Pharmacogenomics of Alzheimer’s Disease: Novel Strategies for Drug Utilization and Development

Cacabelos, Ramón; Naidoo, Vinogran; Martínez-Iglesias, Olaia; Corzo, Lola; Cacabelos, Natalia; Pego, Rocío; Carril, Juan Carlos

doi:10.1007/978-1-0716-2573-6_13

Cited by 8 publications

(5 citation statements)

References 232 publications

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“…Approximately 20% of the direct costs are associated with pharmacological treatment, with little cost-effectiveness. Alzheimer's disease is the most prevalent form of dementia (50-60%), followed by vascular dementia (30-40%), other forms of dementia (10-15%), and mixed dementia, which is the most prevalent form of dementia (>70%) in patients over 75 years of age [17].…”

Section: Genuine Behavior Of Brain Diseasesmentioning

confidence: 99%

“…From a strictly scientific point of view, in terms of quality, genomics contributed enormously to a better understanding of the etiopathogenesis of diseases of the nervous system [19][20][21][22][23][24][25][26][27][28][29][30][31][32], to the discovery of diagnostic biomarkers [33][34][35], and to accelerating the implementation of new pharmacogenomics protocols, both for the use of common drugs and for the development of new drugs [17,36,37].…”

Section: Increase In Number Of Genomic Studiesmentioning

confidence: 99%

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Genomics of Brain Disorders 4.0

Cacabelos

2024

IJMS

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Section: Genuine Behavior Of Brain Diseasesmentioning

confidence: 99%

Section: Increase In Number Of Genomic Studiesmentioning

confidence: 99%

Genomics of Brain Disorders 4.0

Cacabelos

2024

IJMS

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“…Such treatments span a wide array of pharmacological approaches, from neuroprotective and anti-dementia drugs to medications targeting concurrent pathologies, neuropsychiatric disorders, and drugs to treat metabolic deficits. Here, the application of pharmacogenetic procedures can be particularly beneficial [ 4 ]. Over 90% of AD patients require these multifactorial treatments, which often involve treating coexisting conditions such as hypertension (>25%), obesity (>70%), type 2 diabetes mellitus (>25%), hypercholesterolemia (40%), hypertriglyceridemia (20%), metabolic syndrome (20%), hepatobiliary disorder (15%), endocrine/metabolic disorders (>20%), cardiovascular disorder (40%), cerebrovascular disorder (60–90%), neuropsychiatric disorders (60–90%), and cancer (10%) [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

“…Here, the application of pharmacogenetic procedures can be particularly beneficial [ 4 ]. Over 90% of AD patients require these multifactorial treatments, which often involve treating coexisting conditions such as hypertension (>25%), obesity (>70%), type 2 diabetes mellitus (>25%), hypercholesterolemia (40%), hypertriglyceridemia (20%), metabolic syndrome (20%), hepatobiliary disorder (15%), endocrine/metabolic disorders (>20%), cardiovascular disorder (40%), cerebrovascular disorder (60–90%), neuropsychiatric disorders (60–90%), and cancer (10%) [ 4 ]. However, this strategy can increase the risk of ADRs and DDIs.…”

Section: Introductionmentioning

confidence: 99%

“…Pharmacogenetic outcome is influenced by various classes of genes, including pathogenic, mechanistic, metabolic, transporter and pleiotropic genes that comprise the pharmacogenetic machinery. These genes are regulated by epigenetic factors such as DNA methylation, chromatin/histone modifications, and miRNAs [ 4 , 13 ]. The enzymes and transporters that are integral to metabolic pathways exhibit a considerable degree of polymorphism.…”

Section: Introductionmentioning

confidence: 99%

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Influence of Metabolic, Transporter, and Pathogenic Genes on Pharmacogenetics and DNA Methylation in Neurological Disorders

Martínez-Iglesias,

Naidoo,

Carrera

et al. 2023

Biology

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Pharmacogenetics and DNA methylation influence therapeutic outcomes and provide insights into potential therapeutic targets for brain-related disorders. To understand the effect of genetic polymorphisms on drug response and disease risk, we analyzed the relationship between global DNA methylation, drug-metabolizing enzymes, transport genes, and pathogenic gene phenotypes in serum samples from two groups of patients: Group A, which showed increased 5-methylcytosine (5mC) levels during clinical follow-up, and Group B, which exhibited no discernible change in 5mC levels. We identified specific SNPs in several metabolizing genes, including CYP1A2, CYP2C9, CYP4F2, GSTP1, and NAT2, that were associated with differential drug responses. Specific SNPs in CYP had a significant impact on enzyme activity, leading to changes in phenotypic distribution between the two patient groups. Group B, which contained a lower frequency of normal metabolizers and a higher frequency of ultra-rapid metabolizers compared to patients in Group A, did not show an improvement in 5mC levels during follow-up. Furthermore, there were significant differences in phenotype distribution between patient Groups A and B for several SNPs associated with transporter genes (ABCB1, ABCC2, SLC2A9, SLC39A8, and SLCO1B1) and pathogenic genes (APOE, NBEA, and PTGS2). These findings appear to suggest that the interplay between pharmacogenomics and DNA methylation has important implications for improving treatment outcomes in patients with brain-related disorders.

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Genetic predictors of neurocognitive outcomes in survivors of pediatric brain tumors

Grob,

Miller,

Sanford

et al. 2023

J Neurooncol

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Background Neurocognitive deficits are common in pediatric brain tumor survivors. The use of single nucleotide polymorphism (SNP) analysis in DNA repair genes may identify children treated with radiation therapy for brain tumors at increased risk for treatment toxicity and adverse neurocognitive outcomes. Materials The Human 660W-Quad v1.0 DNA BeadChip analysis (Illumina) was used to evaluate 1048 SNPs from 59 DNA repair genes in 46 subjects. IQ testing was measured by the Wechsler Intelligence Scale for Children. Linear regression was used to identify the 10 SNPs with the strongest association with IQ scores while adjusting for radiation type. Results The low vs high IQ patient cohorts were well matched for time from first treatment to most recent IQ, first treatment age, sex, and treatments received. 5 SNPs on 3 different genes (CYP29, XRCC1, and BRCA1) and on 3 different chromosomes (10, 19, and 17) had the strongest association with most recent IQ score that was not modified by radiation type. Furthermore, 5 SNPs on 4 different genes (WRN, NR3C1, ERCC4, RAD51L1) on 4 different chromosomes (8, 5, 16, 14) had the strongest association with change in IQ independent of radiation type, first IQ, and years between IQ measures. Conclusions SNPs offer the potential to predict adverse neurocognitive outcomes in pediatric brain tumor survivors. Our results require validation in a larger patient cohort. Improving the ability to identify children at risk of treatment related neurocognitive deficits could allow for better treatment stratification and early cognitive interventions.

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Pharmacogenomics of Alzheimer’s Disease: Novel Strategies for Drug Utilization and Development

Cited by 8 publications

References 232 publications

Genomics of Brain Disorders 4.0

Genomics of Brain Disorders 4.0

Influence of Metabolic, Transporter, and Pathogenic Genes on Pharmacogenetics and DNA Methylation in Neurological Disorders

Genetic predictors of neurocognitive outcomes in survivors of pediatric brain tumors

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