Allen Brain Atlas Research Articles

Brain‐wide spatial analysis reveals cell‐type‐specific genetic modifiers of Alzheimer’s disease progression

AbstractBackgroundThere is significant variation in the age at onset and severity of cognitive decline among those with Alzheimer’s disease (AD). Despite strong genetic links to AD loci, the specific variants, target genes and cell types that drive AD‐related deterioration remain elusive. Recent advances in brain‐wide cell type and pathology quantification across our AD mouse genetic reference panel provide new opportunities to identify genetic factors that act in a cell‐type‐specific fashion to modify disease progression in response to causal AD mutations; linking, for the first time, genetics to regional cell composition to characterize susceptibility versus resilience to AD.MethodImmunohistochemistry was completed to evaluate neurodegeneration(NeuN), gliosis(Iba1&GFAP), and amyloid pathology(AB1‐42) in 250 mice from the AD‐BXD genetic reference panel. Using the QUINT workflow, hemibrain slices were systematically segmented and registered to the Allen Brain Atlas to gain a global perspective of percent cell/pathology coverage. The heritability of individual cell composition was calculated and quantitative trait loci(QTL) mapping was completed.ResultCompositional differences between the strains, particularly the BXD founder strains, became apparent when evaluating neurodegeneration and microglial proliferation. Despite comparable levels of amyloid, cortical and hippocampal NeuN and Iba1 coverage significantly varied among strains; however, this variation did not explain individual differences in short and long‐term memory capacity. Genetic mapping of individual cell composition traits identified a significant QTL associated with cortical neuron load (h = 0.6) on chromosome 17. Lrfn2 was identified as a gene of interest as it was differentially expressed between mice that had the BB vs BD genotype at the most significant variant location under the peak.ConclusionThis method of combining omics and imaging data to link changes in gene expression, cell composition, and behavior allows for the assessment of disease subtypes with the potential to aid the development of precision medicine solutions to AD. Specifically, changes in cell coverage can be associated with differences in gene expression among the AD‐BXD population to detect genes associated with regional cell composition. These candidates will be validated by creating cell‐type‐specific knock‐in or knock‐out models and measuring cognitive functioning to determine the effect of these genes on memory performance.

Structural and functional changes in drug-naïve benign childhood epilepsy with centrotemporal spikes and their associated gene expression profiles.

Benign epilepsy with centrotemporal spikes (BECTS) is a common pediatric epilepsy syndrome that has been widely reported to show abnormal brain structure and function. However, the genetic mechanisms underlying structural and functional changes remain largely unknown. Based on the structural and resting-state functional magnetic resonance imaging data of 22 drug-naïve children with BECTS and 33 healthy controls, we conducted voxel-based morphology (VBM) and fractional amplitude of low-frequency fluctuation (fALFF) analyses to compare cortical morphology and spontaneous brain activity between the 2 groups. In combination with the Allen Human Brain Atlas, transcriptome-neuroimaging spatial correlation analyses were applied to explore gene expression profiles associated with gray matter volume (GMV) and fALFF changes in BECTS. VBM analysis demonstrated significantly increased GMV in the right brainstem and right middle cingulate gyrus in BECTS. Moreover, children with BECTS exhibited significantly increased fALFF in left temporal pole, while decreased fALFF in right thalamus and left precuneus. These brain structural and functional alterations were closely related to behavioral and cognitive deficits, and the fALFF-linked gene expression profiles were enriched in voltage-gated ion channel and synaptic activity as well as neuron projection. Our findings suggest that brain morphological and functional abnormalities in children with BECTS involve complex polygenic genetic mechanisms.

Linking neuroanatomical abnormalities in autism spectrum disorder with gene expression of candidate ASD genes: A meta-analytic and network-oriented approach.

Autism spectrum disorder (ASD) is a set of developmental conditions with widespread neuroanatomical abnormalities and a strong genetic basis. Although neuroimaging studies have indicated anatomical changes in grey matter (GM) morphometry, their associations with gene expression remain elusive. Here, we aim to understand how gene expression correlates with neuroanatomical atypicalities in ASD. To do so, we performed a coordinate-based meta-analysis to determine the common GM variation pattern in the autistic brain. From the Allen Human Brain Atlas, we selected eight genes from the SHANK, NRXN, NLGN family and MECP2, which have been implicated with ASD, particularly in regards to altered synaptic transmission and plasticity. The gene expression maps for each gene were built. We then assessed the correlation between the gene expression maps and the GM alteration maps. Lastly, we projected the obtained clusters of GM alteration-gene correlations on top of the canonical resting state networks, in order to provide a functional characterization of the structural evidence. We found that gene expression of most genes correlated with GM alteration (both increase and decrease) in regions located in the default mode network. Decreased GM was also correlated with gene expression of some ASD genes in areas associated with the dorsal attention and cerebellar network. Lastly, single genes were found to be significantly correlated with increased GM in areas located in the somatomotor, limbic and ganglia/thalamus networks. This approach allowed us to combine the well beaten path of genetic and brain imaging in a novel way, to specifically investigate the relation between gene expression and brain with structural damage, and individuate genes of potential interest for further investigation in the functional domain.

Cortical profiles of numerous psychiatric disorders and normal development share a common pattern.

The neurobiological bases of the association between development and psychopathology remain poorly understood. Here, we identify a shared spatial pattern of cortical thickness (CT) in normative development and several psychiatric and neurological disorders. Principal component analysis (PCA) was applied to CT of 68 regions in the Desikan-Killiany atlas derived from three large-scale datasets comprising a total of 41,075 neurotypical participants. PCA produced a spatially broad first principal component (PC1) that was reproducible across datasets. Then PC1 derived from healthy adult participants was compared to the pattern of CT differences associated with psychiatric and neurological disorders comprising a total of 14,886 cases and 20,962 controls from seven ENIGMA disease-related working groups, normative maturation and aging comprising a total of 17,697 scans from the ABCD Study® and the IMAGEN developmental study, and 17,075 participants from the ENIGMA Lifespan working group, as well as gene expression maps from the Allen Human Brain Atlas. Results revealed substantial spatial correspondences between PC1 and widespread lower CT observed in numerous psychiatric disorders. Moreover, the PC1 pattern was also correlated with the spatial pattern of normative maturation and aging. The transcriptional analysis identified a set of genes including KCNA2, KCNS1 and KCNS2 with expression patterns closely related to the spatial pattern of PC1. The gene category enrichment analysis indicated that the transcriptional correlations of PC1 were enriched to multiple gene ontology categories and were specifically over-represented starting at late childhood, coinciding with the onset of significant cortical maturation and emergence of psychopathology during the prepubertal-to-pubertal transition. Collectively, the present study reports a reproducible latent pattern of CT that captures interregional profiles of cortical changes in both normative brain maturation and a spectrum of psychiatric disorders. The pubertal timing of the expression of PC1-related genes implicates disrupted neurodevelopment in the pathogenesis of the spectrum of psychiatric diseases emerging during adolescence.

Cortical morphometric vulnerability to generalised epilepsy reflects chromosome- and cell type-specific transcriptomic signatures.

Generalised epilepsy is thought to involve distributed brain networks. However, the molecular and cellular factors that render different brain regions more vulnerable to epileptogenesis remain largely unknown. We aimed to investigate epilepsy-related morphometric similarity network (MSN) abnormalities at the macroscale level and their relationships with microscale gene expressions at the microscale level. We compared the MSN of genetic generalised epilepsy with generalised tonic-clonic seizure patients (GGE-GTCS, n= 101) to demographically matched healthy controls (HC, n= 150). Cortical MSNs were estimated by combining seven morphometric features derived from structural magnetic resonance imaging for each individual. Regional gene expression profiles were derived from brain-wide microarray measurements provided by the Allen Human Brain Atlas. GGE-GTCS patients exhibited decreased regional MSNs in primary motor, prefrontal and temporal regions and increases in occipital, insular and posterior cingulate cortices, when compared with the HC. These case-control neuroimaging differences were validated using split-half analyses and were not affected by medication or drug response effects. When assessing associations with gene expression, genes associated with GGE-GTCS-related MSN differences were enriched in several biological processes, including 'synapse organisation', 'neurotransmitter transport' pathways and excitatory/inhibitory neuronal cell types. Collectively, the GGE-GTCS-related cortical vulnerabilities were associated with chromosomes 4, 5, 11 and 16 and were dispersed bottom-up at the cellular, pathway and disease levels, which contributed to epileptogenesis, suggesting diverse neurobiologically relevant enrichments in GGE-GTCS. By bridging the gaps between transcriptional signatures and in vivo neuroimaging, we highlighted the importance of using MSN abnormalities of the human brain in GGE-GTCS patients to investigate disease-relevant genes and biological processes.

How Do Our Brains Change as We Age?

Aging, which is a natural process in which an organism’s functions decline, is present in all living organisms. As we age, our brains begin to break down—certain brain regions get smaller and certain cell types decrease in number. These changes are similar to those seen in diseases like Alzheimer’s and Parkinson’s diseases. The similarities between aging and these neurodegenerative diseases tells us that the same genes might be affecting both processes. However, it is difficult to get samples of human brains to study aging, so we still do not understand what happens to genes in the various regions of the human brain during the aging process. Through global collaboration, a resource called the mouse brain Allen Brain Atlas (BrainMap) of 7 different cell types from cortex has been used, which is like a catalog of genes that are active in the human brain. We downloaded this database as used it as a comparative platform to our brain expression data. The study described in this article shows how protein coding regions of genes involved in different pathways are expressed across the brain, including in specific brain regions and specifically examining different cell type marker genes.

Cerebellar Functional Dysconnectivity in Drug-Naïve Patients With First-Episode Schizophrenia.

Cerebellar functional dysconnectivity has long been implicated in schizophrenia. However, the detailed dysconnectivity pattern and its underlying biological mechanisms have not been well-charted. This study aimed to conduct an in-depth characterization of cerebellar dysconnectivity maps in early schizophrenia. Resting-state fMRI data were processed from 196 drug-naïve patients with first-episode schizophrenia and 167 demographically matched healthy controls. The cerebellum was parcellated into nine functional systems based on a state-of-the-art atlas, and seed-based connectivity for each cerebellar system was examined. The observed connectivity alterations were further associated with schizophrenia risk gene expressions using data from the Allen Human Brain Atlas. Overall, we observed significantly increased cerebellar connectivity with the sensorimotor cortex, default-mode regions, ventral part of visual cortex, insula, and striatum. In contrast, decreased connectivity was shown chiefly within the cerebellum, and between the cerebellum and the lateral prefrontal cortex, temporal lobe, and dorsal visual areas. Such dysconnectivity pattern was statistically similar across seeds, with no significant group by seed interactions identified. Moreover, connectivity strengths of hypoconnected but not hyperconnected regions were significantly correlated with schizophrenia risk gene expressions, suggesting potential genetic underpinnings for the observed hypoconnectivity. These findings suggest a common bidirectional dysconnectivity pattern across different cerebellar subsystems, and imply that such bidirectional alterations may relate to different biological mechanisms.

Reduced signal propagation elicited by frontal transcranial magnetic stimulation is associated with oligodendrocyte abnormalities in treatment-resistant depression.

Background:The efficacy of repetitive transcranial magnetic stimulation (rTMS) to the left dorsolateral prefrontal cortex (dlPFC) has been established in patients with treatment-resistant depression (TRD), suggesting that alterations in signal propagation from the left dlPFC to other brain regions may be linked to the pathophysiology of TRD. Alterations at the cellular level, including dysfunction of oligodendrocytes, may contribute to these network abnormalities. The objectives of the present study were to compare signal propagation from the left dlPFC to other neural networks in patients with TRD and healthy controls. We used TMS combined with electroencephalography to explore links between cell-specific gene expression and signal propagation in TRD using a virtual-histology approach.Methods:We examined source-level estimated signal propagation from the left dlPFC to the 7 neural networks in 60 patients with TRD and 30 healthy controls. We also calculated correlations between the interregional profiles of altered signal propagation and gene expression for 9 neural cell types derived from the Allen Human Brain Atlas data set.Results:Signal propagation from the left dlPFC to the salience network was reduced in the θ and α bands in patients with TRD (p = 0.0055). Furthermore, this decreased signal propagation was correlated with cellspecific gene expression of oligodendrocytes (p < 0.000001).Limitations:These results show only part of the pathophysiology of TRD, because stimulation was limited to the left dlPFC.Conclusion:Reduced signal propagation from the left dlPFC to the salience network may represent a pathophysiological endophenotype of TRD; this finding may be associated with reduced expression of oligodendrocytes.

Public Transcriptomic Data Meta-Analysis Demonstrates TAAR6 Expression in the Mental Disorder-Related Brain Areas in Human and Mouse Brain

G protein-coupled trace amine-associated receptors (TAAR) recognize different classes of amine compounds, including trace amines or other exogenous and endogenous molecules. Yet, most members of the TAAR family (TAAR2-TAAR9) are considered olfactory receptors involved in sensing innate odors. In this study, TAAR6 mRNA expression was evaluated in the brain transcriptomic datasets available in the GEO, Allen Brain Atlas, and GTEx databases. Transcriptomic data analysis demonstrated ubiquitous weak TAAR6 mRNA expression in the brain, especially in the prefrontal cortex and nucleus accumbens. RNA sequencing of isolated cells from the nucleus accumbens showed that the expression of TAAR6 in some cell populations may be more pronounced than in whole-tissue samples. Curiously, in D1 and D2 dopamine receptor-expressing medium spiny GABAergic neurons of the nucleus accumbens, TAAR6 expression was co-regulated with genes involved in G protein-coupled receptor signaling. However, in cholinergic interneurons of the nucleus accumbens, TAAR6 expression was not associated with the activation of any specific biological process. Finally, TAAR6 expression in the mouse prefrontal cortex was validated experimentally by RT-PCR analysis. These data demonstrated that TAAR6 is expressed at low levels in the human and mouse brain, particularly in limbic structures involved in the pathogenesis of mental disorders, and thus might represent a new pharmacotherapeutic target.

Microstructural imaging and transcriptomics of the basal forebrain in first-episode psychosis

Cholinergic dysfunction has been implicated in the pathophysiology of psychosis and psychiatric disorders such as schizophrenia, depression, and bipolar disorder. The basal forebrain (BF) cholinergic nuclei, defined as cholinergic cell groups Ch1-3 and Ch4 (Nucleus Basalis of Meynert; NBM), provide extensive cholinergic projections to the rest of the brain. Here, we examined microstructural neuroimaging measures of the cholinergic nuclei in patients with untreated psychosis (~31 weeks of psychosis, <2 defined daily dose of antipsychotics) and used magnetic resonance spectroscopy (MRS) and transcriptomic data to support our findings. We used a cytoarchitectonic atlas of the BF to map the nuclei and obtained measures of myelin (quantitative T1, or qT1 as myelin surrogate) and microstructure (axial diffusion; AxD). In a clinical sample (n = 85; 29 healthy controls, 56 first-episode psychosis), we found significant correlations between qT1 of Ch1-3, left NBM and MRS-based dorsal anterior cingulate choline in healthy controls while this relationship was disrupted in FEP (p > 0.05). Case-control differences in qT1 and AxD were observed in the Ch1-3, with increased qT1 (reflecting reduced myelin content) and AxD (reflecting reduced axonal integrity). We found clinical correlates between left NBM qT1 with manic symptom severity, and AxD with negative symptom burden in FEP. Intracortical and subcortical myelin maps were derived and correlated with BF myelin. BF-cortical and BF-subcortical myelin correlations demonstrate known projection patterns from the BF. Using data from the Allen Human Brain Atlas, cholinergic nuclei showed significant enrichment for schizophrenia and depression-related genes. Cell-type specific enrichment indicated enrichment for cholinergic neuron markers as expected. Further relating the neuroimaging correlations to transcriptomics demonstrated links with cholinergic receptor genes and cell type markers of oligodendrocytes and cholinergic neurons, providing biological validity to the measures. These results provide genetic, neuroimaging, and clinical evidence for cholinergic dysfunction in schizophrenia.

Linking gene expression patterns and brain morphometry to trauma and symptom severity in patients with functional seizures

Within stress-diathesis models, adverse life experiences (ALEs) increase the susceptibility to functional neurological symptoms through neuroplasticity effects. We aimed to characterize potential genetic influences on this relationship in 20 patients with functional seizures. Questionnaires, structural MRIs and Allen Human Brain Atlas gene expression information were used to probe the intersection of symptom severity (Somatoform Dissociation Questionnaire, SDQ-20), ALE burden, and gray matter volumes. SDQ-20 scores positively correlated with sexual trauma, emotional neglect, and threat to life experiences. Higher SDQ-20 scores related to lower bilateral insula, left orbitofrontal, right amygdala, and perigenual/posterior cingulate volumes. Higher sexual trauma burden correlated with lower right posterior insula and putamen volumes; higher emotional neglect related to lower bilateral insula/right amygdala volumes. Findings in left insula/ventral precentral gyrus (SDQ-20), right insula/putamen (sexual trauma), and right amygdala (emotional neglect) held when controlling for comorbid psychopathology. At the intersection of symptom severity and sexual trauma volumetric findings, genes overrepresented in adrenergic, serotonergic, and oxytocin receptor signaling as well as in cortical and amygdala development were spatially correlated. In conclusion, ALEs and symptom severity were associated with gray matter volumes in cingulo-insular and amygdala areas, spatially overlapping with expression patterns of genes involved in stress-related signaling and neurodevelopment.

In Alzheimer-prone brain regions, metabolism and risk-gene expression are strongly correlated.

Neuroimaging in the preclinical phase of Alzheimer’s disease provides information crucial to early intervention, particularly in people with a high genetic risk. Metabolic network modularity, recently applied to the study of dementia, is increased in Alzheimer’s disease patients compared with controls, but network modularity in cognitively unimpaired elderly with various risks of developing Alzheimer’s disease needs to be determined. Based on their 5-year cognitive progression, we stratified 117 cognitively normal participants (78.3 ± 4.0 years of age, 52 women) into three age-matched groups, each with a different level of risk for Alzheimer’s disease. From their fluorodeoxyglucose PET we constructed metabolic networks, evaluated their modular structures using the Louvain algorithm, and compared them between risk groups. As the risk for Alzheimer’s disease increased, the metabolic connections among brain regions weakened and became more modular, indicating network fragmentation and functional impairment of the brain. We then set out to determine the correlation between regional brain metabolism, particularly in the modules derived from the previous analysis, and the regional expression of Alzheimer-risk genes in the brain, obtained from the Allen Human Brain Atlas. In all risk groups of this elderly population, the regional brain expression of most Alzheimer-risk genes showed a strong correlation with brain metabolism, particularly in the module that corresponded to regions of the brain that are affected earliest and most severely in Alzheimer’s disease. Among the genes, APOE and CD33 showed the strongest negative correlation and SORL1 showed the strongest positive correlation with brain metabolism. The Pearson correlation coefficients remained significant when contrasted against a null-hypothesis distribution of correlation coefficients across the whole transcriptome of 20 736 genes (SORL1: P = 0.0130; CD33, P = 0.0136; APOE: P = 0.0093). The strong regional correlation between Alzheimer-related gene expression in the brain and brain metabolism in older adults highlights the role of brain metabolism in the genesis of dementia.

Sex differences in the functional topography of association networks in youth

Prior work has shown that there is substantial interindividual variation in the spatial distribution of functional networks across the cerebral cortex, or functional topography. However, it remains unknown whether there are sex differences in the topography of individualized networks in youth. Here, we leveraged an advanced machine learning method (sparsity-regularized non-negative matrix factorization) to define individualized functional networks in 693 youth (ages 8 to 23 y) who underwent functional MRI as part of the Philadelphia Neurodevelopmental Cohort. Multivariate pattern analysis using support vector machines classified participant sex based on functional topography with 82.9% accuracy (P < 0.0001). Brain regions most effective in classifying participant sex belonged to association networks, including the ventral attention, default mode, and frontoparietal networks. Mass univariate analyses using generalized additive models with penalized splines provided convergent results. Furthermore, transcriptomic data from the Allen Human Brain Atlas revealed that sex differences in multivariate patterns of functional topography were spatially correlated with the expression of genes on the X chromosome. These results highlight the role of sex as a biological variable in shaping functional topography.

Association Between Accelerometer-Derived Physical Activity Measurements and Brain Structure: A Population-Based Cohort Study.

While there is growing evidence that physical activity promotes neuronal health, studies examining the relation between physical activity and brain morphology remain inconclusive. We therefore examined whether objectively quantified physical activity is related to brain volume, cortical thickness, and gray matter density in a large cohort study. In addition, we assessed molecular pathways that may underlie the effects of physical activity on brain morphology. We used cross-sectional baseline data from 2,550 eligible participants (57.6% women; mean age: 54.7 years, range: 30-94 years) of a prospective cohort study. Physical activity dose (metabolic equivalent hours and step counts) and intensity (sedentary and light-intensity and moderate-to-vigorous intensity activities) were recorded with accelerometers. Brain volumetric, gray matter density, and cortical thickness measures were obtained from 3T MRI scans using FreeSurfer and Statistical Parametric Mapping. The relation of physical activity (independent variable) and brain structure (outcome) was examined with polynomial multivariable regression, while adjusting for age, sex, intracranial volume, education, and smoking. Using gene expression profiles from the Allen Brain Atlas, we extracted molecular signatures associated with the effects of physical activity on brain morphology. Physical activity dose and intensity were independently associated with larger brain volumes, gray matter density, and cortical thickness of several brain regions. The effects of physical activity on brain volume were most pronounced at low physical activity quantities and differed between men and women and across age. For example, more time spent in moderate-to-vigorous intensity activities was associated with greater total gray matter volume, but the relation leveled off with more activity (standardized β [95% CIs]: 1.37 [0.35-2.39] and -0.70 [-1.25 to -0.15] for the linear and quadratic terms, respectively). The strongest effects of physical activity were observed in motor regions and cortical regions enriched for genes involved in mitochondrial respiration. Our findings suggest that physical activity benefits brain health, with the strongest effects in motor regions and regions with a high oxidative demand. While young adults may particularly profit from additional high-intensity activities, older adults may already benefit from light-intensity activities. Physical activity and reduced sedentary time may be critical in the prevention of age-associated brain atrophy and neurodegenerative diseases.

Transcriptional substrates underlying functional connectivity profiles of subregions within the human sensorimotor cortex.

The human sensorimotor cortex has multiple subregions showing functional commonalities and differences, likely attributable to their connectivity profiles. However, the molecular substrates underlying such connectivity profiles are unclear. Here, transcriptome-neuroimaging spatial correlation analyses were performed between transcriptomic data from the Allen human brain atlas and resting-state functional connectivity (rsFC) of 24 fine-grained sensorimotor subregions from 793 healthy subjects. Results showed that rsFC of six sensorimotor subregions were associated with expression measures of six gene sets that were specifically expressed in brain tissue. These sensorimotor subregions could be classified into the polygenic- and oligogenic-modulated subregions, whose rsFC were related to gene sets diverging on their numbers (hundreds vs. dozens) and functional characteristics. First, the former were specifically expressed in multiple types of neurons and immune cells, yet the latter were not specifically expressed in any cortical cell types. Second, the former were preferentially expressed during the middle and late stages of cortical development, while the latter showed no preferential expression during any stages. Third, the former were prone to be enriched for general biological functions and pathways, but the latter for specialized biological functions and pathways. Fourth, the former were enriched for neuropsychiatric disorders, whereas this enrichment was absent for the latter. Finally, although the identified genes were commonly associated with sensorimotor behavioral processes, the polygenic-modulated subregions associated genes were additionally related to vision and dementia. These findings may advance our understanding of the functional homogeneity and heterogeneity of the human sensorimotor cortex from the perspective of underlying genetic architecture.

Genetic mechanisms underlying brain functional homotopy: a combined transcriptome and resting-state functional MRI study.

Functional homotopy, the high degree of spontaneous activity synchrony and functional coactivation between geometrically corresponding interhemispheric regions, is a fundamental characteristic of the intrinsic functional architecture of the brain. However, little is known about the genetic mechanisms underlying functional homotopy. Resting-state functional magnetic resonance imaging data from a discovery dataset (656 healthy subjects) and 2 independent cross-race, cross-scanner validation datasets (103 and 329 healthy subjects) were used to calculate voxel-mirrored homotopic connectivity (VMHC) indexing brain functional homotopy. In combination with the Allen Human Brain Atlas, transcriptome-neuroimaging spatial correlation analysis was conducted to identify genes linked to VMHC. We found 1,001 genes whose expression measures were spatially associated with VMHC. Functional enrichment analyses demonstrated that these VMHC-related genes were enriched for biological functions including protein kinase activity, ion channel regulation, and synaptic function as well as many neuropsychiatric disorders. Concurrently, specific expression analyses showed that these genes were specifically expressed in the brain tissue, in neurons and immune cells, and during nearly all developmental periods. In addition, the VMHC-associated genes were linked to multiple behavioral domains, including vision, execution, and attention. Our findings suggest that interhemispheric communication and coordination involve a complex interaction of polygenes with a rich range of functional features.

Neurotransmitter receptor densities are associated with changes in regional Cerebral blood flow during clinical ongoing pain.

Arterial spin labelling (ASL) plays an increasingly important role in neuroimaging pain research but does not provide molecular insights regarding how regional cerebral blood flow (rCBF) relates to underlying neurotransmission. Here, we integrate ASL with positron emission tomography (PET) and brain transcriptome data to investigate the molecular substrates of rCBF underlying clinically relevant pain states. Two data sets, representing acute and chronic ongoing pain respectively, were utilised to quantify changes in rCBF; one examining pre-surgical versus post-surgical pain, and the second comparing patients with painful hand Osteoarthritis to a group of matched controls. We implemented a whole-brain spatial correlation analysis to explore associations between change in rCBF (ΔCBF) and neurotransmitter receptor distributions derived from normative PET templates. Additionally, we utilised transcriptomic data from the Allen Brain Atlas to inform distributions of receptor expression. Both datasets presented significant correlations of ΔCBF with the μ-opioid and dopamine-D2 receptor expressions, which play fundamental roles in brain activity associated with pain experiences. ΔCBF also correlated with the gene expression distributions of several receptors involved in pain processing. Overall, this is the first study illustrating the molecular basis of ongoing pain ASL indices and emphasises the potential of rCBF as a biomarker in pain research.

Neurofilament light-associated connectivity in young-adult Huntington's disease is related to neuronal genes.

Upregulation of functional network connectivity in the presence of structural degeneration is seen in the premanifest stages of Huntington's disease (preHD) 10-15 years from clinical diagnosis. However, whether widespread network connectivity changes are seen in gene carriers much further from onset has yet to be explored. We characterized functional network connectivity throughout the brain and related it to a measure of disease pathology burden (CSF neurofilament light, NfL) and measures of structural connectivity in asymptomatic gene carriers, on average 24 years from onset. We related these measurements to estimates of cortical and subcortical gene expression. We found no overall differences in functional (or structural) connectivity anywhere in the brain comparing control and preHD participants. However, increased functional connectivity, particularly between posterior cortical areas, correlated with increasing CSF NfL level in preHD participants. Using the Allen Human Brain Atlas and expression-weighted cell-type enrichment analysis, we demonstrated that this functional connectivity upregulation occurred in cortical regions associated with regional expression of genes specific to neuronal cells. This relationship was validated using single-nucleus RNAseq data from post-mortem Huntington's disease and control brains showing enrichment of neuronal-specific genes that are differentially expressed in Huntington's disease. Functional brain networks in asymptomatic preHD gene carriers very far from disease onset show evidence of upregulated connectivity correlating with increased disease burden. These changes occur among brain areas that show regional expression of genes specific to neuronal GABAergic and glutamatergic cells.

Layer-Specific Changes in the Prefrontal Glia/Neuron Ratio Characterizes Patches of GeneExpression Disorganization in Children with Autism.

Autism spectrum disorder (ASD) is manifested by abnormal cell numbers and patches of gene expression disruption in higher-order brain regions. Here, we investigated whether layer-specific changes in glia/neuron ratios (GNR) characterize patches in the dorsolateral prefrontal cortex (DL-PFC) of children with ASD. We analyzed high-resolution digital images of postmortem human brains from 11 ASD and 11 non-ASD children obtained from the Autism Study of the Allen Human Brain Atlas. We found the GNR is overall reduced in the ASD DL-PFC. Moreover, layers II-III belonging to patches presented a lower GNR in comparison with layers V-VI. We here provide a new insight into how brain cells are arranged within patches that contributes to elucidate how neurodevelopmental programs are altered in ASD.

Alzheimer’s Disease-Related Genes Identified by Linking Spatial Patterns of Pathology and Gene Expression

BackgroundAlzheimer’s Disease (AD) is an age-related neurodegenerative disease with a poorly understood etiology, shown to be partly genetic. Glucose hypometabolism, extracellular Amyloid-beta (Aβ) deposition, and intracellular Tau deposition are cardinal features of AD and display characteristic spatial patterns in the brain. We hypothesize that regional differences in underlying gene expression confer either resistance or susceptibility to AD pathogenic processes and are associated with these spatial patterns. Data-driven methods for the identification of genes involved in AD pathogenesis complement hypothesis-driven approaches that reflect current theories about the disease. Here we present a data driven method for the identification of genes involved in AD pathogenesis based on comparing spatial patterns of normal gene expression to Positron Emission Tomography (PET) images of glucose hypometabolism, Aβ deposition, and Tau deposition.MethodsWe performed correlations between the cerebral cortex microarray samples from the six cognitively normal (CN) post-mortem Allen Human Brain Atlas (AHBA) specimens and PET FDG-18, AV-45, and AV-1451 tracer images from AD and CN participants in the Alzheimer’s Disease and Neuroimaging Initiative (ADNI) database. Correlation coefficients for each gene by each ADNI subject were then entered into a partial least squares discriminant analysis (PLS-DA) to determine sets that best classified the AD and CN groups. Pathway analysis via BioPlanet 2019 was then used to infer the function of implicated genes.ResultsWe identified distinct sets of genes strongly associated with each PET modality. Pathway analyses implicated novel genes involved in mitochondrial function, and Notch signaling, as well as genes previously associated with AD.ConclusionUsing an unbiased approach, we derived sets of genes with expression patterns spatially associated with FDG hypometabolism, Aβ deposition, and Tau deposition in AD. This methodology may complement population-based approaches for identifying the genetic underpinnings of AD.