Parkinson’s disease (PD) is the second most important age-related neurodegenerative disorder in developed societies, after Alzheimer’s disease, with a prevalence ranging from 41 per 100,000 in the fourth decade of life to over 1900 per 100,000 in people over 80 years of age. As a movement disorder, the PD phenotype is characterized by rigidity, resting tremor, and bradykinesia. Parkinson’s disease -related neurodegeneration is likely to occur several decades before the onset of the motor symptoms. Potential risk factors include environmental toxins, drugs, pesticides, brain microtrauma, focal cerebrovascular damage, and genomic defects. Parkinson’s disease neuropathology is characterized by a selective loss of dopaminergic neurons in the substantia nigra pars compacta, with widespread involvement of other central nervous system (CNS) structures and peripheral tissues. Pathogenic mechanisms associated with genomic, epigenetic and environmental factors lead to conformational changes and deposits of key proteins due to abnormalities in the ubiquitin–proteasome system together with dysregulation of mitochondrial function and oxidative stress. Conventional pharmacological treatments for PD are dopamine precursors (levodopa, l-DOPA, l-3,4 dihidroxifenilalanina), and other symptomatic treatments including dopamine agonists (amantadine, apomorphine, bromocriptine, cabergoline, lisuride, pergolide, pramipexole, ropinirole, rotigotine), monoamine oxidase (MAO) inhibitors (selegiline, rasagiline), and catechol-O-methyltransferase (COMT) inhibitors (entacapone, tolcapone). The chronic administration of antiparkinsonian drugs currently induces the “wearing-off phenomenon”, with additional psychomotor and autonomic complications. In order to minimize these clinical complications, novel compounds have been developed. Novel drugs and bioproducts for the treatment of PD should address dopaminergic neuroprotection to reduce premature neurodegeneration in addition to enhancing dopaminergic neurotransmission. Since biochemical changes and therapeutic outcomes are highly dependent upon the genomic profiles of PD patients, personalized treatments should rely on pharmacogenetic procedures to optimize therapeutics.

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Pharmacological treatment in Alzheimer's disease (AD) accounts for 10-20% of direct costs, and fewer than 20% of AD patients are moderate responders to conventional drugs (donepezil, rivastigmine, galantamine, memantine), with doubtful cost-effectiveness. Both AD pathogenesis and drug metabolism are genetically regulated complex traits in which hundreds of genes cooperatively participate. Structural genomics studies demonstrated that more than 200 genes might be involved in AD pathogenesis regulating dysfunctional genetic networks leading to premature neuronal death. The AD population exhibits a higher genetic variation rate than the control population, with absolute and relative genetic variations of 40-60% and 0.85-1.89%, respectively. AD patients also differ in their genomic architecture from patients with other forms of dementia. Functional genomics studies in AD revealed that age of onset, brain atrophy, cerebrovascular hemodynamics, brain bioelectrical activity, cognitive decline, apoptosis, immune function, lipid metabolism dyshomeostasis, and amyloid deposition are associated with AD-related genes. Pioneering pharmacogenomics studies also demonstrated that the therapeutic response in AD is genotype-specific, with apolipoprotein E (APOE) 4/4 carriers the worst responders to conventional treatments. About 10-20% of Caucasians are carriers of defective cytochrome P450 (CYP) 2D6 polymorphic variants that alter the metabolism and effects of AD drugs and many psychotropic agents currently administered to patients with dementia. There is a moderate accumulation of AD-related genetic variants of risk in CYP2D6 poor metabolizers (PMs) and ultrarapid metabolizers (UMs), who are the worst responders to conventional drugs. The association of the APOE-4 allele with specific genetic variants of other genes (e.g., CYP2D6, angiotensin-converting enzyme [ACE]) negatively modulates the therapeutic response to multifactorial treatments affecting cognition, mood, and behavior. Pharmacogenetic and pharmacogenomic factors may account for 60-90% of drug variability in drug disposition and pharmacodynamics. The incorporation of pharmacogenetic/pharmacogenomic protocols to AD research and clinical practice can foster therapeutics optimization by helping to develop cost-effective pharmaceuticals and improving drug efficacy and safety.

Alzheimer's disease (AD) is a major problem of health and disability, with a relevant economic impact on our society. Despite important advances in pathogenesis, diagnosis, and treatment, its primary causes still remain elusive, accurate biomarkers are not well characterized, and the available pharmacological treatments are not cost-effective. As a complex disorder, AD is a polygenic and multifactorial clinical entity in which hundreds of defective genes distributed across the human genome may contribute to its pathogenesis. Diverse environmental factors, cerebrovascular dysfunction, and epigenetic phenomena, together with structural and functional genomic dysfunctions, lead to amyloid deposition, neurofibrillary tangle formation, and premature neuronal death, the major neuropathological hallmarks of AD. Future perspectives for the global management of AD predict that genomics and proteomics may help in the search for reliable biomarkers. In practical terms, the therapeutic response to conventional drugs (cholinesterase inhibitors, multifactorial strategies) is genotype-specific. Genomic factors potentially involved in AD pharmacogenomics include at least five categories of gene clusters: (1) genes associated with disease pathogenesis; (2) genes associated with the mechanism of action of drugs; (3) genes associated with drug metabolism (phase I and II reactions); (4) genes associated with drug transporters; and (5) pleiotropic genes involved in multifaceted cascades and metabolic reactions. The implementation of pharmacogenomic strategies will contribute to optimize drug development and therapeutics in AD and related disorders.

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