Pharmacogenomic Variants and Drug Interactions Identified Through the Genetic Analysis of Clozapine Metabolism

Semi-physiological Pharmacokinetic Model of Clozapine and Norclozapine in Healthy, Non-smoking Volunteers: The Impact of Race and Genetics

BACKGROUND AND OBJECTIVES: Clozapine is the medication of choice for treatment-resistant schizophrenia. However, it has a complex metabolism and unexplained interindividual variability. The current work aims to develop a pharmacokinetic model of clozapine and norclozapine in non-smokers and assess the impact of demographic and genetic predictors.

METHODS

Healthy volunteers were recruited in a population pharmacokinetic study. Blood samples were collected at 30 min and 1, 2, 3, 5 and 8 h following a single flat dose of clozapine (12.5 mg). The clozapine and norclozapine concentrations were measured via high-performance liquid chromatography-ultraviolet method. A semi-physiological pharmacokinetic model of clozapine and norclozapine was developed using nonlinear mixed-effects modeling. Clinical and genetic predictors were evaluated, including CYP1A2 (rs762551) and ABCB1 (rs2032582), using restriction fragment length polymorphism.

RESULTS

A total of 270 samples were collected from 33 participants. The data were best described using a two-compartment model for clozapine and a two-compartment model for norclozapine with first-order absorption and elimination and pre-systemic metabolism. The estimated (relative standard error) clearance of clozapine and norclozapine were 27 L h-1 (31.5 %) and 19.6 L h-1 (30%), respectively. Clozapine clearance was lower in sub-Saharan Africans (n = 4) and higher in Caucasians (n = 9) than Asians (n = 20). Participants with CYP1A2 (rs762551) (n = 18) and ABCB1 (rs2032582) (n = 12) mutant alleles had lower clozapine clearance in the univariate analysis.

CONCLUSIONS

This is the first study to develop a semi-physiological pharmacokinetic model of clozapine and norclozapine accounting for the pre-systemic metabolism. Asians required lower doses of clozapine as compared with Caucasians, while clozapine pharmacokinetics in sub-Saharan Africans should be further investigated in larger trials.

Optimisation of pharmacotherapy in psychiatry through therapeutic drug monitoring, molecular brain imaging and pharmacogenetic tests: focus on antipsychotics

BACKGROUND

For psychotic disorders (i.e. schizophrenia), pharmacotherapy plays a key role in controlling acute and long-term symptoms. To find the optimal individual dose and dosage strategy, specialized tools are used. Three tools have been proven useful to personalize drug treatments: therapeutic drug monitoring (TDM) of drug levels, pharmacogenetic testing (PG), and molecular neuroimaging.

METHODS

In these Guidelines, we provide an in-depth review of pharmacokinetics, pharmacodynamics, and pharmacogenetics for 50 antipsychotics. Over 30 international experts in psychiatry selected studies that have measured drug concentrations in the blood (TDM), gene polymorphisms of enzymes involved in drug metabolism, or receptor/transporter occupancies in the brain (positron emission tomography (PET)).

RESULTS

Study results strongly support the use of TDM and the cytochrome P450 (CYP) genotyping and/or phenotyping to guide drug therapies. Evidence-based target ranges are available for titrating drug doses that are often supported by PET findings.

CONCLUSION

All three tools discussed in these Guidelines are essential for drug treatment. TDM goes well beyond typical indications such as unclear compliance and polypharmacy. Despite its enormous potential to optimize treatment effects, minimize side effects and ultimately reduce the global burden of diseases, personalized drug treatment has not yet become the standard of care in psychiatry.

A Genome-Wide Association Study of Oxypurinol Concentrations in Patients Treated with Allopurinol

Cohort studies have identified several genetic determinants that could predict the clinical response to allopurinol. However, they have not been commonly used for genome-wide investigations to identify genetic determinants on allopurinol metabolism and concentrations. We conducted a genome-wide association study of a prior cross-sectional investigation of patients from the Montreal Heart Institute Biobank undergoing allopurinol therapy. Four endpoints were investigated, namely plasma concentrations of oxypurinol, the active metabolite of allopurinol, allopurinol, and allopurinol-riboside, as well as allopurinol daily dosing. A total of 439 participants (mean age 69.4 years; 86.4% male) taking allopurinol (mean daily dose 194.5 mg) and who had quantifiable oxypurinol concentrations were included in the genome-wide analyses. Participants presented with multiple comorbidities and received concomitant cardiovascular medications. No association achieved the predefined genome-wide threshold values for any of the endpoints (all p > 5 × 10-8). Our results are consistent with prior findings regarding the difficulty in identifying genetic determinants of drug concentrations or pharmacokinetics of allopurinol and its metabolites, as well as allopurinol daily dosing. Given the size of this genome-wide study, collaborative investigations involving larger and diverse cohorts may be required to further identify pharmacogenomic determinants of allopurinol and measure their clinical relevance to personalize allopurinol therapy.

Unraveling NEK4 as a Potential Drug Target in Schizophrenia and Bipolar I Disorder: A Proteomic and Genomic Approach

BACKGROUND AND HYPOTHESIS

Investigating the shared brain protein and genetic components of schizophrenia (SCZ) and bipolar I disorder (BD-I) presents a unique opportunity to understand the underlying pathophysiological processes and pinpoint potential drug targets.

STUDY DESIGN

To identify overlapping susceptibility brain proteins in SCZ and BD-I, we carried out proteome-wide association studies (PWAS) and Mendelian Randomization (MR) by integrating human brain protein quantitative trait loci with large-scale genome-wide association studies for both disorders. We utilized transcriptome-wide association studies (TWAS) to determine the consistency of mRNA-protein dysregulation in both disorders. We applied pleiotropy-informed conditional false discovery rate (pleioFDR) analysis to identify common risk genetic loci for SCZ and BD-I. Additionally, we performed a cell-type-specific analysis in the human brain to detect risk genes notably enriched in distinct brain cell types. The impact of risk gene overexpression on dendritic arborization and axon length in neurons was also examined.

STUDY RESULTS

Our PWAS identified 42 proteins associated with SCZ and 14 with BD-I, among which NEK4, HARS2, SUGP1, and DUS2 were common to both conditions. TWAS and MR analysis verified the significant risk gene NEK4 for both SCZ and BD-I. PleioFDR analysis further supported genetic risk loci associated with NEK4 for both conditions. The cell-type specificity analysis revealed that NEK4 is expressed on the surface of glutamatergic neurons, and its overexpression enhances dendritic arborization and axon length in cultured primary neurons.

CONCLUSIONS

These findings underscore a shared genetic origin for SCZ and BD-I, offering novel insights for potential therapeutic target identification.

Prediction of antipsychotics efficacy based on a polygenic risk score: a real-world cohort study

Background: Response to antipsychotics is subject to a wide interindividual variability, due to genetic and non-genetic factors. Several single nucleotide polymorphisms (SNPs) have been associated with response to antipsychotics in genome-wide association studies (GWAS). Polygenic risk scores (PRS) are a powerful tool to aggregate into a single measure the small effects of multiple risk alleles. Materials and methods: We studied the association between a PRS composed of SNPs associated with response to antipsychotics in GWAS studies (PRSresponse) in a real-world sample of patients (N = 460) with different diagnoses (schizophrenia spectrum, bipolar, depressive, neurocognitive, substance use disorders and miscellaneous). Two other PRSs composed of SNPs previously associated with risk of schizophrenia (PRSschizophrenia1 and PRSschizophrenia2) were also tested for their association with response to treatment. Results: PRSresponse was significantly associated with response to antipsychotics considering the whole cohort (OR = 1.14, CI = 1.03-1.26, p = 0.010), the subgroup of patients with schizophrenia, schizoaffective disorder or bipolar disorder (OR = 1.18, CI = 1.02-1.37, p = 0.022, N = 235), with schizophrenia or schizoaffective disorder (OR = 1.24, CI = 1.04-1.47, p = 0.01, N = 176) and with schizophrenia (OR = 1.27, CI = 1.04-1.55, p = 0.01, N = 149). Sensitivity and specificity were sub-optimal (schizophrenia 62%, 61%; schizophrenia spectrum 56%, 55%; schizophrenia spectrum plus bipolar disorder 60%, 56%; all patients 63%, 58%, respectively). PRSschizophrenia1 and PRSschizophrenia2 were not significantly associated with response to treatment. Conclusion: PRSresponse defined from GWAS studies is significantly associated with response to antipsychotics in a real-world cohort; however, the results of the sensitivity-specificity analysis preclude its use as a predictive tool in clinical practice.

Rare variants in pharmacogenes influence clozapine metabolism in individuals with schizophrenia

Clozapine is the only licensed medication for treatment-resistant schizophrenia (TRS). Few predictors for variation in response to clozapine have been identified, but clozapine metabolism is known to influence therapeutic response and adverse side effects. Here, we expand on genome-wide studies of clozapine metabolism, previously focused on common genetic variation, by analysing whole-exome sequencing data from 2062 individuals with schizophrenia taking clozapine in the UK. We investigated whether rare genomic variation in genes and gene sets involved in the clozapine metabolism pathway influences plasma concentrations of clozapine metabolites, assessed through the longitudinal analysis of 6585 pharmacokinetic assays. We observed a statistically significant association between the burden of rare damaging coding variants (MAF ≤ 1 %) in gene sets broadly related to drug pharmacokinetics and lower clozapine (β = -0.054, SE = 0.019, P-value = 0.005) concentrations in plasma. We estimate that the effects in clozapine plasma concentrations of a single damaging allele in this gene set are akin to reducing the clozapine dose by about 35 mg/day. The gene-based analysis identified rare variants in CYP1A2, which encodes the enzyme responsible for converting clozapine to norclozapine, as having the strongest effects of any gene on clozapine metabolism (β = 0.324, SE = 0.124, P = 0.009). Our findings support the hypothesis that rare genetic variants in known drug-metabolising enzymes and transporters can markedly influence clozapine plasma concentrations; these results suggest that pharmacogenomic efforts trying to predict clozapine metabolism and personalise drug therapy could benefit from the inclusion of rare damaging variants in pharmacogenes beyond those already identified and catalogued as PGx star alleles.

Role of Transporters and Enzymes in Metabolism and Distribution of 4-Chlorokynurenine (AV-101)

4-Chlorokynurenine (4-Cl-KYN, AV-101) is a prodrug of a NMDA receptor antagonist and is in clinical development for potential CNS indications. We sought to further understand the distribution and metabolism of 4-Cl-KYN, as this information might provide a strategy to enhance the clinical development of this drug. We used excretion studies in rats, in vitro transporter assays, and pharmacogenetic analysis of clinical trial data to determine how 4-Cl-KYN and metabolites are distributed. Our data indicated that a novel acetylated metabolite (N-acetyl-4-Cl-KYN) did not affect the uptake of 4-Cl-KYN across the blood-brain barrier via LAT1. 4-Cl-KYN and its metabolites were found to be renally excreted in rodents. In addition, we found that N-acetyl-4-Cl-KYN inhibited renal and hepatic transporters involved in excretion. Thus, this metabolite has the potential to limit the excretion of a range of compounds. Our pharmacogenetic analysis found that a SNP in N-acetyltransferase 8 (NAT8, rs13538) was linked to levels of N-acetyl-4-Cl-KYN relative to 4-Cl-KYN found in the plasma and that a SNP in SLC7A5 (rs28582913) was associated with the plasma levels of the active metabolite, 7-Cl-KYNA. Thus, we have a pharmacogenetics-based association for plasma drug level that could aid in the drug development of 4-Cl-KYN and have investigated the interaction of a novel metabolite with drug transporters.

Polygenetic risk scores and phenotypic constellations of obsessive-compulsive disorder in clozapine-treated schizophrenia

Obsessive-compulsive symptoms (OCS) are frequently observed in individuals with schizophrenia (SCZ) treated with clozapine (CLZ). This study aimed to analyze prevalence of OCS and obsessive-compulsive disorder (OCD) in this subgroup and find possible correlations with different phenotypes. Additionally, this is the first study to examine polygenetic risk scores (PRS) in individuals with SCZ and OCS. A multicenter cohort of 91 individuals with SCZ who were treated with CLZ was recruited and clinically and genetically assessed. Symptom severity was examined using the Positive and Negative Symptom Scale (PANSS), Clinical Global Impression Scale (CGI), the Calgary Depression Scale for Schizophrenia (CDSS), Global Assessment of Functioning Scale (GAF) and Yale-Brown Obsessive-Compulsive Scale (Y-BOCS). Participants were divided into subgroups based on phenotypic OCS or OCD using Y-BOCS scores. Genomic-wide data were generated, and PRS analyses were performed to evaluate the association between either phenotypic OCD or OCS severity and genotype-predicted predisposition for OCD, SCZ, cross-disorder, and CLZ/norclozapine (NorCLZ) ratio, CLZ metabolism and NorCLZ metabolism. OCS and OCD were frequent comorbidities in our sample of CLZ-treated SCZ individuals, with a prevalence of 39.6% and 27.5%, respectively. Furthermore, the Y-BOCS total score correlated positively with the duration of CLZ treatment in years (r = 0.28; p = 0.008) and the PANSS general psychopathology subscale score (r = 0.23; p = 0.028). A significant correlation was found between OCD occurrence and PRS for CLZ metabolism. We found no correlation between OCS severity and PRS for CLZ metabolism. We found no correlation for either OCD or OCS and PRS for OCD, cross-disorder, SCZ, CLZ/NorCLZ ratio or NorCLZ metabolism. Our study was able to replicate previous findings on clinical characteristics of CLZ-treated SCZ individuals. OCS is a frequent comorbidity in this cohort and is correlated with CLZ treatment duration in years and PANSS general psychopathology subscale score. We found a correlation between OCD and PRS for CLZ metabolism, which should be interpreted as incidental for now. Future research is necessary to replicate significant findings and to assess possible genetic predisposition of CLZ-treated individuals with SCZ to OCS/OCD. Limitations attributed to the small sample size or the inclusion of subjects on co-medication must be considered. If the association between OCD and PRS for CLZ metabolism can be replicated, it should be further evaluated if CYP1A2 alteration, respectively lower CLZ plasma level, is relevant for OCD development.

Mediation and longitudinal analysis to interpret the association between clozapine pharmacokinetics, pharmacogenomics, and absolute neutrophil count

Clozapine is effective at reducing symptoms of treatment-resistant schizophrenia, but it can also induce several adverse outcomes including neutropenia and agranulocytosis. We used linear mixed-effect models and structural equation modelling to determine whether pharmacokinetic and genetic variables influence absolute neutrophil count in a longitudinal UK-based sample of clozapine users not currently experiencing neutropenia (N = 811). Increased daily clozapine dose was associated with elevated neutrophil count, amounting to a 133 cells/mm3 rise per standard deviation increase in clozapine dose. One-third of the total effect of clozapine dose was mediated by plasma clozapine and norclozapine levels, which themselves demonstrated opposing, independent associations with absolute neutrophil count. Finally, CYP1A2 pharmacogenomic activity score was associated with absolute neutrophil count, supporting lower neutrophil levels in CYP1A2 poor metabolisers during clozapine use. This information may facilitate identifying at-risk patients and then introducing preventative interventions or individualised pharmacovigilance procedures to help mitigate these adverse haematological reactions.

Infections associated with clozapine: a pharmacovigilance study using VigiBase®

Introduction: Clozapine is primarily reserved for treatment-resistant schizophrenia due to safety concerns associated with its use. Infections have been reported with clozapine, which may lead to elevated serum levels of the drug. However, the existing literature on this topic is limited. Therefore, we conducted a study using VigiBase® to investigate the potential over-reporting of infections associated with clozapine, to explore the presence of dose-dependency, and to investigate the underlying mechanism. Methods: Disproportionality analyses were performed using VigiBase to assess the association between clozapine and all types of infections, the association between clozapine-associated infections and neutropenia, the association between clozapine-associated infections and agranulocytosis, the dose-effect relationship between clozapine and infections, and the interaction between clozapine and the main strong CYP450 inhibitors using reports carried out until 11 April 2023. Results: A statistically significant signal of infections was observed with clozapine, as indicated by an information component of 0.43 [95% CI: (0.41-0.45)]. The most commonly reported infections were respiratory and gastrointestinal in nature. Neutropenia showed weaker association with clozapine-associated reports of infections compared to other clozapine-associated reports [X2 (1, N = 204,073) = 454; p < 0.005], while agranulocytosis demonstrated a stronger association with clozapine-associated reports of infections [X2 (1, N = 204,073) = 56; p < 0.005]. No evidence of dose-dependency was observed. Among the 17 tested CYP inhibitors, significant drug-drug interactions were found with clarithromycin, metronidazole, valproic acid, lansoprazole, omeprazole, amiodarone, and esomeprazole. Discussion: Our study revealed a significant safety signal between clozapine use and infections, predominantly respiratory and gastrointestinal infections. The co-administration of clozapine with valproic acid or proton pump inhibitors may potentially contribute to an increased risk of infection. Further vigilance is warranted in clinical practice, and consideration of therapeutic drug monitoring of clozapine in cases involving concomitant use of these drugs or in the presence of infections may be beneficial.

Genome-Wide Association Studies of Coffee Intake in UK/US Participants of European Ancestry Uncover Gene-Cohort Influences

Coffee is one of the most widely consumed beverages. We performed a genome-wide association study (GWAS) of coffee intake in US-based 23andMe participants (N=130,153) and identified 7 significant loci, with many replicating in three multi-ancestral cohorts. We examined genetic correlations and performed a phenome-wide association study across thousands of biomarkers and health and lifestyle traits, then compared our results to the largest available GWAS of coffee intake from UK Biobank (UKB; N=334,659). The results of these two GWAS were highly discrepant. We observed positive genetic correlations between coffee intake and psychiatric illnesses, pain, and gastrointestinal traits in 23andMe that were absent or negative in UKB. Genetic correlations with cognition were negative in 23andMe but positive in UKB. The only consistent observations were positive genetic correlations with substance use and obesity. Our study shows that GWAS in different cohorts could capture cultural differences in the relationship between behavior and genetics.

Dopamine Dynamics and Neurobiology of Non-Response to Antipsychotics, Relevance for Treatment Resistant Schizophrenia: A Systematic Review and Critical Appraisal

Treatment resistant schizophrenia (TRS) is characterized by a lack of, or suboptimal response to, antipsychotic agents. The biological underpinnings of this clinical condition are still scarcely understood. Since all antipsychotics block dopamine D2 receptors (D2R), dopamine-related mechanisms should be considered the main candidates in the neurobiology of antipsychotic non-response, although other neurotransmitter systems play a role. The aims of this review are: (i) to recapitulate and critically appraise the relevant literature on dopamine-related mechanisms of TRS; (ii) to discuss the methodological limitations of the studies so far conducted and delineate a theoretical framework on dopamine mechanisms of TRS; and (iii) to highlight future perspectives of research and unmet needs. Dopamine-related neurobiological mechanisms of TRS may be multiple and putatively subdivided into three biological points: (1) D2R-related, including increased D2R levels; increased density of D2Rs in the high-affinity state; aberrant D2R dimer or heteromer formation; imbalance between D2R short and long variants; extrastriatal D2Rs; (2) presynaptic dopamine, including low or normal dopamine synthesis and/or release compared to responder patients; and (3) exaggerated postsynaptic D2R-mediated neurotransmission. Future points to be addressed are: (i) a more neurobiologically-oriented phenotypic categorization of TRS; (ii) implementation of neurobiological studies by directly comparing treatment resistant vs. treatment responder patients; (iii) development of a reliable animal model of non-response to antipsychotics.

Pharmacokinetics and pharmacogenomics of clozapine in an ancestrally diverse sample: a longitudinal analysis and genome-wide association study using UK clinical monitoring data

BACKGROUND

The antipsychotic, clozapine, is the only licensed drug against the treatment-resistant symptoms that affect 20-30% of people with schizophrenia. Clozapine is markedly underprescribed, partly because of concerns about its narrow therapeutic range and adverse drug reaction profile. Both concerns are linked to drug metabolism, which varies across populations globally and is partly genetically determined. Our study aimed to use a cross-ancestry genome-wide association study (GWAS) design to investigate variations in clozapine metabolism within and between genetically inferred ancestral backgrounds, to discover genomic associations to clozapine plasma concentrations, and to assess the effects of pharmacogenomic predictors across different ancestries.

METHODS

In this GWAS, we analysed data from the UK Zaponex Treatment Access System clozapine monitoring service as part of the CLOZUK study. We included all available individuals with clozapine pharmacokinetic assays requested by their clinicians. We excluded people younger than 18 years, or whose records contained clerical errors, or with blood drawn 6-24 h after dose, a clozapine or norclozapine concentration less than 50 ng/mL, a clozapine concentration of more than 2000 ng/mL, a clozapine-to-norclozapine ratio outside of the 0·5-3·0 interval, or a clozapine dose of more than 900 mg/day. Using genomic information, we identified five biogeographical ancestries: European, sub-Saharan African, north African, southwest Asian, and east Asian. We did pharmacokinetic modelling, a GWAS, and a polygenic risk score association analysis using longitudinal regression analysis with three primary outcome variables: two metabolite plasma concentrations (clozapine and norclozapine) and the clozapine-to-norclozapine ratio.

FINDINGS

19 096 pharmacokinetic assays were available for 4760 individuals in the CLOZUK study. After data quality control, 4495 individuals (3268 [72·7%] male and 1227 [27·3%] female; mean age 42·19 years [range 18-85]) linked to 16 068 assays were included in this study. We found a faster average clozapine metabolism in people of sub-Saharan African ancestry than in those of European ancestry. By contrast, individuals with east Asian or southwest Asian ancestry were more likely to be slow clozapine metabolisers than those with European ancestry. Eight pharmacogenomic loci were identified in the GWAS, seven with significant effects in non-European groups. Polygenic scores generated from these loci were associated with clozapine outcome variables in the whole sample and within individual ancestries; the maximum variance explained was 7·26% for the metabolic ratio.

INTERPRETATION

Longitudinal cross-ancestry GWAS can discover pharmacogenomic markers of clozapine metabolism that, individually or as polygenic scores, have consistent effects across ancestries. Our findings suggest that ancestral differences in clozapine metabolism could be considered for optimising clozapine prescription protocols for diverse populations.

FUNDING

UK Academy of Medical Sciences, UK Medical Research Council, and European Commission.

Promises and challenges in pharmacoepigenetics

Pharmacogenetics, the study of how interindividual genetic differences affect drug response, does not explain all observed heritable variance in drug response. Epigenetic mechanisms, such as DNA methylation, and histone acetylation may account for some of the unexplained variances. Epigenetic mechanisms modulate gene expression and can be suitable drug targets and can impact the action of nonepigenetic drugs. Pharmacoepigenetics is the field that studies the relationship between epigenetic variability and drug response. Much of this research focuses on compounds targeting epigenetic mechanisms, called epigenetic drugs, which are used to treat cancers, immune disorders, and other diseases. Several studies also suggest an epigenetic role in classical drug response; however, we know little about this area. The amount of information correlating epigenetic biomarkers to molecular datasets has recently expanded due to technological advances, and novel computational approaches have emerged to better identify and predict epigenetic interactions. We propose that the relationship between epigenetics and classical drug response may be examined using data already available by (1) finding regions of epigenetic variance, (2) pinpointing key epigenetic biomarkers within these regions, and (3) mapping these biomarkers to a drug-response phenotype. This approach expands on existing knowledge to generate putative pharmacoepigenetic relationships, which can be tested experimentally. Epigenetic modifications are involved in disease and drug response. Therefore, understanding how epigenetic drivers impact the response to classical drugs is important for improving drug design and administration to better treat disease.

Genomic Stratification of Clozapine Prescription Patterns Using Schizophrenia Polygenic Scores

BACKGROUND

Treatment-resistant schizophrenia affects approximately 30% of individuals with the disorder. Clozapine is the medication of choice in treatment-resistant schizophrenia, but optimizing administration and dose titration is complex. The identification of factors influencing clozapine prescription and response, including genetics, is of interest in a precision psychiatry framework.

METHODS

We used linear regression models accounting for demographic, pharmacological, and clinical covariates to determine whether a polygenic risk score (PRS) for schizophrenia would be associated with the highest dose recorded during clozapine treatment. Analyses were performed across 2 independent multiancestry samples of individuals from a UK patient monitoring system, CLOZUK2 (n = 3133) and CLOZUK3 (n = 909), and a European sample from a Norwegian therapeutic drug monitoring service (n = 417). In a secondary analysis merging both UK cohorts, logistic regression models were used to estimate the relationship between schizophrenia PRSs and clozapine doses classified as low, standard, or high.

RESULTS

After controlling for relevant covariates, the schizophrenia PRS was correlated with the highest clozapine dose on record for each individual across all samples: CLOZUK2 (β = 12.22, SE = 3.78, p = .001), CLOZUK3 (β = 12.73, SE = 5.99, p = .034), and the Norwegian cohort (β = 46.45, SE = 18.83, p = .014). In a secondary analysis, the schizophrenia PRS was associated with taking clozapine doses >600 mg/day (odds ratio = 1.279, p = .006).

CONCLUSIONS

The schizophrenia PRS was associated with the highest clozapine dose prescribed for an individual in records from 3 independent samples, suggesting that the genetic liability for schizophrenia might index factors associated with therapeutic decisions in cohorts of patients with treatment-resistant schizophrenia.

Impact of NFIB and CYP1A variants on clozapine serum concentration-A retrospective naturalistic cohort study on 526 patients with known smoking habits

Clinical response of clozapine is closely associated with serum concentration. Although tobacco smoking is the key environmental factor underlying interindividual variability in clozapine metabolism, recent genome-wide studies suggest that CYP1A and NFIB genetic variants may also be of significant importance, but their quantitative impact is unclear. We investigated the effects of the rs2472297 C>T (CYP1A) and rs28379954 T>C (NFIB) polymorphisms on serum concentrations in smokers and nonsmokers. The study retrospectively included 526 patients with known smoking habits (63.7% smokers) from a therapeutic drug monitoring service in Norway. Clozapine dose-adjusted concentrations (C/D) and patient proportions with subtherapeutic levels (<1070 nmol/L) were compared between CYP1A/NFIB variant allele carriers and homozygous wild-type carriers (noncarriers), in both smokers and nonsmokers. Clozapine C/D was reduced in patients carrying CYP1A-T and NFIB-C variants versus noncarriers, both among smokers (-48%; p < 0.0001) and nonsmokers (-35%; p = 0.028). Patients who smoke carrying CYP1A-T and NFIB-C variants had a 66% reduction in clozapine C/D versus nonsmoking noncarriers (p < 0.0001). The patient proportion with subtherapeutic levels was 2.9-fold higher in patients who smoke carrying NFIB-C and CYP1A-T variants versus nonsmoking noncarriers (p < 0.0001). In conclusion, CYP1A and NFIB variants have significant and additive impact on clozapine dose requirements for reaching target serum concentrations. Patients who smoke carrying the studied CYP1A and NFIB variants, comprising 2.5% of the study population, may need threefold higher doses to prevent risk of clozapine undertreatment. The results suggest that pre-emptive genotyping of NFIB and CYP1A may be utilized to guide clozapine dosing and improve clinical outcomes in patients with treatment-resistant schizophrenia.

Attenuated transcriptional response to pro-inflammatory cytokines in schizophrenia hiPSC-derived neural progenitor cells

Maternal immune activation (MIA) during prenatal development is an environmental risk factor for psychiatric disorders including schizophrenia (SZ). Converging lines of evidence from human and animal model studies suggest that elevated cytokine levels in the maternal and fetal compartments are an important indication of the mechanisms driving this association. However, there is variability in susceptibility to the psychiatric risk conferred by MIA, likely influenced by genetic factors. How MIA interacts with a genetic profile susceptible to SZ is challenging to test in animal models. To address this gap, we examined whether differential gene expression responses occur in forebrain-lineage neural progenitor cells (NPCs) derived from human induced pluripotent stem cells (hiPSC) generated from three individuals with a diagnosis of schizophrenia and three healthy controls. Following acute (24 h) treatment with either interferon-gamma (IFNγ; 25 ng/μl) or interleukin (IL)-1β (10 ng/μl), we identified, by RNA sequencing, 3380 differentially expressed genes (DEGs) in the IFNγ-treated control lines (compared to untreated controls), and 1980 DEGs in IFNγ-treated SZ lines (compared to untreated SZ lines). Out of 4137 genes that responded significantly to IFNγ across all lines, 1223 were common to both SZ and control lines. The 2914 genes that appeared to respond differentially to IFNγ treatment in SZ lines were subjected to a further test of significance (multiple testing correction applied to the interaction effect between IFNγ treatment and SZ diagnosis), yielding 359 genes that passed the significance threshold. There were no differentially expressed genes in the IL-1β-treatment conditions after Benjamini-Hochberg correction. Gene set enrichment analysis however showed that IL-1β impacts immune function and neuronal differentiation. Overall, our data suggest that a) SZ NPCs show an attenuated transcriptional response to IFNγ treatment compared to controls; b) Due to low IL-1β receptor expression in NPCs, NPC cultures appear to be less responsive to IL-1β than IFNγ; and c) the genes differentially regulated in SZ lines - in the face of a cytokine challenge - are primarily associated with mitochondrial, "loss-of-function", pre- and post-synaptic gene sets. Our findings particularly highlight the role of early synaptic development in the association between maternal immune activation and schizophrenia risk.

Pharmacokinetic interactions between clozapine and valproic acid in patients with treatment-resistant schizophrenia: Does UGT polymorphism affect these drug interactions?

The combination of valproic acid (VPA) and clozapine (CLZ) is regularly prescribed for augmentation therapy in treatment resistant schizophrenia. The VPA has been shown to reduce norclozapine (NCLZ) plasma levels, but the mechanism of this interaction remains unknown. The aim of this study is to examine the differences between patients treated with CLZ and patients treated with CLZ plus VPA. For it, various factors have been evaluated. The study was based on plasma samples from CLZ and CLZ plus VPA treated patients (n = 61) subjected to routine therapeutic drug monitoring considering clinical data, smoking status, daily dose of CLZ and VPA, concomitant medications, albumin, and renal and hepatic function. Genotyping of polymorphisms of CYP1A2, CYP3A4/5, CYP2C19, ABCB1, UGT2B10 and CYP2C19 were performed by real time PCR. CYP2D6 were genotyped using competitive allele-specific PCR and by a long PCR based method. Plasma CLZ and NCLZ concentrations were measured by Liquid Chromatography-Tandem masses (LC-MS/MS) and plasma VPA by Ultraviolet-Visible (UV-vis) spectrophotometric immunoassay. The patients presented adequate CLZ levels in relation to the dose. However, NCLZ levels were excessively low and the CLZ/NCLZ ratio very high. Patients with UGT2B10 GT (rs61750900) genotype showed lower NCLZ plasma levels and C/D NCLZ, and higher CLZ/NCLZ ratio versus patients with UGT2B10 GG genotype. VPA, smoking, the presence of UGT2B10 GT genotype and having low albumin levels indicate that the CLZ/NCLZ ratio is affected, mostly coinciding with decreased NCLZ levels and possibly with an increased risk of neutropenia.

Dopaminergic dysfunction and excitatory/inhibitory imbalance in treatment-resistant schizophrenia and novel neuromodulatory treatment

Antipsychotic drugs are the mainstay in the treatment of schizophrenia. However, one-third of patients do not show adequate improvement in positive symptoms with non-clozapine antipsychotics. Additionally, approximately half of them show poor response to clozapine, electroconvulsive therapy, or other augmentation strategies. However, the development of novel treatment for these conditions is difficult due to the complex and heterogenous pathophysiology of treatment-resistant schizophrenia (TRS). Therefore, this review provides key findings, potential treatments, and a roadmap for future research in this area. First, we review the neurobiological pathophysiology of TRS, particularly the dopaminergic, glutamatergic, and GABAergic pathways. Next, the limitations of existing and promising treatments are presented. Specifically, this article focuses on the therapeutic potential of neuromodulation, including electroconvulsive therapy, repetitive transcranial magnetic stimulation, transcranial direct current stimulation, and deep brain stimulation. Finally, we propose multivariate analyses that integrate various perspectives of the pathogenesis, such as dopaminergic dysfunction and excitatory/inhibitory imbalance, thereby elucidating the heterogeneity of TRS that could not be obtained by conventional statistics. These analyses can in turn lead to a precision medicine approach with closed-loop neuromodulation targeting the detected pathophysiology of TRS.

Improving lithium dose prediction using population pharmacokinetics and pharmacogenomics: a cohort genome-wide association study in Sweden

BACKGROUND

Lithium is the most effective treatment for bipolar disorder, resulting in strong suicide prevention effects. The therapeutic range of lithium, however, is narrow and treatment initiation requires individual titration to address inter-individual variability. We aimed to improve lithium dose prediction using clinical and genomic data.

METHODS

We performed a population pharmacokinetic study followed by a genome-wide association study (GWAS), including two clinical Swedish cohorts. Participants in cohort 1 were from specialised outpatient clinics at Huddinge Hospital, in Stockholm, Sweden, and participants in cohort 2 were identified using the Swedish National Quality Registry for Bipolar disorder (BipoläR). Patients who received a lithium dose corresponding to at least one tablet of lithium sulphate (6 mmol) per day and had clinically relevant plasma concentrations of lithium were included in the study. Data on age, sex, bodyweight, height, creatinine concentration, estimated glomerular filtration rate (eGFR), lithium preparation, number of tablets of lithium per day, serum lithium concentration, and medications affecting kidney function (C09 antihypertensives, C03 [except C03D] sodium-retaining diuretics, and non-steroidal anti-inflammatory drugs) were obtained retrospectively for several timepoints when possible from electronic health records, BipoläR, and the Swedish prescription registry. The median time between timepoints was 1·07 years for cohort 1 and 1·09 years for cohort 2. The primary outcome of interest was the natural logarithm of total body clearance for lithium (CL_Li) associated with the clinical variables. The residual effects after accounting for age and sex, representing the individual-level effects (CL_Li,age/sex), were used as the dependent variable in a GWAS.

FINDINGS

2357 patients who were administered lithium (1423 women [60·4%] and 934 men [39·6%]; mean age 53·6 years [range 17-89], mainly of European descent) were included and 5627 data points were obtained. Age (variance explained [R²]: R²_cohort1=0·41 and R²_cohort2=0·31; both p<0·0001), sex (R²_cohort1=0·0063 [p=0·045] and R²_cohort2=0·026 [p<0·0001]), eGFR (R²_cohort1=0·38 and R²_cohort2=0·20; both p<0·0001), comedication with diuretics (R²_cohort1=0·0058 [p=0·014] and R²_cohort2=0·0026 [p<0·0001]), and agents acting on the renin-aldosterone-angiotensin system (R²_cohort1=0·028 and R²_cohort2=0·015; both p<0·0001) were clinical predictors of CL_Li. Notably, an association between CL_Li and serum lithium was observed, with a lower CL_Li being associated with higher serum lithium (R²_cohort1=0·13 and R²_cohort2=0·15; both p<0·0001). In a GWAS of CL_Li,age/sex, one locus was associated with a change in CL_Li (rs583503; β=-0·053 [95% CI -0·071 to -0·034]; p<0·00000005). We also found enrichment of the associations with genes expressed in the medulla (p=0·0014, corrected FDR=0·04) and cortex of the kidney (p=0·0015, corrected FDR=0·04), as well as associations with polygenic risk scores for eGFR (p value threshold: 0·05, p=0·01), body-mass index (p value threshold: 0·05, p=0·00025), and blood urea nitrogen (p value threshold: 0·001, p=0·00043). The model based on six clinical predictors explained 61·4% of the variance in CL_Li in cohort 1 and 49·8% in cohort 2. Adding genetic markers did not lead to major improvement of the models: within the subsample of genotyped individuals, the variance explained only increased from 59·32% to 59·36% in cohort 1 and from 49·21% to 50·03% in cohort 2 when including rs583503 and the four first principal components.

INTERPRETATION

Our model predictors could be used clinically to better guide lithium dosage, shortening the time to reach therapeutic concentrations, thus improving care. Identification of the first genomic locus and PRS to be associated with CL_Li introduces the opportunity of individualised medicine in lithium treatment.

FUNDING

Stanley Medical Research Institute, Swedish Research Council, Swedish Foundation for Strategic Research, Swedish Brain Foundation, Swedish Research Council, Söderström-Königska Foundation, Bror Gadelius Minnesfond, Swedish Mental Health Fund, Karolinska Institutet and Hospital.

Non-convulsive Status Epilepticus in a Patient With Schizoaffective and Seizure Disorder on Clozapine and Electroconvulsive Therapy: A Case Report

There is limited literature on electroconvulsive therapy (ECT) in patients with a severe schizophrenia spectrum illness and concomitant seizure disorder. In addition, it is unclear whether it is safe to perform ECT in a patient with these comorbidities and a history of status epilepticus.

This is the case of a 48-year-old patient with a history of schizoaffective disorder, bipolar type, refractory psychosis on clozapine and ECT, and seizure disorder on carbamazepine. She presented to the emergency department with suspected post-ECT delirium four days after her last ECT treatment, was found to be in non-convulsive status epilepticus, and was admitted to the neuroscience intensive care unit. Coma induction was required for seizure control. As she stabilized, her psychosis worsened, and she required psychiatric hospitalization.

Multiple factors may have contributed to the development of status epilepticus in this patient. She was on clozapine, which has a time- and dose-dependent risk of seizure that prescribers should be wary of. She had also been prescribed the antiepileptic drug carbamazepine, which induces clozapine and itself, decreasing their effectiveness. Upon the patient’s discharge, ECT was suspended indefinitely due to concern that it may have led to status epilepticus. However, case reports suggest that intractable seizures following ECT are rare.

We found no reports of status epilepticus occurring more than 60 minutes after the completion of ECT. If the benefits of ECT are significant, then it should remain a treatment option for the patient.

Genome-wide association analyses of symptom severity among clozapine-treated patients with schizophrenia spectrum disorders

Clozapine is the most effective antipsychotic for patients with treatment-resistant schizophrenia. However, response is highly variable and possible genetic underpinnings of this variability remain unknown. Here, we performed polygenic risk score (PRS) analyses to estimate the amount of variance in symptom severity among clozapine-treated patients explained by PRSs (R2) and examined the association between symptom severity and genotype-predicted CYP1A2, CYP2D6, and CYP2C19 enzyme activity. Genome-wide association (GWA) analyses were performed to explore loci associated with symptom severity. A multicenter cohort of 804 patients (after quality control N = 684) with schizophrenia spectrum disorder treated with clozapine were cross-sectionally assessed using the Positive and Negative Syndrome Scale and/or the Clinical Global Impression-Severity (CGI-S) scale. GWA and PRS regression analyses were conducted. Genotype-predicted CYP1A2, CYP2D6, and CYP2C19 enzyme activities were calculated. Schizophrenia-PRS was most significantly and positively associated with low symptom severity (p = 1.03 × 10^-3; R2 = 1.85). Cross-disorder-PRS was also positively associated with lower CGI-S score (p = 0.01; R2 = 0.81). Compared to the lowest tertile, patients in the highest schizophrenia-PRS tertile had 1.94 times (p = 6.84×10^-4) increased probability of low symptom severity. Higher genotype-predicted CYP2C19 enzyme activity was independently associated with lower symptom severity (p = 8.44×10^-3). While no locus surpassed the genome-wide significance threshold, rs1923778 within NFIB showed a suggestive association (p = 3.78×10^-7) with symptom severity. We show that high schizophrenia-PRS and genotype-predicted CYP2C19 enzyme activity are independently associated with lower symptom severity among individuals treated with clozapine. Our findings open avenues for future pharmacogenomic projects investigating the potential of PRS and genotype-predicted CYP-activity in schizophrenia.

The role of alcohol intake in the pharmacogenetics of treatment with clozapine

Clozapine (CLZ) is an atypical antipsychotic reserved for patients with refractory psychosis, but it is associated with a significant risk of severe adverse reactions (ADRs) that are potentiated with the concomitant use of alcohol. Additionally, pharmacogenetic studies have explored the influence of several genetic variants in CYP450, receptors and transporters involved in the interindividual response to CLZ. Herein, we systematically review the current multiomics knowledge behind the interaction between CLZ and alcohol intake, and how its concomitant use might modulate the pharmacogenetics. CYP1A2*1F, *1C and other alleles not yet discovered could support a precision medicine approach for better therapeutic effects and fewer CLZ ADRs. CLZ monitoring systems should be amended and include alcohol intake to protect patients from severe CLZ ADRs.

Effects of a novel UGT2B haplotype and UGT1A4*3 allele variants on glucuronidation of clozapine in vivo

BACKGROUND

Glucuronidation is an important metabolic pathway of clozapine (CLZ), but the impact of various uridine 5'diphospho-glucuronosyltransferases (UGT) polymorphisms on the exposure and metabolism of CLZ in vivo is unclear.

OBJECTIVE

The objective of this study was to investigate the impact of UGT2B haplotype and UGT1A4*3 allele variants on the formation of CLZ glucuronide metabolites (5N- and N+-glucuronide) and CLZ exposure in patients' serum after adjusting for sex, age and smoking habits.

METHODS

The study was based on serum samples from CLZ-treated patients (n=79) subjected to routine therapeutic drug monitoring (TDM) at Diakonhjemmet Hospital, Oslo, Norway. From the same patients the following UGT variants were genotyped using Real-Time PCR: UGT2B:GA haplotype (defined as UGT2B:GA; rs1513559A>G and rs416593T>A) and UGT1A4*3 (rs2011425T>G). Serum concentrations of CLZ 5N- and N+-glucuronide were measured by UPLC high-resolution mass spectrometry.

RESULTS

None of the genotypes had significant impact on CLZ exposure (p>0.05). However, compared to UGT2B:AT/AT and UGT1A4*1/*1, the 5N-glucuronide exposure was reduced in UGT2B:GA/GA carriers (-75%, p=0.03) while the exposure was non-significantly increased in UGT1A4*3 carriers (+100%, p=0.14), respectively. The N+-glucuronide exposure was unchanged in UGT1A4*3 vs noncarriers (p=0.28), but significantly reduced in heterozygous (-50%, p=0.016) and homozygous carriers (-70%, p=0.021) of UGT2B:GA compared to UGT2B:AT/AT carriers, respectively.

CONCLUSION

The UGT2B:GA and UGT1A4*3 variants had no impact on CLZ exposure, but were associated with differences and preferences in CLZ glucuronidation. The latter might be of potential relevance for CLZ tolerability, since levels of the N+-glucuronide metabolite may reflect the generation and trapping of reactive metabolites involved in CLZ-induced toxicity.

Shared genetic influences on resting‐state functional networks of the brain

The amplitude of activation in brain resting state networks (RSNs), measured with resting‐state functional magnetic resonance imaging, is heritable and genetically correlated across RSNs, indicating pleiotropy. Recent univariate genome‐wide association studies (GWASs) explored the genetic underpinnings of individual variation in RSN activity. Yet univariate genomic analyses do not describe the pleiotropic nature of RSNs. In this study, we used a novel multivariate method called genomic structural equation modeling to model latent factors that capture the shared genomic influence on RSNs and to identify single nucleotide polymorphisms (SNPs) and genes driving this pleiotropy. Using summary statistics from GWAS of 21 RSNs reported in UK Biobank (N = 31,688), the genomic latent factor analysis was first conducted in a discovery sample (N = 21,081), and then tested in an independent sample from the same cohort (N = 10,607). In the discovery sample, we show that the genetic organization of RSNs can be best explained by two distinct but correlated genetic factors that divide multimodal association networks and sensory networks. Eleven of the 17 factor loadings were replicated in the independent sample. With the multivariate GWAS, we found and replicated nine independent SNPs associated with the joint architecture of RSNs. Further, by combining the discovery and replication samples, we discovered additional SNP and gene associations with the two factors of RSN amplitude. We conclude that modeling the genetic effects on brain function in a multivariate way is a powerful approach to learn more about the biological mechanisms involved in brain function.

Effect of Valproic Acid on the Metabolic Spectrum of Clozapine in Patients With Schizophrenia

BACKGROUND

Valproic acid (VPA) is frequently used with clozapine (CLZ) as mood stabilizer and/or seizure prophylaxis. Valproic acid is known to reduce N-desmethylclozapine (N-DMC) but not CLZ levels. This leads to the hypothesis that VPA induces the CLZ metabolism via non-N-desmethylation pathways. Therefore, we aimed to investigate the effect of concurrent VPA use on the serum concentrations of a spectrum of CLZ metabolites in patients, adjusting for smoking.

METHODS

In total, 288 patients with an overall number of 737 serum concentration measurements of CLZ and metabolites concurrently using VPA (cases, n = 22) or no interacting drugs (controls, n = 266) were included from a routine therapeutic drug monitoring service. Linear mixed model analyses were performed to compare the dose-adjusted concentrations (C/D) of CLZ, N-DMC, CLZ 5N/N+-glucuronides, and metabolite-to-parent ratios in cases versus controls.

RESULTS

After adjusting for covariates, the N-DMC (-40%, P < 0.001) and N+-glucuronide C/Ds (-78%, P < 0.001) were reduced in cases versus controls, while the CLZ C/D was unchanged (P > 0.7). In contrast, the 5N-glucuronide C/D (+250%, P < 0.001) and 5N-glucuronide-to-CLZ ratios (+120%, P = 0.01) were increased in cases versus controls.

CONCLUSIONS

Our findings show that complex changes in CLZ metabolism underly the pharmacokinetic interaction with VPA. The lower levels of N-DMC seem to be caused by VPA-mediated induction of CLZ 5N-glucuronide formation, subsequently leading to reduced substrate availability for N-desmethylation. Whether the changes in CLZ metabolism caused by VPA affects the clinical outcome warrants further investigation.

Cigarette smoking, coffee consumption, alcohol intake, and clozapine metabolism: A Mendelian randomization study

BACKGROUND

Clozapine is an effective antipsychotic medication for patients with treatment-resistant schizophrenia. Previous studies revealed that smoking, alcohol intake, and coffee consumption altered the metabolism of clozapine. However, causal associations between substance use and clozapine levels were not sufficiently established.

METHODS

Several genome-wide association studies provided genetic tools for six measures of substance use, including age of smoking, cigarettes per day, smoking cessation, smoking initiation, coffee consumption, and alcohol consumption (GWASs). Utilizing the CLOZUK consortium's dataset, their associations with clozapine and its metabolite concentrations were evaluated. All GWAS data were collected from the European population. Mendelian randomization (MR) estimations from each genetic test were combined using inverse variance weighted (IVW) meta-analysis in combination with complementing techniques (such as weighted median and MR Egger). We also analyze horizontal pleiotropy and heterogeneity using various sensitivity analyses.

RESULTS

Genetically predicted higher level of smoking initiation was significantly associated with reduced clozapine (β = -0.14, P = 4.53E-04) concentrations and norclozapine concentrations (β = -0.14, P = 3.33E-04), and increased coffee consumption was significantly associated with lower level of clozapine concentrations (β = -0.42, P = 1.70E-14), norclozapine concentrations (β = -0.27, P = 1.51E-07), and the metabolic ratio of clozapine to norclozapine (β = -0.15, P = 5.35E-07), survived after the Bonferroni correction (P = 0.05/6 = 0.008). In sensitivity analyses, the weighted median and MR Egger methods demonstrated directionally consistent effects. In addition, our sensitive test indicated no significant horizontal pleiotropy and heterogeneity (P > 0.05). However, other measures of substance use (age of initiation smoking, cigarettes per day, smoking cessation, and drinks per week) were not associated with clozapine metabolism.

CONCLUSION

Our investigation revealed a correlation between greater smoking initiation and coffee consumption and reduced blood levels of clozapine and norclozapine. Providing clinicians with guidance on how to adjust clozapine levels for clozapine-treated patients.

Integrative omics of schizophrenia: from genetic determinants to clinical classification and risk prediction

Schizophrenia (SCZ) is a debilitating neuropsychiatric disorder with high heritability and complex inheritance. In the past decade, successful identification of numerous susceptibility loci has provided useful insights into the molecular etiology of SCZ. However, applications of these findings to clinical classification and diagnosis, risk prediction, or intervention for SCZ have been limited, and elucidating the underlying genomic and molecular mechanisms of SCZ is still challenging. More recently, multiple Omics technologies - genomics, transcriptomics, epigenomics, proteomics, metabolomics, connectomics, and gut microbiomics - have all been applied to examine different aspects of SCZ pathogenesis. Integration of multi-Omics data has thus emerged as an approach to provide a more comprehensive view of biological complexity, which is vital to enable translation into assessments and interventions of clinical benefit to individuals with SCZ. In this review, we provide a broad survey of the single-omics studies of SCZ, summarize the advantages and challenges of different Omics technologies, and then focus on studies in which multiple omics data are integrated to unravel the complex pathophysiology of SCZ. We believe that integration of multi-Omics technologies would provide a roadmap to create a more comprehensive picture of interactions involved in the complex pathogenesis of SCZ, constitute a rich resource for elucidating the potential molecular mechanisms of the illness, and eventually improve clinical assessments and interventions of SCZ to address clinical translational questions from bench to bedside.

Pharmacogenomics: A road ahead for precision medicine in psychiatry

Psychiatric genomics is providing insights into the nature of psychiatric conditions that in time should identify new drug targets and improve patient care. Less attention has been paid to psychiatric pharmacogenomics research, despite its potential to deliver more rapid change in clinical practice and patient outcomes. The pharmacogenomics of treatment response encapsulates both pharmacokinetic ("what the body does to a drug") and pharmacodynamic ("what the drug does to the body") effects. Despite early optimism and substantial research in both these areas, they have to date made little impact on clinical management in psychiatry. A number of bottlenecks have hampered progress, including a lack of large-scale replication studies, inconsistencies in defining valid treatment outcomes across experiments, a failure to routinely incorporate adverse drug reactions and serum metabolite monitoring in study designs, and inadequate investment in the longitudinal data collections required to demonstrate clinical utility. Nonetheless, advances in genomics and health informatics present distinct opportunities for psychiatric pharmacogenomics to enter a new and productive phase of research discovery and translation.

Therapeutic drug monitoring of clozapine in adults with schizophrenia: a review of challenges and strategies

INTRODUCTION

Clozapine (CLZ) is the superior drug in treatment of schizophrenia. Serum concentration of CLZ is associated with clinical response and dose-dependents side effects, where generalized tonic-clonic seizures are most critical. Thus, therapeutic drug monitoring (TDM) of CLZ may guide individual dosing to reach target exposure and prevent dose-dependent side effects. However, current TDM methods are not capable of predicting the risk of agranulocytosis, which is a dose-independent side effect restricting use of CLZ to treatment-resistant schizophrenia (TRS).

AREAS COVERED

The article provides an overview of clinical, pharmacological, and toxicological aspects of CLZ, and the role of TDM as a tool for dose titration and follow-up in patients with TRS. Main focus is on current challenges and strategies in CLZ TDM, including future perspectives on potential identification/analysis of CLZ metabolite biomarkers reflecting the risk of granulocyte toxicity.

EXPERT OPINION

The association between CLZ serum concentration, clinical response and risk of seizures is indisputable. TDM should therefore always guide CLZ dose titration. Development of advanced TDM methods, including biomarkers predicting the risk of granulocyte toxicity might extend TDM to be a tool for deciding which patients that can be treated safely with CLZ, potentially increasing its utility beyond TRS.

Distinct genetic regions are associated with differential population susceptibility to chemical exposures

Interactions between environmental factors and genetics underlie the majority of chronic human diseases. Chemical exposures are likely an underestimated contributor, yet gene-environment (GxE) interaction studies rarely assess their modifying effects. Here, we describe a novel method to profile the human genome and identify regions associated with differential population susceptibility to chemical exposures. Single nucleotide polymorphisms (SNPs) implicated in enriched chemical-disease intersections were identified and validated for three chemical classes with expected GxE interaction potential (neuroactive, hepatoactive, and cardioactive compounds). The same approach was then used to characterize consumer product classes with unknown risk for GxE interactions (washing products, cosmetics, and adhesives). Additionally, high-risk variant sets that may confer differential population susceptibility were identified for these consumer product groups through frequent itemset mining and pathway analysis. A dataset of 2454 consumer product chemical-disease linkages, with risk values, SNPs, and pathways for each association was developed, describing the interplay between environmental factors and genetics in human disease progression. We found that genetic hotspots implicated in GxE interactions differ across chemical classes (e.g., washing products had high-risk SNPs implicated in nervous system disease) and illustrate how this approach can discover new associations (e.g., washing product n-butoxyethanol implicated SNPs in the PI3K-Akt signaling pathway for Alzheimer's disease). Hence, our approach can predict high-risk genetic regions for differential population susceptibility to chemical exposures and characterize chemical modifying factors in specific diseases. These methods show promise for describing how chemical exposures can lead to varied health outcomes in a population and for incorporating inter-individual variability into chemical risk assessment.

Clozapine Metabolism is Associated With Absolute Neutrophil Count in Individuals With Treatment-Resistant Schizophrenia

Up to one-third of those with schizophrenia fail to respond to standard antipsychotics and are considered to have treatment-resistant schizophrenia, a condition for which clozapine is the only evidence-based medication. While up to 60% of treated individuals obtain therapeutic benefits from clozapine, it is currently underprescribed worldwide, partly because of concerns related to its broad adverse effect profile. In particular, the potential effects of clozapine on the immune system have gained relevance after a recent study showed that drug plasma concentrations were inversely correlated with neutrophil counts in individuals routinely undergoing treatment. Seeking to investigate this relationship in more detail, we extracted metabolic, immune, and genetic data from a UK cohort of long-term clozapine users linked to a clozapine monitoring service, CLOZUK2 (N = 208). Whilst a correlation analysis was compatible with the original results, a multiple linear regression accounting for dose and other confounding factors additionally allowed us to estimate the decrease in absolute neutrophil counts to approximately 141 cells/mm3 for every 0.1 mg/L increase in clozapine concentration. However, this association was attenuated after controlling for the metabolic ratio between clozapine and its main metabolite, norclozapine, which was itself negatively associated with neutrophil concentrations. Further analyses revealed that these relationships are likely moderated by genetic factors, as three pharmacogenomic SNPs previously associated to norclozapine plasma concentrations and the metabolic ratio (rs61750900, rs2011425 and rs1126545) were shown to be independently associated with a variation in neutrophil counts of about 400 cells/mm3 per effect allele. Such results are compatible with an effect of norclozapine, but not necessarily clozapine, on immune cell counts, and highlight the need for further investigations into the potential role of genetic determinants of clozapine pharmacokinetics in the occurrence of adverse effects during treatment.

Special Article: Translational Science Update. Pharmacological Implications of Emerging Schizophrenia Genetics: Can the Bridge From 'Genomics' to 'Therapeutics' be Defined and Traversed?

Recent schizophrenia genome-wide association studies (GWAS) have identified genomic variants of common and rare frequency, significantly associated with schizophrenia. While numerous functional genomics efforts are ongoing to elucidate the biological effects of schizophrenia risk variants, a consideration of their therapeutic implications is timely and imperative, for patients as well as for an iterative effect on elucidating the underlying biology and pathophysiology of illness. The current article reviews efforts to translate emerging schizophrenia genomics into novel approaches to target discovery and therapeutic intervention. Though the path from 'genetic risk to therapy' is far from straightforward, there are provocative early possibilities that harbor the promise of treatment based on causation rather than phenomenology, as well as 'precision psychiatry,' a basis for stratifying patients to enable more precise and effective, personalized therapy.

Voltammetric Behaviour of Drug Molecules as a Predictor of Metabolic Liabilities

Electron transfer plays a vital role in drug metabolism and underlying toxicity mechanisms. Currently, pharmaceutical research relies on pharmacokinetics (PK) and absorption, distribution, metabolism, elimination and toxicity (ADMET) measurements to understand and predict drug reactions in the body. Metabolic stability (and toxicity) prediction in the early phases of the drug discovery and development process is key in identifying a suitable lead compound for optimisation. Voltammetric methods have the potential to overcome the significant barrier of new drug failure rates, by giving insight into phase I metabolism events which can have a direct bearing on the stability and toxicity of the parent drug being dosed. Herein, we report for the first time a data-mining investigation into the voltammetric behaviour of reported drug molecules and their correlation with metabolic stability (indirectly measured via t½), as a potential predictor of drug stability/toxicity in vivo. We observed an inverse relationship between oxidation potential and drug stability. Furthermore, we selected and prepared short- (<10 min) and longer-circulation (>2 h) drug molecules to prospectively survey the relationship between oxidation potential and stability.

Identification of a novel polymorphism associated with reduced clozapine concentration in schizophrenia patients-a genome-wide association study adjusting for smoking habits

Clozapine (CLZ) is the superior antipsychotic drug for treatment of schizophrenia, but exhibits an extensive interpatient pharmacokinetic variability. Here, we conducted a genome-wide association study (GWAS) of CLZ serum concentration adjusting for known smoking habits, which is a major nongenetic factor reducing CLZ levels. The study included 484 patients with 10,283 steady-state serum concentrations of CLZ and N-desmethylclozapine, prescribed dosing, co-medications and known smoking habits (n = 422; 9284 serum samples) from a therapeutic drug monitoring (TDM) service. The GWAS analyses were performed with and without smoking habits as covariate, where possible hits were assessed in relation to the target CLZ concentration range applied in the TDM service (300-2500 nmol/L). The smoking-independent analysis of N-desmethylclozapine serum concentration and the CLZ-to-N-desmethylclozapine ratio replicated the previously identified locus on chromosome 4. After adjusting for smoking habits in patients confirmed as 'smokers' (61%) or 'nonsmokers' (39%), a novel variant (rs28379954; minor T>C allele frequency 4.1%; 7.6% CT carriers in the population) within the gene encoding the nuclear factor 1 B-type (NFIB) was significantly associated with reduced CLZ serum concentration (p = 1.68 × 10-8, beta = -0.376; explained variance 7.63%). There was no significant association between rs28379954 and N-desmethylclozapine concentration in the GWAS analysis (p = 5.63 × 10-5). The fraction of CLZ TDM samples below 300 nmol/L was significantly higher in carriers vs. noncarriers of the rs28379954 minor C allele [12.0% (95% CI: 9.4-14.7) vs. 6.2% (95% CI: 5.7-6.8), p < 0.001]. We identified a novel variant in the NFIB gene associated with reduced CLZ levels and increased risk of subtherapeutic serum concentrations. This warrants testing of clinical relevance of screening for this gene variant, and also experimental studies to investigate the biological mechanisms of NFIB involvement in CLZ pharmacokinetics.

Translating insights from neuropsychiatric genetics and genomics for precision psychiatry

The primary aim of precision medicine is to tailor healthcare more closely to the needs of individual patients. This requires progress in two areas: the development of more precise treatments and the ability to identify patients or groups of patients in the clinic for whom such treatments are likely to be the most effective. There is widespread optimism that advances in genomics will facilitate both of these endeavors. It can be argued that of all medical specialties psychiatry has most to gain in these respects, given its current reliance on syndromic diagnoses, the minimal foundation of existing mechanistic knowledge, and the substantial heritability of psychiatric phenotypes. Here, we review recent advances in psychiatric genomics and assess the likely impact of these findings on attempts to develop precision psychiatry. Emerging findings indicate a high degree of polygenicity and that genetic risk maps poorly onto the diagnostic categories used in the clinic. The highly polygenic and pleiotropic nature of psychiatric genetics will impact attempts to use genomic data for prediction and risk stratification, and also poses substantial challenges for conventional approaches to gaining biological insights from genetic findings. While there are many challenges to overcome, genomics is building an empirical platform upon which psychiatry can now progress towards better understanding of disease mechanisms, better treatments, and better ways of targeting treatments to the patients most likely to benefit, thus paving the way for precision psychiatry.

Delineating significant genome-wide associations of variants with antipsychotic and antidepressant treatment response: implications for clinical pharmacogenomics

Background

Genome-wide association studies (GWAS) have significantly contributed to the association of many clinical conditions and phenotypic characteristics with genomic variants. The majority of these genomic findings have been deposited to the GWAS catalog. So far, findings uncovering associations of single nucleotide polymorphisms (SNPs) with treatment efficacy in mood disorders are encouraging, but not adequate.

Methods

Statistical, genomic, and literature information was retrieved from EBI’s GWAS catalog, while we also searched for potential clinical information/clinical guidelines in well-established pharmacogenomics databases regarding the assessed drug-SNP correlations of the present study.

Results

Here, we provide an overview of significant genome-wide associations of SNPs with the response to commonly prescribed antipsychotics and antidepressants. Up to date, this is the first study providing novel insight in previously reported pharmacogenomics associations for antipsychotic/antidepressant treatment. We also show that although there are published CPIC guidelines for antidepressant agents, as well as the FDA labels include genome-based drug prescription information for both antipsychotic and antidepressant treatments, there are no specific clinical guidelines for the assessed drug-SNP correlations of this study.

Conclusions

Our present findings suggest that more effort should be implemented towards identifying GWA-significant antipsychotic and antidepressant pharmacogenomics correlations. Moreover, additional functional studies are required in order to characterise the potential role of the assessed SNPs as biomarkers for the response of patients to antipsychotic/antidepressant treatment.

Population Pharmacokinetics of Clozapine: A Systematic Review

BACKGROUND AND OBJECTIVE

Clozapine is a second-generation antipsychotic drug that is considered the most effective treatment for refractory schizophrenia. Several clozapine population pharmacokinetic models have been introduced in the last decades. Thus, a systematic review was performed (i) to compare published pharmacokinetics models and (ii) to summarize and explore identified covariates influencing the clozapine pharmacokinetics models.

METHODS

A search of publications for population pharmacokinetic analyses of clozapine either in healthy volunteers or patients from inception to April 2019 was conducted in PubMed and SCOPUS databases. Reviews, methodology articles, in vitro and animal studies, and noncompartmental analysis were excluded.

RESULTS

Twelve studies were included in this review. Clozapine pharmacokinetics was described as one-compartment with first-order absorption and elimination in most of the studies. Significant interindividual variations of clozapine pharmacokinetic parameters were found in most of the included studies. Age, sex, smoking status, and cytochrome P450 1A2 were found to be the most common identified covariates affecting these parameters. External validation was only performed in one study to determine the predictive performance of the models.

CONCLUSIONS

Large pharmacokinetic variability remains despite the inclusion of several covariates. This can be improved by including other potential factors such as genetic polymorphisms, metabolic factors, and significant drug-drug interactions in a well-designed population pharmacokinetic model in the future, taking into account the incorporation of larger sample size and more stringent sampling strategy. External validation should also be performed to the previously published models to compare their predictive performances.

Pharmacogenomics of Antidepressant and Antipsychotic Treatment: How Far Have We Got and Where Are We Going?

In recent decades, very few new psychiatric drugs have entered the market. Thus, improvement in the use of antidepressant and antipsychotic therapy has to focus mainly on enhanced and more personalized treatment with the currently available drugs. One important aspect of such individualization is emphasizing interindividual differences in genes relevant to treatment, an area that can be termed neuropsychopharmacogenomics. Here, we review previous efforts to identify such critical genetic variants and summarize the results obtained to date. We conclude that most clinically relevant genetic variation is connected to phase I drug metabolism, in particular to genetic polymorphism of CYP2C19 and CYP2D6. To further improve individualized pharmacotherapy, there is a need to take both common and rare relevant mutations into consideration; we discuss the present and future possibilities of using whole genome sequencing to identify patient-specific genetic variation relevant to treatment in psychiatry. Translation of pharmacogenomic knowledge into clinical practice can be considered for specific drugs, but this requires education of clinicians, instructive guidelines, as well as full attention to polypharmacy and other clinically relevant factors. Recent large patient studies (n > 1,000) have replicated previous findings and produced robust evidence warranting the clinical utility of relevant genetic biomarkers. To further judge the clinical and financial benefits of preemptive genotyping in psychiatry, large prospective randomized trials are needed to quantify the value of genetic-based patient stratification in neuropsychopharmacotherapy and to demonstrate the cost-effectiveness of such interventions.

Functional neuroimaging in treatment resistant schizophrenia: A systematic review

Despite the availability of several drugs, about 30% of patients with schizophrenia still fail to respond properly to a course of appropriate antipsychotic treatment. Functional neuroimaging studies have shown widespread patterns of altered activation and functional connectivity in treatment-resistant schizophrenia (TRS). The aim of the present study was to examine the available functional magnetic resonance imaging studies investigating TRS and to identify common patterns of altered brain function that could predict the lack of response to antipsychotic treatment in this disorder. Alterations of activation and functional connectivity in fronto-temporal, cortico-striatal, default mode network and salience networks, and of their interplay, were associated with TRS. Our findings support the notion that large-scale network alterations present in schizophrenia lie in a continuum within treatment response with the most severe dysfunction in TRS. Few studies with small sample size and without adequate control group limit the generalizability of current literature. Future controlled longitudinal studies are needed to identify neuroimaging biomarkers of pharmacotherapy response to inform individual treatment selection and facilitate early clinical response.