This international guideline proposes improving clozapine package inserts worldwide by using ancestry-based dosing and titration. Adverse drug reaction (ADR) databases suggest that clozapine is the third most toxic drug in the United States (US), and it produces four times higher worldwide pneumonia mortality than that by agranulocytosis or myocarditis. For trough steady-state clozapine serum concentrations, the therapeutic reference range is narrow, from 350 to 600 ng/mL with the potential for toxicity and ADRs as concentrations increase. Clozapine is mainly metabolized by CYP1A2 (female non-smokers, the lowest dose; male smokers, the highest dose). Poor metabolizer status through phenotypic conversion is associated with co-prescription of inhibitors (including oral contraceptives and valproate), obesity, or inflammation with C-reactive protein (CRP) elevations. The Asian population (Pakistan to Japan) or the Americas’ original inhabitants have lower CYP1A2 activity and require lower clozapine doses to reach concentrations of 350 ng/mL. In the US, daily doses of 300–600 mg/day are recommended. Slow personalized titration may prevent early ADRs (including syncope, myocarditis, and pneumonia). This guideline defines six personalized titration schedules for inpatients: 1) ancestry from Asia or the original people from the Americas with lower metabolism (obesity or valproate) needing minimum therapeutic dosages of 75–150 mg/day, 2) ancestry from Asia or the original people from the Americas with average metabolism needing 175–300 mg/day, 3) European/Western Asian ancestry with lower metabolism (obesity or valproate) needing 100–200 mg/day, 4) European/Western Asian ancestry with average metabolism needing 250–400 mg/day, 5) in the US with ancestries other than from Asia or the original people from the Americas with lower clozapine metabolism (obesity or valproate) needing 150–300 mg/day, and 6) in the US with ancestries other than from Asia or the original people from the Americas with average clozapine metabolism needing 300–600 mg/day. Baseline and weekly CRP monitoring for at least four weeks is required to identify any inflammation, including inflammation secondary to clozapine rapid titration.

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Schizophrenia (SCZ) and bipolar disorder (BPD) are polygenic disorders with many genes contributing to their etiologies. The aim of this investigation was to search for dysregulated molecular and cellular pathways for these disorders as well as psychosis. We conducted a blood-based microarray investigation in two independent samples with SCZ and BPD from San Diego (SCZ = 13, BPD = 9, control = 8) and Taiwan (SCZ = 11, BPD = 14, control = 16). Diagnostic groups were compared to controls, and subjects with a history of psychosis [PSYCH(+): San Diego (n = 6), Taiwan (n = 14)] were compared to subjects without such history [PSYCH(−): San Diego (n = 11), Taiwan (n = 14)]. Analyses of covariance comparing mean expression levels on a gene-by-gene basis were conducted to generate the top 100 significantly dysregulated gene lists for both samples by each diagnostic group. Gene lists were imported into Ingenuity Pathway Analysis (IPA) software. Results showed the ubiquitin proteasome pathway (UPS) was listed in the top ten canonical pathways for BPD and psychosis diagnostic groups across both samples with a considerably low likelihood of a chance occurrence (P = 0.001). No overlap in dysregulated genes populating these pathways was observed between the two independent samples. Findings provide preliminary evidence of UPS dysregulation in BPD and psychosis as well as support further investigation of the UPS and other molecular and cellular pathways for potential biomarkers for SCZ, BPD, and/or psychosis.

Efforts to understand the biological processes that increase susceptibility to methamphetamine (METH) use disorders (i.e., abuse, dependence, and psychosis) have uncovered several putative genotypic variants. However, to date a synthesis of this information has not been conducted. Thus, systematic searches of the current literature were undertaken for genetic-association studies of METH use disorders. Each gene's chromosomal location, function, and examined polymorphic markers were extracted. Frequencies, odds ratios and 95% confidence intervals for risk alleles, as well as sample size and power, were calculated. We uncovered 38 studies examining 39 genes, of which 18 were found to have a significant genotypic, allelic, and/or haplotypic association with METH use disorders. Three genes (COMT, DRD4, and GABRA1) were associated with METH abuse, nine (ARRB2, BDNF, CYP2D6, GLYT1, GSTM1, GSTP1, PDYN, PICK1, and SLC22A3) with METH dependence, two (AKT1 and GABRG2) with METH abuse/dependence, and four (DTNBP1, OPRM1, SNCA, and SOD2) with METH psychosis. Limitations related to phenotypic classification, statistical power, and potential publication bias in the current literature were noted. Similar to other behavioral, psychiatric, and substance use disorders, the genetic epidemiology of METH use disorders is complex and likely polygenic. National and international collaborative efforts are needed to increase the availability of large population-based samples and improve upon the power to detect genetic associations of small magnitude. Further, replication of the findings reviewed here along with further development of more rigorous methodologies and reporting protocols will aid in delineating the complex genetic epidemiology of METH use disorders.

The ATP-binding cassette family of transporter proteins, subfamily B (MDR/TAP), member 1 (ABCB1) (P-glycoprotein) transporter is a key component of the blood–brain barrier. Many antidepressants are subject to ABCB1 efflux. Functional polymorphisms of ABCB1 may influence central nervous system bioavailability of antidepressants subject to efflux. Single-nucleotide polymorphisms (SNPs) at rs1045642 (C3435T) of ABCB1 have been associated with efflux pump efficiency. This may explain part of the interindividual variation in antidepressant dose needed to remit. Individuals (N=113) with DSM-IV (Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition) major depressive disorder (MDD) were treated with escitalopram (ESC) or venlafaxine (VEN) over 8 weeks. The17-item Hamilton Depression Rating Scale was assessed serially, blind to genotype. SNP rs1045642 of ABCB1 along with two SNPs previously reported to be in linkage disequilibrium with it (rs2032582 and rs1128503) were genotyped. Demographic features, clinical features, P450 metabolizer status and 5-HTTLPR (serotonin-transporter-linked promoter region) genotype were controlled for. Carriers of rs1045642 TT needed on average 11 mg of ESC to remit, whereas TC and CC carriers required 24 and 19 mg, respectively (P=0.0001). This equates to a 2.0- (95% confidence interval=1.5–3.4; P<0.001) fold greater ESC dose needed to remit for C carriers compared with TT carriers at rs1045642. Of VEN-treated subjects carrying TT genotype at rs1045642, 73.3% remitted compared with 12.5% for CC genotype (odds ratio=6.69; 95% confidence interval=1.72–25.9, P=0.006). These data suggest that antidepressant dose needed to remit can be predicted by an ABCB1 SNP. This has the potential clinical translation implications for dose selection and remission from MDD.

OPRM1, which codes for the mu-opioid receptor, is the most frequently studied candidate gene for opioid dependence. Despite numerous allelic association studies, no definitive conclusion has been reached regarding the role of OPRM1 polymorphisms in determining risk for opioid dependence. We attempted to resolve this by conducting a family-based association study and meta-analysis which may be more robust and powerful, respectively, than traditional case-control analyses. First, we genotyped three single nucleotide polymorphisms (SNPs) of OPRM1 in 1208 individuals from 473 Han Chinese families ascertained on the basis of having two or more siblings with DSM-IV-defined opioid dependence. The Val6Ala and Arg111His SNPs were detected, but with low minor allele frequencies (0.002 and 0.001, respectively). The Asn40Asp SNP was more informative (minor allele frequency: 0.419), but no significant evidence was observed for either a dominant (p=0.810) or additive (p=0.406) effect of this polymorphism on risk for opioid dependence. In addition, a meta-analysis of case-control studies of opioid dependence was performed, and found a similar lack of evidence for an association with the Asn40Asp SNP (p=0.859). Although a role of OPRM1 polymorphisms in determining risk for opioid dependence cannot be entirely discounted, a major contribution of the Asn40Asp polymorphism seems unlikely. Further analysis is warranted in samples from specific ancestral groups. In addition, it is critical that other OPRM1 variants, including all haplotype-tagging and amino-acid-coding SNPs, be tested for an influence on risk for opioid dependence, since the Asn40Asp polymorphism is only one of several hundred known mutations in the gene.

Objective Transcriptomic biomarkers of psychiatric diseases obtained from a query of peripheral tissues that are clinically accessible (e.g., blood cells instead of post-mortem brain tissue) have substantial practical appeal to discern the molecular subtypes of common complex diseases such as major psychosis. To this end, spliceome-profiling is a new methodological approach that has considerable conceptual relevance for discovery and clinical translation of novel biomarkers for psychiatric illnesses. Advances in microarray technology now allow for improved sensitivity in measuring the transcriptome while simultaneously querying the “exome” (all exons) and “spliceome” (all alternatively spliced variants). The present study aimed to evaluate the feasibility of spliceome-profiling to discern transcriptomic biomarkers of psychosis. Methods We measured exome and spliceome expression in peripheral blood mononuclear cells from 13 schizophrenia patients, nine bipolar disorder patients, and eight healthy control subjects. Each diagnostic group was compared to each other, and the combined group of bipolar disorder and schizophrenia patients was also compared to the control group. Furthermore, we compared subjects with a history of psychosis to subjects without such history. Results After applying Bonferroni corrections for the 21,866 full-length gene transcripts analyzed, we found significant interactions between diagnostic group and exon identity, consistent with group differences in rates or types of alternative splicing. Relative to the control group, 18 genes in the bipolar disorder group, eight genes in the schizophrenia group, and 15 genes in the combined bipolar disorder and schizophrenia group appeared differentially spliced. Importantly, thirty-three genes showed differential splicing patterns between the bipolar disorder and schizophrenia groups. More frequent exon inclusion and/or over-expression was observed in psychosis. Finally, these observations are reconciled with an analysis of the ontologies, the pathways and the protein domains significantly over-represented among the alternatively spliced genes, several of which support prior discoveries. Conclusions To our knowledge, this is the first blood-based spliceome-profiling study of schizophrenia and bipolar disorder to be reported. The battery of alternatively spliced genes and exons identified in this discovery-oriented exploratory study, if replicated, may have potential utility to discern the molecular subtypes of psychosis. Spliceome-profiling, as a new methodological approach in transcriptomics, warrants further work to evaluate its utility in personalized medicine. Potentially, this approach could also permit the future development of tissue-sampling methodologies in a form that is more acceptable to patients and thereby allow monitoring of dynamic and time-dependent plasticity in disease severity and response to therapeutic interventions in clinical psychiatry.

Early reports of clinical utility are published. The current evidence base for antidepressant pharmacogenetics is, however, not yet empirically robust enough to inform routine prescribing guidelines. Over the coming years, genetically guided versus unguided trials will help determine if antidepressant pharmacogenetics merits more widespread application.