The influence of season on glutamate and GABA levels in the healthy human brain investigated by magnetic resonance spectroscopy imaging.

Seasonal changes in neurotransmitter systems have been demonstrated in imaging studies and are especially noticeable in diseased states such as seasonal affective disorder (SAD). These modulatory neurotransmitters, such as serotonin, are influencing glutamatergic and GABAergic neurotransmission. Furthermore, central components of the circadian pacemaker are regulated by GABA (the suprachiasmatic nucleus) or glutamate (e.g., the retinohypothalamic tract). Therefore, we explored seasonal differences in the GABAergic and glutamatergic system in 159 healthy individuals using magnetic resonance spectroscopy imaging with a GABA-edited 3D-MEGA-LASER sequence at 3T. We quantified GABA+/tCr, GABA+/Glx, and Glx/tCr ratios (GABA+, GABA+ macromolecules; Glx, glutamate + glutamine; tCr, total creatine) in five different subcortical brain regions. Differences between time periods throughout the year, seasonal patterns, and stationarity were tested using ANCOVA models, curve fitting approaches, and unit root and stationarity tests, respectively. Finally, Spearman correlation analyses between neurotransmitter ratios within each brain region and cumulated daylight and global radiation were performed. No seasonal or monthly differences, seasonal patterns, nor significant correlations could be shown in any region or ratio. Unit root and stationarity tests showed stable patterns of GABA+/tCr, GABA+/Glx, and Glx/tCr levels throughout the year, except for hippocampal Glx/tCr. Our results indicate that neurotransmitter levels of glutamate and GABA in healthy individuals are stable throughout the year. Hence, despite the important correction for age and gender in the analyses of MRS derived GABA and glutamate, a correction for seasonality in future studies does not seem necessary. Future investigations in SAD and other psychiatric patients will be of high interest.

Escitalopram administration, relearning, and neuroplastic effects: A diffusion tensor imaging study in healthy individuals.

BACKGROUND: Neuroplastic processes are influenced by serotonergic agents, which reportedly alter white matter microstructure in humans in conjunction with learning. The goal of this double-blind, placebo-controlled imaging study was to investigate the neuroplastic properties of escitalopram and cognitive training on white matter plasticity during (re)learning as a model for antidepressant treatment and environmental factors. METHODS: Seventy-one healthy individuals (age=25.6 ± 5.0, 43 females) underwent three diffusion magnetic resonance imaging scans: at baseline, after 3 weeks of associative learning (emotional/non-emotional content), and after relearning shuffled associations for an additional 3 weeks. During the relearning phase, participants received a daily dose of 10 mg escitalopram or placebo orally. Fractional anisotropy (FA), and mean (MD), axial (AD), and radial diffusivity (RD) were calculated within the FMRIB software library and analyzed using tract-based spatial statistics. RESULTS: In a three-way repeated-measures marginal model with sandwich estimator standard errors, we found no significant effects of escitalopram and content on AD, FA, MD, and RD during both learning and relearning periods (pFDR>0.05). When testing for escitalopram or content effects separately, we also demonstrated no significant findings (pFDR>0.05) for any of the diffusion tensor imaging metrics. LIMITATIONS: The intensity of the study interventions might have been too brief to induce detectable white matter changes. DISCUSSION: Previous studies examining the effects of SSRIs on white matter tracts in humans have yielded inconclusive outcomes. Our results indicate that relearning under escitalopram does not affect the white matter microstructures in healthy individuals when administered for 3 weeks.

Neuroplastic effects of a selective serotonin reuptake inhibitor in relearning and retrieval.

Animal studies using selective serotonin reuptake inhibitors (SSRIs) and learning paradigms have demonstrated that serotonin is important for flexibility in executive functions and learning. SSRIs might facilitate relearning through neuroplastic processes and thus exert their clinical effects in psychiatric diseases where cognitive functioning is affected. However, translation of these mechanisms to humans is missing. In this randomized placebo-controlled trial, we assessed functional brain activation during learning and memory retrieval in healthy volunteers performing associative learning tasks aiming to translate facilitated relearning by SSRIs. To this extent, seventy-six participants underwent three MRI scanning sessions: (1) at baseline, (2) after three weeks of daily associative learning and subsequent retrieval (face-matching or Chinese character-noun matching) and (3) after three weeks of relearning under escitalopram (10 mg/day) or placebo. Associative learning and retrieval tasks were performed during each functional MRI (fMRI) session. Statistical modeling was done using a repeated-measures ANOVA, to test for content-by-treatment-by-time interaction effects. During the learning task, a significant substance-by-time interaction was found in the right insula showing a greater deactivation in the SSRI cohort after 21 days of relearning compared to the learning phase. In the retrieval task, there was a significant content-by-time interaction in the left angular gyrus (AG) with an increased activation in face-matching compared to Chinese-character matching for both learning and relearning phases. A further substance-by-time interaction was found in task performance after 21 days of relearning, indicating a greater decrease of performance in the placebo group. Our findings that escitalopram modulate insula activation demonstrates successful translation of relearning as a mechanism of SSRIs in human. Furthermore, we show that the left AG is an active component of correct memory retrieval, which coincides with previous literature. We extend the function of this region by demonstrating its activation is not only stimulus dependent but also time constrained. Finally, we were able to show that escitalopram aids in relearning, irrespective of content.

The Influence of Acute SSRI Administration on White Matter Microstructure in Patients Suffering From Major Depressive Disorder and Healthy Controls.

BACKGROUND: Selective serotonin reuptake inhibitors (SSRIs) are predominantly prescribed for people suffering from major depressive disorder. These antidepressants exert their effects by blocking the serotonin transporter (SERT), leading to increased levels of serotonin in the synaptic cleft and subsequently to an attenuation of depressive symptoms and elevation in mood. Although long-term studies investigating white matter (WM) alterations after exposure to antidepressant treatment exist, results on the acute effects on the brain's WM microstructure are lacking. METHODS: In this interventional longitudinal study, 81 participants were included (33 patients and 48 healthy controls). All participants underwent diffusion weighted imaging on 2 separate days, receiving either citalopram or placebo using a randomized, double-blind, cross-over design. Fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity were calculated within the FMRIB software library and analyzed using tract-based spatial statistics. RESULTS: The repeated-measures ANOVA model revealed significant decreases after SSRI administration in mean diffusivity, axial diffusivity, and radial diffusivity regardless of the group (P < .05, family-wise error [FWE] corrected). Results were predominantly evident in frontal WM regions comprising the anterior corona radiata, corpus callosum, and external capsule and in distinct areas of the frontal blade. No increases in diffusivity were found, and no changes in fractional anisotropy were present. CONCLUSIONS: Our investigation provides the first evidence, to our knowledge, that fast WM microstructure adaptations within 1 hour after i.v. SSRI administration precede elevations in mood due to SSRI treatment. These results add a new facet to the complex mode of action of antidepressant therapy. This study was registered at clinicaltrials.gov with the identifier NCT02711215.

Effects of SSRI treatment on GABA and glutamate levels in an associative relearning paradigm.

Impaired cognitive flexibility represents a widespread symptom in psychiatric disorders, including major depressive disorder (MDD), a disease, characterized by an imbalance of neurotransmitter concentrations. While memory formation is mostly associated with glutamate, also gamma-Aminobutyric acid (GABA) and serotonin show attributions in a complex interplay between neurotransmitter systems. Treatment with selective serotonin reuptake inhibitors (SSRIs) does not solely affect the serotonergic system but shows downstream effects on GABA- and glutamatergic neurotransmission, potentially helping to restore cognitive function via neuroplastic effects. Hence, this study aims to elaborate the effects of associative relearning and SSRI treatment on GABAergic and glutamatergic function within and between five brain regions using magnetic resonance spectroscopy imaging (MRSI). In this study, healthy subjects were randomized into four groups which underwent three weeks of an associative relearning paradigm, with or without emotional connotation, under SSRI (10mg escitalopram) or placebo administration. MRSI measurements, using a spiral-encoded, 3D-GABA-edited MEGA-LASER sequence at 3T, were performed on the first and last day of relearning. Mean GABA+/tCr (GABA+ = GABA + macromolecules; tCr = total creatine) and Glx/tCr (Glx = glutamate + glutamine) ratios were quantified in a ROI-based approach for the hippocampus, insula, putamen, pallidum and thalamus, using LCModel. A total of 66 subjects ((37 female, mean age ± SD = 25.4±4.7) for Glx/tCr and 58 subjects (32 female, mean age ± SD = 25.1±4.7) for GABA+/tCr were included in the final analysis. A significant measurement by region and treatment (SSRI vs placebo) interaction on Glx/tCr ratios was found (pcor=0.017), with post hoc tests confirming differential effects on hippocampus and thalamus (pcor=0.046). Moreover, treatment by time comparison, for each ROI independently, showed a reduction of hippocampal Glx/tCr ratios after SSRI treatment (puncor=0.033). No significant treatment effects on GABA+/tCr ratios or effects of relearning condition on any neurotransmitter ratio could be found. Here, we showed a significant SSRI- and relearning-driven interaction effect of hippocampal and thalamic Glx/tCr levels, suggesting differential behavior based on different serotonin transporter and receptor densities. Moreover, an indication for Glx/tCr adaptions in the hippocampus after three weeks of SSRI treatment could be revealed. Our findings are in line with animal studies reporting glutamate adaptions in the hippocampus following chronic SSRI intake. Due to the complex interplay of serotonin and hippocampal function, involving multiple serotonin receptor subtypes on glutamatergic cells and GABAergic interneurons, the interpretation of underlying neurobiological actions remains challenging.

Association of norepinephrine transporter methylation with in vivo NET expression and hyperactivity-impulsivity symptoms in ADHD measured with PET.

Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder with a robust genetic influence. The norepinephrine transporter (NET) is of particular interest as it is one of the main targets in treatment of the disorder. As ADHD is a complex and polygenetic condition, the possible regulation by epigenetic processes has received increased attention. We sought to determine possible differences in NET promoter DNA methylation between patients with ADHD and healthy controls. DNA methylation levels in the promoter region of the NET were determined in 23 adult patients with ADHD and 23 healthy controls. A subgroup of 18 patients with ADHD and 18 healthy controls underwent positron emission tomography (PET) with the radioligand (S,S)-[18F]FMeNER-D2 to quantify the NET in several brain areas in vivo. Analyses revealed significant differences in NET methylation levels at several cytosine-phosphate-guanine (CpG) sites between groups. A defined segment of the NET promoter ("region 1") was hypermethylated in patients in comparison with controls. In ADHD patients, a negative correlation between methylation of a CpG site in this region and NET distribution in the thalamus, locus coeruleus, and the raphe nuclei was detected. Furthermore, methylation of several sites in region 1 was negatively associated with the severity of hyperactivity-impulsivity symptoms. Our results point to an epigenetic dysregulation in ADHD, possibly due to a compensatory mechanisms or additional factors involved in transcriptional processing.

Machine learning classification of ADHD and HC by multimodal serotonergic data.

Serotonin neurotransmission may impact the etiology and pathology of attention-deficit and hyperactivity disorder (ADHD), partly mediated through single nucleotide polymorphisms (SNPs). We propose a multivariate, genetic and positron emission tomography (PET) imaging classification model for ADHD and healthy controls (HC). Sixteen patients with ADHD and 22 HC were scanned by PET to measure serotonin transporter (SERT') binding potential with [11C]DASB. All subjects were genotyped for thirty SNPs within the HTR1A, HTR1B, HTR2A and TPH2 genes. Cortical and subcortical regions of interest (ROI) were defined and random forest (RF) machine learning was used for feature selection and classification in a five-fold cross-validation model with ten repeats. Variable selection highlighted the ROI posterior cingulate gyrus, cuneus, precuneus, pre-, para- and postcentral gyri as well as the SNPs HTR2A rs1328684 and rs6311 and HTR1B rs130058 as most discriminative between ADHD and HC status. The mean accuracy for the validation sets across repeats was 0.82 (±0.09) with balanced sensitivity and specificity of 0.75 and 0.86, respectively. With a prediction accuracy above 0.8, the findings underlying the proposed model advocate the relevance of the SERT as well as the HTR1B and HTR2A genes in ADHD and hint towards disease-specific effects. Regarding the high rates of comorbidities and difficult differential diagnosis especially for ADHD, a reliable computer-aided diagnostic tool for disorders anchored in the serotonergic system will support clinical decisions.

Repetitive enhancement of serum BDNF subsequent to continuation ECT.

INTRODUCTION: Continuation electroconvulsive therapy (c-ECT) is highly effective for the prevention of depressive symptom relapse. There is a lack of understanding, about how c-ECT works in humans, particularly with regard to its effects on brain derived neurotrophic factor (BDNF) concentrations. Here, we aimed to close a gap in the literature by evaluating BDNF levels in patients receiving c-ECT. METHODS: We included 13 patients with either unipolar or bipolar depression (mean age ± SD: 55.5 ± 17.1; f/m: 10/3; unipolar/bipolar: 10/3) who received between one and four c-ECT (average per patient: 2.8). Serum BDNF (sBDNF) levels were assessed before and after each c-ECT sessions. Clinical assessments were also administered both before and after treatment. RESULTS: Our analysis revealed a significant increase in sBDNF after each treatment (c-ECT 1-3: P < 0.001, c-ECT 4: P = 0.018). The application of multiple c-ECT treatments was not, however, associated with further sBDNF enhancements. Psychometric scores were not significantly altered following c-ECT. DISCUSSION: An increase in sBDNF concentrations subsequent to c-ECT parallel data from the animal literature, which has linked regularly applied electrical stimulation to neuroplastic processes. This finding suggests a relationship between ECT-induced sBDNF concentrations and (sustained) remission status, considering a stable clinical condition across c-ECT.

The influence of the rs6295 gene polymorphism on serotonin-1A receptor distribution investigated with PET in patients with major depression applying machine learning.

Major depressive disorder (MDD) is the most common neuropsychiatric disease and despite extensive research, its genetic substrate is still not sufficiently understood. The common polymorphism rs6295 of the serotonin-1A receptor gene (HTR1A) is affecting the transcriptional regulation of the 5-HT1A receptor and has been closely linked to MDD. Here, we used positron emission tomography (PET) exploiting advances in data mining and statistics by using machine learning in 62 healthy subjects and 19 patients with MDD, which were scanned with PET using the radioligand [carbonyl-11C]WAY-100635. All the subjects were genotyped for rs6295 and genotype was grouped in GG vs C allele carriers. Mixed model was applied in a ROI-based (region of interest) approach. ROI binding potential (BPND) was divided by dorsal raphe BPND as a specific measure to highlight rs6295 effects (BPDiv). Mixed model produced an interaction effect of ROI and genotype in the patients' group but no effects in healthy controls. Differences of BPDiv was demonstrated in seven ROIs; parahippocampus, hippocampus, fusiform gyrus, gyrus rectus, supplementary motor area, inferior frontal occipital gyrus and lingual gyrus. For classification of genotype, 'RandomForest' and Support Vector Machines were used, however, no model with sufficient predictive capability could be computed. Our results are in line with preclinical data, mouse model knockout studies as well as previous clinical analyses, demonstrating the two-pronged effect of the G allele on 5-HT1A BPND for, we believe, the first time. Future endeavors should address epigenetic effects and allosteric heteroreceptor complexes. Replication in larger samples of MDD patients is necessary to substantiate our findings.

Simple and rapid quantification of serotonin transporter binding using [11C]DASB bolus plus constant infusion.

INTRODUCTION: In-vivo quantification of serotonin transporters (SERT) in human brain has been a mainstay of molecular imaging in the field of neuropsychiatric disorders and helped to explore the underpinnings of several medical conditions, therapeutic and environmental influences. The emergence of PET/MR hybrid systems and the heterogeneity of SERT binding call for the development of efficient methods making the investigation of larger or vulnerable populations with limited scanner time and simultaneous changes in molecular and functional measures possible. We propose [11C]DASB bolus plus constant infusion for these applications and validate it against standard analyses of dynamic PET data. METHODS: [11C]DASB bolus/infusion optimization was performed on data acquired after [11C]DASB bolus in 8 healthy subjects. Subsequently, 16 subjects underwent one scan using [11C]DASB bolus plus constant infusion with Kbol 160-179min and one scan after [11C]DASB bolus for inter-method reliability analysis. Arterial blood sampling and metabolite analysis were performed for all scans. Distribution volumes (VT) were obtained using Logan plots for bolus scans and ratios between tissue and plasma parent activity for bolus plus infusion scans for different time spans of the scan (VT-70 for 60-70min after start of tracer infusion, VT-90 for 75-90min, VT-120 for 100-120min) in 9 subjects. Omitting blood data, binding potentials (BPND) obtained using multilinear reference tissue modeling (MRTM2) and cerebellar gray matter as reference region were compared in 11 subjects. RESULTS: A Kbol of 160min was observed to be optimal for rapid equilibration in thalamus and striatum. VT-70 showed good intraclass correlation coefficients (ICCs) of 0.61-0.70 for thalamus, striatal regions and olfactory cortex with bias ≤5.1% compared to bolus scans. ICCs increased to 0.72-0.78 for VT-90 and 0.77-0.93 for VT-120 in these regions. BPND-90 had negligible bias ≤2.5%, low variability ≤7.9% and ICCs of 0.74-0.87; BPND-120 had ICCs of 0.73-0.90. Low-binding cortical regions and cerebellar gray matter showed a positive bias of ~8% and ICCs 0.57-0.68 at VT-90. Cortical BPND suffered from high variability and bias, best results were obtained for olfactory cortex and anterior cingulate cortex with ICC=0.74-0.75 for BPND-90. High-density regions amygdala and midbrain had a negative bias of -5.5% and -22.5% at VT-90 with ICC 0.70 and 0.63, respectively. CONCLUSIONS: We have optimized the equilibrium method with [11C]DASB bolus plus constant infusion and demonstrated good inter-method reliability with accepted standard methods and for SERT quantification using both VT and BPND in a range of different brain regions. With as little as 10-15min of scanning valid estimates of SERT VT and BPND in thalamus, amygdala, striatal and high-binding cortical regions could be obtained. Blood sampling seems vital for valid quantification of SERT in low-binding cortical regions. These methods allow the investigation of up to three subjects with a single radiosynthesis.

Imaging the neuroplastic effects of ketamine with VBM and the necessity of placebo control.

In the last years a plethora of studies have investigated morphological changes induced by behavioural or pharmacological interventions using structural T1-weighted MRI and voxel-based morphometry (VBM). Ketamine is thought to exert its antidepressant action by restoring neuroplasticity. In order to test for acute impact of a single ketamine infusion on grey matter volume we performed a placebo-controlled, double-blind investigation in healthy volunteers using VBM. 28 healthy individuals underwent two MRI sessions within a timeframe of 2 weeks, each consisting of two structural T1-weighted MRIs within a single session, one before and one 45min after infusion of S-ketamine (bolus of 0.11mg/kg, followed by an maintenance infusion of 0.12mg/kg) or placebo (0.9% NaCl infusion) using a crossover design. In the repeated-measures ANOVA with time (post-infusion/pre-infusion) and medication (placebo/ketamine) as factors, no significant effect of interaction and no effect of medication was found (FWE-corrected). Importantly, further post-hoc t-tests revealed a strong "decrease" of grey matter both in the placebo and the ketamine condition over time. This effect was evident mainly in frontal and temporal regions bilaterally with t-values ranging from 4.95 to 5.31 (FWE-corrected at p<0.05 voxel level). The vulnerabilities of VBM have been repeatedly demonstrated, with reports of influence of blood flow, tissue water and direct effects of pharmacological compounds on the MRI signal. Here again, we highlight that the relationship between intervention and VBM results is apparently subject to a number of physiological influences, which are partly unknown. Future studies focusing on the effects of ketamine on grey matter should try to integrate known influential factors such as blood flow into analysis. Furthermore, the results of this study highlight the importance of a carefully performed placebo condition in pharmacological fMRI studies.

Association of Protein Distribution and Gene Expression Revealed by PET and Post-Mortem Quantification in the Serotonergic System of the Human Brain.

Regional differences in posttranscriptional mechanisms may influence in vivo protein densities. The association of positron emission tomography (PET) imaging data from 112 healthy controls and gene expression values from the Allen Human Brain Atlas, based on post-mortem brains, was investigated for key serotonergic proteins. PET binding values and gene expression intensities were correlated for the main inhibitory (5-HT1A) and excitatory (5-HT2A) serotonin receptor, the serotonin transporter (SERT) as well as monoamine oxidase-A (MAO-A), using Spearman's correlation coefficients (rs) in a voxel-wise and region-wise analysis. Correlations indicated a strong linear relationship between gene and protein expression for both the 5-HT1A (voxel-wise rs = 0.71; region-wise rs = 0.93) and the 5-HT2A receptor (rs = 0.66; 0.75), but only a weak association for MAO-A (rs = 0.26; 0.66) and no clear correlation for SERT (rs = 0.17; 0.29). Additionally, region-wise correlations were performed using mRNA expression from the HBT, yielding comparable results (5-HT1Ars = 0.82; 5-HT2Ars = 0.88; MAO-A rs = 0.50; SERT rs = -0.01). The SERT and MAO-A appear to be regulated in a region-specific manner across the whole brain. In contrast, the serotonin-1A and -2A receptors are presumably targeted by common posttranscriptional processes similar in all brain areas suggesting the applicability of mRNA expression as surrogate parameter for density of these proteins.