Identifying time-resolved features of nocturnal sleep characteristics of narcolepsy using machine learning.

The differential diagnosis of narcolepsy type 1, a rare, chronic, central disorder of hypersomnolence, is challenging due to overlapping symptoms with other hypersomnolence disorders. While recent years have seen significant growth in our understanding of nocturnal polysomnography narcolepsy type 1 features, there remains a need for improving methods to differentiate narcolepsy type 1 nighttime sleep features from those of individuals without narcolepsy type 1. We aimed to develop a machine learning framework for identifying sleep features to discriminate narcolepsy type 1 from clinical controls, narcolepsy type 2 and idiopathic hypersomnia. The population included polysomnography data from 350 drug-free individuals (114 narcolepsy type 1, 90 narcolepsy type 2, 105 idiopathic hypersomnia, and 41 clinical controls) collected at the National Reference Centers for Narcolepsy in Montpelier, France. Several sets of nocturnal sleep features were explored, as well as the value of time-resolving sleep architecture by analysing sleep per quarter-night. Several patterns of nighttime sleep evolution emerged that differed between narcolepsy type 1, clinical controls, narcolepsy type 2 and idiopathic hypersomnia, with increased nighttime instability observed in patients with narcolepsy type 1. Using machine learning models, we identified rapid eye movement sleep onset as the best single polysomnography feature to distinguish narcolepsy type 1 from controls, narcolepsy type 2 and idiopathic hypersomnia. By combining multiple feature sets capturing different aspects of sleep across quarter-night periods, we were able to further improve between-group discrimination and could identify the most discriminative sleep features. Our results highlight salient polysomnography features and the relevance of assessing their time-dependent changes during sleep that could aid diagnosis and measure the impact of novel therapeutics in future clinical trials.

Towards interpretable speech biomarkers: exploring MFCCs.

While speech biomarkers of disease have attracted increased interest in recent years, a challenge is that features derived from signal processing or machine learning approaches may lack clinical interpretability. As an example, Mel frequency cepstral coefficients (MFCCs) have been identified in several studies as a useful marker of disease, but are regarded as uninterpretable. Here we explore correlations between MFCC coefficients and more interpretable speech biomarkers. In particular we quantify the MFCC2 endpoint, which can be interpreted as a weighted ratio of low- to high-frequency energy, a concept which has been previously linked to disease-induced voice changes. By exploring MFCC2 in several datasets, we show how its sensitivity to disease can be increased by adjusting computation parameters.

Using a smartwatch and smartphone to assess early Parkinson's disease in the WATCH-PD study.

Digital health technologies can provide continuous monitoring and objective, real-world measures of Parkinson's disease (PD), but have primarily been evaluated in small, single-site studies. In this 12-month, multicenter observational study, we evaluated whether a smartwatch and smartphone application could measure features of early PD. 82 individuals with early, untreated PD and 50 age-matched controls wore research-grade sensors, a smartwatch, and a smartphone while performing standardized assessments in the clinic. At home, participants wore the smartwatch for seven days after each clinic visit and completed motor, speech and cognitive tasks on the smartphone every other week. Features derived from the devices, particularly arm swing, the proportion of time with tremor, and finger tapping, differed significantly between individuals with early PD and age-matched controls and had variable correlation with traditional assessments. Longitudinal assessments will inform the value of these digital measures for use in future clinical trials.

Distributional data analysis via quantile functions and its application to modeling digital biomarkers of gait in Alzheimer's Disease.

With the advent of continuous health monitoring with wearable devices, users now generate their unique streams of continuous data such as minute-level step counts or heartbeats. Summarizing these streams via scalar summaries often ignores the distributional nature of wearable data and almost unavoidably leads to the loss of critical information. We propose to capture the distributional nature of wearable data via user-specific quantile functions (QF) and use these QFs as predictors in scalar-on-quantile-function-regression (SOQFR). As an alternative approach, we also propose to represent QFs via user-specific L-moments, robust rank-based analogs of traditional moments, and use L-moments as predictors in SOQFR (SOQFR-L). These two approaches provide two mutually consistent interpretations: in terms of quantile levels by SOQFR and in terms of L-moments by SOQFR-L. We also demonstrate how to deal with multi-modal distributional data via Joint and Individual Variation Explained using L-moments. The proposed methods are illustrated in a study of association of digital gait biomarkers with cognitive function in Alzheimers disease. Our analysis shows that the proposed methods demonstrate higher predictive performance and attain much stronger associations with clinical cognitive scales compared to simple distributional summaries.

Scalar on time-by-distribution regression and its application for modelling associations between daily-living physical activity and cognitive functions in Alzheimer's Disease.

Wearable data is a rich source of information that can provide a deeper understanding of links between human behaviors and human health. Existing modelling approaches use wearable data summarized at subject level via scalar summaries in regression, temporal (time-of-day) curves in functional data analysis (FDA), and distributions in distributional data analysis (DDA). We propose to capture temporally local distributional information in wearable data using subject-specific time-by-distribution (TD) data objects. Specifically, we develop scalar on time-by-distribution regression (SOTDR) to model associations between scalar response of interest such as health outcomes or disease status and TD predictors. Additionally, we show that TD data objects can be parsimoniously represented via a collection of time-varying L-moments that capture distributional changes over the time-of-day. The proposed method is applied to the accelerometry study of mild Alzheimer's disease (AD). We found that mild AD is significantly associated with reduced upper quantile levels of physical activity, particularly during morning hours. In-sample cross validation demonstrated that TD predictors attain much stronger associations with clinical cognitive scales of attention, verbal memory, and executive function when compared to predictors summarized via scalar total activity counts, temporal functional curves, and quantile functions. Taken together, the present results suggest that SOTDR analysis provides novel insights into cognitive function and AD.

Safety, pharmacokinetics and quantitative EEG modulation of TAK-071, a novel muscarinic M1 receptor positive allosteric modulator, in healthy subjects.

AIMS: TAK-071 is a muscarinic M1 receptor positive allosteric modulator designed to have low cooperativity with acetylcholine. This was a first-in-human study to evaluate the safety, pharmacokinetics, and pharmacodynamics of TAK-071. METHODS: TAK-071 was administered as single and multiple doses in a randomized, double-blind, placebo-controlled, parallel-group design in healthy volunteers alone and in combination with donepezil. Laboratory, electrocardiogram (ECG) and electroencephalogram (EEG) evaluations were performed. Cerebrospinal fluid and blood samples were taken to evaluate the pharmacokinetics (PK), relative bioavailability and food effect. RESULTS: TAK-071 was safe and well tolerated, and no deaths or serious adverse events occurred. TAK-071 demonstrated a long mean (% coefficient of variation) half-life of 46.3 (25.2%) to 60.5 (51.5%) hours and excellent brain penetration following oral dosing. Coadministration with donepezil had no impact on the PK of either drug. There was no food effect on systemic exposure. Quantitative EEG analysis revealed that TAK-071 40-80 mg increased power in the 7-9 Hz range in the posterior electrode group with eyes open and 120-160 mg doses increased power in the 16-18 Hz range and reduced power in the 2-4 Hz range in central-posterior areas with eyes open and eyes closed. Functional connectivity was significantly reduced after TAK-071 at high doses and was enhanced with coadministration of donepezil under the eyes-closed condition. CONCLUSIONS: PK and safety profiles of TAK-071 were favorable, including those exceeding expected pharmacologically active doses based on preclinical data. When administered without donepezil TAK-071 was largely free of cholinergic adverse effects. Further clinical evaluation of TAK-071 is warranted.

Voice Biomarkers of Recovery From Acute Respiratory Illness.

Voice analysis is an emerging technology which has the potential to provide low-cost, at-home monitoring of symptoms associated with a variety of health conditions. While voice has received significant attention for monitoring neurological disease, few studies have focused on voice changes related to flu-like symptoms. Herein, we investigate the relationship between changes in acoustic features of voice and self-reported symptoms during recovery from a flu-like illness in a cohort of 29 subjects. Acoustic features were automatically extracted from "sick" and "well" visit data collected in the laboratory setting, and feature down-selection was used to identify those that change significantly between visits. The selected acoustic features were extracted from at-home data and used to construct a combined distance metric that correlated with self-reported symptoms (0.63 rank correlation). Changes in self-reported symptoms corresponding to 10% of the ordinal scale used in the study were detected with an area under the curve of 0.72. The results show that acoustic features derived from voice recordings may provide an objective measure for diagnosing and monitoring symptoms of respiratory illnesses.

The Effects of a Novel Non-catechol Dopamine Partial Agonist on Working Memory in the Aged Rhesus Monkey.

Aged-related declines in cognition, especially working memory and executive function, begin in middle-age and these abilities are known to be mediated by the prefrontal cortex (PFC) and more specifically the dopamine (DA) system within the PFC. In both humans and monkeys, there is significant evidence that the PFC is the first cortical region to change with age and the PFC appears to be particularly vulnerable to age-related loss of dopamine (DA). Therefore, the DA system is a strong candidate for therapeutic intervention to slow or reverse age related declines in cognition. In the present study, we administered a novel selective, potent, non-catechol DA D1 R agonist PF-6294 (Pfizer, Inc.) to aged female rhesus monkeys and assessed their performance on two benchmark tasks of working memory - the Delayed Non-match to Sample Task (DNMS) and Delayed Recognition Span Task (DRST). The DNMS task was administered first with the standard 10 s delay and then with 5 min delays, with and without distractors. The DRST was administered each day with four trials with unique sequences and one trial of a repeated sequence to assess evidence learning and retention. Overall, there was no significant effect of drug on performance on any aspect of the DNMS task. In contrast, we demonstrated that a middle range dose of PF-6294 significantly increased memory span on the DRST on the first and last days of testing and by the last day of testing the increased memory span was driven by the performance on the repeated trials.

Continuous gait monitoring discriminates community-dwelling mild Alzheimer's disease from cognitively normal controls.

INTRODUCTION: Few studies have explored whether gait measured continuously within a community setting can identify individuals with Alzheimer's disease (AD). This study tests the feasibility of this method to identify individuals at the earliest stage of AD. METHODS: Mild AD (n = 38) and cognitively normal control (CNC; n = 48) participants from the University of Kansas Alzheimer's Disease Center Registry wore a GT3x+ accelerometer continuously for 7 days to assess gait. Penalized logistic regression with repeated five-fold cross-validation followed by adjusted logistic regression was used to identify gait metrics with the highest predictive performance in discriminating mild AD from CNC. RESULTS: Variability in step velocity and cadence had the highest predictive utility in identifying individuals with mild AD. Metrics were also associated with cognitive domains impacted in early AD. DISCUSSION: Continuous gait monitoring may be a scalable method to identify individuals at-risk for developing dementia within large, population-based studies.

Assessment of brain cholesterol metabolism biomarker 24S-hydroxycholesterol in schizophrenia.

Plasma 24S-hydroxycholesterol mostly originates in brain tissue and likely reflects the turnover of cholesterol in the central nervous system. As cholesterol is disproportionally enriched in many key brain structures, 24S-hydroxycholesterol is a promising biomarker for psychiatric and neurologic disorders that impact brain structure. We hypothesized that, as schizophrenia patients have widely reported gray and white matter deficits, they would have abnormal levels of plasma 24S-hydroxycholesterol, and that plasma levels of 24S-hydroxycholesterol would be associated with brain structural and functional biomarkers for schizophrenia. Plasma levels of 24S-hydroxycholesterol were measured in 226 individuals with schizophrenia and 204 healthy controls. The results showed that levels of 24S-hydroxycholesterol were not significantly different between patients and controls. Age was significantly and negatively correlated with 24S-hydroxycholesterol in both groups, and in both groups, females had significantly higher levels of 24S-hydroxycholesterol compared to males. Levels of 24S-hydroxycholesterol were not related to average fractional anisotropy of white matter or cortical thickness, or to cognitive deficits in schizophrenia. Based on these results from a large sample and using multiple brain biomarkers, we conclude there is little to no value of plasma 24S-hydroxycholesterol as a brain metabolite biomarker for schizophrenia.

Characterization of PF-6142, a Novel, Non-Catecholamine Dopamine Receptor D1 Agonist, in Murine and Nonhuman Primate Models of Dopaminergic Activation.

Selective activation of dopamine D1 receptors remains a promising pro-cognitive therapeutic strategy awaiting robust clinical investigation. PF-6142 is a key example from a recently disclosed novel series of non-catechol agonists and partial agonists of the dopamine D1/5 receptors (D1R) that exhibit pharmacokinetic (PK) properties suitable for oral delivery. Given their reported potential for functionally biased signaling compared to known catechol-based selective agonists, and the promising rodent PK profile of PF-6142, we utilized relevant in vivo assays in male rodents and male and female non-human primates (NHP) to evaluate the pharmacology of this new series. Studies in rodents showed that PF-6142 increased locomotor activity and prefrontal cortex acetylcholine release, increased time spent in wakefulness, and desynchronized the EEG, like known D1R agonists. D1R selectivity of PF-6142 was supported by lack of effect in D1R knock-out mice and blocked response in the presence of the D1R antagonist SCH-23390. Further, PF-6142 improved performance in rodent models of NMDA receptor antagonist-induced cognitive dysfunction, such as MK-801-disrupted paired-pulse facilitation, and ketamine-disrupted working memory performance in the radial arm maze. Similarly, PF-6142 reversed ketamine-induced deficits in NHP performing the spatial delayed recognition task. Of importance, PF-6142 did not alter the efficacy of risperidone in assays predictive of antipsychotic-like effect in rodents including pre-pulse inhibition and conditioned avoidance responding. These data support the continued development of non-catechol based D1R agonists for the treatment of cognitive impairment associated with brain disorders including schizophrenia.

Development of digital biomarkers for resting tremor and bradykinesia using a wrist-worn wearable device.

Objective assessment of Parkinson's disease symptoms during daily life can help improve disease management and accelerate the development of new therapies. However, many current approaches require the use of multiple devices, or performance of prescribed motor activities, which makes them ill-suited for free-living conditions. Furthermore, there is a lack of open methods that have demonstrated both criterion and discriminative validity for continuous objective assessment of motor symptoms in this population. Hence, there is a need for systems that can reduce patient burden by using a minimal sensor setup while continuously capturing clinically meaningful measures of motor symptom severity under free-living conditions. We propose a method that sequentially processes epochs of raw sensor data from a single wrist-worn accelerometer by using heuristic and machine learning models in a hierarchical framework to provide continuous monitoring of tremor and bradykinesia. Results show that sensor derived continuous measures of resting tremor and bradykinesia achieve good to strong agreement with clinical assessment of symptom severity and are able to discriminate between treatment-related changes in motor states.

Continuous Monitoring Using a Wearable Device Detects Activity-Induced Heart Rate Changes After Administration of Amphetamine.

Wearable digital devices offer potential advantages over traditional methods for the collection of health-related information, including continuous collection of dense data while study subjects are ambulatory or in remote settings. We assessed the utility of collecting continuous actigraphy and cardiac monitoring by deploying two US Food and Drug Administration (FDA) 510(k)-cleared devices in a phase I clinical trial of a novel compound, which included the use of an amphetamine challenge. The Phillips Actiwatch Spectrum Pro (Actiwatch) was used to assess mobility and sleep. The Preventice BodyGuardian (BodyGuardian) was used for monitoring heart rate (HR) and respiratory rate (RR), via single-lead electrocardiogram (ECG) recordings, together with physical activity. We measured data collection rates, compared device readouts with conventional measures, and monitored changes in HR measures during the amphetamine challenge. Completeness of data collection was good for the Actiwatch (96%) and lower for the BodyGuardian (80%). A good correlation was observed between device and in-clinic measures for HR (r = 0.99; P < 0.001), but was poor for RR (r = 0.39; P = 0.004). Manual reviews of selected ECG strips corresponding to HR measures below, within, and above the normal range were consistent with BodyGuardian measurements. The BodyGuardian device detected clear HR responses after amphetamine administration while subjects were physically active, whereas conventional measures collected at predefined timepoints while subjects were resting and supine did not. Wearable digital technology shows promise for monitoring human subjects for physiologic changes and pharmacologic responses, although fit-for-purpose evaluation and validation continues to be important prior to the wider deployment of these devices.

Postmortem transcriptional profiling reveals widespread increase in inflammation in schizophrenia: a comparison of prefrontal cortex, striatum, and hippocampus among matched tetrads of controls with subjects diagnosed with schizophrenia, bipolar or major depressive disorder.

Psychiatric disorders such as schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD) arise from complex interactions between genetic and environmental factors. Common genetic variants associated with multiple psychiatric disorders suggest that shared genetic architecture could contribute to divergent clinical syndromes. To evaluate shared transcriptional alterations across connected brain regions, Affymetrix microarrays were used to profile postmortem dorsolateral prefrontal cortex (DLPFC), hippocampus, and associative striatum from 19 well-matched tetrads of subjects with SCZ, BD, MDD, or unaffected controls. SCZ subjects showed a substantial burden of differentially expressed genes across all examined brain regions with the greatest effects in hippocampus, whereas BD and MDD showed less robust alterations. Pathway analysis of transcriptional profiles compared across diagnoses demonstrated commonly enriched pathways between all three disorders in hippocampus, significant overlap between SCZ and BD in DLPFC, but no significant overlap of enriched pathways between disorders in striatum. SCZ samples showed increased expression of transcripts associated with inflammation across all brain regions examined, which was not evident in BD or MDD, or in rat brain following chronic dosing with antipsychotic drugs. Several markers of inflammation were confirmed by RT-PCR in hippocampus, including S100A8/9, IL-6, MAFF, APOLD1, IFITM3, and BAG3. A cytokine ELISA panel showed significant increases in IL-2 and IL-12p70 protein content in hippocampal tissue collected from same SCZ subjects when compared to matched control subjects. These data suggest an overlapping subset of dysregulated pathways across psychiatric disorders; however, a widespread increase in inflammation appears to be a specific feature of the SCZ brain and is not likely to be attributable to chronic antipsychotic drug treatment.

Pharmacological evaluation of clinically relevant concentrations of (2R,6R)-hydroxynorketamine.

Ketamine is a rapid-onset antidepressant whose efficacy long outlasts its pharmacokinetics. Multiple studies suggest ketamine's antidepressant effects require increased α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR)-dependent currents, which have recently been exclusively attributed to its N-methyl-d-aspartate receptor-inactive metabolite (2R,6R)-hydroxynorketamine ((2R,6R)-HNK). To investigate this AMPAR-activation claim further, we estimated and evaluated preclinically and clinically relevant unbound brain HNK concentrations (Cb,u). (2S,6S)-HNK and (2R,6R)-HNK were novelly synthesized, and their neuropharmacokinetic profiles were determined to project relevant Cb,u. Using concentrations (0.01-10 µM) bracketing the pertinent cross-species Cb,u, both compounds' AMPAR modulation was assessed in vitro by electrophysiological recordings and GluA1 surface expression. Neither (2S,6S)-HNK nor (2R,6R)-HNK bound orthosterically to or directly functionally activated AMPARs. (2R,6R)-HNK failed to evoke AMPAR-centric changes in any electrophysiological endpoint from adult rodent hippocampal slices. Conversely, time- and concentration-dependent increases in GluA1 expression occurred only with (2R,6R)-HNK (≥0.1 µM at ≥90 min). The (2R,6R)-HNK concentrations that increased GluA1 expression are consistent with its maximal Cb,u (0.92-4.84 µM) at reportedly efficacious doses of ketamine or (2R,6R)-HNK in mouse depression models, but ≥3-fold above its projected maximal human Cb,u (≤37.8 ±â€¯14.3 nM) following ketamine's clinically antidepressant infusion. These findings provide insight into the observed AMPAR-affecting (2R,6R)-HNK concentrations versus its exposures attained clinically at an antidepressant ketamine dose. To optimize any clinical study with (2R,6R)-HNK to fully assess its translational pharmacology, future preclinical work should test (2R,6R)-HNK concentrations and/or Cb,u of 0.01-0.1 µM to parallel its projected human Cb,u at a clinically antidepressant ketamine dose.

Abnormal clotting of the intrinsic/contact pathway in Alzheimer disease patients is related to cognitive ability.

Alzheimer disease (AD) is a neurodegenerative disorder characterized by extracellular ß-amyloid (Aß) deposition. Although peripheral inflammation and cerebrovascular pathology are reported in AD, there is a lack of plasma biomarkers in this field. Because the contact system is triggered in patient plasma, we hypothesized that the hemostasis profile could be a novel biomarker in AD. Here, we assessed the clotting profile in plasma from AD patients and age-matched controls. Utilizing clinically relevant assays, thromboelastography and activated partial thromboplastin time, we found impaired clot initiation and formation rate in AD patient plasma. These coagulation end points correlated with cerebrospinal fluid neurofilament-light levels and cognition and were more profound in younger AD patients. Ex vivo intrinsic clotting of plasma from AD mice expressing human amyloid precursor protein (APP) was also delayed in an age-dependent manner, suggesting that this phenotype is related to APP, the parent protein of Aß. Further analysis of coagulation factors in human plasma indicated that endogenous inhibitor(s) of factors XII and XI in AD plasma contribute to this delayed clotting. Together, these data suggest that delayed clotting in young AD patients is a novel biomarker and that therapies aimed to correct this phenotype might be beneficial in this patient population. Follow-up studies in additional AD patient cohorts are warranted to further evaluate these findings.

Impaired ß-arrestin recruitment and reduced desensitization by non-catechol agonists of the D1 dopamine receptor.

Selective activation of dopamine D1 receptors (D1Rs) has been pursued for 40 years as a therapeutic strategy for neurologic and psychiatric diseases due to the fundamental role of D1Rs in motor function, reward processing, and cognition. All known D1R-selective agonists are catechols, which are rapidly metabolized and desensitize the D1R after prolonged exposure, reducing agonist response. As such, drug-like selective D1R agonists have remained elusive. Here we report a novel series of selective, potent non-catechol D1R agonists with promising in vivo pharmacokinetic properties. These ligands stimulate adenylyl cyclase signaling and are efficacious in a rodent model of Parkinson's disease after oral administration. They exhibit distinct binding to the D1R orthosteric site and a novel functional profile including minimal receptor desensitization, reduced recruitment of ß-arrestin, and sustained in vivo efficacy. These results reveal a novel class of D1 agonists with favorable drug-like properties, and define the molecular basis for catechol-specific recruitment of ß-arrestin to D1Rs.

Passive immunotherapy targeting amyloid-ß reduces cerebral amyloid angiopathy and improves vascular reactivity.

Prominent cerebral amyloid angiopathy is often observed in the brains of elderly individuals and is almost universally found in patients with Alzheimer's disease. Cerebral amyloid angiopathy is characterized by accumulation of the shorter amyloid-ß isoform(s) (predominantly amyloid-ß40) in the walls of leptomeningeal and cortical arterioles and is likely a contributory factor to vascular dysfunction leading to stroke and dementia in the elderly. We used transgenic mice with prominent cerebral amyloid angiopathy to investigate the ability of ponezumab, an anti-amyloid-ß40 selective antibody, to attenuate amyloid-ß accrual in cerebral vessels and to acutely restore vascular reactivity. Chronic administration of ponezumab to transgenic mice led to a significant reduction in amyloid and amyloid-ß accumulation both in leptomeningeal and brain vessels when measured by intravital multiphoton imaging and immunohistochemistry. By enriching for cerebral vascular elements, we also measured a significant reduction in the levels of soluble amyloid-ß biochemically. We hypothesized that the reduction in vascular amyloid-ß40 after ponezumab administration may reflect the ability of ponezumab to mobilize an interstitial fluid pool of amyloid-ß40 in brain. Acutely, ponezumab triggered a significant and transient increase in interstitial fluid amyloid-ß40 levels in old plaque-bearing transgenic mice but not in young animals. We also measured a beneficial effect on vascular reactivity following acute administration of ponezumab, even in vessels where there was a severe cerebral amyloid angiopathy burden. Taken together, the beneficial effects ponezumab administration has on reducing the rate of cerebral amyloid angiopathy deposition and restoring cerebral vascular health favours a mechanism that involves rapid removal and/or neutralization of amyloid-ß species that may otherwise be detrimental to normal vessel function.

Evaluation of TrkB and BDNF transcripts in prefrontal cortex, hippocampus, and striatum from subjects with schizophrenia, bipolar disorder, and major depressive disorder.

Brain-derived neurotrophic factor (BDNF) signaling is integral to a range of neural functions, including synaptic plasticity and exhibits activity-dependent regulation of expression. As altered BDNF signaling has been implicated in multiple psychiatric diseases, here we report a quantitative reverse transcription polymerase chain reaction (RT-PCR) analysis of mRNAs encoding TrkB, total BDNF, and the four most abundant BDNF transcripts (I, IIc, IV, and VI) in postmortem tissue from matched tetrads of subjects with schizophrenia, bipolar disorder, or major depressive disorder (MDD) and healthy comparison subjects. In all three regions examined, dorsolateral prefrontal cortex (DLPFC), associative striatum and hippocampus, total BDNF mRNA levels did not differ in any disease state. In DLPFC, BDNF IIc was significantly lower in schizophrenia relative to healthy comparison subjects. In hippocampus, BDNF I, IIc, and VI were lower in subjects with both schizophrenia and bipolar disorder relative to comparison subjects. In striatum, TrkB mRNA was lower in bipolar disorder and MDD, while BDNF IIc was elevated in MDD, relative to comparison subjects. These data highlight potential alterations in BDNF signaling in the corticohippocampal circuit in schizophrenia, and within the striatum in mood disorders. Novel therapies aimed at improving BDNF-TrkB signaling may therefore have potential to impact on a range of psychiatric disorders.