Genetic mapping and evolutionary analysis of human-expanded cognitive networks

Wei, Yongbin; Lange, Siemon C. de; Scholtens, Lianne H.; Watanabe, Kyoko; Ardesch, Dirk Jan; Jansen, Philip R.; Savage, Jeanne E.; Li, Longchuan; Preuss, Todd M.; Rilling, James K.; Posthuma, Daniëlle; Heuvel, Martijn P. van den

doi:10.1038/s41467-019-12764-8

Cited by 147 publications

(240 citation statements)

References 71 publications

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“…The specific wiring-rule names are shown along the horizontal-axis, with formal definitions provided in Table 2. show elevated expression in multimodal association networks (62).…”

Section: Discussionmentioning

confidence: 99%

Genetic influences on hub connectivity of the human connectome

Arnatkevičiūtė

Fulcher

Oldham

et al. 2020

Preprint

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Brain network hubs are both highly connected and highly inter-connected, forming a critical communication backbone for coherent neural dynamics. The mechanisms driving this organization are poorly understood. Using diffusion-weighted imaging in twins, we identify a major role for genes in shaping hub connectivity of the human connectome, showing that genes preferentially influence connectivity strength between network hubs. In two independent samples, we show that DNA variants preferentially related to hub connectivity are expression quantitative trait loci for genes that overlap with those implicated in intelligence, schizophrenia, and metabolism. Using transcriptomic atlas data, we show that connected hubs demonstrate tight coupling of transcriptional activity related to metabolic and cytoarchitectonic similarity. Finally, comparing thirteen generative models of network growth, we show that stochastic processes cannot explain the spatial distribution, and thus the precise wiring pattern, of hub connectivity. Together, our findings indicate that genetic influences on brain connectivity are not uniformly distributed throughout the brain, but are instead concentrated on the functionally valuable, metabolically costly connections between connectome hubs. gene expression | connectome | hub | heritability | transcriptome | GWAS | MRICorrespondence: aurina.arnatkeviciute@monash.edu.au

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“…The specific wiring-rule names are shown along the horizontal-axis, with formal definitions provided in Table 2. show elevated expression in multimodal association networks (62).…”

Section: Discussionmentioning

confidence: 99%

Genetic influences on hub connectivity of the human connectome

Arnatkevičiūtė

Fulcher

Oldham

et al. 2020

Preprint

View full text Add to dashboard Cite

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“…By systematically studying inter-nodal distances within the structural manifold, it may be possible to gain a more complete understanding of the difference between specialised systems at the periphery and more centrally localised zones of multimodal integration, such as the temporo-parietal junction and cingulate cortex. Many of these regions have undergone recent evolutionary expansion 65 , are sites of increased macaque-human genetic mutation rates 66 , and exhibit the lowest macaque-human functional homology 67 . In this context, the more complete model of cortical wiring provided by our structural manifold may play a critical role in advancing our understanding of how changes in cortical organisation have given rise to some of the most sophisticated features of human cognition.…”

Section: Discussionmentioning

confidence: 99%

A cortical wiring space links cellular architecture, functional dynamics and hierarchies in humans

Paquola

Seidlitz

Benkarim

et al. 2020

Preprint

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The vast net of fibres within and underneath the cortical mantle is optimised to support the convergence of different levels of brain organisation, specifically through linking cellular and architectural features of different cortical areas to give rise to more integrated neural function. Leveraging multimodal neuroimaging and machine learning techniques, we identified a novel manifold space that is governed by geometric, microstructural, and connectional aspects of cortico-cortical wiring. Principal dimensions of this manifold recapitulated established sensory-limbic and anterior-posterior gradients of brain organisation, and were found to reflect neural and glial gradients of cytoarchitectural organisation and gene expression. Manifold features were accurate in predicting cortico-cortical functional interactions derived from resting-state functional neuroimaging. Furthermore, application of this approach to a group of neurological patients, who underwent intracerebral encephalographic recordings, established that manifold features also explained the direction of information flow between different cortical areas. These results advance our understanding of how cell-specific neurobiological gradients produce a hierarchical cortical wiring scheme that is concordant with increasing functional sophistication of human brain organisation. RESULTSA multi-scale model of cortical wiring The wiring model was first derived from a Discovery subset of the Human Connectome Project dataset (n=100 unrelated adults) that offers high resolution structural magnetic resonance imaging (MRI), diffusion MRI, and microstructurally sensitive T1w/T2w maps 38 (Figure 1A, see Methods for details). and diffusion-based tractography strength (TS) were estimated between all pairs of nodes. (B) Normalised matrices were concatenated and transformed into an affinity matrix. Manifold learning identified a lower dimensional representation of cortical wiring. (C) Left. Node positions in this newly-discovered structural manifold, coloured according to proximity to axis limits. Closeness to the maximum of the second eigenvector is redness, towards the minimum of the first eigenvector is greenness and towards the maximum of the first eigenvector is blueness. The first two eigenvectors are shown on the respective axes. Right. Equivalent cortical surface representation. (D) Calculation of inter-regional distances in the structural manifold from specific seeds to other regions of cortex (left). Overall distance to all other nodes can also be quantified to index centrality of different regions, with more integrative areas having shorter distances to nodes (right). Figure 4: Hierarchical information processing is organised by the structural manifold. (A)Intracerebral implantations of ten epileptic patients were mapped to cortical surface. Intracortical EEG recordings were selected across five minutes of rest. (B) Boxplots show the variance explained in coherence by the structural manifold using adaboost machine learning across all nodes. (C) The phase slope ...

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“…Genes encompassed in both genomic regions were organized following highly similar co-expression patterns which may provide clues to FC-similarities between CNVs. Recent work has shown that the brain transcriptome is following broad spatial trends that are closely related to the functional network architecture 36, 37 .…”

Section: Discussionmentioning

confidence: 99%

Neuropsychiatric mutations delineate functional brain connectivity dimensions contributing to autism and schizophrenia

Moreau

Urchs

Orban

et al. 2019

Preprint

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16p11.2 and 22q11.2 Copy Number Variants (CNVs) confer high risk for Autism Spectrum Disorder (ASD), schizophrenia (SZ), and Attention-Deficit-Hyperactivity-Disorder (ADHD), but their impact on functional connectivity (FC) networks remains unclear.We analyzed resting-state functional magnetic resonance imaging data from 101 CNV carriers, 755 individuals with idiopathic ASD, SZ, or ADHD and 1,072 controls. We used CNV FC-signatures to identify major dimensions contributing to complex idiopathic conditions. CNVs had large mirror effects on FC at the global and regional level, and their effect-sizes were twice as large as those of idiopathic conditions. Thalamus, somatomotor, and posterior insula regions played a critical role in dysconnectivity shared across deletions, duplications, idiopathic ASD, SZ but not ADHD.Individuals with higher similarity to deletion FC-signatures exhibited worse behavioral and cognitive symptoms. These seemingly distinct neuropsychiatric mutations showed similar gene co-expression patterns and converged on FC dimensions, that may represent mechanistic building blocks shared across idiopathic conditions.

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Genetic mapping and evolutionary analysis of human-expanded cognitive networks

Cited by 147 publications

References 71 publications

Genetic influences on hub connectivity of the human connectome

Genetic influences on hub connectivity of the human connectome

A cortical wiring space links cellular architecture, functional dynamics and hierarchies in humans

Neuropsychiatric mutations delineate functional brain connectivity dimensions contributing to autism and schizophrenia

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