Increased structural connectivity in high schizotypy

Messaritaki, E.; Foley, Sonya; Barawi, Kali; Ettinger, Ulrich; Jones, Derek K.

doi:10.1162/netn_a_00279

Cited by 4 publications

(1 citation statement)

References 88 publications

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“…This may be contributing to the increased sensitivity of the NS in the differences observed in our study. Other metrics have also been used as edge-weights, such as the inverse radial diffusivity (Caeyenberghs et al, 2016; Messaritaki et al, 2022), which captures myelination and axonal packing and is, therefore, also meaningful is assessing connectivity. From a methodological point of view, this demonstrates that the selection of the metric for the edge weights can impact the results and, if not optimal, it can fail to reveal certain statistically significant relationships.…”

Section: Discussionmentioning

confidence: 99%

The impact of genetic risk for Alzheimer’s disease on the structural brain networks of young adults

Mirza-Davies

Foley

Caseras

et al. 2021

Preprint

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To facilitate pre-symptomatic diagnosis of late-onset Alzheimers disease, non-invasive imaging biomarkers could be combined with genetic risk information. In this work, we investigated the structural brain networks of young adults in relation to polygenic risk for Alzheimers disease, using magnetic resonance imaging (MRI) and genotype data for 564 19-year-old participants from the Avon Longitudinal Study of Parents and Children. Diffusion MRI was acquired on a 3T scanner, and the data were used to perform whole-brain tractography. The resulting tractograms were used to generate structural brain networks, using the number of streamlines and the diffusion tensor fractional anisotropy as edge weights. This was done for the whole-brain connectome, and for the default mode, limbic and visual subnetworks. Graph theoretical metrics were calculated for these networks, for each participant. The hubs of the networks were also identified, and the connectivity of the rich-club, feeder and local connections was also calculated. Polygenic risk scores (PRS), estimating the burden of genetic risk carried by an individual, were calculated both at genome-wide level and for nine specific disease pathways. The correlation coefficients were calculated between the PRSs and a) the graph theoretical metrics of the structural networks and b) the rich-club, feeder and local connectivity of the whole brain networks. In the visual subnetwork, the mean nodal strength exhibited a negative correlation with the genome-wide PRS including the APOE locus, while the mean betweenness centrality showed a positive correlation with the pathway-specific PRS for plasma lipoprotein particle assembly including the APOE locus. The rich-club connectivity was reduced in participants with higher genome-wide PRS including the APOE locus. Our results indicate small changes in the brain connectome of young adults at risk of developing Alzheimers disease in later life

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Section: Discussionmentioning

confidence: 99%

The impact of genetic risk for Alzheimer’s disease on the structural brain networks of young adults

Mirza-Davies

Foley

Caseras

et al. 2021

Preprint

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Graph-based analysis of EEG for schizotypy classification applying flicker Ganzfeld stimulation

Zandbagleh,

Mirzakuchaki,

Daliri

et al. 2023

Schizophr

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Ganzfeld conditions induce alterations in brain function and pseudo-hallucinatory experiences, particularly in people with high positive schizotypy. The current study uses graph-based parameters to investigate and classify brain networks under Ganzfeld conditions as a function of positive schizotypy. Participants from the general population (14 high schizotypy (HS), 29 low schizotypy (LS)) had an electroencephalography assessment during Ganzfeld conditions, with varying visual activation (8 frequencies of random light flicker) and soundscape-induced mood (neutral, serenity, and anxiety). Weighted functional networks were computed in six frequency sub-bands (delta, theta, alpha-low, alpha-high, beta, and gamma) as a function of light-flicker frequency and mood. The brain network was analyzed using graph theory parameters, including clustering coefficient (CC), strength, and global efficiency (GE). It was found that the LS groups had higher CC and strength than the HS groups, especially in bilateral temporal and frontotemporal brain regions. Moreover, some decreases in CC and strength measures were found in LS groups among occipital and parieto-occipital brain regions. LS groups also had significantly higher GE in all Ganzfeld conditions compared to the HS groups. The random under-sampling boosting (RUSBoost) algorithm achieved the best classification performance with an accuracy of 95.34%, specificity of 96.55%, and sensitivity of 92.85% during an anxiety-induction Ganzfeld condition. This is the first exploration of the relationship between brain functional state changes under Ganzfeld conditions in individuals who vary in positive schizotypy. The accuracy of graph-based parameters in classifying brain states as a function of schizotypy is shown, particularly for brain activity during anxiety induction, and should be investigated in psychosis.

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Functional Connectome Hierarchy in Schizotypy and Its Associations With Expression of Schizophrenia-Related Genes

Dong,

Wang,

Zhou

et al. 2023

Schizophrenia Bulletin

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Background and Hypothesis Schizotypy has been conceptualized as a continuum of symptoms with marked genetic, neurobiological, and sensory-cognitive overlaps to schizophrenia. Hierarchical organization represents a general organizing principle for both the cortical connectome supporting sensation-to-cognition continuum and gene expression variability across the cortex. However, a mapping of connectome hierarchy to schizotypy remains to be established. Importantly, the underlying changes of the cortical connectome hierarchy that mechanistically link gene expressions to schizotypy are unclear. Study Design The present study applied novel connectome gradient on resting-state fMRI data from 1013 healthy young adults to investigate schizotypy-associated sensorimotor-to-transmodal connectome hierarchy and assessed its similarity with the connectome hierarchy of schizophrenia. Furthermore, normative and differential postmortem gene expression data were utilized to examine transcriptional profiles linked to schizotypy-associated connectome hierarchy. Study Results We found that schizotypy was associated with a compressed functional connectome hierarchy. Moreover, the pattern of schizotypy-related hierarchy exhibited a positive correlation with the connectome hierarchy observed in schizophrenia. This pattern was closely colocated with the expression of schizophrenia-related genes, with the correlated genes being enriched in transsynaptic, receptor signaling and calcium ion binding. Conclusions The compressed connectome hierarchy suggests diminished functional system differentiation, providing a novel and holistic system-level basis for various sensory-cognition deficits in schizotypy. Importantly, its linkage with schizophrenia-altered hierarchy and schizophrenia-related gene expression yields new insights into the neurobiological continuum of psychosis. It also provides mechanistic insight into how gene variation may drive alterations in functional hierarchy, mediating biological vulnerability of schizotypy to schizophrenia.

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Increased structural connectivity in high schizotypy

Cited by 4 publications

References 88 publications

The impact of genetic risk for Alzheimer’s disease on the structural brain networks of young adults

The impact of genetic risk for Alzheimer’s disease on the structural brain networks of young adults

Graph-based analysis of EEG for schizotypy classification applying flicker Ganzfeld stimulation

Functional Connectome Hierarchy in Schizotypy and Its Associations With Expression of Schizophrenia-Related Genes

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