Clinical association between pharmacogenomics and adverse drug reactions

Effect of pharmacogenomic testing on the clinical treatment of patients with depressive disorder: A randomized clinical trial

BACKGROUND

Pharmacotherapy is one of the primary treatment modalities for depression. However, there is considerable variability in the individual response to antidepressant medications. Personalized medicine guided by pharmacogenomic testing may hold promise in addressing this issue.

METHODS

In this study, 665 depressive patients were randomly enrolled into two groups: the pharmacogenomic testing group (n = 333) and the control group (n = 332). In the testing group, participants underwent pharmacogenomic testing, and clinicians customized the treatment plan with the result, while the control group relied solely on clinicians' experience. The primary outcomes were the proportion of remission and response, assessed with Hamilton Depression Rating Scale (HDRS). The secondary outcomes included changes in HDRS scores over time and frequency of adverse drug reactions by the participants.

RESULTS

At week 8, the pharmacogenomic testing group showed significantly higher remission rates (24.0 % v.s. 15.1 %; RR = 1.117; P = 0.007) and response rates (39.3 % v.s. 25.7 %; RR = 1.225; P < 0.001) compared to the control group. By week 12, the pharmacogenomic testing group continued to demonstrate significant advantages in remission (31.0 % v.s. 20.0 %; RR = 1.159; P = 0.003) and response (48.7 % v.s. 37.3 %; RR = 1.224; P = 0.006). Additionally, adverse drug reactions were less frequent in the pharmacogenomic testing group.

LIMITATIONS

This study is not blind to clinicians and it's a single-center study.

CONCLUSIONS

Pharmacogenomic testing-guided drug therapy can provide greater assistance in the treatment of depression.

Targeted next-generation sequencing panel to investigate antiplatelet adverse reactions in acute coronary syndrome patients undergoing percutaneous coronary intervention with stenting

Antiplatelet therapy, the gold standard of care for patients with acute coronary syndrome (ACS) undergoing percutaneous coronary intervention (PCI), is one of the therapeutic approaches most associated with the development of adverse drug reactions (ADRs). Although numerous studies have shown that pharmacological intervention based on a limited number of high-evidence variants (primarily CYP2C19*2 and *3) can reduce the incidence of major adverse cardiovascular events (MACEs), ADRs still occur at variable rates (10.1 % in our case) despite personalized therapy. This study aimed to identify novel genetic variants associated with the endpoint of MACEs 12 months after PCI by designing and analyzing a targeted gene panel. We sequenced 244 ACS-PCI-stent patients (109 with event and 135 without event) and 99 controls without structural cardiovascular disease and performed an association analysis to search for unexpected genetic variants. No single nucleotide polymorphisms reached genomic significance after correction, but three novel variants, including ABCA1 (rs2472434), KLB (rs17618244), and ZNF335 (rs3827066), may play a role in MACEs in ACS patients. These genetic variants are involved in regulating high-density lipoprotein levels and cholesterol deposition, and as they are regulatory variants, they may affect the expression of nearby lipid metabolism-related genes. Our findings suggest new targets (both at the gene and pathway levels) that may increase susceptibility to MACEs, but further research is needed to clarify the role and impact of the identified variants before these findings can be incorporated into the therapeutic decision-making process.

Genetic diversity of variants involved in drug response among Tunisian and Italian populations toward personalized medicine

Adverse drug reactions (ADR) represent a significant contributor to morbidity and mortality, imposing a substantial financial burden. Genetic ancestry plays a crucial role in drug response. The aim of this study is to characterize the genetic variability of selected pharmacogenes involved with ADR in Tunisians and Italians, with a comparative analysis against global populations. A cohort of 135 healthy Tunisians and 737 Italians were genotyped using a SNP array. Variants located in 25 Very Important Pharmacogenes implicated in ADR were extracted from the genotyping data. Distribution analysis of common variants in Tunisian and Italian populations in comparison to 24 publicly available worldwide populations was performed using PLINK and R software. Results from Principle Component and ADMIXTURE analyses showed a high genetic similarity among Mediterranean populations, distinguishing them from Sub-Saharan African and Asian populations. The Fst comparative analysis identified 27 variants exhibiting significant differentiation between the studied populations. Among these variants, four SNPs rs622342, rs3846662, rs7294, rs5215 located in SLC22A1, HMGCR, VKORC1 and KCNJ11 genes respectively, are reported to be associated with ethnic variability in drug responses. In conclusion, correlating the frequencies of genotype risk variants with their associated ADRs would enhance drug outcomes and the implementation of personalized medicine in the studied populations.

Transfer learning enhanced graph neural network for aldehyde oxidase metabolism prediction and its experimental application

Aldehyde oxidase (AOX) is a molybdoenzyme that is primarily expressed in the liver and is involved in the metabolism of drugs and other xenobiotics. AOX-mediated metabolism can result in unexpected outcomes, such as the production of toxic metabolites and high metabolic clearance, which can lead to the clinical failure of novel therapeutic agents. Computational models can assist medicinal chemists in rapidly evaluating the AOX metabolic risk of compounds during the early phases of drug discovery and provide valuable clues for manipulating AOX-mediated metabolism liability. In this study, we developed a novel graph neural network called AOMP for predicting AOX-mediated metabolism. AOMP integrated the tasks of metabolic substrate/non-substrate classification and metabolic site prediction, while utilizing transfer learning from 13C nuclear magnetic resonance data to enhance its performance on both tasks. AOMP significantly outperformed the benchmark methods in both cross-validation and external testing. Using AOMP, we systematically assessed the AOX-mediated metabolism of common fragments in kinase inhibitors and successfully identified four new scaffolds with AOX metabolism liability, which were validated through in vitro experiments. Furthermore, for the convenience of the community, we established the first online service for AOX metabolism prediction based on AOMP, which is freely available at https://aomp.alphama.com.cn.

Longitudinal Influence of Prescribed Antidepressants on Fecal and Oral Microbiomes Among Veterans With Major Depressive Disorder

OBJECTIVE

The purpose of this study was to evaluate the influence of a new course of antidepressant monotherapy on gut and oral microbiomes and the relationship to depressive symptoms.

METHODS

Longitudinal microbiome samples obtained from 10 U.S. veterans were analyzed. Baseline samples were taken before a new course of antidepressant monotherapy (either switching from a previous treatment or starting a new treatment). Targeted genomic sequencing of the microbiome samples was used to analyze changes in taxonomy and diversity across participants, medications, and medication class. Associations between these changes and Patient Health Questionnaire-9 (PHQ-9) scores were analyzed.

RESULTS

Taxonomic variability was observed across participants, with the individual being the main microbial community driver. In terms of the fecal microbiome, antidepressants were associated with shifts toward Bacteroides being less abundant and Blautia, Pseudomonas, or Faecalibacterium being more abundant. Likewise, the composition of the oral microbiome was variable, with individual participants being the primary drivers of community composition. In the oral samples, the relative abundance of Haemophilus decreased after antidepressants were started. Increases in Blautia and decreases in Bacteroides were associated with lower PHQ-9 scores.

CONCLUSIONS

Antidepressants were found to influence fecal and oral microbiomes such that a new course of antidepressant monotherapy was associated with taxonomic alterations toward healthier states in both fecal and oral microbiomes, which were associated with decreases in depressive symptoms. Additional longitudinal research is required to increase understanding of microbiomes and symptom-based changes, with a particular focus on potential differences between medication classes and underlying mechanisms.

The relationship between sensory processing sensitivity and medication sensitivity: brief report

Sensory processing sensitivity (SPS) is a biological/temperament trait that is associated with greater awareness of and reactivity to the environment, which results in amplified responses to various stimuli, and possibly medications. We investigated the relationship between SPS and medication sensitivity in three studies. Participants (ages 18-81) were recruited from university (Study 1: N = 125; Study 2: N = 214) and online (Study 3: N = 351) samples. In each study, participants completed a medication sensitivity scale, the standard highly sensitive person (HSP) scale to assess SPS, and a negative affectivity (NA) scale as a control variable. All three studies found moderate, significant correlations between SPS and medication sensitivity (r = 0.34, p < 0.001: r = 0.21, p = 0.003; r = 0.36, p < 0.001, respectively). Correlations remained significant, and similar, when controlling for NA and gender; and there were no significant interactions with gender. In sum, our results suggest that SPS is associated with medication sensitivity, even when considering NA and gender. Thus, future work might consider SPS when investigating recommended medication, medication dosage, effectiveness, and adverse drug reactions.

Structure-activity relationships andz interindividual variability of drug responses: pharmacogenomics with antimicrobial drugs as a paradigm

Adverse drug reactions represent a major health burden because they cause notable patient morbidity and mortality. From this viewpoint, several strategies have been developed to prevent or reduce adverse drug reactions. One such strategy is the use of pharmacogenomics. Interindividual variability in drug response and adverse effects is mainly attributable to genetic variation in enzymes such as sulfotransferases and cytochrome P450s. The current narrative review discusses the relationship between the structure and activity of drugs. Specifically, the activity of drugs can be increased and/or their adverse effects can be reduced by altering specific positions in their structures.

Calculation of the pharmacogenomics benefit score for patients with medication-related problems

Unexpected poor efficacy and intolerable adverse effects are medication-related problems that may result from genetic variation in genes encoding key proteins involved in pharmacokinetics or pharmacodynamics. Pharmacogenomic (PGx) testing can be used in medical practice "pre-emptively" to avoid future patient harm from medications and "reactively" to diagnose medication-related problems following their occurrence. A structured approach to PGx consulting is proposed to calculate the pharmacogenomics benefit score (PGxBS), a patient-centered objective measure of congruency between medication-related problems and patient genotypes. An example case of poor efficacy with multiple medications is presented, together with comments on the potential benefits and limitations of using the PGxBS in medical practice.

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.

Pharmacogenomic Profile of Amazonian Amerindians

Given the role of pharmacogenomics in the large variability observed in drug efficacy/safety, an assessment about the pharmacogenomic profile of patients prior to drug prescription or dose adjustment is paramount to improve adherence to treatment and prevent adverse drug reaction events. A population commonly underrepresented in pharmacogenomic studies is the Native American populations, which have a unique genetic profile due to a long process of geographic isolation and other genetic and evolutionary processes. Here, we describe the pharmacogenetic variability of Native American populations regarding 160 pharmacogenes involved in absorption, distribution, metabolism, and excretion processes and biological pathways of different therapies. Data were obtained through complete exome sequencing of individuals from 12 different Amerindian groups of the Brazilian Amazon. The study reports a total of 3311 variants; of this, 167 are exclusive to Amerindian populations, and 1183 are located in coding regions. Among these new variants, we found non-synonymous coding variants in the DPYD and the IFNL4 genes and variants with high allelic frequencies in intronic regions of the MTHFR, TYMS, GSTT1, and CYP2D6 genes. Additionally, 332 variants with either high or moderate (disruptive or non-disruptive impact in protein effectiveness, respectively) significance were found with a minimum of 1% frequency in the Amazonian Amerindian population. The data reported here serve as scientific basis for future design of specific treatment protocols for Amazonian Amerindian populations as well as for populations admixed with them, such as the Northern Brazilian population.

Sub-Analysis of CYP-GUIDES Data: Assessing the Prevalence and Impact of Drug-Gene Interactions in an Ethnically Diverse Cohort of Depressed Individuals

Introduction: Minority groups are underrepresented in pharmacogenomics (PGx) research. Recent sub-analysis of CYP-GUIDES showed reduced length of stay (LOS) in depressed patients with CYP2D6 sub-functional status. Our primary objective was to determine whether PGx guided (G) versus standard treatment (S) influenced LOS among different race/ethnic groups. Secondary objectives included prevalence of drug-gene interactions (DGIs) and readmission rates (RAR).

Methods: Retrospective sub-analysis of CYP-GUIDES data comprising CYP2D6 phenotypes was reclassified using standardized CYP2D6 genotype to phenotype recommendations from the Clinical Pharmacogenetics Implementation Consortium (CPIC) and Dutch Pharmacogenetics Working Group (DPWG). The Mann-Whitney test was used to determine differences in LOS between groups G and S and Kruskal Wallis test to compare LOS among different race/ethnic groups. Logistic regression was used to determine covariates associated with RAR.

Results: This study included 1,459 patients with 67.3% in G group (n = 982). The majority of patients were White (57.5%), followed by Latinos (25.6%) and Blacks (12.3%). Although there were no differences in LOS between G and S groups, Latinos had significant shorter LOS than Whites (p = 0.002). LOS was significantly reduced by 5.6 days in poor metabolizers in group G compared to S (p = 0.002). The proportion of supra functional and ultra-rapid metabolizers (UMs) were 6 and 20.3% using CYP-GUIDES and CPIC/DPWG definitions, respectively. Prevalence of DGIs was 40% with significantly fewer DGIs in Blacks (p < 0.001). Race/ethnicity was significantly associated with RAR (aOR 1.30; p = 0.003).

Conclusion: A greater number of patients were classified as CYP2D6 UMs using CPIC/DPWG definitions as compared to CYP-GUIDES definitions. This finding may have clinical implications for using psychotropics metabolized by CYP2D6.

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-Guided Pharmacotherapy in Patients with Major Depressive Disorder or Bipolar Disorder Affected by Treatment-Resistant Depressive Episodes: A Long-Term Follow-up Study

Treatment-resistant depression (TRD) reduces affected patients’ quality of life and leads to important social health care costs. Pharmacogenomics-guided treatment (PGT) may be effective in the cure of TRD. The main aim of this study was to evaluate the clinical changes after PGT in patients with TRD (two or more recent failed psychopharmacological trials) affected by bipolar disorder (BD) or major depressive disorder (MDD) compared to a control group with treatment as usual (TAU). We based the PGT on assessing different gene polymorphisms involved in the pharmacodynamics and pharmacokinetics of drugs. We analyzed, with a repeated-measure ANOVA, the changes between the baseline and a 6 month follow-up of the efficacy index assessed through the Clinical Global Impression (CGI) scale, and depressive symptoms through the Hamilton Depression Rating Scale (HDRS). The PGT sample included 53 patients (26 BD and 27 MDD), and the TAU group included 52 patients (31 BD and 21 MDD). We found a significant within-subject effect of treatment time on symptoms and efficacy index for the whole sample, with significant improvements in the efficacy index (F = 8.544; partial η² = 0.077, p < 0.004) and clinical global impression of severity of illness (F = 6.818; partial η² = 0.062, p < 0.01) in the PGT vs. the TAU group. We also found a significantly better follow-up response (χ² = 5.479; p = 0.019) and remission (χ² = 10.351; p = 0.001) rates in the PGT vs. the TAU group. PGT may be an important option for the long-term treatment of patients with TRD affected by mood disorders, providing information that can better define drug treatment strategies and increase therapeutic improvement.

Clinical pharmacogenetic analysis in 5,001 individuals with diagnostic Exome Sequencing data

Exome sequencing is utilized in routine clinical genetic diagnosis. The technical robustness of repurposing large-scale next-generation sequencing data for pharmacogenetics has been demonstrated, supporting the implementation of preemptive pharmacogenetic strategies based on adding clinical pharmacogenetic interpretation to exomes. However, a comprehensive study analyzing all actionable pharmacogenetic alleles contained in international guidelines and applied to diagnostic exome data has not been performed. Here, we carried out a systematic analysis based on 5001 Spanish or Latin American individuals with diagnostic exome data, either Whole Exome Sequencing (80%), or the so-called Clinical Exome Sequencing (20%) (60 Mb and 17 Mb, respectively), to provide with global and gene-specific clinical pharmacogenetic utility data. 788 pharmacogenetic alleles, distributed through 19 genes included in Clinical Pharmacogenetics Implementation Consortium guidelines were analyzed. We established that Whole Exome and Clinical Exome Sequencing performed similarly, and 280 alleles in 11 genes (CACNA1S, CYP2B6, CYP2C9, CYP4F2, DPYD, G6PD, NUDT15, RYR1, SLCO1B1, TPMT, and UGT1A1) could be used to inform of pharmacogenetic phenotypes that change drug prescription. Each individual carried in average 2.2 alleles and overall 95% (n = 4646) of the cohort could be informed of at least one actionable pharmacogenetic phenotype. Differences in variant allele frequency were observed among the populations studied and the corresponding gnomAD population for 7.9% of the variants. In addition, in the 11 selected genes we uncovered 197 novel variants, among which 27 were loss-of-function. In conclusion, we provide with the landscape of actionable pharmacogenetic information contained in diagnostic exomes, that can be used preemptively in the clinics.

Ten Years of Experience Support Pharmacogenetic Testing to Guide Individualized Drug Therapy

Precision medicine utilizing the genetic information of genes involved in the metabolism and disposition of drugs can not only improve drug efficacy but also prevent or minimize adverse events. Polypharmacy is common among multimorbid patients and is associated with increased adverse events. One of the main objectives in health care is safe and efficacious drug therapy, which is directly correlated to the individual response to treatment. Precision medicine can increase drug safety in many scenarios, including polypharmacy. In this report, we share our experience utilizing precision medicine over the past ten years. Based on our experience using pharmacogenetic (PGx)-informed prescribing, we implemented a five-step precision medicine protocol (5SPM) that includes the assessment of the biological-clinical characteristics of the patient, current and past prescription history, and the patient's PGx test results. To illustrate our approach, we present cases highlighting the clinical relevance of precision medicine with a focus on patients with a complex history and polypharmacy.

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.

Genetic analysis of pharmacogenomic VIP variants in the Wa population from Yunnan Province of China

Background

The variation of drug responses and target does among individuals is mostly determined by genes. With the development of pharmacogenetics and pharmacogenomics, the differences in drug response between different races seem to be mainly caused by the genetic diversity of pharmacodynamics and pharmacokinetics genes. Very important pharmacogenetic (VIP) variants mean that genes or variants play important and vital roles in drug response, which have been listed in pharmacogenomics databases, such as Pharmacogenomics Knowledge Base (PharmGKB). The information of Chinese ethnic minorities such as the Wa ethnic group is scarce. This study aimed to uncover the significantly different loci in the Wa population in Yunnan Province of China from the perspective of pharmacogenomics, to provide a theoretical basis for the future medication guidance, and to ultimately achieve the best treatment in the future.

Results

In this study, we recruited 200 unrelated healthy Wa adults from the Yunnan province of China, selected 52 VIP variants from the PharmGKB for genotyping. We also compared the genotype frequency and allele distribution of VIP variants between Wa population and the other 26 populations from the 1000 Genomes Project (http://www.1000Genomes.org/). Next, χ² test was used to determine the significant points between these populations. The study results showed that compared with the other 26 population groups, five variants rs776746 (CYP3A5), rs4291 (ACE), rs3093105 (CYP4F2), rs1051298 (SLC19A1), and rs1065852 (CYP2D6) had higher frequencies in the Wa population. The genotype frequencies rs4291-TA, rs3093105-CA, rs1051298-AG and rs1065852-GA were higher than those of the other populations, and the allele distributions of rs4291-T and rs3093105-C were significantly different. Additionally, the difference between the Wa ethnic group and East Asian populations, such as CDX, CHB, and CHS, was the smallest.

Conclusions

Our research results show that there is a significant difference in the distribution of VIP variants between the Wa ethnic group and the other 26 populations. The study results will have an effect on supplementing the pharmacogenomics information for the Wa population and providing a theoretical basis for individualised medication for the Wa population.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-021-00999-8.

A novel machine learning-based approach for the computational functional assessment of pharmacogenomic variants

BACKGROUND

The field of pharmacogenomics focuses on the way a person's genome affects his or her response to a certain dose of a specified medication. The main aim is to utilize this information to guide and personalize the treatment in a way that maximizes the clinical benefits and minimizes the risks for the patients, thus fulfilling the promises of personalized medicine. Technological advances in genome sequencing, combined with the development of improved computational methods for the efficient analysis of the huge amount of generated data, have allowed the fast and inexpensive sequencing of a patient's genome, hence rendering its incorporation into clinical routine practice a realistic possibility.

METHODS

This study exploited thoroughly characterized in functional level SNVs within genes involved in drug metabolism and transport, to train a classifier that would categorize novel variants according to their expected effect on protein functionality. This categorization is based on the available in silico prediction and/or conservation scores, which are selected with the use of recursive feature elimination process. Toward this end, information regarding 190 pharmacovariants was leveraged, alongside with 4 machine learning algorithms, namely AdaBoost, XGBoost, multinomial logistic regression, and random forest, of which the performance was assessed through 5-fold cross validation.

RESULTS

All models achieved similar performance toward making informed conclusions, with RF model achieving the highest accuracy (85%, 95% CI: 0.79, 0.90), as well as improved overall performance (precision 85%, sensitivity 84%, specificity 94%) and being used for subsequent analyses. When applied on real world WGS data, the selected RF model identified 2 missense variants, expected to lead to decreased function proteins and 1 to increased. As expected, a greater number of variants were highlighted when the approach was used on NGS data derived from targeted resequencing of coding regions. Specifically, 71 variants (out of 156 with sufficient annotation information) were classified as to "Decreased function," 41 variants as "No" function proteins, and 1 variant in "Increased function."

CONCLUSION

Overall, the proposed RF-based classification model holds promise to lead to an extremely useful variant prioritization and act as a scoring tool with interesting clinical applications in the fields of pharmacogenomics and personalized medicine.

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.

PharmVar GeneFocus: CYP2C19

The Pharmacogene Variation Consortium (PharmVar) catalogues star (*) allele nomenclature for the polymorphic human CYP2C19 gene. CYP2C19 genetic variation impacts the metabolism of many drugs and has been associated with both efficacy and safety issues for several commonly prescribed medications. This GeneFocus provides a comprehensive overview and summary of CYP2C19 and describes how haplotype information catalogued by PharmVar is utilized by the Pharmacogenomics Knowledgebase and the Clinical Pharmacogenetics Implementation Consortium (CPIC).

The Impact of Cannabidiol on Psychiatric and Medical Conditions

Cannabidiol (CBD) is a substance chemically derived from Cannabis sativa and discussed to be non-psychoactive. According to the FDA, marijuana is classified as a schedule I substance; however, hemp which is defined as extracts from marijuana including cannabinoids containing less than 0.3% tetrahydrocannabinol (THC), is excluded from that controlled substance act and available at local convenience stores in the US as it is seen as an herbal supplement. CBD is purported to be used for various medical and psychiatric conditions: depression, anxiety, post-traumatic stress disorder, Alzheimer's or other cognitive illnesses as well as pain. There is also a new trend to use CBD for the treatment of opioid use disorder. The one CBD product on the market that is FDA approved for the treatment of childhood epilepsy forms Dravet and Lennox-Gastaut syndromes is available under the name Epidiolex. There is a significant difference between this medication and the over-the-counter CBD products that contain very inconsistent strengths of CBD, if they contain it at all, and vary in percentage even from sample to sample. Frequently the so-called CBD products are not containing any CBD at all, but mostly containing THC. This article is a systematic review of literature reviewing the available clinical data on CBD, for use in various medical and psychiatric conditions with focus on a review of the pharmacology and toxicity. Resources used were ORVID, PubMed, MEDLINE, PsychINFO, EMBASE with keywords CBD, cannabidiol, hemp and cannabinoids.

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.

[Perspectives of the use of pharmacogenetic tests in neurology and psychiatry]

The review is devoted to the analysis of the current state of pharmacogenetic research and their use in psychiatric practice. The main genes responsible for the pharmacodynamics and pharmacokinetics of drugs used in psychiatry are listed. Foreign pharmacogenetic clinical recommendations and progress on their implementation in medical practice in various countries of Europe and the USA are analyzed. The need to create Russian clinical guidelines on pharmacogenomics to improve the effectiveness of patient care and to implement a personalized approach to therapy is discussed.

PharmVar GeneFocus: CYP2D6

The Pharmacogene Variation Consortium (PharmVar) provides nomenclature for the highly polymorphic human CYP2D6 gene locus. CYP2D6 genetic variation impacts the metabolism of numerous drugs and, thus, can impact drug efficacy and safety. This GeneFocus provides a comprehensive overview and summary of CYP2D6 genetic variation and describes how the information provided by PharmVar is utilized by the Pharmacogenomics Knowledgebase (PharmGKB) and the Clinical Pharmacogenetics Implementation Consortium (CPIC).

Genetic associations of docetaxel-based chemotherapy-induced myelosuppression in Chinese Han population

WHAT IS KNOWN AND OBJECTIVE

Myelosuppression, an adverse drug reaction (ADR), often causes medical treatment termination in cancer patients. It has been known that genetic components, such as single-nucleotide polymorphisms (SNPs), influence the risk of myelosuppression at the individual-patient level. However, due to ethnic variation in frequency of genetic polymorphisms, results reported in Caucasian patients may not be generalizable to the Chinese Han population. Until now, few researches on myelosuppression included Chinese Han patients. In this study, we conducted a systematic study of potential biomarkers for docetaxel-induced myelosuppression in Han Chinese patients.

METHODS

We examined 61 SNPs in 36 genes that code for drug transporters, metabolism enzymes, nuclear receptors and DNA repair pathway in 110 Chinese Han patients receiving docetaxel-based chemotherapy. Genotyping was conducted using the Sequenom MassARRAY system. Significant SNPs were identified by logistic regression, and gene-gene interactions were investigated by generalized multifactor dimensionality reduction (GMDR) analysis.

RESULTS AND DISCUSSION

Our results revealed that 11 SNPs in nine genes (SLC15A1, SLCO1A2, CYP2D6, FMO3, UGT1A1, NAT2, SULT2A1, PXR and HNF4α) were associated with docetaxel-induced myelosuppression. GMDR analyses suggested that a 3-locus model: SLC15A1 rs2297322-PXR rs3732359-FMO3 rs2266782 was an appropriate predictive model of docetaxel-induced myelosuppression (P = .017, Testing Bal.Acc = 0.653, CV Consistency = 10/10).

WHAT IS NEW AND CONCLUSION

Our findings suggest multiple novel predictive biomarkers of docetaxel-induced myelosuppression: SLC15A1 rs2297322, PXR rs3732359 and FMO3 rs2266782. These discoveries should help in advancing future personalized therapy of docetaxel-based chemotherapy specific to Chinese Han patients.

Potential Adverse Drug Events and Drug-Drug Interactions with Medical and Consumer Cannabidiol (CBD) Use

Cannabidiol (CBD) is ubiquitous in state-based medical cannabis programs and consumer products for complementary health or recreational use. CBD has intrinsic pharmacologic effects and associated adverse drug events (ADEs) along with the potential for pharmacokinetic and pharmacodynamic drug–drug interactions (DDIs). Given CBD use among patients with complex conditions and treatment regimens, as well as its expanded consumer use, awareness of potential safety issues with CBD is needed. Prescribing information for federally approved products containing CBD were reviewed. Data on ADEs and DDIs were extracted and summarized. Nearly one-half of CBD users experienced ADEs, which displayed a general dose-response relationship. Common ADEs include transaminase elevations, sedation, sleep disturbances, infection, and anemia. Given CBD effects on common biological targets implicated in drug metabolism (e.g., CYP3A4/2C19) and excretion (e.g., P-glycoprotein), the potential for DDIs with commonly used medication is high. General clinical recommendations of reducing substrate doses, monitoring for ADEs, and finding alternative therapy should be considered, especially in medically complex patients. CBD is implicated as both a victim and perpetrator of DDIs and has its own ADE profile. These effects should be considered in the risk-benefit assessment of CBD therapy and patients and consumers made aware of potential safety issues with CBD use.

Impact of pharmacogenomics on clinical outcomes in major depressive disorder in the GUIDED trial: A large, patient- and rater-blinded, randomized, controlled study

Current prescribing practices for major depressive disorder (MDD) produce limited treatment success. Although pharmacogenomics may improve outcomes by identifying genetically inappropriate medications, studies to date were limited in scope. Outpatients (N = 1167) diagnosed with MDD and with a patient- or clinician-reported inadequate response to at least one antidepressant were enrolled in the Genomics Used to Improve DEpression Decisions (GUIDED) trial - a rater- and patient-blind randomized controlled trial. Patients were randomized to treatment as usual (TAU) or a pharmacogenomics-guided intervention arm in which clinicians had access to a pharmacogenomic test report to inform medication selections (guided-care). Medications were considered congruent ('use as directed' or 'use with caution' test categories) or incongruent ('use with increased caution and with more frequent monitoring' test category) with test results. Unblinding occurred after week 8. Primary outcome was symptom improvement [change in 17-item Hamilton Depression Rating Scale (HAM-D17)] at week 8; secondary outcomes were response (≥50% decrease in HAM-D17) and remission (HAM-D17 ≤ 7) at week 8. At week 8, symptom improvement for guided-care was not significantly different than TAU (27.2% versus 24.4%, p = 0.107); however, improvements in response (26.0% versus 19.9%, p = 0.013) and remission (15.3% versus 10.1%, p = 0.007) were statistically significant. Patients taking incongruent medications prior to baseline who switched to congruent medications by week 8 experienced greater symptom improvement (33.5% versus 21.1%, p = 0.002), response (28.5% versus 16.7%, p = 0.036), and remission (21.5% versus 8.5%, p = 0.007) compared to those remaining incongruent. Pharmacogenomic testing did not significantly improve mean symptoms but did significantly improve response and remission rates for difficult-to-treat depression patients over standard of care (ClinicalTrials.gov NCT02109939).

Analytical validation of a psychiatric pharmacogenomic test

Aim: The aim of this study was to validate the analytical performance of a combinatorial pharmacogenomics test designed to aid in the appropriate medication selection for neuropsychiatric conditions. Materials & methods: Genomic DNA was isolated from buccal swabs. Twelve genes (65 variants/alleles) associated with psychotropic medication metabolism, side effects, and mechanisms of actions were evaluated by bead array, MALDI-TOF mass spectrometry, and/or capillary electrophoresis methods (GeneSight Psychotropic, Assurex Health, Inc.). Results: The combinatorial pharmacogenomics test has a dynamic range of 2.5–20 ng/μl of input genomic DNA, with comparable performance for all assays included in the test. Both the precision and accuracy of the test were >99.9%, with individual gene components between 99.4 and 100%. Conclusion: This study demonstrates that the combinatorial pharmacogenomics test is robust and reproducible, making it suitable for clinical use.

Estimating cost savings of pharmacogenetic testing for depression in real-world clinical settings

The burden of depression significantly impacts the patient, the health care system, and society, at large. Medication management guided by pharmacogenetics has been shown to increase therapeutic efficacy and improve symptoms in patients diagnosed with depression, but limited data are available on the cost savings of pharmacogenetic-guided interventions outside of psychiatric clinical specialties. Our study utilizes published health care costs and clinical patient outcome data to model the economic impact of pharmacogenetic-guided treatment for depression in a variety of clinical settings. Assuming a test cost of USD$2,000 for pharmacogenetic testing, the model predicts a savings of USD$3,962 annually per patient with pharmacogenetic-guided medication management.

Genome sequencing as a platform for pharmacogenetic genotyping: a pediatric cohort study

Whole-genome sequencing and whole-exome sequencing have proven valuable for diagnosing inherited diseases, particularly in children. However, usage of sequencing data as a pharmacogenetic screening tool to ensure medication safety and effectiveness remains to be explored. Sixty-seven variants in 19 genes with known effects on drug response were compared between genome sequencing and targeted genotyping data for coverage and concordance in 98 pediatric patients. We used targeted genotyping data as a benchmark to assess accuracy of variant calling, and to identify copy number variations of the CYP2D6 gene. We then predicted clinical impact of these variants on drug therapy. We find genotype concordance across those panels to be > 97%. Concordance of CYP2D6 predicted phenotype between estimates of whole-genome sequencing and targeted genotyping panel were 90%; a result from a lower coverage depth or variant calling difficulties in our whole-genome sequencing data when copy number variation and/or the CYP2D6*4 haplotype were present. Importantly, 95 children had at least one clinically actionable pharmacogenetic variant. Diagnostic genomic sequencing data can be used for pre-emptive pharmacogenetic screening. However, concordance between genome-wide sequencing and target genotyping needs to be characterized for each of the pharmacologically important genes.

Genome sequencing, in addition to helping diagnose disease, can inform medication decisions and improve drug safety for children. Ronald Cohn, Shinya Ito and colleagues at the Hospital for Sick Children in Toronto, Canada, studied a cohort of 98 pediatric patients who had undergone whole genome sequencing to help diagnose their unexplained congenital malformations or neurodevelopmental disorders. The researchers looked for 67 DNA variants found in 19 genes with known effects on drug responses. They used targeted genotyping to assess the accuracy of the sequence data. Sequencing proved to be more than 99% accurate for all but one of the pharmacologically important genes, showing the power of diagnostic genomic sequencing to identify DNA variants in children that affect medication safety and effectiveness. However, the accuracy of the method may need to be validated for each relevant gene.

Role of Pharmacogenetics in Improving the Safety of Psychiatric Care by Predicting the Potential Risks of Mania in CYP2D6 Poor Metabolizers Diagnosed With Bipolar Disorder

One of the main concerns in psychiatric care is safety related to drug management. Pharmacogenetics provides an important tool to assess causes that may have contributed the adverse events during psychiatric therapy. This study illustrates the potential of pharmacogenetics to identify those patients for which pharmacogenetic-guided therapy could be appropriate. It aimed to investigate CYP2D6 genotype in our psychiatric population to assess the value of introducing pharmacogenetics as a primary improvement for predicting side effects.A broad series of 224 psychiatric patients comprising psychotic disorders, depressive disturbances, bipolar disorders, and anxiety disorders was included. The patients were genotyped with the AmpliChip CYP450 Test to analyzing 33 allelic variants of the CYP2D6 gene.All bipolar patients with poor metabolizer status showed maniac switching when CYP2D6 substrates such as selective serotonin reuptake inhibitors were prescribed. No specific patterns were identified for adverse events for other disorders.We propose to utilize pharmacogenetic testing as an intervention to aid in the identification of patients who are at risk of developing affective switching in bipolar disorder treated with selective serotonin reuptake inhibitors, CYP2D6 substrates, and inhibitors.

Constellation: a tool for rapid, automated phenotype assignment of a highly polymorphic pharmacogene, CYP2D6, from whole-genome sequences

An important component of precision medicine-the use of whole-genome sequencing (WGS) to guide lifelong healthcare-is electronic decision support to inform drug choice and dosing. To achieve this, automated identification of genetic variation in genes involved in drug absorption, distribution, metabolism, excretion and response (ADMER) is required. CYP2D6 is a major enzyme for drug bioactivation and elimination. CYP2D6 activity is predominantly governed by genetic variation; however, it is technically arduous to haplotype. Not only is the nucleotide sequence of CYP2D6 highly polymorphic, but the locus also features diverse structural variations, including gene deletion, duplication, multiplication events and rearrangements with the nonfunctional, neighbouring CYP2D7 and CYP2D8 genes. We developed Constellation, a probabilistic scoring system, enabling automated ascertainment of CYP2D6 activity scores from 2×100 paired-end WGS. The consensus reference method included TaqMan genotyping assays, quantitative copy-number variation determination and Sanger sequencing. When compared with the consensus reference Constellation had an analytic sensitivity of 97% (59 of 61 diplotypes) and analytic specificity of 95% (116 of 122 haplotypes). All extreme phenotypes, i.e., poor and ultrarapid metabolisers were accurately identified by Constellation. Constellation is anticipated to be extensible to functional variation in all ADMER genes, and to be performed at marginal incremental financial and computational costs in the setting of diagnostic WGS.

CYP2D7 Sequence Variation Interferes with TaqMan CYP2D6 (*) 15 and (*) 35 Genotyping

TaqMan™ genotyping assays are widely used to genotype CYP2D6, which encodes a major drug metabolizing enzyme. Assay design for CYP2D6 can be challenging owing to the presence of two pseudogenes, CYP2D7 and CYP2D8, structural and copy number variation and numerous single nucleotide polymorphisms (SNPs) some of which reflect the wild-type sequence of the CYP2D7 pseudogene. The aim of this study was to identify the mechanism causing false-positive CYP2D6^*15 calls and remediate those by redesigning and validating alternative TaqMan genotype assays. Among 13,866 DNA samples genotyped by the CompanionDx® lab on the OpenArray platform, 70 samples were identified as heterozygotes for 137Tins, the key SNP of CYP2D6^*15. However, only 15 samples were confirmed when tested with the Luminex xTAG CYP2D6 Kit and sequencing of CYP2D6-specific long range (XL)-PCR products. Genotype and gene resequencing of CYP2D6 and CYP2D7-specific XL-PCR products revealed a CC>GT dinucleotide SNP in exon 1 of CYP2D7 that reverts the sequence to CYP2D6 and allows a TaqMan assay PCR primer to bind. Because CYP2D7 also carries a Tins, a false-positive mutation signal is generated. This CYP2D7 SNP was also responsible for generating false-positive signals for rs769258 (CYP2D6^*35) which is also located in exon 1. Although alternative CYP2D6^*15 and ^*35 assays resolved the issue, we discovered a novel CYP2D6^*15 subvariant in one sample that carries additional SNPs preventing detection with the alternate assay. The frequency of CYP2D6^*15 was 0.1% in this ethnically diverse U.S. population sample. In addition, we also discovered linkage between the CYP2D7 CC>GT dinucleotide SNP and the 77G>A (rs28371696) SNP of CYP2D6^*43. The frequency of this tentatively functional allele was 0.2%. Taken together, these findings emphasize that regardless of how careful genotyping assays are designed and evaluated before being commercially marketed, rare or unknown SNPs underneath primer and/or probe regions can impact the performance of PCR-based genotype assays, including TaqMan. Regardless of the test platform used, it is prudent to confirm rare allele calls by an independent method.