Human Brain Atlas Research Articles

Molecular basis underlying functional connectivity of fusiform gyrus subregions: A transcriptome-neuroimaging spatial correlation study

The fusiform gyrus (FG) subserves a range of visual cognitive functions likely arising from its distinct subregions that present different connectivity profiles. Nevertheless, the molecular basis underlying such connectivity variability across FG subregions is still an open question. Resting-state functional magnetic resonance imaging (fMRI) data were collected from a discovery dataset (361 healthy subjects) and two independent cross-race, cross-scanner validation datasets (103 and 329 healthy subjects). We adopted a newly developed standardized pipeline to process gene expression data from the Allen Human Brain Atlas. Fine-grained FG subregions derived from the Human Brainnetome Atlas were utilized to measure seed-based resting-state functional connectivity (rsFC). Then, transcriptome-neuroimaging spatial association analyses were conducted to identify genes related to rsFC of each FG subregion. Results showed that rsFC of the left A37mv was associated with expression measures of 1063 genes, while there were no expression-rsFC correlations for the other subregions. The 1063 genes were mainly enriched for biological functions and pathways related to synaptic transmission, neurons, and neurotransmitter systems as well as for autism spectrum disorder. Specific expression analyses revealed that these rsFC-related genes were specifically expressed in brain tissue, in cortical neurons and immune cells, and during nearly all developmental periods. In addition, these genes were associated with multiple behavioral domains such as vision, language, and sensation. Finally, protein–protein interaction (PPI) analysis demonstrated that the genes could construct a PPI network with 37 hub genes. These findings may offer unique insights into the molecular basis underlying the functional heterogeneity of the FG.

Inflammation and Brain Structure in Schizophrenia and Other Neuropsychiatric Disorders

Previous in vitro and postmortem research suggests that inflammation may lead to structural brain changes via activation of microglia and/or astrocytic dysfunction in a range of neuropsychiatric disorders. To investigate the relationship between inflammation and changes in brain structures in vivo and to explore a transcriptome-driven functional basis with relevance to mental illness. This study used multistage linked analyses, including mendelian randomization (MR), gene expression correlation, and connectivity analyses. A total of 20 688 participants in the UK Biobank, which includes clinical, genomic, and neuroimaging data, and 6 postmortem brains from neurotypical individuals in the Allen Human Brain Atlas (AHBA), including RNA microarray data. Data were extracted in February 2021 and analyzed between March and October 2021. Genetic variants regulating levels and activity of circulating interleukin 1 (IL-1), IL-2, IL-6, C-reactive protein (CRP), and brain-derived neurotrophic factor (BDNF) were used as exposures in MR analyses. Brain imaging measures, including gray matter volume (GMV) and cortical thickness (CT), were used as outcomes. Associations were considered significant at a multiple testing-corrected threshold of P < 1.1 × 10-4. Differential gene expression in AHBA data was modeled in brain regions mapped to areas significant in MR analyses; genes were tested for biological and disease overrepresentation in annotation databases and for connectivity in protein-protein interaction networks. Of 20 688 participants in the UK Biobank sample, 10 828 (52.3%) were female, and the mean (SD) age was 55.5 (7.5) years. In the UK Biobank sample, genetically predicted levels of IL-6 were associated with GMV in the middle temporal cortex (z score, 5.76; P = 8.39 × 10-9), inferior temporal (z score, 3.38; P = 7.20 × 10-5), fusiform (z score, 4.70; P = 2.60 × 10-7), and frontal (z score, -3.59; P = 3.30 × 10-5) cortex together with CT in the superior frontal region (z score, -5.11; P = 3.22 × 10-7). No significant associations were found for IL-1, IL-2, CRP, or BDNF after correction for multiple comparison. In the AHBA sample, 5 of 6 participants (83%) were male, and the mean (SD) age was 42.5 (13.4) years. Brain-wide coexpression analysis showed a highly interconnected network of genes preferentially expressed in the middle temporal gyrus (MTG), which further formed a highly connected protein-protein interaction network with IL-6 (enrichment test of expected vs observed network given the prevalence and degree of interactions in the STRING database: 43 nodes/30 edges observed vs 8 edges expected; mean node degree, 1.4; genome-wide significance, P = 4.54 × 10-9). MTG differentially expressed genes that were functionally enriched for biological processes in schizophrenia, autism spectrum disorder, and epilepsy. In this study, genetically determined IL-6 was associated with brain structure and potentially affects areas implicated in developmental neuropsychiatric disorders, including schizophrenia and autism.

Unsuppressed Striatal Activity and Genetic Risk for Schizophrenia Associated With Individual Cognitive Performance Under Social Competition.

Social competition affects human behaviors by inducing psychosocial stress. The neural and genetic mechanisms of individual differences of cognitive-behavioral response to stressful situations in a competitive context remain unknown. We hypothesized that variation in stress-related brain activation and genetic heterogeneity associated with psychiatric disorders may play roles towards individually differential responses under stress. A total of 419 healthy subjects and 66 patients with schizophrenia were examined functional magnetic resonance imaging during working memory task including social competition stressors. We explored the correlation between stress-induced brain activity and individual working memory performance. The partial least squares regression was performed to examine the genetic correlates between stress-related activity and gene expression data from Allen Human Brain Atlas. Polygenic risk score (PRS) was used to assess individual genetic risk for schizophrenia. Greater suppression of bilateral striatal activity was associated with better behavioral improvement in working memory manipulation under social competition (left: rPearson = -0.245, P = 4.0 × 10-6, right: rPearson = -0.234, P = 1.0 × 10-5). Genes transcriptionally related to stress-induced activation were linked to genetic risk for schizophrenia (PFDR < 0.005). Participants with decreased accuracy under social competition exhibited higher PRS of schizophrenia (t = 2.328, P = .021). Patients with schizophrenia showed less suppressed striatal activity under social stress (F = 13.493, P = 3.5 × 10-4). Striatal activity change and genetic risk for schizophrenia might play a role in the individually behavioral difference in working memory manipulation under stress.

Transcriptomic and cellular decoding of functional brain connectivity changes reveal regional brain vulnerability to pro- and anti-inflammatory therapies

BackgroundSystemic inflammation induces acute changes in mood, motivation and cognition that closely resemble those observed in depressed individuals. However, the mechanistic pathways linking peripheral inflammation to depression-like psychopathology via intermediate effects on brain function remain incompletely understood. MethodsWe combined data from 30 patients initiating interferon-α treatment for Hepatitis-C and 20 anti-tumour necrosis factor (TNF) therapy for inflammatory arthritis and used resting-state functional magnetic resonance imaging to investigate acute effects of each treatment on regional global brain connectivity (GBC). We leveraged transcriptomic data from the Allen Human Brain Atlas to uncover potential biological and cellular pathways underpinning regional vulnerability to GBC changes induced by each treatment. ResultsInterferon-α and anti-TNF therapies both produced differential small-to-medium sized decreases in regional GBC. However, these were observed within distinct brain regions and the regional patterns of GBC changes induced by each treatment did not correlate suggesting independent underlying processes. Further, the spatial distribution of these differential GBC decreases could be captured by multivariate patterns of constitutive regional expression of genes respectively related to: i) neuroinflammation and glial cells; and ii) glutamatergic neurotransmission and neurons. The extent to which each participant expressed patterns of GBC changes aligning with these patterns of transcriptomic vulnerability also correlated with both acute treatment-induced changes in interleukin-6 (IL-6) and, for Interferon-α, longer-term treatment-associated changes in depressive symptoms. ConclusionsTogether, we present two transcriptomic models separately linking regional vulnerability to the acute effects of interferon-α and anti-TNF treatments on brain function to glial neuroinflammation and glutamatergic neurotransmission. These findings generate hypotheses about two potential brain mechanisms through which bidirectional changes in peripheral inflammation may contribute to the development/resolution of psychopathology.

Gene expression associated with human brain activations in facial expression recognition.

Previous studies identified some genetic loci of emotion, but few focused on human emotion-related gene expression. In this study, the facial expression recognition (FER) task-based high-resolution fMRI data of 203 subjects in the Human Connectome Project (HCP) and expression data of the six healthy human postmortem brain tissues in theAllen Human Brain Atlas (AHBA) were used to conduct a transcriptome-neuroimaging spatial association analysis. Finally, 371 genes were identified to be significantly associated with FER-related brain activations. Enrichment analyses revealed that FER-related genes were mainly expressed in the brain, especially neurons, and might be related to cell junction organization, synaptic functions, and nervous system development regulation, indicating that FER was a complex polygenetic biological process involving multiple pathways. Moreover, these genes exhibited higher enrichment for psychiatric diseases with heavy emotion impairments. This study provided new insight into understanding the FER-related biological mechanisms and might be helpful to explore treatment methods for emotion-related psychiatric disorders.

Limited power of dopamine transporter mRNA mapping for predicting dopamine transporter availability.

Dopamine transporters (DAT) are transmembrane proteins that translocate dopamine from the extracellular space into presynaptic neurons. We aimed to investigate the predictive power of DAT mRNA for DAT protein expression, measured using positron emission tomography (PET). We performed 18 F-FP-CIT PET scans in 35 healthy individuals. Binding potentials (BPND ) from the ventral striatum, caudate nucleus, putamen, and middle frontal, orbitofrontal, cingulate, parietal, and temporal cortices were measured. DAT gene expression data were obtained from the freely available Allen Human Brain Atlas derived from six healthy donors. The auto-correlation of PET-derived BPND s for DAT was intermediate (mean ρ2 =.66) with ρ2 ranging from .0811 to 1. However, the auto-correlation of mRNA expression was weak across the probes with a mean ρ2 of .09-.23. Cross-correlations between PET-derived BPND s and mRNA expression were weak with a mean ρ2 ranging from 0 to .22 across the probes. In conclusion, we observed weak associations between DAT mRNA expression and DAT availability in human brains. Therefore, DAT mRNA mapping may have only limited predictive power for DAT availability in humans. However, the difference in distribution of DAT mRNA and DAT protein may influence this limitation.

Frequency-dependent genetic modulation of neuronal oscillations: a combined transcriptome and resting-state functional MRI study.

Neuronal oscillations within certain frequency bands are assumed to associate with specific neural processes and cognitive functions. To examine this hypothesis, transcriptome-neuroimaging spatial correlation analysis was applied to resting-state functional magnetic resonance imaging data from 793 healthy individuals and gene expression data from the Allen Human Brain Atlas. We found that expression measures of 336 genes were correlated with fractional amplitude of low-frequency fluctuations (fALFF) in the slow-4 band (0.027-0.073Hz), whereas there were no expression-fALFF correlations for the other frequency bands. Furthermore, functional enrichment analyses showed that these slow-4 fALFF-related genes were mainly enriched for ion channel, synaptic function, and neuronal system as well as many neuropsychiatric disorders. Specific expression analyses demonstrated that these genes were specifically expressed in brain tissue, in neurons, and during the late stage of cortical development. Concurrently, the fALFF-related genes were linked to multiple behavioral domains, including dementia, attention, and emotion. In addition, these genes could construct a protein-protein interaction network supported by 30 hub genes. Our findings of a frequency-dependent genetic modulation of spontaneous neuronal activity may support the concept that neuronal oscillations within different frequency bands capture distinct neurobiological processes from the perspective of underlying molecular mechanisms.

Dynamic Functional Connectivity Alterations and Their Associated Gene Expression Pattern in Autism Spectrum Disorders.

Autism spectrum disorders (ASDs) are a group of heterogeneous neurodevelopmental disorders that are highly heritable and are associated with impaired dynamic functional connectivity (DFC). However, the molecular mechanisms behind DFC alterations remain largely unknown. Eighty-eight patients with ASDs and 87 demographically matched typical controls (TCs) from the Autism Brain Imaging Data Exchange II database were included in this study. A seed-based sliding window approach was then performed to investigate the DFC changes in each of the 29 seeds in 10 classic resting-state functional networks and the whole brain. Subsequently, the relationships between DFC alterations in patients with ASDs and their symptom severity were assessed. Finally, transcription-neuroimaging association analyses were conducted to explore the molecular mechanisms of DFC disruptions in patients with ASDs. Compared with TCs, patients with ASDs showed significantly increased DFC between the right dorsolateral prefrontal cortex (DLPFC) and left fusiform/lingual gyrus, between the DLPFC and the superior temporal gyrus, between the right frontal eye field (FEF) and left middle frontal gyrus, between the FEF and the right angular gyrus, and between the left intraparietal sulcus and the right middle temporal gyrus. Moreover, significant relationships between DFC alterations and symptom severity were observed. Furthermore, the genes associated with DFC changes in ASDs were identified by performing gene-wise across-sample spatial correlation analysis between gene expression extracted from six donors’ brain of the Allen Human Brain Atlas and case-control DFC difference. In enrichment analysis, these genes were enriched for processes associated with synaptic signaling and voltage-gated ion channels and calcium pathways; also, these genes were highly expressed in autistic disorder, chronic alcoholic intoxication and several disorders related to depression. These results not only demonstrated higher DFC in patients with ASDs but also provided novel insight into the molecular mechanisms underlying these alterations.

Transcriptomic Signatures Associated With Gray Matter Volume Changes in Patients With Functional Constipation.

Functional constipation, which belongs to the functional gastrointestinal disorder (FGID), is a common disease and significantly impacts daily life. FGID patients have been progressively proven with functional and structural alterations in various brain regions, but whether and how functional constipation affects the brain gray matter volume (GMV) remains unclear; besides, which genes are associated with the GMV changes in functional constipation is largely unknown. On account of the structural MRI image from the 30 functional constipation patients and 30 healthy controls (HCs), GMV analysis showed that functional constipation patients had significantly decreased GMV in the right orbital prefrontal cortex (OFC), left precentral gyrus (PreG), and bilateral thalamus (THA). Correlation analysis showed that the self-rating depressive scale, patient assessment of constipation quality of life (PAC-QOL), and Wexner constipation scores were negatively correlated with GMV of the OFC and negative correlations between PAC-QOL score and GMV of the bilateral THA. Based on the Allen Human Brain Atlas, a cross-sample spatial correlation was conducted and found that 18 genes’ expression values showed robust correlations with GMV changes in functional constipation patients. These outcomes highlight our recognition of the transcriptional features related to GMV changes in functional constipation and could be regarded as candidates to detect biological mechanisms of abnormality in functional constipation patients.

Structural brain and spinal cord damage in symptomatic and pre-symptomatic VAPB-related ALS

IntroductionThe VAPB gene is associated with fALS (fALS 8). This disease presents a variable phenotype and no study sought to characterize its neuroanatomical abnormalities until now. This study aims to evaluate structural brain and spinal cord abnormalities in symptomatic and pre-symptomatic VAPB-related ALS. MethodsThis cohort included 10 presymptomatic and 20 symptomatic carriers of the Pro56Ser VAPB variant as well as 30 matched controls and 20 individuals with sporadic ALS. They underwent detailed clinical evaluation and MRI in a 3 T scanner. Using volumetric T1 sequence, we computed cerebral cortical thickness (FreeSurfer), basal ganglia volumetry (T1 Multi-atlas) and SC morphometry (SpineSeg). DTI was used to assess white matter integrity (DTI Multi-atlas). Groups were compared using a generalized linear model with Bonferroni-corrected p values<0.05. We also plotted VAPB brain expression map using Allen Human Brain Atlas to compare with imaging findings. ResultsMean age of presymptomatic and symptomatic subjects were 43.2 and 51.9 years, respectively. Most patients had a predominant lower motor neuron phenotype (16/20). Sleep complaints and tremor were the most frequent additional manifestations. Compared to controls, symptomatic subjects had pallidal, brainstem and SC atrophy, whereas presymptomatic only had SC atrophy. This pattern also contrasted with the sALS group that presented motor cortex and corticospinal abnormalities. Brain structural damage and VAPB expression maps were highly overlapping. ConclusionVAPB-related ALS has a distinctive structural signature that targets the basal ganglia, brainstem and SC, which are regions with high VAPB expression. Neuroanatomical SC changes are evident before clinical onset of the disease.

Choroid plexus enlargement is associated with neuroinflammation and reduction of blood brain barrier permeability in depression

BackgroundRecent studies have shown that choroid plexuses (CP) may be involved in the neuro-immune axes, playing a role in the interaction between the central and peripheral inflammation. Here we aimed to investigate CP volume alterations in depression and their associations with inflammation. Methods51 depressed participants (HDRS score > 13) and 25 age- and sex-matched healthy controls (HCs) from the Wellcome Trust NIMA consortium were re-analysed for the study. All the participants underwent full peripheral cytokine profiling and simultaneous [11C]PK11195 PET/structural MRI imaging for measuring neuroinflammation and CP volume respectively. ResultsWe found a significantly greater CP volume in depressed subjects compared to HCs (t(76) = +2.17) that was positively correlated with [11C]PK11195 PET binding in the anterior cingulate cortex (r = 0.28, p = 0.02), prefrontal cortex (r = 0.24, p = 0.04), and insular cortex (r = 0.24, p = 0.04), but not with the peripheral inflammatory markers: CRP levels (r = 0.07, p = 0.53), IL-6 (r = -0.08, p = 0.61), and TNF-α (r = -0.06, p = 0.70). The CP volume correlated with the [11C]PK11195 PET binding in CP (r = 0.34, p = 0.005). Integration of transcriptomic data from the Allen Human Brain Atlas with the brain map depicting the correlations between CP volume and PET imaging found significant gene enrichment for several pathways involved in neuroinflammatory response. ConclusionThis result supports the hypothesis that changes in brain barriers may cause reduction in solute exchanges between blood and CSF, disturbing the brain homeostasis and ultimately contributing to inflammation in depression. Given that CP anomalies have been recently detected in other brain disorders, these results may not be specific to depression and might extend to other conditions with a peripheral inflammatory component.

Coexpression of Gene Transcripts with Monoamine Oxidase A Quantified by Human In Vivo Positron Emission Tomography.

The monoamine oxidase A (MAO-A) is integral to monoamine metabolism and is thus relevant to the pathophysiology of various neuropsychiatric disorders; however, associated gene-enzyme relations are not well understood. This study aimed to unveil genes coexpressed with MAO-A. Therefore, 18 179 mRNA expression maps (based on the Allen Human Brain Atlas) were correlated with the cerebral distribution volume (VT) of MAO-A assessed in 36 healthy subjects (mean age ± standard deviation: 32.9 ± 8.8 years, 18 female) using [11C]harmine positron emission tomography scans. Coexpression analysis was based on Spearman's ρ, over-representation tests on Fisher's exact test with false discovery rate (FDR) correction. The analysis revealed 35 genes in cortex (including B-cell translocation gene family, member 3, implicated in neuroinflammation) and 247 genes in subcortex (including kallikrein-related peptidase 10, implicated in Alzheimer's disease). Significantly over-represented Gene Ontology terms included "neuron development", "neuron differentiation", and "cell-cell signaling" as well as "axon" and "neuron projection". In vivo MAO-A enzyme distribution and MAOA expression did not correlate in cortical areas (ρ = 0.08) while correlation was found in subcortical areas (ρ = 0.52), suggesting influences of region-specific post-transcriptional and -translational modifications. The herein reported information could contribute to guide future genetic studies, deepen the understanding of associated pathomechanisms and assist in the pursuit of novel therapeutic targets.

Integrative ‐omics for discovery of network‐level disease biomarkers for Alzheimer’s disease

AbstractBackgroundA large number of genetic variations have been identified to be associated with Alzheimer’s disease (AD) and related traits. But the downstream biology through which they exert effect on the development of AD remains unknown. Leveraging genomic, transcriptomic and proteomic data, and various biological networks, we proposed a modularity‐constrained logistic regression model (M‐logistic) to identify a set of functionally connected SNPs, genes and proteins related to AD.MethodThe GWAS genotype data, RNA‐Seq gene expression data and Protein expression data were obtained from the ROS/MAP Project. Detailed data processing steps can be found in AMP‐AD (https://www.synapse.org). In total, 179 subjects with full set of data were included (Table. 1). Using peptides as seed, we prefiltered the data and included 186 peptides, 743 unique genes and 822 Single‐nucleotide polymorphisms (SNPs) from upstream of their connected genes (Fig. 1). Functional interactions from REACTOME database [1] and the SNP‐gene mapping relationship were used to construct the prior network. These functional connected ‐omics features were used to classify AD patients from non‐symptomatic group, including cognitive normal and mild cognitive impairment.ResultAcross 10‐fold cross‐validation, we observed that M‐logistic largely outperforms other state‐of‐the‐art models (Table. 2). For feature selection, the proposed model identified 305 features predictive of disease status, which appeared in more than 6 folds. When mapped back to the prior network, these features formed three big sub‐networks with &gt; 10 nodes (Fig. 2). For 20 genes in the largest sub‐network, their brain‐wide expression profile in the Allen Human Brain Atlas were found to be mostly correlated with the activation map of brain function term “vision” in Neurosynth [2] (Fig. 3).ConclusionM‐Logistic identified a set of SNPs, genes and proteins that are not only predictive of AD but also densely connected in the prior network. The trans‐omic paths in the selected sub‐networks indicates a potential pathway underlying the development of AD from SNPs to gene expression, protein expression and ultimately brain functional and structural changes. Future efforts are warranted to enable integrative analysis of multi‐omics data from decoupled subjects. [1] Fabregat et al., Nucleic acids research, 2018. [2] Yarkoni et al., Nature Method, 2011.

A novel MRI approach for evaluation of microstructural neurodegeneration in early Alzheimer disease

AbstractBackgroundCurrently, brain tissue atrophy serves as in vivo structural MRI biomarker of neurodegeneration in Alzheimer Disease (AD). However, postmortem histopathological studies show that neuronal loss in AD exceeds volumetric loss of tissue and that AD‐related memory loss begins when neurons are lost. Hence, in vivo detection of neurodegeneration preceding detectable atrophy is essential for early AD diagnosis.MethodOur innovative approach to assessing neuronal damage in vivo is based on (a) quantitative Gradient Recalled Echo (qGRE) MRI technique and (b) genetically‐informed relationships between qGRE metrics and major components of brain tissue cellular structure (neurons/neurites and glia) that were obtained using gene expression profiles across the human brain provided by the Allen Human Brain Atlas. Seventy participants were recruited from the Knight Alzheimer Disease Research Center, representing three groups: Healthy controls [Clinical Dementia Rating® (CDR®)=0, amyloid β (Aβ)‐negative), n=34] HC; Preclinical AD (CDR=0, Aβ‐positive, n=19), PC; and mild AD (CDR=0.5 or 1, Aβ‐positive, n=17), AD.ResultPreliminary data show that qGRE identified new biomarkers in AD brain characterizing tissues with significantly lower (termed Dark Matter) and relatively preserved (termed Viable Tissue) concentrations of neurons. The fraction of Dark Matter showed clinically important and significant differences between HC and PC groups in hippocampus, middle temporal, fusiform, postcentral, and inferior parietal brain regions. However, no HC vs. PC group difference was detected by the volumetric measurements (Figure 1). Further, measurements of the Dark Matter fraction in the hippocampus showed strong associations with Cerebrospinal fluid (CSF) amyloid Aβ42 (r=‐0.52), CSF ptau (r=0.60), 18F‐AV1415‐PET tau imaging (r=0.60), and PiB‐PET amyloid imaging (r=0.60). These associations were significantly stronger compared with volumetric measurements: CSF amyloid Aβ42 (r=0.18), CSF ptau (r=‐0.24), PET tau imaging (r=‐0.39), and PiB‐PET amyloid imaging (r=‐0.17)). Importantly, the Dark Matter fraction had a significant inter‐regional association (r=0.87) with neuronal count in the hippocampal subfields obtained from histopathological study of one participant who underwent in vivo qGRE 14 months prior to expiration (Figure 2).ConclusionqGRE‐based measurements identify the microstructural changes in early AD‐related neurodegeneration that are not recognized by structural MRI atrophy measurements, therefore providing new biomarkers for early AD detection.

Associating cognitive reserve and brain‐wide gene expression regarding Alzheimer's disease

AbstractBackgroundCognitive reserve (CR) is susceptibility to brain damages, which impacts the development of Alzheimer’s disease (AD). Whereas CR is associated with certain subnetworks of brain connectivity, little research has been done on identifying genes that contribute to these subnetworks. In this study, we linked these subnetworks to regional variation in brain‐wide gene expression. We utilized Allen Human Brain Atlas (AHBA) in that it comprises gene expression data spanning the whole brain.MethodWe extracted a binary subnetwork regarding CR from AD patients. Then we drew out gene expression patterns in the subnetwork’s regions of interest (ROIs) and constructed a gene network through Weighted Gene Co‐expression Network Analysis (WGCNA). To research the distinctive trait of this sub‐region gene network (SGN), we also constructed a whole‐brain gene network (WGN). We detected modules (clusters of highly interconnected genes) of each network and identified their hub genes (genes with high intra‐modular connectivity). We sought non‐preserved, unique modules in SGN compared to WGN using the median rank statistic. Finally, the biological process ontology of the hub genes was investigated by functional enrichment analysis.ResultWe constructed gene networks based on gene expression data of 10544 genes. WGN consisted of 90 nodes of whole‐brain regions and SGN consisted of 49 nodes of the subnetwork ROIs. While 18 modules were detected in SGN, modules yellow, magenta, red and black were identified as unique modules. Module magenta included novel co‐expressed gene clusters, and the other modules combined genes that were classified as different modules in WGN. Apoptotic process, including apoptosis‐regulation and neuron death, was enriched distinctively in the 4 non‐preserved modules. Neuronal death due to apoptosis is a common pathological feature in the brains of AD patients.ConclusionWe identified brain‐wide gene co‐expression modules that have unique specific connectivity patterns related to the CR subnetwork. This non‐preservation highlights the relevance of CR and gene expression patterns. Moreover, the modules were enriched for AD risk genes, further demonstrating the functional context of CR in AD. This study will provide the groundwork for novel insights and extensive research to associate brain‐wide gene expression and connectome‐wide phenotype regarding AD.

The interaction of APOE genotype and amyloid‐β PET predicts PET but not CSF measures of tauopathy in regions of high APOE mRNA expression

AbstractBackgroundThe apolipoprotein E (APOE) ε4 allele is the most well‐established genetic risk factor for late‐onset Alzheimer disease (AD). The ε4 allele is strongly linked with cerebral β‐amyloidosis whereas its relationship with tauopathy is less established. Here we investigate the relationship between APOE ε4 carrier status, regional amyloid‐β‐ (Aβ) and tau‐ positron emission topography (PET), APOE mRNA expression patterns, and cerebrospinal fluid phosphorylated tau (CSF ptau).Method350 participants from the Knight Alzheimer Disease Research Center (mean age = 69.7) underwent tau‐PET ([18F]‐flortaucipir) and Aβ‐PET ([18F]‐florbetapir) imaging. Tau‐ and Aβ‐ PET data were converted to standardized uptake value ratios (SUVRs). APOE ε4 carrier status was defined by the presence of at least one ε4 allele. CSF ptau data was available for 270 of the participants. Linear regression models were used to predict regional Aβ‐ and tau‐PET levels from APOE ε4 carrier status. Additional models were used to predict regional tau‐PET and CSF ptau from the interaction of APOE genotype and global Aβ‐PET. Age and sex were included as covariates in all models. Regional APOE mRNA expression was derived from the Allen Human Brain Atlas (Fig. 3G).ResultStrong associations were found between elevated regional tau‐ and Aβ‐ PET levels and APOE ε4 carrier status (Fig. 1A, B). There was a significant interaction between APOE genotype and global Aβ‐PET predicting tau‐PET levels specifically in the entorhinal, amygdala, and superior temporal regions (Fig 1C), but not CSF ptau (Fig. 2). The spatial pattern of APOE mRNA expression was significantly associated to the spatial pattern of APOE ε4 genotype exerted on regional tau‐PET, but less so for regional Aβ‐PET (Fig. 3).Conclusion APOE ε4 genotype exerts influence on tauopathy above its effect on Aβ. These effects occur in regions of the brain that have high APOE mRNA expression, suggesting potential local tissue vulnerability to tauopathy. The lack of an interaction in CSF ptau may be due to different roles soluble and aggregated forms of the tau protein play in AD pathophysiology.

Gene expression associated with individual variability in intrinsic functional connectivity

It has been revealed that intersubject variability (ISV) in intrinsic functional connectivity (FC) is associated with a wide variety of cognitive and behavioral performances. However, the underlying organizational principle of ISV in FC and its related gene transcriptional profiles remain unclear. Using resting-state fMRI data from the Human Connectome Project (299 adult participants) and microarray gene expression data from the Allen Human Brain Atlas, we conducted a transcription-neuroimaging association study to investigate the spatial configurations of ISV in intrinsic FC and their associations with spatial gene transcriptional profiles. We found that the multimodal association cortices showed the greatest ISV in FC, while the unimodal cortices and subcortical areas showed the least ISV. Importantly, partial least squares regression analysis revealed that the transcriptional profiles of genes associated with human accelerated regions (HARs) could explain 31.29% of the variation in the spatial distribution of ISV in FC. The top-related genes in the transcriptional profiles were enriched for the development of the central nervous system, neurogenesis and the cellular components of synapse. Moreover, we observed that the effect of gene expression profile on the heterogeneous distribution of ISV in FC was significantly mediated by the cerebral blood flow configuration. These findings highlighted the spatial arrangement of ISV in FC and their coupling with variations in transcriptional profiles and cerebral blood flow supply.

Standardizing workflows in imaging transcriptomics with the abagen toolbox.

Gene expression fundamentally shapes the structural and functional architecture of the human brain. Open-access transcriptomic datasets like the Allen Human Brain Atlas provide an unprecedented ability to examine these mechanisms in vivo; however, a lack of standardization across research groups has given rise to myriad processing pipelines for using these data. Here, we develop the abagen toolbox, an open-access software package for working with transcriptomic data, and use it to examine how methodological variability influences the outcomes of research using the Allen Human Brain Atlas. Applying three prototypical analyses to the outputs of 750,000 unique processing pipelines, we find that choice of pipeline has a large impact on research findings, with parameters commonly varied in the literature influencing correlations between derived gene expression and other imaging phenotypes by as much as ρ ≥ 1.0. Our results further reveal an ordering of parameter importance, with processing steps that influence gene normalization yielding the greatest impact on downstream statistical inferences and conclusions. The presented work and the development of the abagen toolbox lay the foundation for more standardized and systematic research in imaging transcriptomics, and will help to advance future understanding of the influence of gene expression in the human brain.

Divergent connectomic organization delineates genetic evolutionary traits in the human brain

The relationship between human brain connectomics and genetic evolutionary traits remains elusive due to the inherent challenges in combining complex associations within cerebral tissue. In this study, insights are provided about the relationship between connectomics, gene expression and divergent evolutionary pathways from non-human primates to humans. Using in vivo human brain resting-state data, we detected two co-existing idiosyncratic functional systems: the segregation network, in charge of module specialization, and the integration network, responsible for information flow. Their topology was approximated to whole-brain genetic expression (Allen Human Brain Atlas) and the co-localization patterns yielded that neuron communication functionalities—linked to Neuron Projection—were overrepresented cell traits. Homologue-orthologue comparisons using dN/dS-ratios bridged the gap between neurogenetic outcomes and biological data, summarizing the known evolutionary divergent pathways within the Homo Sapiens lineage. Evidence suggests that a crosstalk between functional specialization and information flow reflects putative biological qualities of brain architecture, such as neurite cellular functions like axonal or dendrite processes, hypothesized to have been selectively conserved in the species through positive selection. These findings expand our understanding of human brain function and unveil aspects of our cognitive trajectory in relation to our simian ancestors previously left unexplored.

Transcriptomic Signatures Associated With Regional Cortical Thickness Changes in Parkinson's Disease.

Cortical atrophy is a common manifestation in Parkinson’s disease (PD), particularly in advanced stages of the disease. To elucidate the molecular underpinnings of cortical thickness changes in PD, we performed an integrated analysis of brain-wide healthy transcriptomic data from the Allen Human Brain Atlas and patterns of cortical thickness based on T1-weighted anatomical MRI data of 149 PD patients and 369 controls. For this purpose, we used partial least squares regression to identify gene expression patterns correlated with cortical thickness changes. In addition, we identified gene expression patterns underlying the relationship between cortical thickness and clinical domains of PD. Our results show that genes whose expression in the healthy brain is associated with cortical thickness changes in PD are enriched in biological pathways related to sumoylation, regulation of mitotic cell cycle, mitochondrial translation, DNA damage responses, and ER-Golgi traffic. The associated pathways were highly related to each other and all belong to cellular maintenance mechanisms. The expression of genes within most pathways was negatively correlated with cortical thickness changes, showing higher expression in regions associated with decreased cortical thickness (atrophy). On the other hand, sumoylation pathways were positively correlated with cortical thickness changes, showing higher expression in regions with increased cortical thickness (hypertrophy). Our findings suggest that alterations in the balanced interplay of these mechanisms play a role in changes of cortical thickness in PD and possibly influence motor and cognitive functions.