Total Sleep Deprivation Increases Brain Age Prediction Reversibly in Multisite Samples of Young Healthy Adults.

Sleep loss pervasively affects the human brain at multiple levels. Age-related changes in several sleep characteristics indicate that reduced sleep quality is a frequent characteristic of aging. Conversely, sleep disruption may accelerate the aging process, yet it is not known what will happen to the age status of the brain if we can manipulate sleep conditions. To tackle this question, we used an approach of brain age to investigate whether sleep loss would cause age-related changes in the brain. We included MRI data of 134 healthy volunteers (mean chronological age of 25.3 between the age of 19 and 39 years, 42 females/92 males) from five datasets with different sleep conditions. Across three datasets with the condition of total sleep deprivation (>24 h of prolonged wakefulness), we consistently observed that total sleep deprivation increased brain age by 1-2 years regarding the group mean difference with the baseline. Interestingly, after one night of recovery sleep, brain age was not different from baseline. We also demonstrated the associations between the change in brain age after total sleep deprivation and the sleep variables measured during the recovery night. By contrast, brain age was not significantly changed by either acute (3 h time-in-bed for one night) or chronic partial sleep restriction (5 h time-in-bed for five continuous nights). Together, the convergent findings indicate that acute total sleep loss changes brain morphology in an aging-like direction in young participants and that these changes are reversible by recovery sleep.SIGNIFICANCE STATEMENT Sleep is fundamental for humans to maintain normal physical and psychological functions. Experimental sleep deprivation is a variable-controlling approach to engaging the brain among different sleep conditions for investigating the responses of the brain to sleep loss. Here, we quantified the response of the brain to sleep deprivation by using the change of brain age predictable with brain morphologic features. In three independent datasets, we consistently found increased brain age after total sleep deprivation, which was associated with the change in sleep variables. Moreover, no significant change in brain age was found after partial sleep deprivation in another two datasets. Our study provides new evidence to explain the brainwide effect of sleep loss in an aging-like direction.

Assessment of cerebral drug occupancy in humans using a single PET-scan: A [11C]UCB-J PET study.

PURPOSE: Here, we evaluate a PET displacement model with a Single-step and Numerical solution in healthy individuals using the synaptic vesicle glycoprotein (SV2A) PET-tracer [11C]UCB-J and the anti-seizure medication levetiracetam (LEV). We aimed to (1) validate the displacement model by comparing the brain LEV-SV2A occupancy from a single PET scan with the occupancy derived from two PET scans and the Lassen plot and (2) determine the plasma LEV concentration-SV2A occupancy curve in healthy individuals. METHODS: Eleven healthy individuals (five females, mean age 35.5 [range: 25-47] years) underwent two 120-min [11C]UCB-J PET scans where an LEV dose (5-30 mg/kg) was administered intravenously halfway through the first PET scan to partially displace radioligand binding to SV2A. Five individuals were scanned twice on the same day; the remaining six were scanned once on two separate days, receiving two identical LEV doses. Arterial blood samples were acquired to determine the arterial input function and plasma LEV concentrations. Using the displacement model, the SV2A-LEV target engagement was calculated and compared with the Lassen plot method. The resulting data were fitted with a single-site binding model. RESULTS: SV2A occupancies and VND estimates derived from the displacement model were not significantly different from the Lassen plot (p = 0.55 and 0.13, respectively). The coefficient of variation was 14.6% vs. 17.3% for the Numerical and the Single-step solution in Bland-Altman comparisons with the Lassen plot. The average half maximal inhibitory concentration (IC50), as estimated from the area under the curve of the plasma LEV concentration, was 12.5 µg/mL (95% CI: 5-25) for the Single-Step solution, 11.8 µg/mL (95% CI: 4-25) for the Numerical solution, and 6.3 µg/mL (95% CI: 0.08-21) for the Lassen plot. Constraining Emax to 100% did not significantly improve model fits. CONCLUSION: Plasma LEV concentration vs. SV2A occupancy can be determined in humans using a single PET scan displacement model. The average concentration of the three computed IC50 values ranges between 6.3 and 12.5 µg/mL. The next step is to use the displacement model to evaluate LEV occupancy and corresponding plasma concentrations in relation to treatment efficacy. CLINICAL TRIAL REGISTRATION: NCT05450822. Retrospectively registered 5 July 2022 https://clinicaltrials.gov/ct2/results? term=NCT05450822&Search=Search.

Effects of escitalopram on synaptic density in the healthy human brain: a randomized controlled trial.

Selective serotonin reuptake inhibitors (SSRIs) are widely used for treating neuropsychiatric disorders. However, the exact mechanism of action and why effects can take several weeks to manifest is not clear. The hypothesis of neuroplasticity is supported by preclinical studies, but the evidence in humans is limited. Here, we investigate the effects of the SSRI escitalopram on presynaptic density as a proxy for synaptic plasticity. In a double-blind placebo-controlled study (NCT04239339), 32 healthy participants with no history of psychiatric or cognitive disorders were randomized to receive daily oral dosing of either 20 mg escitalopram (n = 17) or a placebo (n = 15). After an intervention period of 3-5 weeks, participants underwent a [11C]UCB-J PET scan (29 with full arterial input function) to quantify synaptic vesicle glycoprotein 2A (SV2A) density in the hippocampus and the neocortex. Whereas we find no statistically significant group difference in SV2A binding after an average of 29 (range: 24-38) days of intervention, our secondary analyses show a time-dependent effect of escitalopram on cerebral SV2A binding with positive associations between [11C]UCB-J binding and duration of escitalopram intervention. Our findings suggest that brain synaptic plasticity evolves over 3-5 weeks in healthy humans following daily intake of escitalopram. This is the first in vivo evidence to support the hypothesis of neuroplasticity as a mechanism of action for SSRIs in humans and it offers a plausible biological explanation for the delayed treatment response commonly observed in patients treated with SSRIs. While replication is warranted, these results have important implications for the design of future clinical studies investigating the neurobiological effects of SSRIs.

Stable neural underpinnings of emotional cognition subgroups in patients newly diagnosed with bipolar disorder: A prospective fMRI study.

OBJECTIVES: This study aimed to investigate the neural underpinnings of emotional cognition subgroups in recently diagnosed patients with bipolar disorder (BD) and change over time over a 15-month follow-up period. METHODS: Patients and healthy controls (HC) underwent emotional and nonemotional cognitive assessments and functional magnetic resonance imaging (fMRI) at the baseline (BD n = 87; HC n = 65) and at 15-month follow-up (BD n = 44; HC n = 38). Neural activity during emotion reactivity and regulation in response to aversive pictures was assessed during fMRI. Patients were clustered into subgroups based on their emotional cognition and, with HC, were compared longitudinally on cognition and neural activity during emotion reactivity and regulation. RESULTS: Patients were optimally clustered into two subgroups: Subgroup 1 (n = 40, 46%) was characterized by heightened emotional reactivity in negative social scenarios, which persisted over time, but were otherwise cognitively intact. This subgroup exhibited stable left amygdala hyper-activity over time during emotion reactivity compared to subgroup 2. Subgroup 2 (n = 47, 54%) was characterized by global emotional cognitive impairments, including stable difficulties with emotion regulation over time. During emotion regulation across both time points, this group exhibited hypo-activity in the left dorsolateral prefrontal cortex. Additionally, patients in subgroup 2 had poorer nonemotional cognition, had more psychiatric hospital admissions and history of psychotic episodes than those in subgroup 1. CONCLUSIONS: Broad impairments in emotional cognition in approximately half of BD patients and associated nonemotional cognitive deficits may originate from insufficient recruitment of prefrontal resources, contributing to poorer clinical outcomes.

CCH attack frequency reduction after psilocybin correlates with hypothalamic functional connectivity.

OBJECTIVE: To evaluate the feasibility and prophylactic effect of psilocybin as well as its effects on hypothalamic functional connectivity (FC) in patients with chronic cluster headache (CCH). BACKGROUND: CCH is an excruciating and difficult-to-treat disorder with incompletely understood pathophysiology, although hypothalamic dysfunction has been implicated. Psilocybin may have beneficial prophylactic effects, but clinical evidence is limited. METHODS: In this small open-label clinical trial, 10 patients with CCH were included and maintained headache diaries for 10 weeks. Patients received three doses of peroral psilocybin (0.14 mg/kg) on the first day of weeks five, six, and seven. The first 4 weeks served as baseline and the last 4 weeks as follow-up. Hypothalamic FC was determined using functional magnetic resonance imaging the day before the first psilocybin dose and 1 week after the last dose. RESULTS: The treatment was well tolerated. Attack frequency was reduced by mean (standard deviation) 31% (31) from baseline to follow-up (pFWER = 0.008). One patient experienced 21 weeks of complete remission. Changes in hypothalamic-diencephalic FC correlated negatively with a percent change in attack frequency (pFWER = 0.03, R = -0.81), implicating this neural pathway in treatment response. CONCLUSION: Our results indicate that psilocybin may have prophylactic potential and implicates the hypothalamus in possible treatment response. Further clinical studies are warranted.

Psychedelics and Neural Plasticity: Therapeutic Implications.

Psychedelic drugs have reemerged as tools to treat several brain disorders. Cultural attitudes toward them are changing, and scientists are once again investigating the neural mechanisms through which these drugs impact brain function. The significance of this research direction is reflected by recent work, including work presented by these authors at the 2022 meeting of the Society for Neuroscience. As of 2022, there were hundreds of clinical trials recruiting participants for testing the therapeutic effects of psychedelics. Emerging evidence suggests that psychedelic drugs may exert some of their long-lasting therapeutic effects by inducing structural and functional neural plasticity. Herein, basic and clinical research attempting to elucidate the mechanisms of these compounds is showcased. Topics covered include psychedelic receptor binding sites, effects of psychedelics on gene expression, and on dendrites, and psychedelic effects on microcircuitry and brain-wide circuits. We describe unmet clinical needs and the current state of translation to the clinic for psychedelics, as well as other unanswered basic neuroscience questions addressable with future studies.

Synaptic density in aging mice measured by [18F]SynVesT-1 PET.

Synaptic alterations in certain brain structures are related to cognitive decline in neurodegeneration and in aging. Synaptic loss in many neurodegenerative diseases can be visualized by positron emission tomography (PET) imaging of synaptic vesicle glycoprotein 2A (SV2A). However, the use of SV2A PET for studying synaptic changes during aging is not particularly explored. Thus, in the present study, PET ligand [18F]SynVesT-1, which binds to SV2A, was used to investigate synaptic density at different ages in healthy mice. Wild type C57BL/6 mice divided into three age groups (4-5 months (n = 7), 12-14 months (n = 11), 17-19 months (n = 7)) were PET scanned with [18F]SynVesT-1. Brain retention of [18F]SynVesT-1 expressed as the volume of distribution (VIDIF) was calculated using an image-derived input function. Estimates of VIDIF were derived using either a one-tissue compartment model (1TCM), a two-tissue compartment model (2TCM), or the Logan plot with blood input to find the best-fit model for [18F]SynVesT-1. After the PET scans, tissue sections were immunostained for the detection of SV2A and neuronal markers. We found that [18F]SynVesT-1 data acquired 60 min post intravenously injection and analyzed with 1TCM described the brain pharmacokinetics of the radioligand in mice well. [18F]SynVesT-1 brain retention was lower in the oldest group of mice, indicating a decrease in synaptic density in this age group. However, no gradual age-dependent decrease in synaptic density at a region-specific level was observed. Immunostaining indicated that SV2A expression and neuron numbers were similar across all three age groups. In general, these data obtained in healthy aging mice are consistent with previous findings in humans where synaptic density appeared stable during aging up to a certain age, after which a small decrease is observed.

Prediction of brain age using structural magnetic resonance imaging: A comparison of accuracy and test-retest reliability of publicly available software packages.

Brain age prediction algorithms using structural magnetic resonance imaging (MRI) aim to assess the biological age of the human brain. The difference between a person's chronological age and the estimated brain age is thought to reflect deviations from a normal aging trajectory, indicating a slower or accelerated biological aging process. Several pre-trained software packages for predicting brain age are publicly available. In this study, we perform a comparison of such packages with respect to (1) predictive accuracy, (2) test-retest reliability, and (3) the ability to track age progression over time. We evaluated the six brain age prediction packages: brainageR, DeepBrainNet, brainage, ENIGMA, pyment, and mccqrnn. The accuracy and test-retest reliability were assessed on MRI data from 372 healthy people aged between 18.4 and 86.2 years (mean 38.7 ± 17.5 years). All packages showed significant correlations between predicted brain age and chronological age (r = 0.66-0.97, p < 0.001), with pyment displaying the strongest correlation. The mean absolute error was between 3.56 (pyment) and 9.54 years (ENIGMA). brainageR, pyment, and mccqrnn were superior in terms of reliability (ICC values between 0.94-0.98), as well as predicting age progression over a longer time span. Of the six packages, pyment and brainageR consistently showed the highest accuracy and test-retest reliability.

Stress Hormone Dynamics Are Coupled to Brain Serotonin 4 Receptor Availability in Unmedicated Patients With Major Depressive Disorder: A NeuroPharm Study.

BACKGROUND: A prominent finding in major depressive disorder (MDD) is distorted stress hormone dynamics, which is regulated by serotonergic brain signaling. An interesting feature of the cerebral serotonin system is the serotonin 4 receptor (5-HT4R), which is lower in depressed relative to healthy individuals and also has been highlighted as a promising novel antidepressant target. Here, we test the novel hypothesis that brain 5-HT4R availability in untreated patients with MDD is correlated with cortisol dynamics, indexed by the cortisol awakening response (CAR). Further, we evaluate if CAR changes with antidepressant treatment, including a selective serotonin reuptake inhibitor, and if pretreatment CAR can predict treatment outcome. METHODS: Sixty-six patients (76% women) with a moderate to severe depressive episode underwent positron emission tomography imaging with [11C]SB207145 for quantification of brain 5-HT4R binding using BPND as outcome. Serial home sampling of saliva in the first hour from awakening was performed to assess CAR before and after 8 weeks of antidepressant treatment. Treatment outcome was measured by change in Hamilton Depression Rating Scale 6 items. RESULTS: In the unmedicated depressed state, prefrontal and anterior cingulate cortices 5-HT4R binding was positively associated with CAR. CAR remained unaltered after 8 weeks of antidepressant treatment, and pretreatment CAR did not significantly predict treatment outcome. CONCLUSIONS: Our findings highlight a link between serotonergic disturbances in MDD and cortisol dynamics, which likely is involved in disease and treatment mechanisms. Further, our data support 5-HT4R agonism as a promising precision target in patients with MDD and disturbed stress hormone dynamics.

Acute sleep deprivation upregulates serotonin 2A receptors in the frontal cortex of mice via the immediate early gene Egr3.

Serotonin 2A receptors (5-HT2ARs) mediate the hallucinogenic effects of psychedelic drugs and are a key target of the leading class of medications used to treat psychotic disorders. These findings suggest that dysfunction of 5-HT2ARs may contribute to the symptoms of schizophrenia, a mental illness characterized by perceptual and cognitive disturbances. Indeed, numerous studies have found that 5-HT2ARs are reduced in the brains of individuals with schizophrenia. However, the mechanisms that regulate 5-HT2AR expression remain poorly understood. Here, we show that a physiologic environmental stimulus, sleep deprivation, significantly upregulates 5-HT2AR levels in the mouse frontal cortex in as little as 6-8 h (for mRNA and protein, respectively). This induction requires the activity-dependent immediate early gene transcription factor early growth response 3 (Egr3) as it does not occur in Egr3 deficient (-/-) mice. Using chromatin immunoprecipitation, we show that EGR3 protein binds to the promoter of Htr2a, the gene that encodes the 5-HT2AR, in the frontal cortex in vivo, and drives expression of in vitro reporter constructs via two EGR3 binding sites in the Htr2a promoter. These results suggest that EGR3 directly regulates Htr2a expression, and 5-HT2AR levels, in the frontal cortex in response to physiologic stimuli. Analysis of publicly available post-mortem gene expression data revealed that both EGR3 and HTR2A mRNA are reduced in the prefrontal cortex of schizophrenia patients compared to controls. Together these findings suggest a mechanism by which environmental stimuli alter levels of a brain receptor that may mediate the symptoms, and treatment, of mental illness.

Text mining of electronic health records can validate a register-based diagnosis of epilepsy and subgroup into focal and generalized epilepsy.

OBJECTIVE: Combining population-based health registries and electronic health records offers the opportunity to create large, phenotypically detailed patient cohorts of high quality. In this study, we used text mining of clinical notes to confirm International Classification of Diseases, 10th Revision (ICD-10)-registered epilepsy diagnoses and classify patients according to focal and generalized epilepsy types. METHODS: Using the Danish National Patient Registry, we identified patients who between 2006 and 2016 received an ICD-10 diagnosis of epilepsy. To validate the epilepsy diagnosis and stratify patients into focal and generalized epilepsy types, we constructed dictionaries for text mining-based extraction of clinical notes. Two physicians manually reviewed the clinical notes for a total of 527 patients and assigned epilepsy diagnoses, which were compared with the text-mined diagnoses. RESULTS: We identified 23 632 patients with an ICD-10 diagnosis of epilepsy, of whom 50% were registered with an unspecified epilepsy diagnosis. In total, 11 211 patients were considered likely to have epilepsy by text mining, with an F1 measure ranging from 82% to 90%. Manual review of the electronic health records for 310 patients revealed a false discovery rate of 29%. This rate was decreased to 4% by the text mining algorithm. The weighted average F1 measure for text mining-assigned epilepsy types was 79% (82% for focal and 76% for generalized epilepsy). Text mining successfully assigned a focal or generalized epilepsy type to 92% of the text mining-eligible patients registered with unspecified epilepsy. SIGNIFICANCE: Text mining of electronic health records can be used to establish a patient cohort with much higher likelihood of having a diagnosis of epilepsy and a focal or generalized epilepsy type compared to the cohort created from ICD-10 epilepsy codes alone. We believe the concept will be essential for future genome-wide and phenome-wide association studies and subsequently the development of precision medicine for epilepsy patients.

Aberrant resting-state functional connectivity underlies cognitive and functional impairments in remitted patients with bipolar disorder.

BACKGROUND: Bipolar disorder (BD) is commonly associated with cognitive impairments, that directly contribute to patients' functional disability. However, there is no effective treatment targeting cognition in BD. A key reason for the lack of pro-cognitive interventions is the limited insight into the brain correlates of cognitive impairments in these patients. This is the first study investigating the resting-state neural underpinnings of cognitive impairments in different neurocognitive subgroups of patients with BD. METHOD: Patients with BD in full or partial remission and healthy controls (final sample of n = 144 and n = 50, respectively) underwent neuropsychological assessment and resting-state functional magnetic resonance imaging. We classified the patients into cognitively impaired (n = 83) and cognitively normal (n = 61) subgroups using hierarchical cluster analysis of the four cognitive domains. We used independent component analysis (ICA) to investigate the differences between the neurocognitive subgroups and healthy controls in resting-state functional connectivity (rsFC) in the default mode network (DMN), executive central network (ECN), and frontoparietal network (FPN). RESULTS: Cognitively impaired patients displayed greater positive rsFC within the DMN and less negative rsFC within the ECN than healthy controls. Across cognitively impaired patients, lower positive connectivity within DMN and lower negative rsFC within ECN correlated with worse global cognitive performance. CONCLUSION: Cognitive impairments in BD seem to be associated with a hyper-connectivity within the DMN, which may explain the failure to suppress task-irrelevant DMN activity during the cognitive performance, and blunted anticorrelation in the ECN. Thus, aberrant connectivity within the DMN and ECN may serve as brain targets for pro-cognitive interventions.

AI-based dimensional neuroimaging system for characterizing heterogeneity in brain structure and function in major depressive disorder: COORDINATE-MDD consortium design and rationale.

BACKGROUND: Efforts to develop neuroimaging-based biomarkers in major depressive disorder (MDD), at the individual level, have been limited to date. As diagnostic criteria are currently symptom-based, MDD is conceptualized as a disorder rather than a disease with a known etiology; further, neural measures are often confounded by medication status and heterogeneous symptom states. METHODS: We describe a consortium to quantify neuroanatomical and neurofunctional heterogeneity via the dimensions of novel multivariate coordinate system (COORDINATE-MDD). Utilizing imaging harmonization and machine learning methods in a large cohort of medication-free, deeply phenotyped MDD participants, patterns of brain alteration are defined in replicable and neurobiologically-based dimensions and offer the potential to predict treatment response at the individual level. International datasets are being shared from multi-ethnic community populations, first episode and recurrent MDD, which are medication-free, in a current depressive episode with prospective longitudinal treatment outcomes and in remission. Neuroimaging data consist of de-identified, individual, structural MRI and resting-state functional MRI with additional positron emission tomography (PET) data at specific sites. State-of-the-art analytic methods include automated image processing for extraction of anatomical and functional imaging variables, statistical harmonization of imaging variables to account for site and scanner variations, and semi-supervised machine learning methods that identify dominant patterns associated with MDD from neural structure and function in healthy participants. RESULTS: We are applying an iterative process by defining the neural dimensions that characterise deeply phenotyped samples and then testing the dimensions in novel samples to assess specificity and reliability. Crucially, we aim to use machine learning methods to identify novel predictors of treatment response based on prospective longitudinal treatment outcome data, and we can externally validate the dimensions in fully independent sites. CONCLUSION: We describe the consortium, imaging protocols and analytics using preliminary results. Our findings thus far demonstrate how datasets across many sites can be harmonized and constructively pooled to enable execution of this large-scale project.

Psilocybin modulation of time-varying functional connectivity is associated with plasma psilocin and subjective effects.

BACKGROUND: Psilocin, the neuroactive metabolite of psilocybin, is a serotonergic psychedelic that induces an acute altered state of consciousness, evokes lasting changes in mood and personality in healthy individuals, and has potential as an antidepressant treatment. Examining the acute effects of psilocin on resting-state time-varying functional connectivity implicates network-level connectivity motifs that may underlie acute and lasting behavioral and clinical effects. AIM: Evaluate the association between resting-state time-varying functional connectivity (tvFC) characteristics and plasma psilocin level (PPL) and subjective drug intensity (SDI) before and right after intake of a psychedelic dose of psilocybin in healthy humans. METHODS: Fifteen healthy individuals completed the study. Before and at multiple time points after psilocybin intake, we acquired 10-minute resting-state blood-oxygen-level-dependent functional magnetic resonance imaging scans. Leading Eigenvector Dynamics Analysis (LEiDA) and diametrical clustering were applied to estimate discrete, sequentially active brain states. We evaluated associations between the fractional occurrence of brain states during a scan session and PPL and SDI using linear mixed-effects models. We examined associations between brain state dwell time and PPL and SDI using frailty Cox proportional hazards survival analysis. RESULTS: Fractional occurrences for two brain states characterized by lateral frontoparietal and medial fronto-parietal-cingulate coherence were statistically significantly negatively associated with PPL and SDI. Dwell time for these brain states was negatively associated with SDI and, to a lesser extent, PPL. Conversely, fractional occurrence and dwell time of a fully connected brain state partly associated with motion was positively associated with PPL and SDI. CONCLUSION: Our findings suggest that the acute perceptual psychedelic effects induced by psilocybin may stem from drug-level associated decreases in the occurrence and duration of lateral and medial frontoparietal connectivity motifs. We apply and argue for a modified approach to modeling eigenvectors produced by LEiDA that more fully acknowledges their underlying structure. Together these findings contribute to a more comprehensive neurobiological framework underlying acute effects of serotonergic psychedelics.

Brain serotonin transporter is associated with cognitive-affective biases in healthy individuals.

Cognitive affective biases describe the tendency to process negative information or positive information over the other. These biases can be modulated by changing extracellular serotonin (5-HT) levels in the brain, for example, by pharmacologically blocking and downregulating the 5-HT transporter (5-HTT), which remediates negative affective bias. This suggests that higher levels of 5-HTT are linked to a priority of negative information over positive, but this link remains to be tested in vivo in healthy individuals. We, therefore, evaluated the association between 5-HTT levels, as measured with [11 C]DASB positron emission tomography (PET), and affective biases, hypothesising that higher 5-HTT levels are associated with a more negative bias. We included 98 healthy individuals with measures of [11 C]DASB binding potential (BPND ) and affective biases using The Emotional Faces Identification Task by subtracting the per cent hit rate for happy from that of sad faces (EFITAB ). We evaluated the association between [11 C]DASB BPND and EFITAB in a linear latent variable model, with the latent variable (5-HTTLV ) modelled from [11 C]DASB BPND in the fronto-striatal and fronto-limbic networks implicated in affective cognition. We observed an inverse association between 5-HTTLV and EFITAB (ß = -8% EFITAB per unit 5-HTTLV , CI = -14% to -3%, p = .002). These findings show that higher 5-HTT levels are linked to a more negative bias in healthy individuals. High 5-HTT supposedly leads to high clearance of 5-HT, and thus, a negative bias could result from low extracellular 5-HT. Future studies must reveal if a similar inverse association exists in individuals with affective disorders.

Neuronal underpinnings of cognitive impairment in bipolar disorder: A large data-driven functional magnetic resonance imaging study.

OBJECTIVES: Cognitive impairment occurs in approximately 50% of remitted patients with bipolar disorder (BD). However, there exists no treatment with replicated and robust efficacy on cognition in BD. This is partially due to limited insight into the neuronal underpinnings of cognitive impairment in these patients. This is the first study to investigate neuronal underpinnings of cognitive impairment in a large functional magnetic resonance imaging (fMRI) dataset comparing neural activity patterns between distinct neurocognitive subgroups of partially or fully remitted patients with BD. METHODS: Patients (n = 153) and healthy controls (HC) (n = 52) underwent neuropsychological assessment and fMRI, during which they performed a verbal N-back working memory (WM) task. Based on hierarchical cluster analysis of neuropsychological test performance, patients were grouped into one of two neurocognitive subgroups (cognitively impaired, n = 91; cognitively normal compared to HC, n = 62) that were compared on WM-related neural activity. RESULTS: Cognitively impaired patients displayed WM-related hypo-activity in left dorsolateral prefrontal cortex and frontal and parietal regions within a cognitive control network (CCN) as well as hyper-activity in the default mode network (DMN) compared to cognitively normal patients. In contrast, cognitively normal patients only exhibited hypo-activity within a small cluster in the superior frontal gyrus relative to HC. CONCLUSIONS: Cognitive impairment in BD seems to originate from a failure to recruit key regions in the CCN and to suppress task-irrelevant DMN activity during cognitive performance. These results highlight modulation of aberrant dorsal prefrontal and DMN activity as a putative target for pro-cognitive treatment in BD.

Acute Traumatic Stress Screening Can Identify Patients and Their Partners at Risk for Posttraumatic Stress Disorder Symptoms After a Cardiac Arrest: A Multicenter Prospective Cohort Study.

BACKGROUND: Posttraumatic stress disorder (PTSD) is prevalent in patients who have had a cardiac arrest and their partners. Accordingly, acute traumatic stress screening is recommended, but its association with later PTSD symptoms has never been addressed in postresuscitation settings. OBJECTIVE: The aim of this study was to examine whether acute traumatic stress is associated with PTSD symptoms in patients who have had a cardiac arrest and their partners. METHODS: This multicenter longitudinal study of 141 patients and 97 partners measures acute traumatic stress at 3 weeks and PTSD symptoms at 3 months and 1 year after resuscitation, using the Impact of Event Scale. Linear regression models were used to evaluate the association between severity of acute traumatic stress and PTSD symptoms and post hoc to explore effects of group (patients/partners), age, and sex on acute traumatic stress severity. We categorized Impact of Event Scale scores higher than 26 at 3 months and 1 year as clinical severe PTSD symptoms . RESULTS: Higher acute traumatic stress severity is significantly positively associated with higher PTSD symptom severity at 3 months (patients and partners: P < .001) and 1 year (patients and partners: P < .001) postresuscitation, with the strongest association for women compared with men ( P = .03). Acute traumatic stress was higher in women compared with men across groups ( P = .02). Clinical severe PTSD symptoms were present in 26% to 28% of patients and 45% to 48% of partners. CONCLUSION: Experiencing a cardiac arrest may elicit clinical severe PTSD symptoms in patients, but particularly in their partners. Screening patients and partners for acute traumatic stress postresuscitation is warranted to identify those at increased risk of long-term PTSD symptoms.

A high-resolution in vivo atlas of the human brain's benzodiazepine binding site of GABAA receptors.

Gamma-aminobutyric acid (GABA) is the main inhibitory neurotransmitter in the human brain and plays a key role in several brain functions and neuropsychiatric disorders such as anxiety, epilepsy, and depression. For decades, several in vivo and ex vivo techniques have been used to highlight the mechanisms of the GABA system, however, no studies have currently combined the techniques to create a high-resolution multimodal view of the GABA system. Here, we present a quantitative high-resolution in vivo atlas of the human brain benzodiazepine receptor sites (BZR) located on postsynaptic ionotropic GABAA receptors (GABAARs), generated on the basis of in vivo [11C]flumazenil Positron Emission Tomography (PET) data. Next, based on ex vivo autoradiography data, we transform the PET-generated atlas from binding values into BZR protein density. Finally, we examine the brain regional association between BZR protein density and ex vivo mRNA expression for the 19 subunits in the GABAAR, including an estimation of the minimally required expression of mRNA levels for each subunit to translate into BZR protein. This represents the first publicly available quantitative high-resolution in vivo atlas of the spatial distribution of BZR densities in the healthy human brain. The atlas provides a unique neuroscientific tool as well as novel insights into the association between mRNA expression for individual subunits in the GABAAR and the BZR density at each location in the brain.

Common HTR2A variants and 5-HTTLPR are not associated with human in vivo serotonin 2A receptor levels.

The serotonin 2A receptor (5-HT2AR) is implicated in the pathophysiology and treatment of various psychiatric disorders. [18 F]altanserin and [11 C]Cimbi-36 positron emission tomography (PET) allow for high-resolution imaging of 5-HT2AR in the living human brain. Cerebral 5-HT2AR binding is strongly genetically determined, though the impact of specific variants is poorly understood. Candidate gene studies suggest that HTR2A single nucleotide polymorphisms including rs6311/rs6313, rs6314, and rs7997012 may influence risk for psychiatric disorders and mediate treatment response. Although known to impact in vitro expression of 5-HT2AR or other serotonin (5-HT) proteins, their effect on human in vivo brain 5-HT2AR binding has as of yet been insufficiently studied. We thus assessed the extent to which these variants and the commonly studied 5-HTTLPR predict neocortex in vivo 5-HT2AR binding in healthy adult humans. We used linear regression analyses and likelihood ratio tests in 197 subjects scanned with [18 F]altanserin or [11 C]Cimbi-36 PET. Although we observed genotype group differences in 5-HT2AR binding of up to ~10%, no genetic variants were statistically significantly predictive of 5-HT2AR binding in what is the largest human in vivo 5-HT2AR imaging genetics study to date. Thus, in vitro and post mortem results suggesting effects on 5-HT2AR expression did not carry over to the in vivo setting. To any extent these variants might affect clinical risk, our findings do not support that 5-HT2AR binding mediates such effects. Our observations indicate that these individual variants do not significantly contribute to genetic load on human in vivo 5-HT2AR binding.

Abnormal prefrontal cortex processing of reward prediction errors in recently diagnosed patients with bipolar disorder and their unaffected relatives.

OBJECTIVE: Bipolar disorder (BD) has been associated with abnormal reward functioning including pleasure-seeking and impulsivity. Here we sought to clarify whether these changes can be attributed to abnormalities in the neural processing of reward valuation or error prediction. Moreover, we tested whether abnormalities in these processes are associated with familial vulnerability to BD. METHODS: We obtained functional magnetic resonance imaging data from patients with recently diagnosed BD (n = 85), their unaffected first-degree relatives (n = 44), and healthy control participants (n = 66) while they were performing a monetary card game. We used a region-of-interest approach to test for group differences in the activation of the midbrain, the ventral striatum, and the prefrontal cortex during reward valuation and error prediction. RESULTS: Patients with BD showed decreased prediction error signal in ventrolateral prefrontal cortex and the unaffected relatives showed decreased prediction error signal in the supplementary motor area in comparison to healthy controls. There were no significant group differences in the activation of the ventral striatum during the task. In healthy controls, prediction error signal in dorsal anterior cingulate cortex correlated with an out-of-scanner measure of motor inhibition but this association was absent in patients and relatives. CONCLUSIONS: The findings indicate that abnormal reward processing in BD is primarily related to deficits in the engagement of prefrontal regions involved in inhibitory control during error prediction. In contrast, deficient activation in supplementary motor cortex involved in planning of movement emerged as a familial vulnerability to BD.