Pharmacogenomics for the treatment of dementia.

Alzheimer's disease (AD) is a genetically complex disorder associated with multiple genetic defects either mutational or of susceptibility. Current AD genetics does not explain in full the etiopathogenesis of AD, suggesting that environmental factors and/or epigenetic phenomena may also contribute to AD pathology and phenotypic expression of dementia. The genomics of AD is still in its infancy, but is helping us to understand novel aspects of the disease including genetic epidemiology, multifactorial risk factors, pathogenic mechanisms associated with genetic networks and genetically-regulated metabolic cascades. AD genomics is also fostering new strategies in pharmacogenomic research and prevention. Functional genomics, proteomics, pharmacogenomics, high-throughput methods, combinatorial chemistry and modern bioinformatics will greatly contribute to accelerating drug development for AD and other complex disorders. The multifactorial genetic dysfunction in AD includes mutational loci (APP, PS1, PS2) and diverse susceptibility loci (APOE, A2M, AACT, LRP1, IL1A, TNF, ACE, BACE, BCHE, CST3, MTHFR, GSK3B, NOS3) distributed across the human genome, probably converging in common pathogenic mechanisms that lead to premature neuronal death. Genomic associations integrate polygenic matrix models to elucidate the genomic organization of AD in comparison to the control population. Using APOE-related monogenic models it has been demonstrated that the therapeutic response to drugs (e.g., cholinesterase inhibitors, non-cholinergic compounds) in AD is genotype-specific. A multifactorial therapy combining three different drugs yielded positive results during 6-12 months in approximately 60% of the patients. With this therapeutic strategy, APOE-4/4 carriers were the worst responders and patients with the APOE-3/4 genotype were the best responders. Other polymorphic variants (PS1, PS2) also influence the therapeutic response to different drugs in AD patients, suggesting that the final pharmacological outcome is the result of multiple genomic interactions, including AD-related genes and genes associated with drug metabolism, disposition, and elimination. The pharmacogenomics of AD may contribute in the future to optimise drug development and therapeutics, increasing efficacy and safety, and reducing side-effects and unnecessary costs.