Population-level pharmacogenomics for precision drug development in dementia

Pharmacogenetics of anxiety and depression in Alzheimer's disease

Anxiety and depression coexist with cognitive impairment in Alzheimer's disease along with other concomitant disorders (>60%), which require multipurpose treatments. Polypharmaceutical regimens cause drug-drug interactions and adverse drug reactions, potentially avoidable in number and severity with the implementation of pharmacogenetic procedures. The accumulation of defective variants (>30 genes per patient in more than 50% of cases) in pharmagenes (pathogenic, mechanistic, metabolic, transporter, pleiotropic) influences the therapeutic response to antidementia, antidepressant and anxiolytic drugs in polyvalent regimens. APOE, CYP1A2, CYP2C9, CYP2C19, CYP2D6, CYP2E1, CYP3A4, CYP3A5, CYP4F2, COMT, MAOB, CHAT, GSTP1, NAT2, SLC30A8, SLCO1B1, ADRA2A, ADRB2, BCHE, GABRA1, HMGCR, HTR2C, IFNL3, NBEA, UGT1A1, ABCB1, ABCC2, ABCG2, SLC6A2, SLC6A3, SLC6A4, MTHFR and OPRM1 variants affect anxiety and depression in Alzheimer's disease.

Personalized Management and Treatment of Alzheimer's Disease

Alzheimer’s disease (AD) is a priority health problem with a high cost to society and a large consumption of medical and social resources. The management of AD patients is complex and multidisciplinary. Over 90% of patients suffer from concomitant diseases and require personalized therapeutic regimens to reduce adverse drug reactions (ADRs), drug−drug interactions (DDIs), and unnecessary costs. Men and women show substantial differences in their AD-related phenotypes. Genomic, epigenetic, neuroimaging, and biochemical biomarkers are useful for predictive and differential diagnosis. The most frequent concomitant diseases include hypertension (>25%), obesity (>70%), diabetes mellitus type 2 (>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%). Over 90% of AD patients require multifactorial treatments with risk of ADRs and DDIs. The implementation of pharmacogenetics in clinical practice can help optimize the limited therapeutic resources available to treat AD and personalize the use of anti-dementia drugs, in combination with other medications, for the treatment of concomitant disorders.

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

Alzheimer's disease (AD) is a priority health problem in developed countries with a high cost to society. Approximately 20% of direct costs are associated with pharmacological treatment. Over 90% of patients require multifactorial treatments, with risk of adverse drug reactions (ADRs) and drug-drug interactions (DDIs) for the treatment of concomitant diseases such as hypertension (>25%), obesity (>70%), diabetes mellitus type 2 (>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%).For the past decades, pharmacological studies in search of potential treatments for AD focused on the following categories: neurotransmitter enhancers (11.38%), multitarget drugs (2.45%), anti-amyloid agents (13.30%), anti-tau agents (2.03%), natural products and derivatives (25.58%), novel synthetic drugs (8.13%), novel targets (5.66%), repository drugs (11.77%), anti-inflammatory drugs (1.20%), neuroprotective peptides (1.25%), stem cell therapy (1.85%), nanocarriers/nanotherapeutics (1.52%), and other compounds (<1%).Pharmacogenetic studies have shown that the therapeutic response to drugs in AD is genotype-specific in close association with the gene clusters that constitute the pharmacogenetic machinery (pathogenic, mechanistic, metabolic, transporter, pleiotropic genes) under the regulatory control of epigenetic mechanisms (DNA methylation, histone/chromatin remodeling, microRNA regulation). Most AD patients (>60%) are carriers of over ten pathogenic genes. The genes that most frequently (>50%) accumulate pathogenic variants in the same AD case are A2M (54.38%), ACE (78.94%), BIN1 (57.89%), CLU (63.15%), CPZ (63.15%), LHFPL6 (52.63%), MS4A4E (50.87%), MS4A6A (63.15%), PICALM (54.38%), PRNP (80.7059), and PSEN1 (77.19%). There is also an accumulation of 15 to 26 defective pharmagenes in approximately 85% of AD patients. About 50% of AD patients are carriers of at least 20 mutant pharmagenes, and over 80% are deficient metabolizers for the most common drugs, which are metabolized via the CYP2D6, CYP2C9, CYP2C19, and CYP3A4/5 enzymes.The implementation of pharmacogenetics can help optimize drug development and the limited therapeutic resources available to treat AD, and personalize the use of anti-dementia drugs in combination with other medications for the treatment of concomitant disorders.

Genophenotypic Factors and Pharmacogenomics in Adverse Drug Reactions

Adverse drug reactions (ADRs) rank as one of the top 10 leading causes of death and illness in developed countries. ADRs show differential features depending upon genotype, age, sex, race, pathology, drug category, route of administration, and drug–drug interactions. Pharmacogenomics (PGx) provides the physician effective clues for optimizing drug efficacy and safety in major problems of health such as cardiovascular disease and associated disorders, cancer and brain disorders. Important aspects to be considered are also the impact of immunopharmacogenomics in cutaneous ADRs as well as the influence of genomic factors associated with COVID-19 and vaccination strategies. Major limitations for the routine use of PGx procedures for ADRs prevention are the lack of education and training in physicians and pharmacists, poor characterization of drug-related PGx, unspecific biomarkers of drug efficacy and toxicity, cost-effectiveness, administrative problems in health organizations, and insufficient regulation for the generalized use of PGx in the clinical setting. The implementation of PGx requires: (i) education of physicians and all other parties involved in the use and benefits of PGx; (ii) prospective studies to demonstrate the benefits of PGx genotyping; (iii) standardization of PGx procedures and development of clinical guidelines; (iv) NGS and microarrays to cover genes with high PGx potential; and (v) new regulations for PGx-related drug development and PGx drug labelling.

What is the gold standard model for Alzheimer's disease drug discovery and development?

Introduction: Alzheimer's disease models (ADMs) are currently used for drug development (DD). More than 20,000 molecules were screened for AD treatment over decades, with only one drug (Aducanumab)FDA-approved over the past 18 years. A revision of pathogenic concepts and ADMs are needed.Areas covered: The authors discuss herein preclinical models including: (i) in vitro models (cell lines, primary neuron cell cultures, iPSC-derived brain cells), (ii) ex vivo models, and (iii) in vivo models (artificial, transgenic, non-transgenic and induced).Expert opinion: The following types of ADMs have been reported: Mouse models (45.08%), Rat models (15.04%), Non-human Primate models (0.76%), Rabbit models (0.46%), Cat models (0.53%), Pig models (0.30%), Guinea pig models (0.15%), Octodon degu models (0.02%), Dog models (0.54%), Drosophila melanogaster models (1.79%), Zebrafish models (0.50%), Caenorhabditis elegans (1.21%), Cell culture models (3.31%), Cholinergic models (8.26%), Neurotoxic models (6.79%), Neuroinflammation models (6.92%), Neurovascular models (7.88%), and Microbiome models (0.45%).No single ADM faithfully reproduces all the pathogenic events in the human AD phenotype spectrum. ADMs should be different for (i) pathogenic studies vs basic DD, and (ii) preventive interventions vs symptomatic treatments. There cannot be an ideal ADM for DD, because AD is a spectrum of syndromes. DD can integrate pathogenic, mechanistic, metabolic, transporter and pleiotropic genes in a multisystem model.

Prescription Pattern of Antidepressants and the Potential for Personalized Medicine in the Qatari Population

Studying the prescription pattern of medications will help in understanding potential unnecessary prescriptions, due to the trial-and-error method of prescribing, and the need for personalized medicine in a population. Therefore, in this study, our aim was to explore the prescribing pattern and off-label use of antidepressants in the Qatari population. We conducted a retrospective study of Qatari patients who received prescriptions for antidepressants from the major healthcare providers in Qatar, for a period of 24 months between June 2018 and May 2020. The number of patients, prescriptions, and diagnostic indications were analyzed. The chi-square test was used for identifying statistically significant association of the number of individuals prescribed with age category or gender. Of the 14,601 Qatari patients who were prescribed antidepressants, the majority were female (61%, p < 2.2 × 10^-16), and were at or above 60 years of age (27%, p < 2.2 × 10^-16). More numbers of selective serotonin reuptake inhibitors (SSRIs) (22,085 out of 48,031; 46%), were dispensed than other classes of antidepressants, with escitalopram (26%) at the top of the list. Preponderance of prescription of antidepressants for non-mental health diseases was observed. Population-level prescription trends, as we reported here, when combined with patient genetic variability and outcome data, will have the power to predict the potential for treatment failures and adverse effects of these medications in the population. We also recommend educating non-mental health prescribers about the adherence to evidence and guidelines to ensure patient safety while prescribing antidepressants.

Influence of Pathogenic and Metabolic Genes on the Pharmacogenetics of Mood Disorders in Alzheimer's Disease

Background: Mood disorders represent a risk factor for dementia and are present in over 60% of cases with Alzheimer’s disease (AD). More than 80% variability in drug pharmacokinetics and pharmacodynamics is associated with pharmacogenetics. Methods: Anxiety and depression symptoms were assessed in 1006 patients with dementia (591 females, 415 males) and the influence of pathogenic (APOE) and metabolic (CYP2D6, CYP2C19, and CYP2C9) gene variants on the therapeutic outcome were analyzed after treatment with a multifactorial regime in a natural setting. Results and Conclusions: (i) Biochemical, hematological, and metabolic differences may contribute to changes in drug efficacy and safety; (ii) anxiety and depression are more frequent and severe in females than males; (iii) both females and males respond similarly to treatment, showing significant improvements in anxiety and depression; (iv) APOE-3 carriers are the best responders and APOE-4 carriers tend to be the worst responders to conventional treatments; and (v) among CYP2D6, CYP2C19, and CYP2C9 genophenotypes, normal metabolizers (NMs) and intermediate metabolizers (IMs) are significantly better responders than poor metabolizers (PMs) and ultra-rapid metabolizers (UMs) to therapeutic interventions that modify anxiety and depression phenotypes in dementia. APOE-4 carriers and CYP-related PMs and UMs deserve special attention for their vulnerability and poor response to current treatments.

Pharmacogenetic considerations when prescribing cholinesterase inhibitors for the treatment of Alzheimer's disease

INTRODUCTION

Cholinergic dysfunction, demonstrated in the late 1970s and early 1980s, led to the introduction of acetylcholinesterase inhibitors (AChEIs) in 1993 (Tacrine) to enhance cholinergic neurotransmission as the first line of treatment against Alzheimer's disease (AD). The new generation of AChEIs, represented by Donepezil (1996), Galantamine (2001) and Rivastigmine (2002), is the only treatment for AD to date, together with Memantine (2003). AChEIs are not devoid of side-effects and their cost-effectiveness is limited. An option to optimize the correct use of AChEIs is the implementation of pharmacogenetics (PGx) in the clinical practice.

AREAS COVERED

(i) The cholinergic system in AD, (ii) principles of AD PGx, (iii) PGx of Donepezil, Galantamine, Rivastigmine, Huperzine and other treatments, and (iv) practical recommendations.

EXPERT OPINION

The most relevant genes influencing AChEI efficacy and safety are APOE and CYPs. APOE-4 carriers are the worst responders to AChEIs. With the exception of Rivastigmine (UGT2B7, BCHE-K), the other AChEIs are primarily metabolized via CYP2D6, CYP3A4, and UGT enzymes, with involvement of ABC transporters and cholinergic genes (CHAT, ACHE, BCHE, SLC5A7, SLC18A3, CHRNA7) in most ethnic groups. Defective variants may affect the clinical response to AChEIs. PGx geno-phenotyping is highly recommended prior to treatment.

Pharmacogenomics of Cognitive Dysfunction and Neuropsychiatric Disorders in Dementia

Symptomatic interventions for patients with dementia involve anti-dementia drugs to improve cognition, psychotropic drugs for the treatment of behavioral disorders (BDs), and different categories of drugs for concomitant disorders. Demented patients may take >6–10 drugs/day with the consequent risk for drug–drug interactions and adverse drug reactions (ADRs >80%) which accelerate cognitive decline. The pharmacoepigenetic machinery is integrated by pathogenic, mechanistic, metabolic, transporter, and pleiotropic genes redundantly and promiscuously regulated by epigenetic mechanisms. CYP2D6, CYP2C9, CYP2C19, and CYP3A4/5 geno-phenotypes are involved in the metabolism of over 90% of drugs currently used in patients with dementia, and only 20% of the population is an extensive metabolizer for this tetragenic cluster. ADRs associated with anti-dementia drugs, antipsychotics, antidepressants, anxiolytics, hypnotics, sedatives, and antiepileptic drugs can be minimized by means of pharmacogenetic screening prior to treatment. These drugs are substrates, inhibitors, or inducers of 58, 37, and 42 enzyme/protein gene products, respectively, and are transported by 40 different protein transporters. APOE is the reference gene in most pharmacogenetic studies. APOE-3 carriers are the best responders and APOE-4 carriers are the worst responders; likewise, CYP2D6-normal metabolizers are the best responders and CYP2D6-poor metabolizers are the worst responders. The incorporation of pharmacogenomic strategies for a personalized treatment in dementia is an effective option to optimize limited therapeutic resources and to reduce unwanted side-effects.

Targeted metabolomic analysis of nitric oxide/L-arginine pathway metabolites in dementia: association with pathology, severity, and structural brain changes

L-Arginine/NO pathway is altered in Alzheimer disease (AD). Its clinical relevance and pathway status in vascular dementia (VaD) are unknown. Using targeted metabolomics (a liquid chromatography-mass spectrometry) we assessed L-arginine, L-citrulline, dimethylamine (DMA), asymmetric dimethyl arginine (ADMA) and symmetric dimethylarginine (SDMA) in AD (n = 48), mixed-type dementia (MD; n = 34), VaD (n = 40) and non-demented individuals (n = 140) and determined their clinical relevance (the association with dementia pathology, cognitive impairment, and structural brain damage). L-Arginine, ADMA, L-arginine/ADMA, and L-citrulline levels were decreased in dementia and L-arginine, L-citrulline, age and sex were its independent predictors correctly classifying 91% of cases. L-Arginine and L-arginine/ADMA were differentiating between VaD and AD with moderate accuracy. L-Arginine, L-arginine/ADMA, SDMA, and DMA reflected structural brain changes. DMA and L-citrulline were elevated in patients with strategic infarcts and SDMA, L-arginine/ADMA, and DMA were independent predictors of Hachinski ischemic score. ADMA and SDMA accumulation reflected severity of cognitive impairment. In summary, L-Arginine/NO pathway is altered in neurodegenerative and vascular dementia in association with neurodegenerative and vascular markers of brain damage and severity of cognitive impairment.