Cytochrome P450 interactions are common and consequential in Massachusetts hospital discharges.

Despite the recognition that drug-drug interactions contribute substantially to preventable health-care costs, the prevalence of such interactions related to the cytochrome P450 system in clinical practice remains poorly characterized. This study drew retrospective hospital discharge cohorts from a large health claims data set and a large health system data set. For every hospital discharge, frequency of co-occurrence of substrates and inducers or inhibitors at cytochrome P450 2D6, 2C19, 3A4 and 1A2 were determined. A total of 124 520 individuals in the state of Massachusetts (health claims cohort) and 77 026 individuals in two large academic medical centers (electronic health record (EHR) cohort) were examined. In the claims cohort, 35 157 (28.2%) exhibited at least one CYP450 drug-drug interaction at hospital discharge, whereas in the EHR cohort, 36 750 (47.7%) had at least one interaction. The most commonly affected CYP450 systems were 2C19 and 2D6, with putative interactions observed in at least 10% of individuals at discharge in each cohort. Odds of hospital readmission within 90 days among those discharged with at least one interaction were 10-16% greater, with mean health-care cost $574/month greater over the subsequent year, after adjusting for age, sex, insurance type, total number of medications prescribed, Charlson comorbidity score and presence or absence of a psychiatric diagnosis. These two distinct clinical data types show that CYP450 drug-drug interactions are prevalent and associated with greater probability of early hospital readmission and greater health-care cost, despite the widespread availability and application of drug-drug interaction checking software.

New insights into the pharmacogenomics of antidepressant response from the GENDEP and STAR*D studies: rare variant analysis and high-density imputation.

Genome-wide association studies have generally failed to identify polymorphisms associated with antidepressant response. Possible reasons include limited coverage of genetic variants that this study tried to address by exome genotyping and dense imputation. A meta-analysis of Genome-Based Therapeutic Drugs for Depression (GENDEP) and Sequenced Treatment Alternatives to Relieve Depression (STAR*D) studies was performed at the single-nucleotide polymorphism (SNP), gene and pathway levels. Coverage of genetic variants was increased compared with previous studies by adding exome genotypes to previously available genome-wide data and using the Haplotype Reference Consortium panel for imputation. Standard quality control was applied. Phenotypes were symptom improvement and remission after 12 weeks of antidepressant treatment. Significant findings were investigated in NEWMEDS consortium samples and Pharmacogenomic Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) for replication. A total of 7062 950 SNPs were analyzed in GENDEP (n=738) and STAR*D (n=1409). rs116692768 (P=1.80e-08, ITGA9 (integrin α9)) and rs76191705 (P=2.59e-08, NRXN3 (neurexin 3)) were significantly associated with symptom improvement during citalopram/escitalopram treatment. At the gene level, no consistent effect was found. At the pathway level, the Gene Ontology (GO) terms GO: 0005694 (chromosome) and GO: 0044427 (chromosomal part) were associated with improvement (corrected P=0.007 and 0.045, respectively). The association between rs116692768 and symptom improvement was replicated in PGRN-AMPS (P=0.047), whereas rs76191705 was not. The two SNPs did not replicate in NEWMEDS. ITGA9 codes for a membrane receptor for neurotrophins and NRXN3 is a transmembrane neuronal adhesion receptor involved in synaptic differentiation. Despite their meaningful biological rationale for being involved in antidepressant effect, replication was partial. Further studies may help in clarifying their role.

Patient-specific models of microglia-mediated engulfment of synapses and neural progenitors.

Engulfment of synapses and neural progenitor cells (NPCs) by microglia is critical for the development and maintenance of proper brain circuitry, and has been implicated in neurodevelopmental as well as neurodegenerative disease etiology. We have developed and validated models of these mechanisms by reprogramming microglia-like cells from peripheral blood mononuclear cells, and combining them with NPCs and neurons derived from induced pluripotent stem cells to create patient-specific cellular models of complement-dependent synaptic pruning and elimination of NPCs. The resulting microglia-like cells express appropriate markers and function as primary human microglia, while patient-matched macrophages differ markedly. As a demonstration of disease-relevant application, we studied the role of C4, recently implicated in schizophrenia, in engulfment of synaptic structures by human microglia. The ability to create complete patient-specific cellular models of critical microglial functions utilizing samples taken during a single clinical visit will extend the ability to model central nervous system disease while facilitating high-throughput screening.

Prevalence and implications of cytochrome P450 substrates in Massachusetts hospital discharges.

The cytochrome P450 (CYP450) system of drug-metabolizing enzymes may contribute to individual variation in drug response. We examined prevalence of CYP450 substrates at hospital discharge for patients in two cohorts: insurance claims of Massachusetts residents and the medical records of two academic medical centers. The claims cohort included 47 473 individuals (38.2%) treated with at least one CYP450 2D6, 2C19, 3A4 or 1A2 substrate. The electronic medical records cohort included 45 905 individuals (57.4%) treated with at least one substrate. In adjusted models, substrates of CYP450 2D6 and 2C19 were associated with greater risk for 90-day readmission in both cohorts (odds ratios of 1.104 and 1.128 (P<0.001), respectively). Presence of any CYP450 substrate was associated with increased monthly medical costs (+$397, P<0.003). These analyses of more than 300 000 admissions using two different cohorts and data types indicate that CYP450 substrates are associated with greater readmission rates and greater health-care cost.

Prevalence of current anxiety disorders in people with bipolar disorder during euthymia: a meta-analysis.

BACKGROUND: Anxiety disorders are highly prevalent in people with bipolar disorder, but it is not clear how many have anxiety disorders even at times when they are free of major mood episodes. We aimed to establish what proportion of euthymic individuals with bipolar disorder meet diagnostic criteria for anxiety disorders. METHOD: We performed a random-effects meta-analysis of prevalence rates of current DSM-III- and DSM-IV-defined anxiety disorders (panic disorder, agoraphobia, social anxiety disorder, generalized anxiety disorder, specific phobia, obsessive-compulsive disorder, post-traumatic stress disorder, and anxiety disorder not otherwise specified) in euthymic adults with bipolar disorder in studies published by 31 December 2015. RESULTS: Across 10 samples with 2120 individuals with bipolar disorder, 34.7% met diagnostic criteria for one or more anxiety disorders during euthymia [95% confidence interval (CI) 23.9-45.5%]. Direct comparison of 189 euthymic individuals with bipolar disorder and 17 109 population controls across three studies showed a 4.6-fold increase (risk ratio 4.60, 95% CI 2.37-8.92, p < 0.001) in prevalence of anxiety disorders in those with bipolar disorder. CONCLUSIONS: These findings suggest that anxiety disorders are common in people with bipolar disorder even when their mood is adequately controlled. Euthymic people with bipolar disorder should be routinely assessed for anxiety disorders and anxiety-focused treatment should be initiated if indicated.

Functional implications of a psychiatric risk variant within CACNA1C in induced human neurons.

Psychiatric disorders have clear heritable risk. Several large-scale genome-wide association studies have revealed a strong association between susceptibility for psychiatric disorders, including bipolar disease, schizophrenia and major depression, and a haplotype located in an intronic region of the L-type voltage-gated calcium channel (VGCC) subunit gene CACNA1C (peak associated SNP rs1006737), making it one of the most replicable and consistent associations in psychiatric genetics. In the current study, we used induced human neurons to reveal a functional phenotype associated with this psychiatric risk variant. We generated induced human neurons, or iN cells, from more than 20 individuals harboring homozygous risk genotypes, heterozygous or homozygous non-risk genotypes at the rs1006737 locus. Using these iNs, we performed electrophysiology and quantitative PCR experiments that demonstrated increased L-type VGCC current density as well as increased mRNA expression of CACNA1C in iNs homozygous for the risk genotype, compared with non-risk genotypes. These studies demonstrate that the risk genotype at rs1006737 is associated with significant functional alterations in human iNs, and may direct future efforts at developing novel therapeutics for the treatment of psychiatric disease.

Contributions of the social environment to first-onset and recurrent mania.

In treated cohorts, individuals with bipolar disorder are more likely to report childhood adversities and recent stressors than individuals without bipolar disorder; similarly, in registry-based studies, childhood adversities are more common among individuals who later become hospitalized for bipolar disorder. Because these types of studies rely on treatment-seeking samples or hospital diagnoses, they leave unresolved the question of whether or not social experiences are involved in the etiology of bipolar disorder. We investigated the role of childhood adversities and adulthood stressors in liability for bipolar disorder using data from the National Epidemiologic Survey on Alcohol and Related Conditions (n=33 375). We analyzed risk for initial-onset and recurrent DSM-IV (Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition) manic episodes during the study's 3-year follow-up period. Childhood physical abuse and sexual maltreatment were associated with significantly higher risks of both first-onset mania (odds ratio (OR) for abuse: 2.23; 95% confidence interval (CI)=1.71, 2.91; OR for maltreatment: 2.10; CI=1.55, 2.83) and recurrent mania (OR for abuse: 1.55; CI=1.00, 2.40; OR for maltreatment: 1.60; CI=1.00, 2.55). In addition, past-year stressors in the domains of interpersonal instability and financial hardship were associated with a significantly higher risk of incident and recurrent mania. Exposure to childhood adversity potentiated the effects of recent stressors on adult mania. Our findings demonstrate a role of social experiences in the initial onset of bipolar disorder, as well as in its prospective course, and are consistent with etiologic models of bipolar disorder that implicate deficits in developmentally established stress-response pathways.

Prenatal antidepressant exposure is associated with risk for attention-deficit hyperactivity disorder but not autism spectrum disorder in a large health system.

Previous studies suggested that risk for Autism Spectrum Disorder (ASD) may be increased in children exposed to antidepressants during the prenatal period. The disease specificity of this risk has not been addressed and the possibility of confounding has not been excluded. Children with ASD or attention-deficit hyperactivity disorder (ADHD) delivered in a large New England health-care system were identified from electronic health records (EHR), and each diagnostic group was matched 1:3 with children without ASD or ADHD. All children were linked with maternal health data using birth certificates and EHRs to determine prenatal medication exposures. Multiple logistic regression was used to examine association between prenatal antidepressant exposures and ASD or ADHD risk. A total of 1377 children diagnosed with ASD and 2243 with ADHD were matched with healthy controls. In models adjusted for sociodemographic features, antidepressant exposure prior to and during pregnancy was associated with ASD risk, but risk associated with exposure during pregnancy was no longer significant after controlling for maternal major depression (odds ratio (OR) 1.10 (0.70-1.70)). Conversely, antidepressant exposure during but not prior to pregnancy was associated with ADHD risk, even after adjustment for maternal depression (OR 1.81 (1.22-2.70)). These results suggest that the risk of autism observed with prenatal antidepressant exposure is likely confounded by severity of maternal illness, but further indicate that such exposure may still be associated with ADHD risk. This risk, modest in absolute terms, may still be a result of residual confounding and must be balanced against the substantial consequences of untreated maternal depression.

Dysregulation of miR-34a links neuronal development to genetic risk factors for bipolar disorder.

Bipolar disorder (BD) is a heritable neuropsychiatric disorder with largely unknown pathogenesis. Given their prominent role in brain function and disease, we hypothesized that microRNAs (miRNAs) might be of importance for BD. Here we show that levels of miR-34a, which is predicted to target multiple genes implicated as genetic risk factors for BD, are increased in postmortem cerebellar tissue from BD patients, as well as in BD patient-derived neuronal cultures generated by reprogramming of human fibroblasts into induced neurons or into induced pluripotent stem cells (iPSCs) subsequently differentiated into neurons. Of the predicted miR-34a targets, we validated the BD risk genes ankyrin-3 (ANK3) and voltage-dependent L-type calcium channel subunit beta-3 (CACNB3) as direct miR-34a targets. Using human iPSC-derived neuronal progenitor cells, we further show that enhancement of miR-34a expression impairs neuronal differentiation, expression of synaptic proteins and neuronal morphology, whereas reducing endogenous miR-34a expression enhances dendritic elaboration. Taken together, we propose that miR-34a serves as a critical link between multiple etiological factors for BD and its pathogenesis through the regulation of a molecular network essential for neuronal development and synaptogenesis.

Characterization of bipolar disorder patient-specific induced pluripotent stem cells from a family reveals neurodevelopmental and mRNA expression abnormalities.

Bipolar disorder (BD) is a common neuropsychiatric disorder characterized by chronic recurrent episodes of depression and mania. Despite evidence for high heritability of BD, little is known about its underlying pathophysiology. To develop new tools for investigating the molecular and cellular basis of BD, we applied a family-based paradigm to derive and characterize a set of 12 induced pluripotent stem cell (iPSC) lines from a quartet consisting of two BD-affected brothers and their two unaffected parents. Initially, no significant phenotypic differences were observed between iPSCs derived from the different family members. However, upon directed neural differentiation, we observed that CXCR4 (CXC chemokine receptor-4) expressing central nervous system (CNS) neural progenitor cells (NPCs) from both BD patients compared with their unaffected parents exhibited multiple phenotypic differences at the level of neurogenesis and expression of genes critical for neuroplasticity, including WNT pathway components and ion channel subunits. Treatment of the CXCR4(+) NPCs with a pharmacological inhibitor of glycogen synthase kinase 3, a known regulator of WNT signaling, was found to rescue a progenitor proliferation deficit in the BD patient NPCs. Taken together, these studies provide new cellular tools for dissecting the pathophysiology of BD and evidence for dysregulation of key pathways involved in neurodevelopment and neuroplasticity. Future generation of additional iPSCs following a family-based paradigm for modeling complex neuropsychiatric disorders in conjunction with in-depth phenotyping holds promise for providing insights into the pathophysiological substrates of BD and is likely to inform the development of targeted therapeutics for its treatment and ideally prevention.

Proposed DSM-5 mixed features are associated with greater likelihood of remission in out-patients with major depressive disorder.

BACKGROUND: Draft DSM-5 criteria for a mixed major depressive episode have been proposed, but their predictive validity has not yet been established. We hypothesized that such symptoms would be associated with poorer antidepressant treatment outcomes. METHOD: We examined outcomes among individuals with major depressive disorder participating in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study, an effectiveness study conducted at primary and specialty care centers in the USA. Mixed features were derived from the six self-report items of the mania subscale of the Psychiatric Diagnosis Screening Questionnaire. Primary analyses examined the association between the presence of at least two of these in the 6 months before study entry, and remission across up to four sequential treatment trials, as well as adverse outcomes. RESULTS: Of the 2397 subjects with a major depressive episode of at least 6 months' duration, 449 (18.7%) reported at least two mixed symptoms. The presence of such symptoms was associated with a greater likelihood of remission across up to four sequential treatments, which persisted after adjustment for potential confounding clinical and demographic variables (adjusted hazard ratio 1.16, 95% confidence interval 1.03-1.28). Two individual items, expansive mood and cheerfulness, were strongly associated with a greater likelihood of remission. CONCLUSIONS: Proposed DSM-5 mixed state features were associated with a greater rather than a lesser likelihood of remission. While unexpected, this result suggests the potential utility of further investigation of depressive mixed states in major depression.

Pharmacogenetic investigation of response to duloxetine treatment in generalized anxiety disorder.

We examined genetic associations with duloxetine response in generalized anxiety disorder (GAD). Three pooled studies in patients with GAD receiving duloxetine 60-120 mg per day (N=164) or placebo (N=95) were used. Associations between 825 single-nucleotide polymorphisms (SNPs) in 61 candidate genes with change in Hamilton Anxiety Scale scores were examined with set-based testing (adjusted for the number of SNPs within each gene); sets with two-sided adjusted P≤0.05 were examined using repeated measure analysis. Follow-up analysis explored associations of these SNPs with change in Hamilton Rating Scale for Depression-Anxiety Subscale in a 6-week study in duloxetine-treated patients with major depressive disorder (MDD) (N=241). Variants in corticotropin-releasing hormone receptor 1 (CRHR1), dopamine receptor D3 (DRD3), nuclear receptor subfamily group C, member 1 (NR3C1) and phosphodiesterase 1A (PDE1A) were associated with duloxetine response in GAD. Only rs4792888 in CRHR1 showed modest evidence of association with duloxetine response in MDD (P=0.029 in GAD, P=0.054 in MDD). In conclusion, CRHR1 variation merits investigation in pathophysiology of anxiety and its treatment response.

A genome-wide association study of attempted suicide.

The heritable component to attempted and completed suicide is partly related to psychiatric disorders and also partly independent of them. Although attempted suicide linkage regions have been identified on 2p11-12 and 6q25-26, there are likely many more such loci, the discovery of which will require a much higher resolution approach, such as the genome-wide association study (GWAS). With this in mind, we conducted an attempted suicide GWAS that compared the single-nucleotide polymorphism (SNP) genotypes of 1201 bipolar (BP) subjects with a history of suicide attempts to the genotypes of 1497 BP subjects without a history of suicide attempts. In all, 2507 SNPs with evidence for association at P<0.001 were identified. These associated SNPs were subsequently tested for association in a large and independent BP sample set. None of these SNPs were significantly associated in the replication sample after correcting for multiple testing, but the combined analysis of the two sample sets produced an association signal on 2p25 (rs300774) at the threshold of genome-wide significance (P=5.07 × 10(-8)). The associated SNPs on 2p25 fall in a large linkage disequilibrium block containing the ACP1 (acid phosphatase 1) gene, a gene whose expression is significantly elevated in BP subjects who have completed suicide. Furthermore, the ACP1 protein is a tyrosine phosphatase that influences Wnt signaling, a pathway regulated by lithium, making ACP1 a functional candidate for involvement in the phenotype. Larger GWAS sample sets will be required to confirm the signal on 2p25 and to identify additional genetic risk factors increasing susceptibility for attempted suicide.

Depression symptom dimensions as predictors of antidepressant treatment outcome: replicable evidence for interest-activity symptoms.

BACKGROUND: Symptom dimensions have not yet been comprehensively tested as predictors of the substantial heterogeneity in outcomes of antidepressant treatment in major depressive disorder. METHOD: We tested nine symptom dimensions derived from a previously published factor analysis of depression rating scales as predictors of outcome in 811 adults with moderate to severe depression treated with flexibly dosed escitalopram or nortriptyline in Genome-based Therapeutic Drugs for Depression (GENDEP). The effects of symptom dimensions were tested in mixed-effect regression models that controlled for overall initial depression severity, age, sex and recruitment centre. Significant results were tested for replicability in 3637 adult out-patients with non-psychotic major depression treated with citalopram in level I of Sequenced Treatment Alternatives to Relieve Depression (STAR*D). RESULTS: The interest-activity symptom dimension (reflecting low interest, reduced activity, indecisiveness and lack of enjoyment) at baseline strongly predicted poor treatment outcome in GENDEP, irrespective of overall depression severity, antidepressant type and outcome measure used. The prediction of poor treatment outcome by the interest-activity dimension was robustly replicated in STAR*D, independent of a comprehensive list of baseline covariates. CONCLUSIONS: Loss of interest, diminished activity and inability to make decisions predict poor outcome of antidepressant treatment even after adjustment for overall depression severity and other clinical covariates. The prominence of such symptoms may require additional treatment strategies and should be accounted for in future investigations of antidepressant response.

Using electronic medical records to enable large-scale studies in psychiatry: treatment resistant depression as a model.

BACKGROUND: Electronic medical records (EMR) provide a unique opportunity for efficient, large-scale clinical investigation in psychiatry. However, such studies will require development of tools to define treatment outcome. METHOD: Natural language processing (NLP) was applied to classify notes from 127 504 patients with a billing diagnosis of major depressive disorder, drawn from out-patient psychiatry practices affiliated with multiple, large New England hospitals. Classifications were compared with results using billing data (ICD-9 codes) alone and to a clinical gold standard based on chart review by a panel of senior clinicians. These cross-sectional classifications were then used to define longitudinal treatment outcomes, which were compared with a clinician-rated gold standard. RESULTS: Models incorporating NLP were superior to those relying on billing data alone for classifying current mood state (area under receiver operating characteristic curve of 0.85-0.88 v. 0.54-0.55). When these cross-sectional visits were integrated to define longitudinal outcomes and incorporate treatment data, 15% of the cohort remitted with a single antidepressant treatment, while 13% were identified as failing to remit despite at least two antidepressant trials. Non-remitting patients were more likely to be non-Caucasian (p<0.001). CONCLUSIONS: The application of bioinformatics tools such as NLP should enable accurate and efficient determination of longitudinal outcomes, enabling existing EMR data to be applied to clinical research, including biomarker investigations. Continued development will be required to better address moderators of outcome such as adherence and co-morbidity.

Translating biomarkers to clinical practice.

Biomarkers are the measurable characteristics of an individual that may represent risk factors for a disease or outcome, or that may be indicators of disease progression or of treatment-associated changes. In general, the process by which biomarkers, once identified, might be translated into clinical practice has received scant attention in recent psychiatric literature. A body of work in diagnostic development suggests a framework for evaluating and validating novel biomarkers, but this work may be unfamiliar to clinical and translational researchers in psychiatry. Therefore, this review focuses on the steps that might follow the identification of putative biomarkers. It first addresses standard approaches to characterizing biomarker performance, followed by demonstrations of how a putative biomarker might be shown to have clinical relevance. Finally, it addresses ways in which a biomarker-based test might be validated for clinical application in terms of efficacy and cost-effectiveness.

Promoting resilience in healthcare workers during the COVID-19 pandemic with a brief online intervention.

INTRODUCTION: The psychological wellbeing of healthcare workers has been impacted by the high levels of stress many have experienced during the Coronavirus Disease 2019 (COVID-19) pandemic. This study aimed to examine the feasibility and acceptability of a brief online course focused on introducing evidence-based skills that could increase resilience and decreases emotional distress in healthcare workers during the pandemic. MATERIALS AND METHODS: Employees of a large healthcare system completed a mental health survey at baseline, and then one month and two months after some employees participated in an online resilience-enhancement course consisting of three 12-19 min videos focused on mindfulness, mentalization, and self-compassion. RESULTS: A total of 554 participants completed the baseline survey, endorsing moderate to high levels of emotional distress. Of those who completed all three assessments and participated in the course (n = 38), significant improvements in resilience and reductions in emotional distress were found one and two months later, in comparison to those who did not participate in the course (n = 110). DISCUSSION: These findings suggest that a brief, online intervention can improve the mental health of healthcare workers during a crisis such as the COVID-19 pandemic.

Personality and bipolar disorder: dissecting state and trait associations between mood and personality.

BACKGROUND: Some personality characteristics have previously been associated with an increased risk for psychiatric disorder. Longitudinal studies are required in order to tease apart temporary (state) and enduring (trait) differences in personality among individuals with bipolar disorder (BD). This study aimed to determine whether there is a characteristic personality profile in BD, and whether associations between BD and personality are best explained by state or trait effects. METHOD: A total of 2247 participants in the Systematic Treatment Enhancement Program for Bipolar Disorder study completed the NEO Five-Factor Inventory administered at study entry, and at 1 and 2 years. RESULTS: Personality in BD was characterized by high neuroticism (N) and openness (O), and low agreeableness (A), conscientiousness (C) and extraversion (E). This profile was replicated in two independent samples, and openness was found to distinguish BD from major depressive disorder. Latent growth modeling demonstrated that manic symptoms were associated with increased E and decreased A, and depressed symptoms with higher N and lower E, A, C and O. During euthymic phases, high N and low E scores predicted a future depression-prone course. CONCLUSIONS: While there are clear state effects of mood on self-reported personality, personality variables during euthymia predict future course of illness. Personality disturbances in extraversion, neuroticism and openness may be enduring characteristics of patients with BD.