 8 loci were detected, including the chr15 : 30,44 region harboring CHRFAM7A. The association was replicated in the NIA-LOAD Familial Study dataset. CHRFAM7A is a dominant negative regulator of CHRNA7 function, the receptor that facilitates amyloid-β1-42 internalization through endocytosis and has been implicated in AD. OSA, using AAO as a quantitative trait, optimized power and detected replicable signals suggesting that AD is genetically heterogeneous between AAO subsets. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is a progressive neurodegenerative disease with high prevalence, which imposes a substantial public health problem. The heritability of AD is estimated at 60-80% forecasting the potential use of genetic biomarkers for risk stratification in the future. Several large scale genome-wide association studies using high frequency variants identified 10 loci accountable for only a fraction of the estimated heritability. To find the missing heritability, systematic assessment of various mutational mechanisms needs to be performed. This copy number variation (CNV) genome-wide association study with age at onset (AAO) of AD identified 5 CNV regions that may contribute to the heritability of AAO of AD. Two CNV events are intragenic causing a deletion in CPNE4. In addition, to further study the mutational load at the 10 known susceptibility loci, CNVs overlapping with these loci were also catalogued. We identified rare small events overlapping CR1 and BIN1 in AD and normal controls with opposite CNV dosage. The CR1 events are consistent with previous reports. Larger scale studies with deeper genotyping specifically addressing CNV are needed to evaluate the significance of these findings. [ABSTRACT FROM AUTHOR]