Abstract
Until recently, the search for genes contributing to Alzheimer’s disease (AD) had been slow and disappointing, with the notable exception of the APOE ε4 allele, which increases risk and reduces the age at onset of AD in a dose-dependent fashion. Findings from genome-wide association studies (GWAS) made up of fewer than several thousand cases and controls each have not been replicated. Efforts of several consortia—each assembling much larger datasets with sufficient power to detect loci conferring small changes in AD risk—have resulted in robust associations with many novel genes involved in multiple biological pathways. Complex data mining strategies are being used to identify additional members of these pathways and gene–gene interactions contributing to AD risk. Guided by GWAS results, next-generation sequencing and functional studies are under way with the hope of helping us better understand AD pathology and providing new drug targets.
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Acknowledgments
This work was supported by National Institutes of Health grants R01-AG025259, R01-AG17173, R01-AG33193, U01-AG032984, and P30-AG13846 and a grant from an anonymous private foundation.
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Sherva, R., Farrer, L.A. Power and Pitfalls of the Genome-Wide Association Study Approach to Identify Genes for Alzheimer’s Disease. Curr Psychiatry Rep 13, 138–146 (2011). https://doi.org/10.1007/s11920-011-0184-4
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DOI: https://doi.org/10.1007/s11920-011-0184-4