Associations among plasma markers for N-methyl-d-aspartate receptor hypofunction, redox dysregulation, and insufficient myelination in patients with schizophrenia.

Background: Several hypotheses regarding the pathomechanisms of schizophrenia have been proposed. If schizophrenia is a unitary disease, then these pathological processes must be linked; however, if such links do not exist, schizophrenia may best be considered a group of disorders. Only a few studies have examined the relationships among these pathomechanisms. Herein, we examined the relationships among deficient myelination, NMDA receptor hypofunction, and metabolic dysregulation by measuring various plasma markers and examining their correlations. Methods: Plasma samples were collected from 90 patients with schizophrenia and 68 healthy controls. Concentrations of nardilysin (N-arginine dibasic convertase, NRDC), a positive regulator of myelination, the NMDA receptor co-agonist d-serine and glycine, various additional amino acids related to NMDA receptor transmission (glutamate, glutamine, and l-serine), and homocysteine (Hcy), were measured. Concentrations were compared using independent samples t-test or logistic regression, and associations were evaluated using Pearson's correlation coefficients. Results: Plasma glycine (t = 2.05, p = 0.042), l-serine (t = 2.25, p = 0.027), and homocysteine (t = 3.71, p < 0.001) concentrations were significantly higher in patients with schizophrenia compared to those in healthy controls. Logistic regression models using age, sex, smoking status, glutamine, glutamate, glycine, l-serine, d-serine, homocysteine, and NRDC as independent variables revealed significantly lower plasma d-serine (p = 0.024) and NRDC (p = 0.028), but significantly higher l-serine (p = 0.024) and homocysteine (p = 0.001) in patients with schizophrenia. Several unique correlations were found between NMDA receptor-related amino acids and NRDC in patients with schizophrenia compared to those in healthy controls, while no correlations were found between plasma homocysteine and other markers. No associations were found between plasma marker concentrations and disease status or cognitive function in patients with schizophrenia, except for a significant correlation between plasma glycine and full intelligence quotient. Conclusion: Reduced myelination and NMDA receptor hypofunction may be related to pathological mechanisms in schizophrenia, while homocysteine dysregulation appears to be an independent pathological process. These results suggest that schizophrenia may be a group of disorders with unique or partially overlapping etiologies.

Lithium response in bipolar disorder is associated with focal adhesion and PI3K-Akt networks: a multi-omics replication study.

Lithium is the gold standard treatment for bipolar disorder (BD). However, its mechanism of action is incompletely understood, and prediction of treatment outcomes is limited. In our previous multi-omics study of the Pharmacogenomics of Bipolar Disorder (PGBD) sample combining transcriptomic and genomic data, we found that focal adhesion, the extracellular matrix (ECM), and PI3K-Akt signaling networks were associated with response to lithium. In this study, we replicated the results of our previous study using network propagation methods in a genome-wide association study of an independent sample of 2039 patients from the International Consortium on Lithium Genetics (ConLiGen) study. We identified functional enrichment in focal adhesion and PI3K-Akt pathways, but we did not find an association with the ECM pathway. Our results suggest that deficits in the neuronal growth cone and PI3K-Akt signaling, but not in ECM proteins, may influence response to lithium in BD.

Activation of prefrontal parvalbumin interneurons ameliorates working memory deficit even under clinically comparable antipsychotic treatment in a mouse model of schizophrenia.

One of the critical unmet medical needs in schizophrenia is the treatment for cognitive deficits. However, the neural circuit mechanisms of them remain unresolved. Previous studies utilizing animal models of schizophrenia did not consider the fact that patients with schizophrenia generally cannot discontinue antipsychotic medication due to the high risk of relapse. Here, we used multi-dimensional approaches, including histological analysis of the prelimbic cortex (PL), LC-MS/MS-based in vivo dopamine D2 receptor occupancy analysis for antipsychotics, in vivo calcium imaging, and behavioral analyses of mice using chemogenetics to investigate neural mechanisms and potential therapeutic strategies for working memory deficit in a chronic phencyclidine (PCP) mouse model of schizophrenia. Chronic PCP administration led to alterations in excitatory and inhibitory synapses, specifically in dendritic spines of pyramidal neurons, vesicular glutamate transporter 1 (VGLUT1) positive terminals, and parvalbumin (PV) positive GABAergic interneurons located in layer 2-3 of the PL. Continuous administration of olanzapine, which achieved a sustained therapeutic window of dopamine D2 receptor occupancy (60-80%) in the striatum, did not ameliorate these synaptic abnormalities and working memory deficit in the chronic PCP-treated mice. We demonstrated that chemogenetic activation of PV neurons in the PL, as confirmed by in vivo calcium imaging, ameliorated working memory deficit in this model even under clinically comparable olanzapine treatment which by itself inhibited only PCP-induced psychomotor hyperactivity. Our study suggests that targeting prefrontal PV neurons could be a promising therapeutic intervention for cognitive deficits in schizophrenia in combination with antipsychotic medication.

Exploring the genetics of lithium response in bipolar disorders.

Background: Lithium (Li) remains the treatment of choice for bipolar disorders (BP). Its mood-stabilizing effects help reduce the long-term burden of mania, depression and suicide risk in patients with BP. It also has been shown to have beneficial effects on disease-associated conditions, including sleep and cardiovascular disorders. However, the individual responses to Li treatment vary within and between diagnostic subtypes of BP (e.g. BP-I and BP-II) according to the clinical presentation. Moreover, long-term Li treatment has been linked to adverse side-effects that are a cause of concern and non-adherence, including the risk of developing chronic medical conditions such as thyroid and renal disease. In recent years, studies by the Consortium on Lithium Genetics (ConLiGen) have uncovered a number of genetic factors that contribute to the variability in Li treatment response in patients with BP. Here, we leveraged the ConLiGen cohort (N=2,064) to investigate the genetic basis of Li effects in BP. For this, we studied how Li response and linked genes associate with the psychiatric symptoms and polygenic load for medical comorbidities, placing particular emphasis on identifying differences between BP-I and BP-II. Results: We found that clinical response to Li treatment, measured with the Alda scale, was associated with a diminished burden of mania, depression, substance and alcohol abuse, psychosis and suicidal ideation in patients with BP-I and, in patients with BP-II, of depression only. Our genetic analyses showed that a stronger clinical response to Li was modestly related to lower polygenic load for diabetes and hypertension in BP-I but not BP-II. Moreover, our results suggested that a number of genes that have been previously linked to Li response variability in BP differentially relate to the psychiatric symptomatology, particularly to the numbers of manic and depressive episodes, and to the polygenic load for comorbid conditions, including diabetes, hypertension and hypothyroidism. Conclusions: Taken together, our findings suggest that the effects of Li on symptomatology and comorbidity in BP are partially modulated by common genetic factors, with differential effects between BP-I and BP-II.

Lithium Response in Bipolar Disorder is Associated with Focal Adhesion and PI3K-Akt Networks: A Multi-omics Replication Study.

Lithium is the gold standard treatment for bipolar disorder (BD). However, its mechanism of action is incompletely understood, and prediction of treatment outcomes is limited. In our previous multi-omics study of the Pharmacogenomics of Bipolar Disorder (PGBD) sample combining transcriptomic and genomic data, we found that focal adhesion, the extracellular matrix (ECM), and PI3K-Akt signaling networks were associated with response to lithium. In this study, we replicated the results of our previous study using network propagation methods in a genome-wide association study of an independent sample of 2,039 patients from the International Consortium on Lithium Genetics (ConLiGen) study. We identified functional enrichment in focal adhesion and PI3K-Akt pathways, but we did not find an association with the ECM pathway. Our results suggest that deficits in the neuronal growth cone and PI3K-Akt signaling, but not in ECM proteins, may influence response to lithium in BD.

Association of polygenic score and the involvement of cholinergic and glutamatergic pathways with lithium treatment response in patients with bipolar disorder.

Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental health disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li+PGS) in patients with BD. To gain further insights into lithium's possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li+PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi+Gen: N = 2367) and replicated in the combined PsyCourse (N = 89) and BipoLife (N = 102) studies. The associations of Li+PGS and lithium treatment response - defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P < 0.05. Li+PGS was positively associated with lithium treatment response in the ConLi+Gen cohort, in both the categorical (P = 9.8 × 10-12, R2 = 1.9%) and continuous (P = 6.4 × 10-9, R2 = 2.6%) outcomes. Compared to bipolar patients in the 1st decile of the risk distribution, individuals in the 10th decile had 3.47-fold (95%CI: 2.22-5.47) higher odds of responding favorably to lithium. The results were replicated in the independent cohorts for the categorical treatment outcome (P = 3.9 × 10-4, R2 = 0.9%), but not for the continuous outcome (P = 0.13). Gene-based analyses revealed 36 candidate genes that are enriched in biological pathways controlled by glutamate and acetylcholine. Li+PGS may be useful in the development of pharmacogenomic testing strategies by enabling a classification of bipolar patients according to their response to treatment.

Immunogenetics of lithium response and psychiatric phenotypes in patients with bipolar disorder.

The link between bipolar disorder (BP) and immune dysfunction remains controversial. While epidemiological studies have long suggested an association, recent research has found only limited evidence of such a relationship. To clarify this, we investigated the contributions of immune-relevant genetic factors to the response to lithium (Li) treatment and the clinical presentation of BP. First, we assessed the association of a large collection of immune-related genes (4,925) with Li response, defined by the Retrospective Assessment of the Lithium Response Phenotype Scale (Alda scale), and clinical characteristics in patients with BP from the International Consortium on Lithium Genetics (ConLi+Gen, N = 2,374). Second, we calculated here previously published polygenic scores (PGSs) for immune-related traits and evaluated their associations with Li response and clinical features. We found several genes associated with Li response at p < 1×10- 4 values, including HAS3, CNTNAP5 and NFIB. Network and functional enrichment analyses uncovered an overrepresentation of pathways involved in cell adhesion and intercellular communication, which appear to converge on the well-known Li-induced inhibition of GSK-3ß. We also found various genes associated with BP's age-at-onset, number of mood episodes, and presence of psychosis, substance abuse and/or suicidal ideation at the exploratory threshold. These included RTN4, XKR4, NRXN1, NRG1/3 and GRK5. Additionally, PGS analyses suggested serum FAS, ECP, TRANCE and cytokine ligands, amongst others, might represent potential circulating biomarkers of Li response and clinical presentation. Taken together, our results support the notion of a relatively weak association between immunity and clinically relevant features of BP at the genetic level.

Association of Polygenic Score and the involvement of Cholinergic and Glutamatergic Pathways with Lithium Treatment Response in Patients with Bipolar Disorder.

Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li+PGS) in patients with BD. To gain further insights into lithium's possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li+PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi+Gen: N=2,367) and replicated in the combined PsyCourse (N=89) and BipoLife (N=102) studies. The associations of Li+PGS and lithium treatment response - defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P<����������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������.

HomotopicLI: Rationale, characteristics, and implications of a new threshold-free lateralization index of functional magnetic resonance imaging.

The reliable preoperative estimation of brain hemispheric asymmetry may be achieved through multiple lateralization indices using functional magnetic resonance imaging. Adding to our previously developed AveLI, we devised a novel threshold-free lateralization index, HomotopicLI, which computes a basic formula, (Left - Right) / (Left + Right), using voxel values of pairs located symmetrically in relation to the midsagittal line as the terms Left and Right, and averages them within the regions-of-interest. The study aimed to evaluate HomotopicLI before clinical applications. Data were collected from 56 healthy participants who performed four language tasks. We compared seven index types, including HomotopicLI, AveLI, and BaseLI; BaseLI was calculated using the sums of voxel values as the terms. Contrary to our expectations, HomotopicLI performed similarly to AveLI but better than BaseLI in detecting right dominance. A detailed analysis of unilaterally activated voxels of the homotopic pairs revealed that unilateral activation occurred more frequently on the right than on the left when HomotopicLI indicated right dominance. The voxel values during right unilateral activation were smaller than those in the left, causing right dominances in the homotopic pairs by HomotopicLI. These unique features provide an advantage in detecting residual, compensative functions spreading weakly in the non-dominant hemisphere.

Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: machine learning approach.

BACKGROUND: Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment. AIMS: To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder. METHOD: This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework. RESULTS: The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data. CONCLUSIONS: Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.

Combining schizophrenia and depression polygenic risk scores improves the genetic prediction of lithium response in bipolar disorder patients.

Lithium is the gold standard therapy for Bipolar Disorder (BD) but its effectiveness differs widely between individuals. The molecular mechanisms underlying treatment response heterogeneity are not well understood, and personalized treatment in BD remains elusive. Genetic analyses of the lithium treatment response phenotype may generate novel molecular insights into lithium's therapeutic mechanisms and lead to testable hypotheses to improve BD management and outcomes. We used fixed effect meta-analysis techniques to develop meta-analytic polygenic risk scores (MET-PRS) from combinations of highly correlated psychiatric traits, namely schizophrenia (SCZ), major depression (MD) and bipolar disorder (BD). We compared the effects of cross-disorder MET-PRS and single genetic trait PRS on lithium response. For the PRS analyses, we included clinical data on lithium treatment response and genetic information for n = 2283 BD cases from the International Consortium on Lithium Genetics (ConLi+Gen; www.ConLiGen.org ). Higher SCZ and MD PRSs were associated with poorer lithium treatment response whereas BD-PRS had no association with treatment outcome. The combined MET2-PRS comprising of SCZ and MD variants (MET2-PRS) and a model using SCZ and MD-PRS sequentially improved response prediction, compared to single-disorder PRS or to a combined score using all three traits (MET3-PRS). Patients in the highest decile for MET2-PRS loading had 2.5 times higher odds of being classified as poor responders than patients with the lowest decile MET2-PRS scores. An exploratory functional pathway analysis of top MET2-PRS variants was conducted. Findings may inform the development of future testing strategies for personalized lithium prescribing in BD.

HLA-DRB1 and HLA-DQB1 genetic diversity modulates response to lithium in bipolar affective disorders.

Bipolar affective disorder (BD) is a severe psychiatric illness, for which lithium (Li) is the gold standard for acute and maintenance therapies. The therapeutic response to Li in BD is heterogeneous and reliable biomarkers allowing patients stratification are still needed. A GWAS performed by the International Consortium on Lithium Genetics (ConLiGen) has recently identified genetic markers associated with treatment responses to Li in the human leukocyte antigens (HLA) region. To better understand the molecular mechanisms underlying this association, we have genetically imputed the classical alleles of the HLA region in the European patients of the ConLiGen cohort. We found our best signal for amino-acid variants belonging to the HLA-DRB1*11:01 classical allele, associated with a better response to Li (p < 1 × 10-3; FDR < 0.09 in the recessive model). Alanine or Leucine at position 74 of the HLA-DRB1 heavy chain was associated with a good response while Arginine or Glutamic acid with a poor response. As these variants have been implicated in common inflammatory/autoimmune processes, our findings strongly suggest that HLA-mediated low inflammatory background may contribute to the efficient response to Li in BD patients, while an inflammatory status overriding Li anti-inflammatory properties would favor a weak response.

Prediction of lithium response using genomic data.

Predicting lithium response prior to treatment could both expedite therapy and avoid exposure to side effects. Since lithium responsiveness may be heritable, its predictability based on genomic data is of interest. We thus evaluate the degree to which lithium response can be predicted with a machine learning (ML) approach using genomic data. Using the largest existing genomic dataset in the lithium response literature (n = 2210 across 14 international sites; 29% responders), we evaluated the degree to which lithium response could be predicted based on 47,465 genotyped single nucleotide polymorphisms using a supervised ML approach. Under appropriate cross-validation procedures, lithium response could be predicted to above-chance levels in two constituent sites (Halifax, Cohen's kappa 0.15, 95% confidence interval, CI [0.07, 0.24]; and Würzburg, kappa 0.2 [0.1, 0.3]). Variants with shared importance in these models showed over-representation of postsynaptic membrane related genes. Lithium response was not predictable in the pooled dataset (kappa 0.02 [- 0.01, 0.04]), although non-trivial performance was achieved within a restricted dataset including only those patients followed prospectively (kappa 0.09 [0.04, 0.14]). Genomic classification of lithium response remains a promising but difficult task. Classification performance could potentially be improved by further harmonization of data collection procedures.

Association of Attention-Deficit/Hyperactivity Disorder and Depression Polygenic Scores with Lithium Response: A Consortium for Lithium Genetics Study.

Response to lithium varies widely between individuals with bipolar disorder (BD). Polygenic risk scores (PRSs) can uncover pharmacogenomics effects and may help predict drug response. Patients (N = 2,510) with BD were assessed for long-term lithium response in the Consortium on Lithium Genetics using the Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder score. PRSs for attention-deficit/hyperactivity disorder (ADHD), major depressive disorder (MDD), and schizophrenia (SCZ) were computed using lassosum and in a model including all three PRSs and other covariates, and the PRS of ADHD (ß = -0.14; 95% confidence interval [CI]: -0.24 to -0.03; p value = 0.010) and MDD (ß = -0.16; 95% CI: -0.27 to -0.04; p value = 0.005) predicted worse quantitative lithium response. A higher SCZ PRS was associated with higher rates of medication nonadherence (OR = 1.61; 95% CI: 1.34-1.93; p value = 2e-7). This study indicates that genetic risk for ADHD and depression may influence lithium treatment response. Interestingly, a higher SCZ PRS was associated with poor adherence, which can negatively impact treatment response. Incorporating genetic risk of ADHD, depression, and SCZ in combination with clinical risk may lead to better clinical care for patients with BD.

Association of polygenic score for major depression with response to lithium in patients with bipolar disorder.

Lithium is a first-line medication for bipolar disorder (BD), but only one in three patients respond optimally to the drug. Since evidence shows a strong clinical and genetic overlap between depression and bipolar disorder, we investigated whether a polygenic susceptibility to major depression is associated with response to lithium treatment in patients with BD. Weighted polygenic scores (PGSs) were computed for major depression (MD) at different GWAS p value thresholds using genetic data obtained from 2586 bipolar patients who received lithium treatment and took part in the Consortium on Lithium Genetics (ConLi+Gen) study. Summary statistics from genome-wide association studies in MD (135,458 cases and 344,901 controls) from the Psychiatric Genomics Consortium (PGC) were used for PGS weighting. Response to lithium treatment was defined by continuous scores and categorical outcome (responders versus non-responders) using measurements on the Alda scale. Associations between PGSs of MD and lithium treatment response were assessed using a linear and binary logistic regression modeling for the continuous and categorical outcomes, respectively. The analysis was performed for the entire cohort, and for European and Asian sub-samples. The PGSs for MD were significantly associated with lithium treatment response in multi-ethnic, European or Asian populations, at various p value thresholds. Bipolar patients with a low polygenic load for MD were more likely to respond well to lithium, compared to those patients with high polygenic load [lowest vs highest PGS quartiles, multi-ethnic sample: OR = 1.54 (95% CI: 1.18-2.01) and European sample: OR = 1.75 (95% CI: 1.30-2.36)]. While our analysis in the Asian sample found equivalent effect size in the same direction: OR = 1.71 (95% CI: 0.61-4.90), this was not statistically significant. Using PGS decile comparison, we found a similar trend of association between a high genetic loading for MD and lower response to lithium. Our findings underscore the genetic contribution to lithium response in BD and support the emerging concept of a lithium-responsive biotype in BD.

Association of genetic variants at 22q11.2 chromosomal region with cognitive performance in Japanese patients with schizophrenia.

22q11.2 heterozygous multigene deletions confer an increased risk of schizophrenia with marked impairment of cognition. We explored whether genes on 22q11.2 are associated with cognitive performance in patients with idiopathic schizophrenia. A total of 240 schizophrenia patients and 240 healthy controls underwent the Japanese-language version of the Brief Assessment of Cognition in Schizophrenia (BACS) and were genotyped for 115 tag single-nucleotide polymorphisms (tag SNPs) at the 22q11.2 region using the golden gate assay (Illumina®). Associations between z-scores of the BACS cognitive domains and SNPs and haplotypes were analyzed using linear regression in PLINK 1.07. An additional set of 149 patients with bipolar disorder were included for cognitive assessment and selected SNPs were genotyped using real-time PCR. Patients with schizophrenia and bipolar disorder showed qualitatively comparable profiles of cognitive impairment across BACS subdomains, as revealed by significant correlation between the two groups in the resulting cognitive effect sizes relative to controls. rs4819522 (TBX1) and rs2238769 (UFD1L) were significantly and nominally associated, respectively, with symbol coding in patients with schizophrenia. Haplotype analyses revealed that haplotypes containing the A allele at rs4819522 and G allele at rs2238769 showed significant negative associations with symbol coding in patients with schizophrenia. There was no effect of any haplotypes on cognition in patients with bipolar disorder. Our results have implications for the understanding of the role of haplotypes of UFD1L and TBX1 genes associated with symbol coding in patients with schizophrenia. Further replication studies in a cohort of newly diagnosed patients and other ethnicities are warranted.

8-Hydroxylation and Glucuronidation of Mirtazapine in Japanese Psychiatric Patients: Significance of the Glucuronidation Pathway of 8-Hydroxy-Mirtazapine.

INTRODUCTION: To investigate the metabolism of mirtazapine (MIR) in Japanese psychiatric patients, we determined the plasma levels of MIR, N-desmethylmirtazapine (DMIR), 8-hydroxy-mirtazapine (8-OH-MIR), mirtazapine glucuronide (MIR-G), and 8-hydroxy-mirtazapine glucuronide (8-OH-MIR-G). METHODS: Seventy-nine Japanese psychiatric patients were treated with MIR for 1-8 weeks to achieve a steady-state concentration. Plasma levels of MIR, DMIR, and 8-OH-MIR were determined using high-performance liquid chromatography. Plasma concentrations of MIR-G and 8-OH-MIR-G were determined by total MIR and total 8-OH-MIR (i. e., concentrations after hydrolysis) minus unconjugated MIR and unconjugated 8-OH-MIR, respectively. Polymerase chain reaction was used to determine CYP2D6 genotypes. RESULTS: Plasma levels of 8-OH-MIR were lower than those of MIR and DMIR (median 1.42 nmol/L vs. 92.71 nmol/L and 44.96 nmol/L, respectively). The plasma levels (median) of MIR-G and 8-OH-MIR-G were 75.00 nmol/L and 111.60 nmol/L, giving MIR-G/MIR and 8-OH-MIR-G/8-OH-MIR ratios of 0.92 and 59.50, respectively. Multiple regression analysis revealed that smoking was correlated with the plasma MIR concentration (dose- and body weight-corrected, p=0.040) and that age (years) was significantly correlated with the plasma DMIR concentration (dose- and body weight-corrected, p=0.018). The steady-state plasma concentrations of MIR and its metabolites were unaffected by the number of CYP2D6*5 and CYP2D6*10 alleles. DISCUSSION: The plasma concentration of 8-OH-MIR was as low as 1.42 nmol/L, whereas 8-OH-MIR-G had an approximate 59.50 times higher concentration than 8-OH-MIR, suggesting a significant role for hydroxylation of MIR and its glucuronidation in the Japanese population.

Analysis of the Influence of microRNAs in Lithium Response in Bipolar Disorder.

Bipolar disorder (BD) is a common, highly heritable neuropsychiatric disease characterized by recurrent episodes of mania and depression. Lithium is the best-established long-term treatment for BD, even though individual response is highly variable. Evidence suggests that some of this variability has a genetic basis. This is supported by the largest genome-wide association study (GWAS) of lithium response to date conducted by the International Consortium on Lithium Genetics (ConLiGen). Recently, we performed the first genome-wide analysis of the involvement of miRNAs in BD and identified nine BD-associated miRNAs. However, it is unknown whether these miRNAs are also associated with lithium response in BD. In the present study, we therefore tested whether common variants at these nine candidate miRNAs contribute to the variance in lithium response in BD. Furthermore, we systematically analyzed whether any other miRNA in the genome is implicated in the response to lithium. For this purpose, we performed gene-based tests for all known miRNA coding genes in the ConLiGen GWAS dataset (n = 2,563 patients) using a set-based testing approach adapted from the versatile gene-based test for GWAS (VEGAS2). In the candidate approach, miR-499a showed a nominally significant association with lithium response, providing some evidence for involvement in both development and treatment of BD. In the genome-wide miRNA analysis, 71 miRNAs showed nominally significant associations with the dichotomous phenotype and 106 with the continuous trait for treatment response. A total of 15 miRNAs revealed nominal significance in both phenotypes with miR-633 showing the strongest association with the continuous trait (p = 9.80E-04) and miR-607 with the dichotomous phenotype (p = 5.79E-04). No association between miRNAs and treatment response to lithium in BD in either of the tested conditions withstood multiple testing correction. Given the limited power of our study, the investigation of miRNAs in larger GWAS samples of BD and lithium response is warranted.