Connectome architecture shapes large-scale cortical alterations in schizophrenia: a worldwide ENIGMA study

Georgiadis, Foivos; Larivière, Sara; Glahn, David C.; Hong, Elliot; Kochunov, Peter; Mowry, Bryan; Loughland, Carmel M.; Pantelis, Christos; Henskens, Frans; Green, Melissa; Cairns, Murray J.; Michie, Patricia T.; Rasser, Paul E.; Tooney, Paul A.; Scott, Rodney J.; Catts, Stanley V.; Schall, Ulrich; Carr, Vaughan J.; Quidé, Yann; Krug, Axel; Stein, Frederike; Nenadić, Igor; Kircher, Tilo; Gur, Raquel E.; Gur, Ruben C.; Satterthwaite, Theodore; Karuk, Andriana; Clotet, Edith; Raduà, Joaquim; Claramonte, Paola; Salvador, Raymond; Spalletta, Gianfranco; Voineskos, Aristotle N.; Sim, Kang; Facorro, Benedicto Crespo; Gutiérrez, Diana Tordesillas; Ehrlich, Stefan; Crossley, Nicolás; Grotegerd, Dominik; Repple, Jonathan; Lencer, Rebekka; Dannlowski, Udo; Calhoun, Vince D.; Demro, Caroline; Ramsay, Ian S.; Schmidt, André; Borgwardt, Stefan; Tomyshev, Alexander; Lebedeva, Irina; Höschl, Cyril; Španiel, Filip; Preda, Adrian; Nguyen, Dana; Uhlmann, Anne; Stein, Dan J.; Howells, Fleur M.; Temmingh, Henk; Sponheim, Scott R.; Zuluaga, Ana Isabel; Jaramillo, Carlos; Iasevoli, Felice; Ji, Ellen; Omlor, Wolfgang; Homan, Stephanie; Homan, Philipp; Kaiser, Stefan; Seifritz, Erich; Mišić, Bratislav; Thompson, Paul M.; Erp, Theo G.M. van; Turner, Jessica A.; Bernhardt, Boris C.; Kirschner, Matthias

doi:10.1101/2023.02.12.527904

Cited by 5 publications

(22 citation statements)

References 84 publications

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“…[22][23][24][25] A network-based spreading process may also be involved in psychosis. Cross-sectional regional GMV reductions in patients correlate with the microstructure of adjacent white matter, 26 across spatially distributed regions, [27][28][29] with normative connectome organization, [30][31][32] and with reductions in structurally connected regions. 33 Together, these findings support the hypothesis that the spatial patterning of GMV loss in psychotic illness is constrained by connectome architecture.…”

Section: Conclusion and Relevancementioning

confidence: 99%

Network-Based Spreading of Gray Matter Changes Across Different Stages of Psychosis

Chopra,

Segal,

Oldham

et al. 2023

JAMA Psychiatry

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ImportancePsychotic illness is associated with anatomically distributed gray matter reductions that can worsen with illness progression, but the mechanisms underlying the specific spatial patterning of these changes is unknown.ObjectiveTo test the hypothesis that brain network architecture constrains cross-sectional and longitudinal gray matter alterations across different stages of psychotic illness and to identify whether certain brain regions act as putative epicenters from which volume loss spreads.Design, Settings, and ParticipantsThis case-control study included 534 individuals from 4 cohorts, spanning early and late stages of psychotic illness. Early-stage cohorts included patients with antipsychotic-naive first-episode psychosis (n = 59) and a group of patients receiving medications within 3 years of psychosis onset (n = 121). Late-stage cohorts comprised 2 independent samples of people with established schizophrenia (n = 136). Each patient group had a corresponding matched control group (n = 218). A sample of healthy adults (n = 356) was used to derive representative structural and functional brain networks for modeling of network-based spreading processes. In Longitudinal illness-related and antipsychotic-related gray matter changes over 3 and 12 months were examined using a triple-blind randomized placebo-control magnetic resonance imaging study of the antipsychotic-naive patients. All data were collected between April 29, 2008, and January 15, 2020, and analyses were performed between March 1, 2021, and January 14, 2023.Main Outcomes and MeasuresCoordinated deformation models were used to estimate the extent of gray matter volume (GMV) change in each of 332 parcellated areas by the volume changes observed in areas to which they were structurally or functionally coupled. To identify putative epicenters of volume loss, a network diffusion model was used to simulate the spread of pathology from different seed regions. Correlations between estimated and empirical spatial patterns of GMV alterations were used to quantify model performance.ResultsOf 534 included individuals, 354 (66.3%) were men, and the mean (SD) age was 28.4 (7.4) years. In both early and late stages of illness, spatial patterns of cross-sectional volume differences between patients and controls were more accurately estimated by coordinated deformation models constrained by structural, rather than functional, network architecture (r range, &gt;0.46 to &lt;0.57; P &lt; .01). The same model also robustly estimated longitudinal volume changes related to illness (r ≥ 0.52; P &lt; .001) and antipsychotic exposure (r ≥ 0.50; P &lt; .004). Network diffusion modeling consistently identified, across all 4 data sets, the anterior hippocampus as a putative epicenter of pathological spread in psychosis. Epicenters of longitudinal GMV loss were apparent in posterior cortex early in the illness and shifted to the prefrontal cortex with illness progression.Conclusion and RelevanceThese findings highlight a central role for white matter fibers as conduits for the spread of pathology across different stages of psychotic illness, mirroring findings reported in neurodegenerative conditions. The structural connectome thus represents a fundamental constraint on brain changes in psychosis, regardless of whether these changes are caused by illness or medication. Moreover, the anterior hippocampus represents a putative epicenter of early brain pathology from which dysfunction may spread to affect connected areas.

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Section: Conclusion and Relevancementioning

confidence: 99%

Network-Based Spreading of Gray Matter Changes Across Different Stages of Psychosis

Chopra,

Segal,

Oldham

et al. 2023

JAMA Psychiatry

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“…Disease epicenters refer to brain regions influenced earlier by schizophrenia, and could serve as a gateway affecting downstream hub nodes via their connections (7). Given both cortical increases and decreases in EOS, we measured positive and negative disease epicenters for the first time, rather than just one epicenter end of cortical decreases (7). Particularly, if the brain connectivity profile of a region is highly negatively correlated with a cortical abnormality map of schizophrenia (negative epicenters), this region is strongly connected to other high-thinning regions and weakly connected to other low-thinning regions.…”

Section: Discussionmentioning

confidence: 99%

“…Schizophrenia-related tissue volume alteration patterns have been reported to be circumscribed by the ventral attention network, with a disease epicenter in the anterior cingulate cortex (6). In agreement with this finding, transmodal epicenters emerged as shared epicenters across disease stages, while occipital and parietal epicenters were additionally found in early courses of adult schizophrenia (7). However, the neurodevelopmental roots of disease epicenters have not been established.…”

Section: Introductionmentioning

confidence: 91%

“…Transmodal connectome has been reported to shape distributed deformation patterns in chronic schizophrenia (6), while unique architecture constrains early patterns in first-episode schizophrenia (7,8). Given the developmental factor, we hypothesize that pathologic processes in early-onset schizophrenia (EOS) is shaped by the developing intrinsic brain organization.…”

Section: Introductionmentioning

confidence: 91%

“…In the current study, we used EOS patients, 7–17 years of age, served as a neurodevelopmental disease model to investigate the putative early pathologic origins that propagate through the brain connectome. We first identified early disease epicenters of EOS by assessing the influence of functional and structural connectivity profiles on the spatial distribution of cortical thickness alterations in patients, as in previous studies (7, 17, 33). We then contextualized these observations within a micro-level transcriptomic architecture by applying partial least squares (PLS) analysis to disease epicenters and AHBA gene expression maps (30).…”

Section: Introductionmentioning

confidence: 99%

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Neurodevelopmentally rooted epicenters in schizophrenia: sensorimotor-association spatial axis of cortical thickness alterations

Fan,

Xu,

Hettwer

et al. 2024

Preprint

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Pathologic perturbations in schizophrenia have been suggested to propagate via the functional and structural connectome across the lifespan. Yet how the connectome guides early cortical reorganization of developing schizophrenia remains unknown. Here, we used early-onset schizophrenia (EOS) as a neurodevelopmental disease model to investigate putative early pathologic origins that propagate through the functional and structural connectome. We compared 95 patients with antipsychotic-naïve first-episode EOS and 99 typically developing controls (7–17 years of age, 120 females). Whereas patients showed widespread cortical thickness reductions, thickness increases were observed in primary cortical areas. Using normative connectomics models, we found that epicenters of thickness reductions were situated in association regions linked to language, affective, and cognitive functions, while epicenters of increased thickness in EOS were located in sensorimotor regions subserving visual, somatosensory, and motor functions. Using post-mortem transcriptomic data of six donors, we observed that the epicenter map differentiated oligodendrocyte-related transcriptional changes at its sensory apex and the association end was related to expression of excitatory/inhibitory neurons. More generally, we observed that the epicenter map was associated with neurodevelopmental disease gene dysregulation and human accelerated region genes, suggesting potential shared genetic determinants across various neurodevelopmental disorders. Taken together, our results underscore the developmentally rooted pathologic origins of schizophrenia and their transcriptomic overlap with other neurodevelopmental diseases.

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Brain heterogeneity in 1,792 individuals with schizophrenia: effects of illness stage, sites of origin and pathophysiology

Jiang,

Palaniyappan,

Chang

et al. 2024

Preprint

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ImportanceSchizophrenia is characterized with greater variability beyond the mean differences in brain structures. This variability is often assumed to be static, reflecting the presence of heterogeneous subgroups, but this assumption and alternative explanations remain untested.ObjectiveTo test if gray matter volume (GMV) variability is more less in later stages of schizophrenia, and evaluate if a putative ‘spreading pattern’ with GMV deficits originating in one part of the brain and diffusing elsewhere explain the variability of schizophrenia.Design, settings, and participantsThis study evaluated the regional GMV variability using MRI of 1,792 individuals with schizophrenia and 1,523 healthy controls (HCs), and the association of GMV variability with neurotransmitter and transcriptomic gene data in the human brain.Main outcomes and measuresRegional variability was evaluated by comparing the relative variability of patients to controls, using the relative mean-scaled log variability ratio (lnCVR). A network diffusion model (NDM) was employed to simulate the possible processes of GMV alteration across brain regions.ResultsCompared with HCs, greater lnCVR (pFDR<0.05) was found in 50 regions in the whole patient group (n=1792; 762 females; mean[SD] age, 29.9[11.9] years), at a much greater frequency (p=5.0×10−13) in the first-episode drug-naïve subsample (73 regions) (n=478; mean[SD] illness duration, 0.548[0.459] years), compared to the chronic medicated subsample (28 regions) (n=398; mean[SD] illness duration, 14.0[10.4] years). The average lnCVR across all regions was greater in the first-episode than chronic subsample (t=10.8,p=1.7×10−7). The areas with largest lnCVR were located at frontotemporal cortex and thalamus (first-episode), or hippocampus and caudate (chronic); there was a significant correlation with case-control mean difference (r=0.367,p=6.7×10−4). We determined a gene expression map that correlated with the lnCVR map in schizophrenia (r=0.491,p=0.003). The NDM performed consistently (72.1% patients,pspin<0.001) in replicating GMV changes when simulated and observed values were compared.Conclusion and relevanceBrain-based heterogeneity is unlikely to be a static feature of schizophrenia; it is more pronounced at the onset of the disorder but reduced over the long term. Differences in the site of ‘origin’ of GMV changes in individual-level may explain the observed anatomical variability in schizophrenia.Key PointsQuestionNo two individuals with schizophrenia have the same anatomical change in the brain. Is this variability a fixed feature of schizophrenia or does it become more pronounced at later stages? Is this variability explained by a putative ‘spreading pattern’ of gray matter deficits originating in one part of the brain and diffusing elsewhere?FindingsIn 1,792 individuals with schizophrenia, neuroanatomical variability is not a fixed feature; it is more pronounced at the illness onset but less prominent in later stages. The neuroanatomical variability is associated with various molecular and neurobiological processes implicated in the neurodevelopmental etiology of schizophrenia. Differences in the site of ‘origin’ of gray matter deficits in each individual with schizophrenia explains most of the observed variability.MeaningOur work finds support for a space-time interaction along a shared pathophysiological continuum (network-based trans-neuronal diffusion), as a possible explanatory model for inter-subject variability. These findings contribute to the understanding that inter-individual variability in schizophrenia may arise from a common cohesive process that varies in its state (across time) and space (across brain regions). This also raises the question of what dynamic processes contribute to the reducing heterogeneity over time in schizophrenia. Answering this question will be a key test to the neurobiological validity of the concept of schizophrenia.

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Connectome architecture shapes large-scale cortical alterations in schizophrenia: a worldwide ENIGMA study

Cited by 5 publications

References 84 publications

Network-Based Spreading of Gray Matter Changes Across Different Stages of Psychosis

Network-Based Spreading of Gray Matter Changes Across Different Stages of Psychosis

Neurodevelopmentally rooted epicenters in schizophrenia: sensorimotor-association spatial axis of cortical thickness alterations

Brain heterogeneity in 1,792 individuals with schizophrenia: effects of illness stage, sites of origin and pathophysiology

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