Connectome architecture shapes large-scale cortical alterations in schizophrenia: a worldwide ENIGMA study.
Journal
Molecular psychiatry
ISSN: 1476-5578
Titre abrégé: Mol Psychiatry
Pays: England
ID NLM: 9607835
Informations de publication
Date de publication:
09 Feb 2024
09 Feb 2024
Historique:
received:
14
09
2023
accepted:
18
01
2024
revised:
08
01
2024
medline:
10
2
2024
pubmed:
10
2
2024
entrez:
9
2
2024
Statut:
aheadofprint
Résumé
Schizophrenia is a prototypical network disorder with widespread brain-morphological alterations, yet it remains unclear whether these distributed alterations robustly reflect the underlying network layout. We tested whether large-scale structural alterations in schizophrenia relate to normative structural and functional connectome architecture, and systematically evaluated robustness and generalizability of these network-level alterations. Leveraging anatomical MRI scans from 2439 adults with schizophrenia and 2867 healthy controls from 26 ENIGMA sites and normative data from the Human Connectome Project (n = 207), we evaluated structural alterations of schizophrenia against two network susceptibility models: (i) hub vulnerability, which examines associations between regional network centrality and magnitude of disease-related alterations; (ii) epicenter mapping, which identifies regions whose typical connectivity profile most closely resembles the disease-related morphological alterations. To assess generalizability and specificity, we contextualized the influence of site, disease stages, and individual clinical factors and compared network associations of schizophrenia with that found in affective disorders. Our findings show schizophrenia-related cortical thinning is spatially associated with functional and structural hubs, suggesting that highly interconnected regions are more vulnerable to morphological alterations. Predominantly temporo-paralimbic and frontal regions emerged as epicenters with connectivity profiles linked to schizophrenia's alteration patterns. Findings were robust across sites, disease stages, and related to individual symptoms. Moreover, transdiagnostic comparisons revealed overlapping epicenters in schizophrenia and bipolar, but not major depressive disorder, suggestive of a pathophysiological continuity within the schizophrenia-bipolar-spectrum. In sum, cortical alterations over the course of schizophrenia robustly follow brain network architecture, emphasizing marked hub susceptibility and temporo-frontal epicenters at both the level of the group and the individual. Subtle variations of epicenters across disease stages suggest interacting pathological processes, while associations with patient-specific symptoms support additional inter-individual variability of hub vulnerability and epicenters in schizophrenia. Our work outlines potential pathways to better understand macroscale structural alterations, and inter- individual variability in schizophrenia.
Identifiants
pubmed: 38336840
doi: 10.1038/s41380-024-02442-7
pii: 10.1038/s41380-024-02442-7
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© 2024. The Author(s).
Références
Fornito A, Zalesky A, Breakspear M. The connectomics of brain disorders. Nat Rev Neurosci. 2015;16:159–72.
pubmed: 25697159
doi: 10.1038/nrn3901
Hansen JY, Shafiei G, Vogel JW, Smart K, Bearden CE, Hoogman M, et al. Local molecular and global connectomic contributions to cross-disorder cortical abnormalities. Nat Commun. 2022;13:1–17.
doi: 10.1038/s41467-022-32420-y
Repple J, Gruber M, Mauritz M, de Lange SC, Winter NR, Opel N, et al. Shared and specific patterns of structural brain connectivity across affective and psychotic disorders. Biol Psychiatry. 2022;93:178–86.
pubmed: 36114041
doi: 10.1016/j.biopsych.2022.05.031
van den Heuvel MP, Sporns O. A cross-disorder connectome landscape of brain dysconnectivity. Nat Rev Neurosci. 2019;20:435–46.
pubmed: 31127193
pmcid: 8864539
doi: 10.1038/s41583-019-0177-6
van Erp TGM, Walton E, Hibar DP, Schmaal L, Jiang W, Glahn DC, et al. Cortical brain abnormalities in 4474 individuals with schizophrenia and 5098 control subjects via the Enhancing Neuro Imaging Genetics Through Meta Analysis (ENIGMA) Consortium. Biol Psychiatry. 2018;84:644–54.
pubmed: 29960671
pmcid: 6177304
doi: 10.1016/j.biopsych.2018.04.023
Van Erp TGM, Hibar DP, Rasmussen JM, Glahn DC, Pearlson GD, Andreassen OA, et al. Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium. Mol Psychiatry. 2016;21:547–53.
pubmed: 26033243
doi: 10.1038/mp.2015.63
Hibar DP, Westlye LT, Doan NT, Jahanshad N, Cheung JW, Ching CRK, et al. Cortical abnormalities in bipolar disorder: An MRI analysis of 6503 individuals from the ENIGMA Bipolar Disorder Working Group. Mol Psychiatry. 2018;23:932–42.
pubmed: 28461699
doi: 10.1038/mp.2017.73
Hibar DP, Westlye LT, Van Erp TGM, Rasmussen J, Leonardo CD, Faskowitz J, et al. Subcortical volumetric abnormalities in bipolar disorder. Mol Psychiatry. 2016;21:1710–6.
pubmed: 26857596
pmcid: 5116479
doi: 10.1038/mp.2015.227
Schmaal L, Hibar DP, Sämann PG, Hall GB, Baune BT, Jahanshad N, et al. Cortical abnormalities in adults and adolescents with major depression based on brain scans from 20 cohorts worldwide in the ENIGMA Major Depressive Disorder Working Group. Mol Psychiatry. 2017;22:900–9.
pubmed: 27137745
doi: 10.1038/mp.2016.60
Schmaal L, Veltman DJ, Van Erp TGM, Smann PG, Frodl T, Jahanshad N, et al. Subcortical brain alterations in major depressive disorder: findings from the ENIGMA Major Depressive Disorder working group. Mol Psychiatry. 2016;21:806–12.
pubmed: 26122586
doi: 10.1038/mp.2015.69
Hettwer MD, Larivière S, Park BY, van den Heuvel OA, Schmaal L, Andreassen OA, et al. Coordinated cortical thickness alterations across six neurodevelopmental and psychiatric disorders. Nat Commun. 2022;13:1–14.
doi: 10.1038/s41467-022-34367-6
Park BY, Kebets V, Larivière S, Hettwer MD, Paquola C, van Rooij D, et al. Multiscale neural gradients reflect transdiagnostic effects of major psychiatric conditions on cortical morphology. Commun Biol. 2022;5:1–14.
doi: 10.1038/s42003-022-03963-z
Cropley VL, Klauser P, Lenroot RK, Bruggemann J, Sundram S, Bousman C, et al. Accelerated gray and white matter deterioration with age in schizophrenia. Am J Psychiatry. 2017;174:286–95.
pubmed: 27919183
doi: 10.1176/appi.ajp.2016.16050610
Shafiei G, Markello RD, Makowski C, Talpalaru A, Kirschner M, Devenyi GA, et al. Spatial patterning of tissue volume loss in schizophrenia reflects brain network architecture. Biol Psychiatry. 2020;87:727–35.
pubmed: 31837746
doi: 10.1016/j.biopsych.2019.09.031
Wannan CMJ, Cropley VL, Chakravarty MM, Bousman C, Ganella EP, Bruggemann JM, et al. Evidence for network-based cortical thickness reductions in schizophrenia. Am J Psychiatry. 2019;176:552–63.
pubmed: 31164006
doi: 10.1176/appi.ajp.2019.18040380
Feeney DM, Baron JC. Diaschisis. Stroke. 1986;17:817–30.
pubmed: 3532434
doi: 10.1161/01.STR.17.5.817
Finger S, Koehler PJ, Jagella C. The Monakow concept of diaschisis: origins and perspectives. Arch Neurol. 2004;61:283–8.
pubmed: 14967781
doi: 10.1001/archneur.61.2.283
Kirschner M, Shafiei G, Markello RD, Makowski C, Talpalaru A, Hodzic-Santor B, et al. Latent clinical-anatomical dimensions of schizophrenia. Schizophr Bull. 2020;46:1426–38.
pubmed: 32744604
pmcid: 8496914
doi: 10.1093/schbul/sbaa097
Hagmann P, Cammoun L, Gigandet X, Meuli R, Van Honey CJ, et al. Mapping the structural core of human cerebral cortex. PLoS Biol. 2008;6:e159.
pubmed: 18597554
pmcid: 2443193
doi: 10.1371/journal.pbio.0060159
Buckner RL, Sepulcre J, Talukdar T, Krienen FM, Liu H, Hedden T, et al. Cortical hubs revealed by intrinsic functional connectivity: mapping, assessment of stability, and relation to Alzheimer’s disease. J Neurosci. 2009;29:1860.
pubmed: 19211893
pmcid: 2750039
doi: 10.1523/JNEUROSCI.5062-08.2009
Avena-Koenigsberger A, Misic B, Sporns O. Communication dynamics in complex brain networks. Nat Rev Neurosci. 2017;19:17–33.
pubmed: 29238085
doi: 10.1038/nrn.2017.149
Zhou J, Gennatas ED, Kramer JH, Miller BL, Seeley WW. Predicting regional neurodegeneration from the healthy brain functional connectome. Neuron. 2012;73:1216.
pubmed: 22445348
pmcid: 3361461
doi: 10.1016/j.neuron.2012.03.004
Zheng YQ, Zhang Y, Yau Y, Zeighami Y, Larcher K, Misic B, et al. Local vulnerability and global connectivity jointly shape neurodegenerative disease propagation. PLoS Biol. 2019;17:e3000495.
pubmed: 31751329
pmcid: 6894889
doi: 10.1371/journal.pbio.3000495
de Haan W, Mott K, van Straaten ECW, Scheltens P, Stam CJ. Activity dependent degeneration explains hub vulnerability in Alzheimer’s disease. PLoS Comput Biol. 2012;8:e1002582.
pubmed: 22915996
pmcid: 3420961
doi: 10.1371/journal.pcbi.1002582
Seeley WW, Crawford RK, Zhou J, Miller BL, Greicius MD. Neurodegenerative diseases target large-scale human brain networks. Neuron. 2009;62:42.
pubmed: 19376066
pmcid: 2691647
doi: 10.1016/j.neuron.2009.03.024
Larivière S, Rodríguez-Cruces R, Royer J, Caligiuri ME, Gambardella A, Concha L, et al. Network-based atrophy modeling in the common epilepsies: a worldwide ENIGMA study. Sci Adv. 2020;6:6457–75.
doi: 10.1126/sciadv.abc6457
Shafiei G, Bazinet V, Dadar M, Manera AL, Collins DL, Dagher A, et al. Network structure and transcriptomic vulnerability shape atrophy in frontotemporal dementia. Brain. 2023;146:321–36.
pubmed: 35188955
doi: 10.1093/brain/awac069
Zeighami Y, Ulla M, Iturria-Medina Y, Dadar M, Zhang Y, Larcher KMH, et al. Network structure of brain atrophy in de novo Parkinson’s disease. Elife. 2015;4:e08440.
pubmed: 26344547
pmcid: 4596689
doi: 10.7554/eLife.08440
Yau Y, Zeighami Y, Baker TE, Larcher K, Vainik U, Dadar M, et al. Network connectivity determines cortical thinning in early Parkinson’s disease progression. Nat Commun. 2018;9:1–10.
doi: 10.1038/s41467-017-02416-0
Vogel JW, Young AL, Oxtoby NP, Smith R, Ossenkoppele R, Strandberg OT, et al. Four distinct trajectories of tau deposition identified in Alzheimer’s disease. Nat Med. 2021;27:871–81.
pubmed: 33927414
pmcid: 8686688
doi: 10.1038/s41591-021-01309-6
Marek S, Tervo-Clemmens B, Calabro FJ, Montez DF, Kay BP, Hatoum AS, et al. Reproducible brain-wide association studies require thousands of individuals. Nature. 2022;603:654–60.
pubmed: 35296861
pmcid: 8991999
doi: 10.1038/s41586-022-04492-9
Larivière S, Paquola C, Park BY, Royer J, Wang Y, Benkarim O, et al. The ENIGMA Toolbox: multiscale neural contextualization of multisite neuroimaging datasets. Nat Methods. 2021;18:698–700.
pubmed: 34194050
pmcid: 8983056
doi: 10.1038/s41592-021-01186-4
Thompson PM, Jahanshad N, Ching CRK, Salminen LE, Thomopoulos SI, Bright J, et al. ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries. Transl Psychiatry. 2020;10:1–28.
doi: 10.1038/s41398-020-0705-1
Elam JS, Glasser MF, Harms MP, Sotiropoulos SN, Andersson JLR, Burgess GC, et al. The Human Connectome Project: a retrospective. Neuroimage. 2021;244:118543.
pubmed: 34508893
doi: 10.1016/j.neuroimage.2021.118543
van Os J, Kapur S. Schizophrenia. Lancet. 2009;374:635–45.
pubmed: 19700006
doi: 10.1016/S0140-6736(09)60995-8
Patel Y, Parker N, Shin J, Howard D, French L, Thomopoulos SI, et al. Virtual histology of cortical thickness and shared neurobiology in 6 psychiatric disorders. JAMA Psychiatry. 2021;78:47–63.
pubmed: 32857118
doi: 10.1001/jamapsychiatry.2020.2694
Opel N, Goltermann J, Hermesdorf M, Berger K, Baune BT, Dannlowski U. Cross-disorder analysis of brain structural abnormalities in six major psychiatric disorders: a secondary analysis of mega- and meta-analytical findings from the ENIGMA Consortium. Biol Psychiatry. 2020;88:678–86.
pubmed: 32646651
doi: 10.1016/j.biopsych.2020.04.027
Lee PH, Anttila V, Won H, Feng YCA, Rosenthal J, Zhu Z, et al. Genomic relationships, novel loci, and pleiotropic mechanisms across eight psychiatric disorders. Cell. 2019;179:1469–1482.e11.
doi: 10.1016/j.cell.2019.11.020
Radonjić N V, Hess JL, Rovira P, Andreassen O, Buitelaar JK, Ching CRK, et al. Structural brain imaging studies offer clues about the effects of the shared genetic etiology among neuropsychiatric disorders. Mol Psychiatry. 2021;26:2101–10.
pubmed: 33456050
pmcid: 8440178
doi: 10.1038/s41380-020-01002-z
Anttila V, Bulik-Sullivan B, Finucane HK, Walters RK, Bras J, Duncan L, et al. Analysis of shared heritability in common disorders of the brain. Science. 2018;360:eaap8757.
pubmed: 29930110
doi: 10.1126/science.aap8757
Ivleva EI, Clementz BA, Dutcher AM, Arnold SJM, Jeon-Slaughter H, Aslan S, et al. Brain structure biomarkers in the psychosis biotypes: findings from the bipolar-schizophrenia network for intermediate phenotypes. Biol Psychiatry. 2017;82:26–39.
pubmed: 27817844
doi: 10.1016/j.biopsych.2016.08.030
Clementz BA, Sweeney JA, Hamm JP, Ivleva EI, Ethridge LE, Pearlson GD, et al. Identification of distinct psychosis biotypes using brain-based biomarkers. Am J Psychiatry. 2016;173:373–84.
pubmed: 26651391
doi: 10.1176/appi.ajp.2015.14091200
Fischl B. FreeSurfer. NeuroImage. 2012;62:774–81.
pubmed: 22248573
doi: 10.1016/j.neuroimage.2012.01.021
Fischl B, Salat DH, Busa E, Albert M, Dieterich M, Haselgrove C, et al. Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron. 2002;33:341–55.
pubmed: 11832223
doi: 10.1016/S0896-6273(02)00569-X
Desikan RS, Ségonne F, Fischl B, Quinn BT, Dickerson BC, Blacker D, et al. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage. 2006;31:968–80.
pubmed: 16530430
doi: 10.1016/j.neuroimage.2006.01.021
Leek JT, Johnson WE, Parker HS, Jaffe AE, Storey JD, The SVA. package for removing batch effects and other unwanted variation in high-throughput experiments. Bioinformatics. 2012;28:882–3.
pubmed: 22257669
pmcid: 3307112
doi: 10.1093/bioinformatics/bts034
Fortin JP, Cullen N, Sheline YI, Taylor WD, Aselcioglu I, Cook PA, et al. Harmonization of cortical thickness measurements across scanners and sites. Neuroimage. 2018;167:104–20.
pubmed: 29155184
doi: 10.1016/j.neuroimage.2017.11.024
Worsley KJ, Taylor JE, Carbonell F, Chung MK, Duerden E, Bernhardt B, et al. SurfStat: A Matlab toolbox for the statistical analysis of univariate and multivariate surface and volumetric data using linear mixed effects models and random field theory. Neuroimage. 2009;47:S102.
Larivière S, Bayrak Ş, Vos de Wael R, Benkarim O, Herholz P, Rodriguez-Cruces R, et al. BrainStat: A toolbox for brain-wide statistics and multimodal feature associations. Neuroimage. 2023;266:119807.
Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B (Methodol). 1995;57:289–300.
Van Essen DC, Ugurbil K, Auerbach E, Barch D, Behrens TEJ, Bucholz R, et al. The Human Connectome Project: a data acquisition perspective. Neuroimage. 2012;62:2222.
pubmed: 22366334
doi: 10.1016/j.neuroimage.2012.02.018
Glasser MF, Sotiropoulos SN, Wilson JA, Coalson TS, Fischl B, Andersson JL, et al. The minimal preprocessing pipelines for the human connectome project. Neuroimage. 2013;80:105.
pubmed: 23668970
doi: 10.1016/j.neuroimage.2013.04.127
Alexander-Bloch AF, Shou H, Liu S, Satterthwaite TD, Glahn DC, Shinohara RT, et al. On testing for spatial correspondence between maps of human brain structure and function. Neuroimage. 2018;178:540.
pubmed: 29860082
doi: 10.1016/j.neuroimage.2018.05.070
Burt JB, Helmer M, Shinn M, Anticevic A, Murray JD. Generative modeling of brain maps with spatial autocorrelation. Neuroimage. 2020;220:117038.
pubmed: 32585343
doi: 10.1016/j.neuroimage.2020.117038
van den Heuvel MP, Sporns O. An anatomical substrate for integration among functional networks in human cortex. J Neurosci. 2013;33:14489–14500.
pubmed: 24005300
pmcid: 6618386
doi: 10.1523/JNEUROSCI.2128-13.2013
Van Den Heuvel MP, Kahn RS, Goñi J, Sporns O. High-cost, high-capacity backbone for global brain communication. Proc Natl Acad Sci USA. 2012;109:11372–7.
pubmed: 22711833
pmcid: 3396547
doi: 10.1073/pnas.1203593109
Grasby KL, Jahanshad N, Painter JN, Colodro-Conde L, Bralten J, Hibar DP, et al. The genetic architecture of the human cerebral cortex. Science. 2020;367:eaay6690.
pubmed: 32193296
pmcid: 7295264
doi: 10.1126/science.aay6690
Grotzinger AD, Mallard TT, Liu Z, Seidlitz J, Ge T, Smoller JW. Multivariate genomic architecture of cortical thickness and surface area at multiple levels of analysis. Nat Commun. 2023;14:1–13.
doi: 10.1038/s41467-023-36605-x
Rubinov M, Bullmore E. Schizophrenia and abnormal brain network hubs. Dialogues Clin Neurosci. 2013;15:339.
pubmed: 24174905
pmcid: 3811105
doi: 10.31887/DCNS.2013.15.3/mrubinov
Crossley NA, Mechelli A, Scott J, Carletti F, Fox PT, Mcguire P, et al. The hubs of the human connectome are generally implicated in the anatomy of brain disorders. Brain. 2014;137:2382–95.
pubmed: 25057133
pmcid: 4107735
doi: 10.1093/brain/awu132
Klauser P, Baker ST, Cropley VL, Bousman C, Fornito A, Cocchi L, et al. White matter disruptions in schizophrenia are spatially widespread and topologically converge on brain network hubs. Schizophr Bull. 2017;43:425–35.
pubmed: 27535082
Saxena S, Caroni P. Selective neuronal vulnerability in neurodegenerative diseases: from stressor thresholds to degeneration. Neuron. 2011;71:35–48.
pubmed: 21745636
doi: 10.1016/j.neuron.2011.06.031
Sydnor VJ, Larsen B, Bassett DS, Alexander-Bloch A, Fair DA, Liston C, et al. Neurodevelopment of the association cortices: Patterns, mechanisms, and implications for psychopathology. Neuron. 2021;109:2820–46.
pubmed: 34270921
pmcid: 8448958
doi: 10.1016/j.neuron.2021.06.016
Fatemi SH, Folsom TD. The neurodevelopmental hypothesis of schizophrenia, revisited. Schizophr Bull. 2009;35:528–48.
pubmed: 19223657
pmcid: 2669580
doi: 10.1093/schbul/sbn187
Chopra S, Oldham S, Segal A, Holmes A, Sabaroedin K, Orchard ER, et al. Network constraints on longitudinal grey matter changes in first episode psychosis. https://doi.org/10.1101/2022.01.11.22268989 .
Jalbrzikowski M, Hayes RA, Wood SJ, Nordholm D, Zhou JH, Fusar-Poli P, et al. Association of structural magnetic resonance imaging measures with psychosis onset in individuals at clinical high risk for developing psychosis: an ENIGMA Working Group Mega-analysis. JAMA Psychiatry. 2021;78:753–66.
pubmed: 33950164
doi: 10.1001/jamapsychiatry.2021.0638
García-Cabezas MÁ, Zikopoulos B, Barbas H. The Structural Model: a theory linking connections, plasticity, pathology, development and evolution of the cerebral cortex. Brain Struct Funct. 2019;224:985–1008.
pubmed: 30739157
pmcid: 6500485
doi: 10.1007/s00429-019-01841-9
Park BY, Bethlehem RAI, Paquola C, Larivière S, Rodríguez-Cruces R, Vos de Wael R, et al. An expanding manifold in transmodal regions characterizes adolescent reconfiguration of structural connectome organization. Elife. 2021;10:e64694.
pubmed: 33787489
pmcid: 8087442
doi: 10.7554/eLife.64694
Honey CJ, Sporns O, Cammoun L, Gigandet X, Thiran JP, Meuli R, et al. Predicting human resting-state functional connectivity from structural connectivity. Proc Natl Acad Sci USA. 2009;106:2035–40.
pubmed: 19188601
pmcid: 2634800
doi: 10.1073/pnas.0811168106
Rakic P. Specification of cerebral cortical areas. Science. 1988;241:170–6.
pubmed: 3291116
doi: 10.1126/science.3291116