Correspondence between gene expression and neurotransmitter receptor and transporter density in the human brain

Involvement of dopamine D3 receptor in impulsive choice decision-making in male rats

Impulsive decision-making has been linked to impulse control disorders and substance use disorders. However, the neural mechanisms underlying impulsive choice are not fully understood. While previous PET imaging and autoradiography studies have shown involvement of dopamine and D2/3 receptors in impulsive behavior, the roles of distinct D1, D2, and D3 receptors in impulsive decision-making remain unclear. In this study, we used a food reward delay-discounting task (DDT) to identify low- and high-impulsive rats, in which low-impulsive rats exhibited preference for large delayed reward over small immediate rewards, while high-impulsive rats showed the opposite preference. We then examined D1, D2, and D3 receptor gene expression using RNAscope in situ hybridization assays. We found that high-impulsive male rats exhibited lower levels of D2 and D3, and particularly D3, receptor expression in the nucleus accumbens (NAc), with no significant changes in the insular, prelimbic, and infralimbic cortices. Based on these findings, we further explored the role of the D3 receptor in impulsive decision-making. Systemic administration of a selective D3 receptor agonist (FOB02-04) significantly reduced impulsive choices in high-impulsive rats but had no effects in low-impulsive rats. Conversely, a selective D3 receptor antagonist (VK4-116) produced increased both impulsive and omission choices in both groups of rats. These findings suggest that impulsive decision-making is associated with a reduction in D3 receptor expression in the NAc. Selective D3 receptor agonists, but not antagonists, may hold therapeutic potentials for mitigating impulsivity in high-impulsive subjects.

An In Vivo High-Resolution Human Brain Atlas of Synaptic Density

Synapses are fundamental to the function of the central nervous system and are implicated in a number of brain disorders. Despite their pivotal role, a comprehensive imaging resource detailing the distribution of synapses in the human brain has been lacking until now. Here, we employ high-resolution PET neuroimaging in healthy humans (17F/16M) to create a 3D atlas of the synaptic marker Synaptic Vesicle glycoprotein 2A (SV2A). Calibration to absolute density values (pmol/ml) was achieved by leveraging postmortem human brain autoradiography data. The atlas unveils distinctive cortical and subcortical gradients of synapse density that reflect functional topography and hierarchical order from core sensory to higher-order integrative areas-a distribution that diverges from SV2A mRNA patterns. Furthermore, we found a positive association between IQ and SV2A density in several higher-order cortical areas. This new resource will help advance our understanding of brain physiology and the pathogenesis of brain disorders, serving as a pivotal tool for future neuroscience research.

Psychosis as a disorder of muscarinic signalling: psychopathology and pharmacology

Dopaminergic receptor antagonism is a crucial component of all licensed treatments for psychosis, and dopamine dysfunction has been central to pathophysiological models of psychotic symptoms. Some clinical trials, however, indicate that drugs that act through muscarinic receptor agonism can also be effective in treating psychosis, potentially implicating muscarinic abnormalities in the pathophysiology of psychosis. Here, we discuss understanding of the central muscarinic system, and we examine preclinical, behavioural, post-mortem, and neuroimaging evidence for its involvement in psychosis. We then consider how altered muscarinic signalling could contribute to the genesis and maintenance of psychotic symptoms, and we review the clinical evidence for muscarinic agents as treatments. Finally, we discuss future research that could clarify the relationship between the muscarinic system and psychotic symptoms.

Genes related to neurotransmitter receptors as potential biomarkers for Alzheimer's disease

INTRODUCTION

Alzheimer's disease (AD) is a leading cause of dementia and is rapidly emerging as one of the costliest and most burdensome diseases. Neurotransmitter receptors play a vital role in many neuronal processes, primarily regulating signal inhibition within the brain to facilitate cell communication.

OBJECTIVES

Our research aims to identify potential biomarkers associated with AD and how these biomarkers impact immune infiltration.

METHODS

We extracted mRNA expression data from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) and differential expression analysis were employed to identify hub genes as biomarkers in AD. The Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and Gene Set Variation Analysis (GSVA) were used for functional enrichment. Furthermore, we examined 22 immune cell types infiltration using "CIBERSORT".

RESULTS

In this study, we identified 70 neurotransmitter receptor genes showing differential expression in AD: 22 were up-regulated, and 48 were down-regulated. Functional analyses indicated these genes were involved in essential biochemical pathways, including G protein-coupled receptors, neurotransmitter receptor activity, and ion channel interactions. WGCNA generated three co-expression modules, with one demonstrating the strongest association with AD. Five key NRGs (HTR3C, HTR3E, ADRA2A, HTR3A, and ADRA1D) were identified using a combination of differential genes. These genes have better diagnostic value by ROC analysis. Immune infiltration analysis showed that these genes were closely associated with the levels of resting mast cells, activated natural killer (NK) cells, and plasma cells in AD compared to controls.

CONCLUSION

Our study identified five NRGs (ADRA1D, ADRA2A, HTR3A, HTR3C, and HTR3E) with significant associations with AD. These findings may offer promising sights for further studies.

Molecular signatures of attention networks

Attention network theory proposes three distinct types of attention-alerting, orienting, and control-that are supported by separate brain networks and modulated by different neurotransmitters, that is, norepinephrine, acetylcholine, and dopamine. Here, we explore the extent of cortical, genetic, and molecular dissociation of these three attention systems using multimodal neuroimaging. We evaluated the spatial overlap between fMRI activation maps from the attention network test (ANT) and cortex-wide gene expression data from the Allen Human Brain Atlas. The goal was to identify genes associated with each of the attention networks in order to determine whether specific groups of genes were co-expressed with the corresponding attention networks. Furthermore, we analyzed publicly available PET-maps of neurotransmitter receptors and transporters to investigate their spatial overlap with the attention networks. Our analyses revealed a substantial number of genes (3871 for alerting, 6905 for orienting, 2556 for control) whose cortex-wide expression co-varied with the activation maps, prioritizing several molecular functions such as the regulation of protein biosynthesis, phosphorylation, and receptor binding. Contrary to the hypothesized associations, the ANT activation maps neither aligned with the distribution of norepinephrine, acetylcholine, and dopamine receptor and transporter molecules, nor with transcriptomic profiles that would suggest clearly separable networks. Independence of the attention networks appeared additionally constrained by a high level of spatial dependency between the network maps. Future work may need to reconceptualize the attention networks in terms of their segregation and reevaluate the presumed independence at the neural and neurochemical level.

CHRNA5 links chandelier cells to severity of amyloid pathology in aging and Alzheimer's disease

Changes in high-affinity nicotinic acetylcholine receptors are intricately connected to neuropathology in Alzheimer's Disease (AD). Protective and cognitive-enhancing roles for the nicotinic α5 subunit have been identified, but this gene has not been closely examined in the context of human aging and dementia. Therefore, we investigate the nicotinic α5 gene CHRNA5 and the impact of relevant single nucleotide polymorphisms (SNPs) in prefrontal cortex from 922 individuals with matched genotypic and post-mortem RNA sequencing in the Religious Orders Study and Memory and Aging Project (ROS/MAP). We find that a genotype robustly linked to increased expression of CHRNA5 (rs1979905A2) predicts significantly reduced cortical β-amyloid load. Intriguingly, co-expression analysis suggests CHRNA5 has a distinct cellular expression profile compared to other nicotinic receptor genes. Consistent with this prediction, single nucleus RNA sequencing from 22 individuals reveals CHRNA5 expression is disproportionately elevated in chandelier neurons, a distinct subtype of inhibitory neuron known for its role in excitatory/inhibitory (E/I) balance. We show that chandelier neurons are enriched in amyloid-binding proteins compared to basket cells, the other major subtype of PVALB-positive interneurons. Consistent with the hypothesis that nicotinic receptors in chandelier cells normally protect against β-amyloid, cell-type proportion analysis from 549 individuals reveals these neurons show amyloid-associated vulnerability only in individuals with impaired function/trafficking of nicotinic α5-containing receptors due to homozygosity of the missense CHRNA5 SNP (rs16969968A2). Taken together, these findings suggest that CHRNA5 and its nicotinic α5 subunit exert a neuroprotective role in aging and Alzheimer's disease centered on chandelier interneurons.

Resting-state alterations in behavioral variant frontotemporal dementia are related to the distribution of monoamine and GABA neurotransmitter systems

Background

Aside to clinical changes, behavioral variant frontotemporal dementia (bvFTD) is characterized by progressive structural and functional alterations in frontal and temporal regions. We examined if there is a selective vulnerability of specific neurotransmitter systems in bvFTD by evaluating the link between disease-related functional alterations and the spatial distribution of specific neurotransmitter systems and their underlying gene expression levels.

Methods

Maps of fractional amplitude of low-frequency fluctuations (fALFF) were derived as a measure of local activity from resting-state functional magnetic resonance imaging for 52 bvFTD patients (mean age = 61.5 ± 10.0 years; 14 females) and 22 healthy controls (HC) (mean age = 63.6 ± 11.9 years; 13 females). We tested if alterations of fALFF in patients co-localize with the non-pathological distribution of specific neurotransmitter systems and their coding mRNA gene expression. Furthermore, we evaluated if the strength of co-localization is associated with the observed clinical symptoms.

Results

Patients displayed significantly reduced fALFF in frontotemporal and frontoparietal regions. These alterations co-localized with the distribution of serotonin (5-HT1b and 5-HT2a) and γ-aminobutyric acid type A (GABAa) receptors, the norepinephrine transporter (NET), and their encoding mRNA gene expression. The strength of co-localization with NET was associated with cognitive symptoms and disease severity of bvFTD.

Conclusions

Local brain functional activity reductions in bvFTD followed the distribution of specific neurotransmitter systems indicating a selective vulnerability. These findings provide novel insight into the disease mechanisms underlying functional alterations. Our data-driven method opens the road to generate new hypotheses for pharmacological interventions in neurodegenerative diseases even beyond bvFTD.

Funding

This study has been supported by the German Consortium for Frontotemporal Lobar Degeneration, funded by the German Federal Ministry of Education and Research (BMBF; grant no. FKZ01GI1007A).

Towards a biologically annotated brain connectome

The brain is a network of interleaved neural circuits. In modern connectomics, brain connectivity is typically encoded as a network of nodes and edges, abstracting away the rich biological detail of local neuronal populations. Yet biological annotations for network nodes - such as gene expression, cytoarchitecture, neurotransmitter receptors or intrinsic dynamics - can be readily measured and overlaid on network models. Here we review how connectomes can be represented and analysed as annotated networks. Annotated connectomes allow us to reconceptualize architectural features of networks and to relate the connection patterns of brain regions to their underlying biology. Emerging work demonstrates that annotated connectomes help to make more veridical models of brain network formation, neural dynamics and disease propagation. Finally, annotations can be used to infer entirely new inter-regional relationships and to construct new types of network that complement existing connectome representations. In summary, biologically annotated connectomes offer a compelling way to study neural wiring in concert with local biological features.

The biological role of local and global fMRI BOLD signal variability in human brain organization

Variability drives the organization and behavior of complex systems, including the human brain. Understanding the variability of brain signals is thus necessary to broaden our window into brain function and behavior. Few empirical investigations of macroscale brain signal variability have yet been undertaken, given the difficulty in separating biological sources of variance from artefactual noise. Here, we characterize the temporal variability of the most predominant macroscale brain signal, the fMRI BOLD signal, and systematically investigate its statistical, topographical and neurobiological properties. We contrast fMRI acquisition protocols, and integrate across histology, microstructure, transcriptomics, neurotransmitter receptor and metabolic data, fMRI static connectivity, and empirical and simulated magnetoencephalography data. We show that BOLD signal variability represents a spatially heterogeneous, central property of multi-scale multi-modal brain organization, distinct from noise. Our work establishes the biological relevance of BOLD signal variability and provides a lens on brain stochasticity across spatial and temporal scales.

Alterations of learning and memory are accompanied by alterations in the expression of 5-HT receptors, glucocorticoid receptor and brain-derived neurotrophic factor in different brain regions of an animal model of depression generated by neonatally male treatment with clomipramine in male rats

Depressive illness has been associated with impaired cognitive processes accompanied by reduced neurotrophin levels, especially brain-derived neurotrophic factor (BDNF), and dysfunctions in the hypothalamic-pituitary-adrenal (HPA) axis. In addition, depression is characterized by a decreased functioning of the serotonergic system due to changes in the activity or expression of its receptors including, most significantly, 5-HT1A, 5-HT2A, and 5-HT3 in brain regions that regulate mood, emotions, and memory, such as the prefrontal cortex, hippocampus, and amygdala. In this regard, rats treated with clomipramine (CMI) in the neonatal stage show depression-like behaviors that persist into adulthood; hence, this constitutes an adequate model of depression for exploring various molecular aspects associated with the etiology of this disorder. This, study, then, was designed to analyze the long-term effects of early postnatal exposure to CMI on the expression of 5-HT1A, 5-HT2A, and 5-HT3 receptors, as well as BDNF and GR in the following brain regions: PFC, amygdala, hippocampus, and hypothalamus, which could be related to alterations in memory and learning, as evaluated using the novel object recognition (NOR) and Morris water maze (MWM). Expression of the 5-HT1A, 5-HT2A, and 5-HT3 receptors, BDNF, and the glucocorticoid receptor (GR) was assessed by RT-qPCR in the four aforementioned brain regions, all of which play important roles in the control of memory and mood. Findings show that neonatal treatment with CMI causes alterations in memory and learning, as indicated by alterations in the results of the MWM and NOR tests. Expression of the 5-HT1A receptor increased in the hippocampus, amygdala, and hypothalamus, but decreased in the PFC, while the 5-HT2A and BDNF receptors decreased their expression in the PFC, amygdala, and hippocampus. There was no change in the expression of the 5-HT3 receptor. In addition, expression of GR in the hippocampus and PFC was low, but increased in the hypothalamus. Taken together, these data show that neonatal CMI treatment produces permanent molecular changes in brain regions related to learning and memory that could contribute to explaining the behavioral alterations observed in this model.

Genomic Structural Equation Modeling Reveals Latent Phenotypes in the Human Cortex with Distinct Genetic Architecture

Genetic contributions to human cortical structure manifest pervasive pleiotropy. This pleiotropy may be harnessed to identify unique genetically-informed parcellations of the cortex that are neurobiologically distinct from functional, cytoarchitectural, or other cortical parcellation schemes. We investigated genetic pleiotropy by applying genomic structural equation modeling (SEM) to map the genetic architecture of cortical surface area (SA) and cortical thickness (CT) for the 34 brain regions recently reported in the ENIGMA cortical GWAS. Genomic SEM uses the empirical genetic covariance estimated from GWAS summary statistics with LD score regression (LDSC) to discover factors underlying genetic covariance, which we are denoting genetically informed brain networks (GIBNs). Genomic SEM can fit a multivariate GWAS from summary statistics for each of the GIBNs, which can subsequently be used for LD score regression (LDSC). We found the best-fitting model of cortical SA identified 6 GIBNs and CT identified 4 GIBNs. The multivariate GWASs of these GIBNs identified 74 genome-wide significant (GWS) loci (p<5×10-8), including many previously implicated in neuroimaging phenotypes, behavioral traits, and psychiatric conditions. LDSC of GIBN GWASs found that SA-derived GIBNs had a positive genetic correlation with bipolar disorder (BPD), and cannabis use disorder, indicating genetic predisposition to a larger SA in the specific GIBN is associated with greater genetic risk of these disorders. A negative genetic correlation was observed with attention deficit hyperactivity disorder (ADHD), major depressive disorder (MDD), and insomnia, indicating genetic predisposition to a larger SA in the specific GIBN is associated with lower genetic risk of these disorders. CT GIBNs displayed a negative genetic correlation with alcohol dependence. Jointly modeling the genetic architecture of complex traits and investigating multivariate genetic links across phenotypes offers a new vantage point for mapping the cortex into genetically informed networks.

Patient-specific models link neurotransmitter receptor mechanisms with motor and visuospatial axes of Parkinson's disease

Parkinson's disease involves multiple neurotransmitter systems beyond the classical dopaminergic circuit, but their influence on structural and functional alterations is not well understood. Here, we use patient-specific causal brain modeling to identify latent neurotransmitter receptor-mediated mechanisms contributing to Parkinson's disease progression. Combining the spatial distribution of 15 receptors from post-mortem autoradiography with 6 neuroimaging-derived pathological factors, we detect a diverse set of receptors influencing gray matter atrophy, functional activity dysregulation, microstructural degeneration, and dendrite and dopaminergic transporter loss. Inter-individual variability in receptor mechanisms correlates with symptom severity along two distinct axes, representing motor and psychomotor symptoms with large GABAergic and glutamatergic contributions, and cholinergically-dominant visuospatial, psychiatric and memory dysfunction. Our work demonstrates that receptor architecture helps explain multi-factorial brain re-organization, and suggests that distinct, co-existing receptor-mediated processes underlie Parkinson's disease.

Cannabinoid receptor gene CNR1 is downregulated in subcortical brain samples and upregulated in blood samples of individuals with schizophrenia: A participant data systematic meta-analysis

Cannabis use leads to symptom exacerbation in schizophrenia patients, and endocannabinoid ligands have been studied as tentative schizophrenia therapeutics. Here, we aimed to characterise the connection between schizophrenia and the cannabinoid receptor 1 gene (CNR1) and explore possible mechanisms affecting its expression in schizophrenia. We performed a participant data systematic meta-analysis of CNR1 gene expression and additional endocannabinoid system genes in both brain (subcortical areas) and blood samples. We integrated eight brain sample datasets (overall 316 samples; 149 schizophrenia and 167 controls) and two blood sample datasets (overall 90 samples; 53 schizophrenia and 37 controls) while following the PRISMA meta-analysis guidelines. CNR1 was downregulated in subcortical regions and upregulated in blood samples of patients with schizophrenia. CNR2 and genes encoding endocannabinoids synthesis and degradation did not show differential expression in the brain or blood, except fatty acid amide hydrolase (FAAH), which showed a downregulation trend in blood. In addition, the brain expression levels of CNR1 and three GABA receptor genes, GABRA1, GABRA6 and GABRG2, were positively correlated (R = .57, .36, .54; p = 2.7 × 10-14 , 6.9 × 10-6 and 1.1 × 10-12 , respectively). Brain CNR1 downregulation and the positive correlation with three GABA receptor genes suggest an association with GABA neurotransmission and possible effects on negative schizophrenia symptoms. Further studies are required for clarifying the opposite CNR1 dysregulation in the brain and blood of schizophrenia patients and the potential of endocannabinoid ligands as schizophrenia therapeutics.

Gradients of neurotransmitter receptor expression in the macaque cortex

Dynamics and functions of neural circuits depend on interactions mediated by receptors. Therefore, a comprehensive map of receptor organization across cortical regions is needed. In this study, we used in vitro receptor autoradiography to measure the density of 14 neurotransmitter receptor types in 109 areas of macaque cortex. We integrated the receptor data with anatomical, genetic and functional connectivity data into a common cortical space. We uncovered a principal gradient of receptor expression per neuron. This aligns with the cortical hierarchy from sensory cortex to higher cognitive areas. A second gradient, driven by serotonin 5-HT1A receptors, peaks in the anterior cingulate, default mode and salience networks. We found a similar pattern of 5-HT1A expression in the human brain. Thus, the macaque may be a promising translational model of serotonergic processing and disorders. The receptor gradients may enable rapid, reliable information processing in sensory cortical areas and slow, flexible integration in higher cognitive areas.

The impact of regional heterogeneity in whole-brain dynamics in the presence of oscillations

Large variability exists across brain regions in health and disease, considering their cellular and molecular composition, connectivity, and function. Large-scale whole-brain models comprising coupled brain regions provide insights into the underlying dynamics that shape complex patterns of spontaneous brain activity. In particular, biophysically grounded mean-field whole-brain models in the asynchronous regime were used to demonstrate the dynamical consequences of including regional variability. Nevertheless, the role of heterogeneities when brain dynamics are supported by synchronous oscillating state, which is a ubiquitous phenomenon in brain, remains poorly understood. Here, we implemented two models capable of presenting oscillatory behavior with different levels of abstraction: a phenomenological Stuart-Landau model and an exact mean-field model. The fit of these models informed by structural- to functional-weighted MRI signal (T1w/T2w) allowed us to explore the implication of the inclusion of heterogeneities for modeling resting-state fMRI recordings from healthy participants. We found that disease-specific regional functional heterogeneity imposed dynamical consequences within the oscillatory regime in fMRI recordings from neurodegeneration with specific impacts on brain atrophy/structure (Alzheimer's patients). Overall, we found that models with oscillations perform better when structural and functional regional heterogeneities are considered, showing that phenomenological and biophysical models behave similarly at the brink of the Hopf bifurcation.

Relationships between neurotransmitter receptor densities and expression levels of their corresponding genes in the human hippocampus

Neurotransmitter receptors are key molecules in signal transmission, their alterations are associated with brain dysfunction. Relationships between receptors and their corresponding genes are poorly understood, especially in humans. We combined in vitro receptor autoradiography and RNA sequencing to quantify, in the same tissue samples (7 subjects), the densities of 14 receptors and expression levels of their corresponding 43 genes in the Cornu Ammonis (CA) and dentate gyrus (DG) of human hippocampus. Significant differences in receptor densities between both structures were found only for metabotropic receptors, whereas significant differences in RNA expression levels mostly pertained ionotropic receptors. Receptor fingerprints of CA and DG differ in shapes but have similar sizes; the opposite holds true for their "RNA fingerprints", which represent the expression levels of multiple genes in a single area. In addition, the correlation coefficients between receptor densities and corresponding gene expression levels vary widely and the mean correlation strength was weak-to-moderate. Our results suggest that receptor densities are not only controlled by corresponding RNA expression levels, but also by multiple regionally specific post-translational factors.

Association of CNR1 gene and cannabinoid 1 receptor protein in the human brain

We aimed to integrate genomic mapping from brain mRNA atlas with the protein expression from positron emission tomography (PET) scans of type 1 cannabinoid (CB1) receptor and to compare the predictive power of CB1 receptor with those of other neuroreceptor/transporters using a meta-analysis. Volume of distribution (V_T ) from F18-FMPEP-d2 PET scans, CNR1 gene (Cannabinoid receptor 1) expression, and H3-CP55940 binding were calculated and correlation analysis was performed. Between V_T of F18-FMPEP-d2 PET scans and CNR1 mRNA expression, moderate strength of correlation was observed (rho = .5067, p = .0337). Strong positive correlation was also found between CNR1 mRNA expression and H3-CP55940 binding (r = .6336, p = .0364), validating the finding between F18-FMPEP-d2 PET scans and CNR1 mRNA. The correlation between V_T of F18-FMPEP-d2 PET scans and H3-CP55940 binding was marginally significant (r = .5025, p = .0563). From the meta-analysis, the correlation coefficient between mRNA expression and protein expressions ranged from -.10 to .99, with a pooled effect of .76. In conclusion, we observed the moderate to strong associations between gene and protein expression for CB1 receptor in the human brain, which was validated by autoradiography. We combined the autoradiographic finding with PET of CB1 receptor, producing the density atlas map of CB1 receptor. From the meta-analysis, the moderate to strong correlation was observed between mRNA expression and protein expressions across multiple genes. Further study is needed to investigate the relationship between multiple genes and in vivo proteins to improve and accelerate drug development.

Chrna5 and lynx prototoxins identify acetylcholine super-responder subplate neurons

Attention depends on cholinergic excitation of prefrontal neurons but is sensitive to perturbation of α5-containing nicotinic receptors encoded by Chrna5. However, Chrna5-expressing (Chrna5+) neurons remain enigmatic, despite their potential as a target to improve attention. Here, we generate complex transgenic mice to probe Chrna5+ neurons and their sensitivity to endogenous acetylcholine. Through opto-physiological experiments, we discover that Chrna5+ neurons contain a distinct population of acetylcholine super-responders. Leveraging single-cell transcriptomics, we discover molecular markers conferring subplate identity on this subset. We determine that Chrna5+ super-responders express a unique complement of GPI-anchored lynx prototoxin genes (Lypd1, Ly6g6e, and Lypd6b), predicting distinct nicotinic receptor regulation. To manipulate lynx regulation of endogenous nicotinic responses, we developed a pharmacological strategy guided by transcriptomic predictions. Overall, we reveal Chrna5-Cre mice as a transgenic tool to target the diversity of subplate neurons in adulthood, yielding new molecular strategies to manipulate their cholinergic activation relevant to attention disorders.