Gene transcription profiles associated with inter-modular hubs and connection distance in human functional magnetic resonance imaging networks

Vértes, Petra E.; Rittman, Timothy; Whitaker, Kirstie; Romero-García, Rafael; Váša, František; Kitzbichler, Manfred G.; Wagstyl, Konrad; Fonagy, Peter; Dolan, Raymond J.; Jones, Peter B.; Goodyer, Ian; Bullmore, Edward T.

doi:10.1098/rstb.2015.0362

Cited by 210 publications

(250 citation statements)

References 68 publications

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“…While differential gene expression is most pronounced during prenatal development [39] and between subcortical structures [40], substantial spatial variation has also been described within the adult human cerebral cortex [40][41][42][43].…”

Section: Glossarymentioning

confidence: 99%

“…Despite the basic relationship between spatial proximity and gene expression similarity, even distant regions can resemble each other in their gene expression patterns if they share long-range connections. This is particularly true for a set of genes enriched in the supragranular layers of the human cortex, from which most cortical connections emerge [42,43]. Expression of these genes differs for example between sensorimotor networks and the DMN, while even distant DMN regions show similar expression patterns.…”

Section: Box 2 Extracting Gradients From High-dimensional Cortical Datamentioning

confidence: 99%

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Large-Scale Gradients in Human Cortical Organization

Huntenburg

Bazin

Margulies

2018

Trends in Cognitive Sciences

752

738

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Recent advances in mapping cortical areas in the human brain provide a basis for investigating the significance of their spatial arrangement. Here we describe a dominant gradient in cortical features that spans between sensorimotor and transmodal areas. We propose that this gradient constitutes a core organizing axis of the human cerebral cortex, and describe an intrinsic coordinate system on its basis. Studying the cortex with respect to these intrinsic dimensions can inform our understanding of how the spectrum of cortical function emerges from structural constraints. The Significance of Cortical LocationFor more than a century, neuroscientists have studied the cerebral cortex by delineating individual cortical areas (see Glossary) and mapping their function [1]. This agenda has substantially advanced in recent years, as automated parcellation methods improve and data sets of unprecedented size and quality become available [2][3][4]. Nevertheless, our understanding of how the complex structure of the cerebral cortex emerges and gives rise to its elaborate functions remains fragmentary. To complement the description of individual cortical areas, we propose an inquiry into the significance of their spatial arrangement, asking the basic question: Why are cortical areas located where they are?Early formulations of this question date to theories from classical neuroanatomy [1,[5][6][7]. They state that the spatial layout of cortical areas is not arbitrary, but a consequence of developmental mechanisms, shaped through evolutionary selection. The location of an area among its neighbors thus provides insight into its microstructural characteristics [6], its connections to other parts of the brain [7], and eventually its position in global processing hierarchies [8]. Consider, for example, the well-researched visual system of the macaque monkey [9,10]. Along the visual hierarchy, low-level visual features are increasingly abstracted and integrated with information from other systems. Traditionally, areas are ordered based on their degree of microstructural differentiation, and the classification of their connections as feedforward or feedback [11]. The framework we advocate emphasizes that an area's position in the visual processing hierarchy -and thus many of its microstructural and connectional features -is strongly related to its distance from the primary visual area [12,13].More generally, we propose that the spatial arrangement of areas along a global gradient between sensorimotor and transmodal regions is a key feature of human cortical organization. A gradient is an axis of variance in cortical features, along which areas fall in a spatially continuous order. Areas that resemble each other with respect to the feature of interest occupy similar positions along the gradient. As we will point out, there is a strong relationship between the similarity of two areas -that is, their relative position along the gradient -and their relative position along the cortical surface. This important role of cortical location pro...

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Section: Glossarymentioning

confidence: 99%

Section: Box 2 Extracting Gradients From High-dimensional Cortical Datamentioning

confidence: 99%

Large-Scale Gradients in Human Cortical Organization

Huntenburg

Bazin

Margulies

2018

Trends in Cognitive Sciences

752

738

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“…26) but not previously related to measures of cortical shrinkage or myelination. Recently, several studies have linked brain regional gene expression to axonal connectivity in the mouse (27,28) and functional MRI networks in humans (29,30), but there have been no previous efforts to investigate genetic mechanisms of adolescent myelination of human cortex.…”

Section: Significancementioning

confidence: 99%

Adolescence is associated with genomically patterned consolidation of the hubs of the human brain connectome

Whitaker

Vértes

Romero-García

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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483

534

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How does human brain structure mature during adolescence? We used MRI to measure cortical thickness and intracortical myelination in 297 population volunteers aged 14-24 y old. We found and replicated that association cortical areas were thicker and less myelinated than primary cortical areas at 14 y. However, association cortex had faster rates of shrinkage and myelination over the course of adolescence. Age-related increases in cortical myelination were maximized approximately at the internal layer of projection neurons. Adolescent cortical myelination and shrinkage were coupled and specifically associated with a dorsoventrally patterned gene expression profile enriched for synaptic, oligodendroglial-and schizophrenia-related genes. Topologically efficient and biologically expensive hubs of the brain anatomical network had greater rates of shrinkage/myelination and were associated with overexpression of the same transcriptional profile as cortical consolidation. We conclude that normative human brain maturation involves a genetically patterned process of consolidating anatomical network hubs. We argue that developmental variation of this consolidation process may be relevant both to normal cognitive and behavioral changes and the high incidence of schizophrenia during human brain adolescence. A dolescence is associated with major behavioral, social, and sexual changes as well as increased risk for many psychiatric disorders (1). However, human brain maturation during adolescence is not yet so well understood. Historically, pioneering studies used histological techniques to show that distinct areas of cortex were differentially myelinated in postmortem examination of perinatal tissue, suggesting "myelinogenesis" as an important process in human brain development (2, 3). MRI can measure human brain development more comprehensively and over a wider age range than is possible for postmortem anatomists. The thickness of human cortex can be reliably and replicably measured by MRI (4), and longitudinal studies have shown that cortical thickness (CT; millimeters) monotonically shrinks over the course of postnatal development, with variable shrinkage rates estimated for different age ranges (5-11; review in ref. 12). CT typically shrinks from about 3.5 mm at age 13 y old (9) to about 2.2 mm at age 75 y old (10, 11). Rates of cortical shrinkage are faster during adolescence (approximately −0.05 mm/y) than in later adulthood or earlier childhood (9).What does this MRI phenomenon of cortical shrinkage represent at a cellular level? There are broadly two tenable models: pruning and myelination. Basic physical principles of MRI predict that shorter longitudinal (T1) relaxation times reflect either a reduction in the fraction of "watery" cytoplasmic material, like cell bodies, synapses, or extracellular fluid, or an increase in the fraction of "fatty" myelinated material, like axons. Pruning models propose that cortical shrinkage in adolescence represents loss or remodeling of synapses, dendrites, or cell bodies (13). Myelin...

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“…To further characterize the relationship between the gene transcription PCs and the AHBA tissue samples within the striatum, and following previous work by Vértes et al (2016), we correlated the PC scores for PCs 2, 5 and 9 with the x, y and z MNI coordinates of the 98 striatal tissue samples. Significant correlations (P < 0.05, FDR-corrected) were only found for PCs 2 and 5.…”

Section: Transcriptomic Prediction Of Striatal Organizationmentioning

confidence: 99%

Transcriptional signatures of connectomic subregions of the human striatum

Parkes

Fulcher

Yücel

et al. 2017

Genes Brain and Behavior

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Functionally distinct regions of the brain are thought to possess a characteristic connectional fingerprint - a profile of incoming and outgoing connections that defines the function of that area. This observation has motivated efforts to subdivide brain areas using their connectivity patterns. However, it remains unclear whether these connectomically-defined subregions can be distinguished at the molecular level. Here, we combine high-resolution diffusion-weighted magnetic resonance imaging with transcriptomic data to show that connectomically-defined subregions of the striatum carry distinct transcriptional signatures. Using data-driven clustering of diffusion tractography, seeded from the striatum in 100 healthy individuals, we identify a tripartite organization of the caudate and putamen that comprises ventral, dorsal and caudal subregions. We then use microarray data of gene expression levels in 19 343 genes, taken from 98 tissue samples distributed throughout the striatum, to accurately discriminate the three connectomically-defined subregions with 80-90% classification accuracy using linear support vector machines. This classification accuracy was robust at the group and individual level and was superior for our parcellation of the striatum when compared with parcellations based on anatomical boundaries or other criteria. Genes contributing strongly to classification were enriched for gene ontology categories including dopamine signaling, glutamate secretion, response to amphetamine and metabolic pathways, and were implicated in risk for disorders such as schizophrenia, autism and Parkinson's disease. Our findings highlight a close link between regional variations in transcriptional activity and inter-regional connectivity in the brain, and suggest that there may be a strong genomic signature of connectomically-defined subregions of the brain.

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Gene transcription profiles associated with inter-modular hubs and connection distance in human functional magnetic resonance imaging networks

Cited by 210 publications

References 68 publications

Large-Scale Gradients in Human Cortical Organization

Large-Scale Gradients in Human Cortical Organization

Adolescence is associated with genomically patterned consolidation of the hubs of the human brain connectome

Transcriptional signatures of connectomic subregions of the human striatum

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