Longitudinal changes in resting-state functional connectivity as markers of vulnerability or resilience in first-degree relatives of patients with bipolar disorder.

BACKGROUND: There is a significant contribution of genetic factors to the etiology of bipolar disorder (BD). Unaffected first-degree relatives of patients (UR) with BD are at increased risk of developing mental disorders and may manifest cognitive impairments and alterations in brain functional and connective dynamics, akin to their affected relatives. METHODS: In this prospective longitudinal study, resting-state functional connectivity was used to explore stable and progressive markers of vulnerability i.e. abnormalities shared between UR and BD compared to healthy controls (HC) and resilience i.e. features unique to UR compared to HC and BD in full or partial remission (UR n = 72, mean age = 28.0 ± 7.2 years; HC n = 64, mean age = 30.0 ± 9.7 years; BD patients n = 91, mean age = 30.6 ± 7.7 years). Out of these, 34 UR, 48 BD, and 38 HC were investigated again following a mean time of 1.3 ± 0.4 years. RESULTS: At baseline, the UR showed lower connectivity values within the default mode network (DMN), frontoparietal network, and the salience network (SN) compared to HC. This connectivity pattern in UR remained stable over the follow-up period and was not present in BD, suggesting a resilience trait. The UR further demonstrated less negative connectivity between the DMN and SN compared to HC, abnormality that remained stable over time and was also present in BD, suggesting a vulnerability marker. CONCLUSION: Our findings indicate the coexistence of both vulnerability-related abnormalities in resting-state connectivity, as well as adaptive changes possibly promoting resilience to psychopathology in individual at familial risk.

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.

Multimodal prediction of residual consciousness in the intensive care unit: the CONNECT-ME study.

Functional MRI (fMRI) and EEG may reveal residual consciousness in patients with disorders of consciousness (DoC), as reflected by a rapidly expanding literature on chronic DoC. However, acute DoC is rarely investigated, although identifying residual consciousness is key to clinical decision-making in the intensive care unit (ICU). Therefore, the objective of the prospective, observational, tertiary centre cohort, diagnostic phase IIb study 'Consciousness in neurocritical care cohort study using EEG and fMRI' (CONNECT-ME, NCT02644265) was to assess the accuracy of fMRI and EEG to identify residual consciousness in acute DoC in the ICU. Between April 2016 and November 2020, 87 acute DoC patients with traumatic or non-traumatic brain injury were examined with repeated clinical assessments, fMRI and EEG. Resting-state EEG and EEG with external stimulations were evaluated by visual analysis, spectral band analysis and a Support Vector Machine (SVM) consciousness classifier. In addition, within- and between-network resting-state connectivity for canonical resting-state fMRI networks was assessed. Next, we used EEG and fMRI data at study enrolment in two different machine-learning algorithms (Random Forest and SVM with a linear kernel) to distinguish patients in a minimally conscious state or better (≥MCS) from those in coma or unresponsive wakefulness state (≤UWS) at time of study enrolment and at ICU discharge (or before death). Prediction performances were assessed with area under the curve (AUC). Of 87 DoC patients (mean age, 50.0 ± 18 years, 43% female), 51 (59%) were ≤UWS and 36 (41%) were ≥ MCS at study enrolment. Thirty-one (36%) patients died in the ICU, including 28 who had life-sustaining therapy withdrawn. EEG and fMRI predicted consciousness levels at study enrolment and ICU discharge, with maximum AUCs of 0.79 (95% CI 0.77-0.80) and 0.71 (95% CI 0.77-0.80), respectively. Models based on combined EEG and fMRI features predicted consciousness levels at study enrolment and ICU discharge with maximum AUCs of 0.78 (95% CI 0.71-0.86) and 0.83 (95% CI 0.75-0.89), respectively, with improved positive predictive value and sensitivity. Overall, both machine-learning algorithms (SVM and Random Forest) performed equally well. In conclusion, we suggest that acute DoC prediction models in the ICU be based on a combination of fMRI and EEG features, regardless of the machine-learning algorithm used.

Arterial Spin Labeling Magnetic Resonance Imaging for Acute Disorders of Consciousness in the Intensive Care Unit.

BACKGROUND: To investigate patients with disorders of consciousness (DoC) for residual awareness, guidelines recommend quantifying glucose brain metabolism using positron emission tomography. However, this is not feasible in the intensive care unit (ICU). Cerebral blood flow (CBF) assessed by arterial spin labeling magnetic resonance imaging (ASL-MRI) could serve as a proxy for brain metabolism and reflect consciousness levels in acute DoC. We hypothesized that ASL-MRI would show compromised CBF in coma and unresponsive wakefulness states (UWS) but relatively preserved CBF in minimally conscious states (MCS) or better. METHODS: We consecutively enrolled ICU patients with acute DoC and categorized them as being clinically unresponsive (i.e., coma or UWS [≤ UWS]) or low responsive (i.e., MCS or better [≥ MCS]). ASL-MRI was then acquired on 1.5 T or 3 T. Healthy controls were investigated with both 1.5 T and 3 T ASL-MRI. RESULTS: We obtained 84 ASL-MRI scans from 59 participants, comprising 36 scans from 35 patients (11 women [31.4%]; median age 56 years, range 18-82 years; 24 ≤ UWS patients, 12 ≥ MCS patients; 32 nontraumatic brain injuries) and 48 scans from 24 healthy controls (12 women [50%]; median age 50 years, range 21-77 years). In linear mixed-effects models of whole-brain cortical CBF, patients had 16.2 mL/100 g/min lower CBF than healthy controls (p = 0.0041). However, ASL-MRI was unable to discriminate between ≤ UWS and ≥ MCS patients (whole-brain cortical CBF: p = 0.33; best hemisphere cortical CBF: p = 0.41). Numerical differences of regional CBF in the thalamus, amygdala, and brainstem in the two patient groups were statistically nonsignificant. CONCLUSIONS: CBF measurement in ICU patients using ASL-MRI is feasible but cannot distinguish between the lower and the upper ends of the acute DoC spectrum. We suggest that pilot testing of diagnostic interventions at the extremes of this spectrum is a time-efficient approach in the continued quest to develop DoC neuroimaging markers in the ICU.

Multimodal Prediction of 3- and 12-Month Outcomes in ICU Patients with Acute Disorders of Consciousness.

BACKGROUND: In intensive care unit (ICU) patients with coma and other disorders of consciousness (DoC), outcome prediction is key to decision-making regarding prognostication, neurorehabilitation, and management of family expectations. Current prediction algorithms are largely based on chronic DoC, whereas multimodal data from acute DoC are scarce. Therefore, the Consciousness in Neurocritical Care Cohort Study Using Electroencephalography and Functional Magnetic Resonance Imaging (i.e. CONNECT-ME; ClinicalTrials.gov identifier: NCT02644265) investigates ICU patients with acute DoC due to traumatic and nontraumatic brain injuries, using electroencephalography (EEG) (resting-state and passive paradigms), functional magnetic resonance imaging (fMRI) (resting-state) and systematic clinical examinations. METHODS: We previously presented results for a subset of patients (n = 87) concerning prediction of consciousness levels in the ICU. Now we report 3- and 12-month outcomes in an extended cohort (n = 123). Favorable outcome was defined as a modified Rankin Scale score ≤ 3, a cerebral performance category score ≤ 2, and a Glasgow Outcome Scale Extended score ≥ 4. EEG features included visual grading, automated spectral categorization, and support vector machine consciousness classifier. fMRI features included functional connectivity measures from six resting-state networks. Random forest and support vector machine were applied to EEG and fMRI features to predict outcomes. Here, random forest results are presented as areas under the curve (AUC) of receiver operating characteristic curves or accuracy. Cox proportional regression with in-hospital death as a competing risk was used to assess independent clinical predictors of time to favorable outcome. RESULTS: Between April 2016 and July 2021, we enrolled 123 patients (mean age 51 years, 42% women). Of 82 (66%) ICU survivors, 3- and 12-month outcomes were available for 79 (96%) and 77 (94%), respectively. EEG features predicted both 3-month (AUC 0.79 [95% confidence interval (CI) 0.77-0.82]) and 12-month (AUC 0.74 [95% CI 0.71-0.77]) outcomes. fMRI features appeared to predict 3-month outcome (accuracy 0.69-0.78) both alone and when combined with some EEG features (accuracies 0.73-0.84) but not 12-month outcome (larger sample sizes needed). Independent clinical predictors of time to favorable outcome were younger age (hazard ratio [HR] 1.04 [95% CI 1.02-1.06]), traumatic brain injury (HR 1.94 [95% CI 1.04-3.61]), command-following abilities at admission (HR 2.70 [95% CI 1.40-5.23]), initial brain imaging without severe pathological findings (HR 2.42 [95% CI 1.12-5.22]), improving consciousness in the ICU (HR 5.76 [95% CI 2.41-15.51]), and favorable visual-graded EEG (HR 2.47 [95% CI 1.46-4.19]). CONCLUSIONS: Our results indicate that EEG and fMRI features and readily available clinical data predict short-term outcome of patients with acute DoC and that EEG also predicts 12-month outcome after ICU discharge.

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.

Associations between aberrant working memory-related neural activity and cognitive impairments in somatically healthy, remitted patients with mood disorders.

BACKGROUND: Persistent cognitive deficits are prevalent in patients with bipolar disorder (BD) and unipolar disorder (UD), but treatments effectively targeting cognition in these mood disorders are lacking. This is partly due to poor insight into the neuronal underpinnings of cognitive deficits. METHODS: The aim of this functional magnetic resonance imaging (fMRI) study was to investigate the neuronal underpinnings of working memory (WM)-related deficits in somatically healthy, remitted patients with BD or UD (n = 66) with cognitive and functional impairments compared to 38 healthy controls (HC). The participants underwent neuropsychological testing and fMRI, while performing a visuospatial and a verbal N-back WM paradigm. RESULTS: Relative to HC, patients exhibited hypo-activity across dorsolateral prefrontal cortex as well as frontal and parietal nodes of the cognitive control network (CCN) and hyper-activity in left orbitofrontal cortex within the default mode network (DMN) during both visuospatial and verbal WM performance. Verbal WM-related response in the left posterior superior frontal gyrus (SFG) within CCN was lower in patients and correlated positively with out-of-scanner executive function performance across all participants. CONCLUSIONS: Our findings suggest that cognitive impairments across BD and UD are associated with insufficient recruitment of task-relevant regions in the CCN and down-regulation of task-irrelevant orbitofrontal activity within the DMN during task performance. Specifically, a lower recruitment of the left posterior SFG within CCN during verbal WM was associated with lower cognitive performance.

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.

Deep phenotyping towards precision psychiatry of first-episode depression - the Brain Drugs-Depression cohort.

BACKGROUND: Major Depressive Disorder (MDD) is a heterogenous brain disorder, with potentially multiple psychosocial and biological disease mechanisms. This is also a plausible explanation for why patients do not respond equally well to treatment with first- or second-line antidepressants, i.e., one-third to one-half of patients do not remit in response to first- or second-line treatment. To map MDD heterogeneity and markers of treatment response to enable a precision medicine approach, we will acquire several possible predictive markers across several domains, e.g., psychosocial, biochemical, and neuroimaging. METHODS: All patients are examined before receiving a standardised treatment package for adults aged 18-65 with first-episode depression in six public outpatient clinics in the Capital Region of Denmark. From this population, we will recruit a cohort of 800 patients for whom we will acquire clinical, cognitive, psychometric, and biological data. A subgroup (subcohort I, n = 600) will additionally provide neuroimaging data, i.e., Magnetic Resonance Imaging, and Electroencephalogram, and a subgroup of patients from subcohort I unmedicated at inclusion (subcohort II, n = 60) will also undergo a brain Positron Emission Tomography with the [11C]-UCB-J tracer binding to the presynaptic glycoprotein-SV2A. Subcohort allocation is based on eligibility and willingness to participate. The treatment package typically lasts six months. Depression severity is assessed with the Quick Inventory of Depressive Symptomatology (QIDS) at baseline, and 6, 12 and 18 months after treatment initiation. The primary outcome is remission (QIDS ≤ 5) and clinical improvement (≥ 50% reduction in QIDS) after 6 months. Secondary endpoints include remission at 12 and 18 months and %-change in QIDS, 10-item Symptom Checklist, 5-item WHO Well-Being Index, and modified Disability Scale from baseline through follow-up. We also assess psychotherapy and medication side-effects. We will use machine learning to determine a combination of characteristics that best predict treatment outcomes and statistical models to investigate the association between individual measures and clinical outcomes. We will assess associations between patient characteristics, treatment choices, and clinical outcomes using path analysis, enabling us to estimate the effect of treatment choices and timing on the clinical outcome. DISCUSSION: The BrainDrugs-Depression study is a real-world deep-phenotyping clinical cohort study of first-episode MDD patients. TRIAL REGISTRATION: Registered at clinicaltrials.gov November 15th, 2022 (NCT05616559).

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.

Extracellular Fluid Collection and Analysis of Drosophila melanogaster Brain Tissue with µ-Low-Flow Push-Pull Perfusion (µLFPP).

The development of methods to generate quantitative chemical content information from precise tissue locations is needed to understand fundamental cellular and tissue physiology. This work describes a method to perfuse the extracellular fluid of fly brains in vivo using µ-low-flow push-pull perfusion (µLFPP) for quantitative chemical content determinations. Miniaturization of push-pull perfusion probe designs allowed the development of methods for probe tip placement into and sampling from the fruit fly's brain. Perfusate analysis identified and quantified arginine, octopamine, histidine, taurine, glycine, glutamate, and aspartate. The perfusate data did not exhibit any statistical differences based on sex. The perfusate analysis was compared to hemolymph samples to confirm probe placement in fly brain tissues. The appearance of probe placement into the brain space was confirmed with the following observations. Hemolymph and perfusate samples were found to contain analytes unique to each sample type. Quantitated levels of perfusate were not a simple dilution of hemolymph content. Further, the discovery of perfusates with composition similar to both hemolymph and brain perfusate when damage was intentionally inflicted supports the observation that perfusates are distinct from hemolymph. The analysis of perfusate collected for greater than an hour of sampling exhibits the possibility of monitoring applications. Altogether, this work demonstrates the viability of performing µ-low-flow push-pull perfusion for in vivo studies of fly brain tissues to identify and quantitate neurotransmitter content.

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.

DNA-Origami NanoTrap for Studying the Selective Barriers Formed by Phenylalanine-Glycine-Rich Nucleoporins.

DNA nanotechnology provides a versatile and powerful tool to dissect the structure-function relationship of biomolecular machines like the nuclear pore complex (NPC), an enormous protein assembly that controls molecular traffic between the nucleus and cytoplasm. To understand how the intrinsically disordered, Phe-Gly-rich nucleoporins (FG-nups) within the NPC establish a selective barrier to macromolecules, we built a DNA-origami NanoTrap. The NanoTrap comprises precisely arranged FG-nups in an NPC-like channel, which sits on a baseplate that captures macromolecules that pass through the FG network. Using this biomimetic construct, we determined that the FG-motif type, grafting density, and spatial arrangement are critical determinants of an effective diffusion barrier. Further, we observed that diffusion barriers formed with cohesive FG interactions dominate in mixed-FG-nup scenarios. Finally, we demonstrated that the nuclear transport receptor, Ntf2, can selectively transport model cargo through NanoTraps composed of FxFG but not GLFG Nups. Our NanoTrap thus recapitulates the NPC's fundamental biological activities, providing a valuable tool for studying nuclear transport.

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.

Visual stimuli induce serotonin release in occipital cortex: A simultaneous positron emission tomography/magnetic resonance imaging study.

Endogenous serotonin (5-HT) release can be measured noninvasively using positron emission tomography (PET) imaging in combination with certain serotonergic radiotracers. This allows us to investigate effects of pharmacological and nonpharmacological interventions on brain 5-HT levels in living humans. Here, we study the neural responses to a visual stimulus using simultaneous PET/MRI. In a cross-over design, 11 healthy individuals were PET/MRI scanned with the 5-HT1B receptor radioligand [11 C]AZ10419369, which is sensitive to changes in endogenous 5-HT. During the last part of the scan, participants either viewed autobiographical images with positive valence (n = 11) or kept their eyes closed (n = 7). The visual stimuli increased cerebral blood flow (CBF) in the occipital cortex, as measured with pseudo-continuous arterial spin labeling. Simultaneously, we found decreased 5-HT1B receptor binding in the occipital cortex (-3.6 ± 3.6%), indicating synaptic 5-HT release. Using a linear regression model, we found that the change in 5-HT1B receptor binding was significantly negatively associated with change in CBF in the occipital cortex (p = .004). For the first time, we here demonstrate how cerebral 5-HT levels change in response to nonpharmacological stimuli in humans, as measured with PET. Our findings more directly support a link between 5-HT signaling and visual processing and/or visual attention.

Trait Openness and serotonin 2A receptors in healthy volunteers: A positron emission tomography study.

Recent research found lasting increases in personality trait Openness in healthy individuals and patients after administration of the serotonin 2A receptor (5-HT2A R) agonist psilocybin. However, no studies have investigated whether 5-HT2A R availability as imaged using positron emission tomography (PET) is associated with this trait. In 159 healthy individuals (53 females), the association between 5-HT2A R binding in neocortex imaged with [18 F]altanserin or [11 C]Cimbi-36 PET and personality trait Openness was investigated using linear regression models. In these models the influence of sex on the association was also investigated. Trait Openness was assessed with the NEO Personality Inventory-Revised. No significant associations between neocortical 5-HT2A R binding and trait Openness were found for [18 F]altanserin (p = 0.5) or [11 C]Cimbi-36 (p = 0.8). Pooling the data in a combined model did not substantially change our results (p = 0.4). No significant interactions with sex were found (p > 0.35). Our results indicate that differences in 5-HT2A R availability are not related to variations in trait Openness in healthy individuals. Although stimulation of the 5-HT2A R with compounds such as psilocybin may contribute to long-term changes in trait Openness, there is no evidence in favor of an association between 5-HT2A R and trait Openness.

A High-Resolution In Vivo Atlas of the Human Brain's Serotonin System.

The serotonin (5-hydroxytryptamine, 5-HT) system modulates many important brain functions and is critically involved in many neuropsychiatric disorders. Here, we present a high-resolution, multidimensional, in vivo atlas of four of the human brain's 5-HT receptors (5-HT1A, 5-HT1B, 5-HT2A, and 5-HT4) and the 5-HT transporter (5-HTT). The atlas is created from molecular and structural high-resolution neuroimaging data consisting of positron emission tomography (PET) and magnetic resonance imaging (MRI) scans acquired in a total of 210 healthy individuals. Comparison of the regional PET binding measures with postmortem human brain autoradiography outcomes showed a high correlation for the five 5-HT targets and this enabled us to transform the atlas to represent protein densities (in picomoles per milliliter). We also assessed the regional association between protein concentration and mRNA expression in the human brain by comparing the 5-HT density across the atlas with data from the Allen Human Brain atlas and identified receptor- and transporter-specific associations that show the regional relation between the two measures. Together, these data provide unparalleled insight into the serotonin system of the human brain. SIGNIFICANCE STATEMENT: We present a high-resolution positron emission tomography (PET)- and magnetic resonance imaging-based human brain atlas of important serotonin receptors and the transporter. The regional PET-derived binding measures correlate strongly with the corresponding autoradiography protein levels. The strong correlation enables the transformation of the PET-derived human brain atlas into a protein density map of the serotonin (5-hydroxytryptamine, 5-HT) system. Next, we compared the regional receptor/transporter protein densities with mRNA levels and uncovered unique associations between protein expression and density at high detail. This new in vivo neuroimaging atlas of the 5-HT system not only provides insight in the human brain's regional protein synthesis, transport, and density, but also represents a valuable source of information for the neuroscience community as a comparative instrument to assess brain disorders.

Men with high serotonin 1B receptor binding respond to provocations with heightened amygdala reactivity.

Serotonin signalling influences amygdala reactivity to threat-related emotional facial expressions in healthy adults, but in vivo serotonin signalling has never been investigated in the context of provocative stimuli in aggressive individuals. The aim of this study was to evaluate associations between serotonin 1B receptor (5-HT1BR) levels and brain reactivity to provocations. We quantified regional 5-HT1BR binding using [11C]AZ10419369 positron emission tomography (PET) and measured brain activation following provocations with functional magnetic resonance imaging (fMRI) in eighteen violent offenders and 25 healthy control subjects. The point-subtraction aggression paradigm (PSAP) was used in fMRI to elicit provocations in terms of monetary subtractions from a fictive opponent. We estimated global 5-HT1BR binding using a linear structural equation model, with a single latent response variable (LV1B) modelling shared correlation between 5-HT1BR binding across multiple brain regions (neocortex, anterior and posterior cingulate cortex, raphe, amygdala, hippocampus and striatum). We tested whether the LV1B was associated with amygdala, striatal and prefrontal reactivity to provocations, adjusting for age, injected mass and group. Across participants, LV1B was statistically significantly positively associated with amygdala (p = 0.01) but not with striatal (p = 0.2) or prefrontal reactivity to provocations (p = 0.3). These findings provide novel evidence that 5-HT1BR levels are linked to amygdala reactivity to provocations in a cohort of men displaying a wide range of aggressive behavior. The data suggest that 5-HT1BR represents an intriguing target for reducing excessive neural reactivity to provocations and thereby putatively violent behavior.

Functional MRI for Assessment of the Default Mode Network in Acute Brain Injury.

BACKGROUND: Assessment of the default mode network (DMN) using resting-state functional magnetic resonance imaging (fMRI) may improve assessment of the level of consciousness in chronic brain injury, and therefore, fMRI may also have prognostic value in acute brain injury. However, fMRI is much more challenging in critically ill patients because of cardiovascular vulnerability, intravenous sedation, and artificial ventilation. METHODS: Using resting-state fMRI, we investigated the DMN in a convenience sample of patients with acute brain injury admitted to the intensive care unit. The DMN was classified dichotomously into "normal" and "grossly abnormal." Clinical outcome was assessed at 3 months. RESULTS: Seven patients with acute brain injury (4 females; median age 37 years [range 14-71 years]; 1 traumatic brain injury [TBI]; 6 non-TBI) were investigated by fMRI a median of 15 days after injury (range 5-25 days). Neurological presentation included 2 coma, 1 vegetative state/unresponsive wakefulness syndrome (VS/UWS), 3 minimal conscious state (MCS) minus, and 1 MCS plus. Clinical outcomes at 3 months included 1 death, 1 VS/UWS, 1 MCS plus, and 4 conscious states (CS; 1 modified Rankin Scale 0; 2 mRS 4; 1 mRS 5). Normal DMNs were seen in 4 out of 7 patients (1 MCS plus, 3 CS at follow-up). CONCLUSIONS: It is feasible to assess the DMN by resting-state fMRI in patients with acute brain injury already in the very early period of intensive care unit admission. Although preliminary data, all patients with a preserved DMN regained consciousness levels at follow-up compatible with MCS+ or better.