Synaptic signaling modeled by functional connectivity predicts metabolic demands of the human brain.

PURPOSE: The human brain is characterized by interacting large-scale functional networks fueled by glucose metabolism. Since former studies could not sufficiently clarify how these functional connections shape glucose metabolism, we aimed to provide a neurophysiologically-based approach. METHODS: 51 healthy volunteers underwent simultaneous PET/MRI to obtain BOLD functional connectivity and [18F]FDG glucose metabolism. These multimodal imaging proxies of fMRI and PET were combined in a whole-brain extension of metabolic connectivity mapping. Specifically, functional connectivity of all brain regions were used as input to explain glucose metabolism of a given target region. This enabled the modeling of postsynaptic energy demands by incoming signals from distinct brain regions. RESULTS: Functional connectivity input explained a substantial part of metabolic demands but with pronounced regional variations (34 - 76%). During cognitive task performance this multimodal association revealed a shift to higher network integration compared to resting state. In healthy aging, a dedifferentiation (decreased segregated/modular structure of the brain) of brain networks during rest was observed. Furthermore, by including data from mRNA maps, [11C]UCB-J synaptic density and aerobic glycolysis (oxygen-to-glucose index from PET data), we show that whole-brain functional input reflects non-oxidative, on-demand metabolism of synaptic signaling. The metabolically-derived directionality of functional inputs further marked them as top-down predictions. In addition, the approach uncovered formerly hidden networks with superior efficiency through metabolically informed network partitioning. CONCLUSIONS: Applying multimodal imaging, we decipher a crucial part of the metabolic and neurophysiological basis of functional connections in the brain as interregional on-demand synaptic signaling fueled by anaerobic metabolism. The observed task- and age-related effects indicate promising future applications to characterize human brain function and clinical alterations.

Validation of cardiac image-derived input functions for functional PET quantification.

PURPOSE: Functional PET (fPET) is a novel technique for studying dynamic changes in brain metabolism and neurotransmitter signaling. Accurate quantification of fPET relies on measuring the arterial input function (AIF), traditionally achieved through invasive arterial blood sampling. While non-invasive image-derived input functions (IDIF) offer an alternative, they suffer from limited spatial resolution and field of view. To overcome these issues, we developed and validated a scan protocol for brain fPET utilizing cardiac IDIF, aiming to mitigate known IDIF limitations. METHODS: Twenty healthy individuals underwent fPET/MR scans using [18F]FDG or 6-[18F]FDOPA, utilizing bed motion shuttling to capture cardiac IDIF and brain task-induced changes. Arterial and venous blood sampling was used to validate IDIFs. Participants performed a monetary incentive delay task. IDIFs from various blood pools and composites estimated from a linear fit over all IDIF blood pools (3VOI) and further supplemented with venous blood samples (3VOIVB) were compared to the AIF. Quantitative task-specific images from both tracers were compared to assess the performance of each input function to the gold standard. RESULTS: For both radiotracer cohorts, moderate to high agreement (r: 0.60-0.89) between IDIFs and AIF for both radiotracer cohorts was observed, with further improvement (r: 0.87-0.93) for composite IDIFs (3VOI and 3VOIVB). Both methods showed equivalent quantitative values and high agreement (r: 0.975-0.998) with AIF-derived measurements. CONCLUSION: Our proposed protocol enables accurate non-invasive estimation of the input function with full quantification of task-specific changes, addressing the limitations of IDIF for brain imaging by sampling larger blood pools over the thorax. These advancements increase applicability to any PET scanner and clinical research setting by reducing experimental complexity and increasing patient comfort.

Effect of MAOA DNA Methylation on Human in Vivo Protein Expression Measured by [11C]harmine Positron Emission Tomography.

BACKGROUND: Epigenetic modifications like DNA methylation are understood as an intermediary between environmental factors and neurobiology. Cerebral monoamine oxidase A (MAO-A) levels are altered in depression, as are DNA methylation levels within the MAOA gene, particularly in the promoter/exon I/intron I region. An effect of MAOA methylation on peripheral protein expression was shown, but the extent to which methylation affects brain MAO-A levels is not fully understood. METHODS: Here, the influence of MAOA promoter/exon I/intron I region DNA methylation on global MAO-A distribution volume (VT), an index of MAO-A density, was assessed via [11C]harmine positron emission tomography in 22 patients (14 females) suffering from seasonal affective disorder and 30 healthy controls (17 females). RESULTS: No significant influence of MAOA DNA methylation on global MAO-A VT was found, despite correction for health status, sex, season, and MAOA variable number of tandem repeat genotype. However, season affected average methylation in women, with higher levels in spring and summer (Puncorr = .03). We thus did not find evidence for an effect of MAOA DNA methylation on brain MAO-A VT. CONCLUSIONS: In contrast to a previous study demonstrating an effect of methylation of a MAOA promoter region located further 5' on brain MAO-A, MAOA methylation of the region assessed here appears to affect brain protein levels to a limited extent at most. The observed effect of season on methylation levels is in accordance with extensive evidence for seasonal effects within the serotonergic system. CLINICALTRIALS.GOV IDENTIFIER: NCT02582398 (https://clinicaltrials.gov/ct2/show/NCT02582398).

Correlation of receptor density and mRNA expression patterns in the human cerebral cortex.

Changes in distribution of associated molecular targets have been reported across several neuropsychiatric disorders. However, the high-resolution topology of most proteins is unknown and simultaneous in vivo measurement in multi-receptor systems is complicated. To account for the missing proteomic information, messenger ribonucleic acid (mRNA) transcripts are typically used as a surrogate. Nonetheless, post-transcriptional and post-translational processes might cause the discrepancy between the final distribution of proteins and gene expression patterns. Therefore, this study aims to investigate ex vivo links between mRNA expression and corresponding receptor density in the human cerebral cortex. To this end, autoradiography data on the density of 15 different receptors in 38 brain regions were correlated with the expression patterns of 50 associated genes derived from microarray data (mA), RNA sequencing data (RNA-Seq) provided by the Allen Human Brain Atlas and predicted mRNA expression patterns (pred-mRNA). Spearman's rank correlation was used to evaluate the possible links between proteomic data and mRNA expression patterns. Correlations between mRNA and protein density varied greatly between targets: Positive associations were found for e.g. the serotonin 1A (pred-mRNA: rs = 0.708; mA: rs = 0.601) or kainate receptor (pred-mRNA: rs = 0.655; mA: rs = 0.601; RNA-Seq: rs = 0.575) as well as a few negative associations e.g. γ-Aminobutyric acid (GABA) A receptor subunit α3 (pred-mRNA: rs = -0.638; mA: rs = -0.619) or subunit α5 (pred-mRNA: rs = -0.565; mA: rs = -0.563), while most of the other investigated target receptors showed low correlations. The high variability in the correspondence of mRNA expression and receptor spatial distribution warrants caution when inferring the topology of molecular targets in the brain from transcriptome data. This not only highlights the longstanding value of molecular imaging but also indicates a need for comprehensive proteomic studies.

Regional gene expression patterns are associated with task-specific brain activation during reward and emotion processing measured with functional MRI.

The exploration of the spatial relationship between gene expression profiles and task-evoked response patterns known to be altered in neuropsychiatric disorders, for example depression, can guide the development of more targeted therapies. Here, we estimated the correlation between human transcriptome data and two different brain activation maps measured with functional magnetic resonance imaging (fMRI) in healthy subjects. Whole-brain activation patterns evoked during an emotional face recognition task were associated with topological mRNA expression of genes involved in cellular transport. In contrast, fMRI activation patterns related to the acceptance of monetary rewards were associated with genes implicated in cellular localization processes, metabolism, translation, and synapse regulation. An overlap of these genes with risk genes from major depressive disorder genome-wide association studies revealed the involvement of the master regulators TCF4 and PAX6 in emotion and reward processing. Overall, the identification of stable relationships between spatial gene expression profiles and fMRI data may reshape the prospects for imaging transcriptomics studies.

Topologically Guided Prioritization of Candidate Gene Transcripts Coexpressed with the 5-HT1A Receptor by Combining In Vivo PET and Allen Human Brain Atlas Data.

The serotonin-1A receptor (5-HT1AR) represents a viable target in the treatment of disorders of the brain. However, development of psychiatric drugs continues to be hindered by the relative inaccessibility of brain tissue. Although the efficacy of drugs selective for the 5-HT1AR has not been proven, research continues to focus on drugs that influence this receptor subtype. To further knowledge on this topic, we investigated the topological coexpression patterns of the 5-HT1AR. We calculated Spearman's rho for the correlation of positron emission tomography-binding potentials (BPND) of the 5-HT1AR assessed in 30 healthy subjects using the tracer [carbonyl-11C]WAY-100635 and predicted whole-brain mRNA expression of 18 686 genes. After applying a threshold of r > 0.3 in a leave-one-out cross-validation of the prediction of mRNA expression, genes with ρ ≥ 0.7 were considered to be relevant. In cortical regions, 199 genes showed high correlation with the BPND of the 5-HT1AR, in subcortical regions 194 genes. Using our approach, we could consolidate the role of BDNF and implicate new genes (AnxA8, NeuroD2) in serotonergic functioning. Despite its explorative nature, the analysis can be seen as a gene prioritization approach to reduce the number of genes potentially connected to 5-HT1AR functioning and guide future in vitro studies.

Association of dopamine D2/3 receptor binding potential measured using PET and [11C]-(+)-PHNO with post-mortem DRD2/3 gene expression in the human brain.

Open access post-mortem transcriptome atlases such as the Allen Human Brain Atlas (AHBA) can inform us about mRNA expression of numerous proteins of interest across the whole brain, while in vivo protein binding in the human brain can be quantified by means of neuroreceptor positron emission tomography (PET). By combining both modalities, the association between regional gene expression and receptor distribution in the living brain can be approximated. Here, we compare the characteristics of D2 and D3 dopamine receptor distribution by applying the dopamine D2/3 receptor agonist radioligand [11C]-(+)-PHNO and human gene expression data. Since [11C]-(+)-PHNO has a higher affinity for D3 compared to D2 receptors, we hypothesized that there is a stronger relationship between D2/3 non-displaceable binding potentials (BPND) and D3 mRNA expression. To investigate the relationship between D2/3 BPND and mRNA expression of DRD2 and DRD3 we performed [11C]-(+)-PHNO PET scans in 27 healthy subjects (12 females) and extracted gene expression data from the AHBA. We also calculated D2/D3 mRNA expression ratios to imitate the mixed D2/3 signal of [11C]-(+)-PHNO. In accordance with our a priori hypothesis, a strong correlation between [11C]-(+)-PHNO and DRD3 expression was found. However, there was no significant correlation with DRD2 expression. Calculated D2/D3 mRNA expression ratios also showed a positive correlation with [11C]-(+)-PHNO binding, reflecting the mixed D2/3 signal of the radioligand. Our study supports the usefulness of combining gene expression data from open access brain atlases with in vivo imaging data in order to gain more detailed knowledge on neurotransmitter signaling.

Impact of genetic variants within serotonin turnover enzymes on human cerebral monoamine oxidase A in vivo.

Variants within the monoamine oxidase A (MAO-A, MAOA) and tryptophan hydroxylase 2 (TPH2) genes, the main enzymes in cerebral serotonin (5-HT) turnover, affect risk for depression. Depressed cohorts show increased cerebral MAO-A in positron emission tomography (PET) studies. TPH2 polymorphisms might also influence brain MAO-A because availability of substrates (i.e. monoamine concentrations) were shown to affect MAO-A levels. We assessed the effect of MAOA (rs1137070, rs2064070, rs6323) and TPH2 (rs1386494, rs4570625) variants associated with risk for depression and related clinical phenomena on global MAO-A distribution volume (VT) using [11C]harmine PET in 51 participants (21 individuals with seasonal affective disorder (SAD) and 30 healthy individuals (HI)). Statistical analyses comprised general linear models with global MAO-A VT as dependent variable, genotype as independent variable and age, sex, group (individuals with SAD, HI) and season as covariates. rs1386494 genotype significantly affected global MAO-A VT after correction for age, group and sex (p < 0.05, corr.), with CC homozygotes showing 26% higher MAO-A levels. The role of rs1386494 on TPH2 function or expression is poorly understood. Our results suggest rs1386494 might have an effect on either, assuming that TPH2 and MAO-A levels are linked by their common product/substrate, 5-HT. Alternatively, rs1386494 might influence MAO-A levels via another mechanism, such as co-inheritance of other genetic variants. Our results provide insight into how genetic variants within serotonin turnover translate to the cerebral serotonin system. Clinicaltrials.gov Identifier: NCT02582398. EUDAMED Number: CIV-AT-13-01-009583.

Effects of bilateral sequential theta-burst stimulation on 5-HT1A receptors in the dorsolateral prefrontal cortex in treatment-resistant depression: a proof-of-concept trial.

Theta-burst stimulation (TBS) represents a brain stimulation technique effective for treatment-resistant depression (TRD) as underlined by meta-analyses. While the methodology undergoes constant refinement, bilateral stimulation of the dorsolateral prefrontal cortex (DLPFC) appears promising to restore left DLPFC hypoactivity and right hyperactivity found in depression. The post-synaptic inhibitory serotonin-1A (5-HT1A) receptor, also occurring in the DLPFC, might be involved in this mechanism of action. To test this hypothesis, we performed PET-imaging using the tracer [carbonyl-11C]WAY-100635 including arterial blood sampling before and after a three-week treatment with TBS in 11 TRD patients compared to sham stimulation (n = 8 and n = 3, respectively). Treatment groups were randomly assigned, and TBS protocol consisted of excitatory intermittent TBS to the left and inhibitory continuous TBS to the right DLPFC. A linear mixed model including group, hemisphere, time, and Hamilton Rating Scale for Depression (HAMD) score revealed a 3-way interaction effect of group, time, and HAMD on specific distribution volume (VS) of 5-HT1A receptor. While post-hoc comparisons showed no significant changes of 5-HT1A receptor VS in either group, higher 5-HT1A receptor VS after treatment correlated with greater difference in HAMD (r = -0.62). The results of this proof-of-concept trial hint towards potential effects of TBS on the distribution of the 5-HT1A receptor. Due to the small sample size, all results must, however, be regarded with caution.

Enrichment of Disease-Associated Genes in Cortical Areas Defined by Transcriptome-Based Parcellation.

BACKGROUND: Parcellation of the cerebral cortex serves the investigation of the emergence of uniquely human brain functions and disorders. Transcriptome data enable the characterization of the molecular properties of cortical areas in unprecedented detail. Previously, we predicted the expression of 18,686 genes in the entire human brain based on microarray data. Here, we employed these data to parcellate the cortex and study the regional enrichment of disease-associated genes. METHODS: We performed agglomerative hierarchical clustering based on normalized transcriptome data to delineate areas with distinct gene expression profiles. Subsequently, we tested these profiles for the enrichment of gene sets associated with brain disorders by genome-wide association studies and expert-curated databases using gene set enrichment analysis. RESULTS: Transcriptome-based parcellation identified borders in line with major anatomical landmarks and the functional differentiation of primary motor, somatosensory, visual, and auditory areas. Gene set enrichment analysis based on curated databases suggested new roles of specific areas in psychiatric and neurological disorders while reproducing well-established links for movement and neurodegenerative disorders, for example, amyotrophic lateral sclerosis (motor cortex) and Alzheimer's disease (entorhinal cortex). Meanwhile, gene sets derived from genome-wide association studies on psychiatric disorders exhibited similar enrichment patterns driven by pleiotropic genes expressed in the posterior fusiform gyrus and inferior parietal lobule. CONCLUSIONS: The identified enrichment patterns suggest the vulnerability of specific cortical areas to various influences that might alter the risk of developing one or several brain disorders. For several diseases, specific genes were highlighted, which could lead to the discovery of novel disease mechanisms and urgently needed treatments.

Simultaneous radiomethylation of [11C]harmine and [11C]DASB and kinetic modeling approach for serotonergic brain imaging in the same individual.

Simultaneous characterization of pathologies by multi-tracer positron emission tomography (PET) is among the most promising applications in nuclear medicine. Aim of this work was the simultaneous production of two PET-tracers in one module and test the relevance for human application. [11C]harmine and [11C]DASB were concurrently synthesized in a 'two-in-one-pot' reaction in quality for application. Dual-tracer protocol was simulated using 16 single PET scans in different orders of tracer application separated by different time intervals. Volume of distribution was calculated for single- and dual-tracer measurements using Logan's plot and arterial input function in 13 brain regions. The 'two-in-one-pot' reaction yielded equivalent amounts of both radiotracers with comparable molar activities. The simulations of the dual-tracer application were comparable to the single bolus injections in 13 brain regions, when [11C]harmine was applied first and [11C]DASB second, with an injection time interval of 45 min (rxy = 0.90). Our study shows the successful simultaneous dual-tracer production leading to decreased radiation burden and costs. The simulation of dual subject injection to quantify the monoamine oxidase-A and serotonin transporter distribution proved its high potential. Multi-tracer imaging may drive more sophisticated study designs and diminish the day-to-day differences in the same individual as well as increase PET scanner efficiency.

Biodistribution and dosimetry of the GluN2B-specific NMDA receptor PET radioligand (R)-[11C]Me-NB1.

BACKGROUND: The NMDA receptor (NMDAR) plays a key role in the central nervous system, e.g., for synaptic transmission. While synaptic NMDARs are thought to have protective characteristics, activation of extrasynaptic NMDARs might trigger excitotoxic processes linked to neuropsychiatric disorders. Since extrasynaptic NMDARs are typically GluN2B-enriched, the subunit is an interesting target for drug development and treatment monitoring. Recently, the novel GluN2B-specific PET radioligand (R)-[11C]Me-NB1 was investigated in rodents and for the first time successfully translated to humans. To assess whether (R)-[11C]Me-NB1 is a valuable radioligand for (repeated) clinical applications, we evaluated its safety, biodistribution and dosimetry. METHODS: Four healthy subjects (two females, two males) underwent one whole-body PET/MR measurement lasting for more than 120 min. The GluN2B-specific radioligand (R)-[11C]Me-NB1 was administered simultaneously with the PET start. Subjects were measured in nine passes and six bed positions from head to mid-thigh. Regions of interest was anatomically defined for the brain, thyroid, lungs, heart wall, spleen, stomach contents, pancreas, liver, kidneys, bone marrow and urinary bladder contents, using both PET and MR images. Time-integrated activity coefficients were estimated to calculate organ equivalent dose coefficients and the effective dose coefficient. Additionally, standardized uptake values (SUV) were computed to visualize the biodistribution. RESULTS: Administration of the radioligand was safe without adverse events. The organs with the highest uptake were the urinary bladder, spleen and pancreas. Organ equivalent dose coefficients were higher in female in almost all organs, except for the urinary bladder of male. The effective dose coefficient was 6.0 µSv/MBq. CONCLUSION: The GluN2B-specific radioligand (R)-[11C]Me-NB1 was well-tolerated without reported side effects. Effective dose was estimated to 1.8 mSv when using 300 MBq of presented radioligand. The critical organ was the urinary bladder. Due to the low effective dose coefficient of this radioligand, longitudinal studies for drug development and treatment monitoring of neuropsychiatric disorders including neurodegenerative diseases are possible. Trial registration Registered on 11th of June 2019 at https://www.basg.gv.at (EudraCT: 2018-002933-39).

First-in-Humans Brain PET Imaging of the GluN2B-Containing N-methyl-d-aspartate Receptor with (R)-11C-Me-NB1.

The N-methyl-d-aspartate receptor (NMDAR) plays a crucial role in neurodegenerative diseases such as Alzheimer disease and in the treatment of major depression by fast-acting antidepressants such as ketamine. Given their broad implications, GluN2B-containing NMDARs have been of interest as diagnostic and therapeutic targets. Recently, (R)-11C-Me-NB1 was investigated preclinically and shown to be a promising radioligand for imaging GluN2B subunits. Here, we report on the performance characteristics of this radioligand in a first-in-humans PET study. Methods: Six healthy male subjects were scanned twice on a fully integrated PET/MR scanner with (R)-11C-Me-NB1 for 120 min. Brain uptake and tracer distribution over time were investigated by SUVs. Test-retest reliability was assessed with the absolute percentage difference and the coefficient of variation. Exploratory total volumes of distribution (VT) were computed using an arterial input function and the Logan plot as well as a constrained 2-tissue-compartment model with the ratio of rate constants between plasma and tissue compartments (K1/k2) coupled (2TCM). SUV was correlated with VT to investigate its potential as a surrogate marker of GluN2B expression. Results: High and heterogeneous radioligand uptake was observed across the entire gray matter with reversible kinetics within the scan time. SUV absolute percentage difference ranged from 6.9% to 8.5% and coefficient of variation from 4.9% to 6.0%, indicating a high test-retest reliability. A moderate correlation was found between SUV averaged from 70 to 90 min and VT using Logan plot (Spearman ρ = 0.44). Correlation between VT Logan and 2TCM was r = 0.76. Conclusion: The radioligand (R)-11C-Me-NB1 was highly effective in mapping GluN2B-enriched NMDARs in the human brain. With a heterogeneous uptake and a high test-retest reliability, this radioligand offers promise to deepen our understanding of the GluN2B-containing NMDAR in the pathophysiology and treatment of neuropsychiatric disease such as Alzheimer disease and major depression. Additionally, it could help in the selection of appropriate doses of GluN2B-targeting drugs.

High-dose testosterone treatment reduces monoamine oxidase A levels in the human brain: A preliminary report.

The sex hormones testosterone and estradiol influence brain structure and function and are implicated in the pathogenesis, prevalence and disease course of major depression. Recent research employing gender-affirming hormone treatment (GHT) of gender dysphoric individuals and utilizing positron emission tomography (PET) indicates increased serotonin transporter binding upon high-dosages of testosterone treatment. Here, we investigated the effects of GHT on levels of monoamine oxidase A (MAO-A), another key target of antidepressant treatment. Participants underwent PET with the radioligand [11C]harmine to assess cerebral MAO-A distribution volumes (VT) before and four months after initiation of GHT. By the time this study was terminated for technical reasons, 18 transgender individuals undergoing GHT (11 transmen, TM and 7 transwomen, TW) and 17 cis-gender subjects had been assessed. Preliminary analysis of available data revealed statistically significant MAO-A VT reductions in TM under testosterone treatment in six of twelve a priori defined regions of interest (middle frontal cortex (-10%), anterior cingulate cortex (-9%), medial cingulate cortex (-10.5%), insula (-8%), amygdala (-9%) and hippocampus (-8.5%, all p<0.05)). MAO-A VT did not change in TW receiving estrogen treatment. Despite the limited sample size, pronounced MAO-A VT reduction could be observed, pointing towards a potential effect of testosterone. Considering MAO-A's central role in regulation of serotonergic neurotransmission, changes to MAO-A VT should be further investigated as a possible mechanism by which testosterone mediates risk for, symptomatology of, and treatment response in affective disorders.

Predicting Ventral Striatal Activation During Reward Anticipation From Functional Connectivity at Rest.

Reward anticipation is essential for directing behavior toward positively valenced stimuli, creating motivational salience. Task-related activation of the ventral striatum (VS) has long been used as a target for understanding reward function. However, some subjects may not be able to perform the respective tasks because of their complexity or subjects' physical or mental disabilities. Moreover, task implementations may differ, which results in limited comparability. Hence, developing a task-free method for evaluating neural gain circuits is essential. Research has shown that fluctuations in neuronal activity at rest denoted individual differences in the brain functional networks. Here, we proposed novel models to predict the activation of the VS during gain anticipation, using the functional magnetic resonance imaging data of 45 healthy subjects acquired during a monetary incentive delay task and under rest. In-sample validation and held-out data were used to estimate the generalizability of the models. It was possible to predict three measures of reward activation (sensitivity, average, maximum) from resting-state functional connectivity (Pearson's r = 0.38-0.54 in validation data). Especially high contributions to the models were observed from the default mode network. These findings highlight the potential of using functional connectivity at rest as a task-free alternative for predicting activation in the VS, offering a possibility to estimate reward response in the broader sampling of subject populations.