Skip to main content
Top

04-05-2024 | Schizophrenia | Review

Unveiling Promising Neuroimaging Biomarkers for Schizophrenia Through Clinical and Genetic Perspectives

Authors: Jing Guo, Changyi He, Huimiao Song, Huiwu Gao, Shi Yao, Shan-Shan Dong, Tie-Lin Yang

Published in: Neuroscience Bulletin

Login to get access

Abstract

Schizophrenia is a complex and serious brain disorder. Neuroscientists have become increasingly interested in using magnetic resonance-based brain imaging-derived phenotypes (IDPs) to investigate the etiology of psychiatric disorders. IDPs capture valuable clinical advantages and hold biological significance in identifying brain abnormalities. In this review, we aim to discuss current and prospective approaches to identify potential biomarkers for schizophrenia using clinical multimodal neuroimaging and imaging genetics. We first described IDPs through their phenotypic classification and neuroimaging genomics. Secondly, we discussed the applications of multimodal neuroimaging by clinical evidence in observational studies and randomized controlled trials. Thirdly, considering the genetic evidence of IDPs, we discussed how can utilize neuroimaging data as an intermediate phenotype to make association inferences by polygenic risk scores and Mendelian randomization. Finally, we discussed machine learning as an optimum approach for validating biomarkers. Together, future research efforts focused on neuroimaging biomarkers aim to enhance our understanding of schizophrenia.
Literature
1.
go back to reference Charlson F, van Ommeren M, Flaxman A, Cornett J, Whiteford H, Saxena S. New WHO prevalence estimates of mental disorders in conflict settings: A systematic review and meta-analysis. Lancet 2019, 394: 240–248.PubMedPubMedCentralCrossRef Charlson F, van Ommeren M, Flaxman A, Cornett J, Whiteford H, Saxena S. New WHO prevalence estimates of mental disorders in conflict settings: A systematic review and meta-analysis. Lancet 2019, 394: 240–248.PubMedPubMedCentralCrossRef
2.
go back to reference Fleischhacker WW, Arango C, Arteel P, Barnes TRE, Carpenter W, Duckworth K. Schizophrenia—time to commit to policy change. Schizophr Bull 2014, 40: S165–S194.PubMedPubMedCentralCrossRef Fleischhacker WW, Arango C, Arteel P, Barnes TRE, Carpenter W, Duckworth K. Schizophrenia—time to commit to policy change. Schizophr Bull 2014, 40: S165–S194.PubMedPubMedCentralCrossRef
3.
go back to reference Hjorthøj C, Stürup AE, McGrath JJ, Nordentoft M. Years of potential life lost and life expectancy in schizophrenia: A systematic review and meta-analysis. Lancet Psychiatry 2017, 4: 295–301.PubMedCrossRef Hjorthøj C, Stürup AE, McGrath JJ, Nordentoft M. Years of potential life lost and life expectancy in schizophrenia: A systematic review and meta-analysis. Lancet Psychiatry 2017, 4: 295–301.PubMedCrossRef
4.
go back to reference Trubetskoy V, Pardiñas AF, Qi T, Panagiotaropoulou G, Awasthi S, Bigdeli TB, et al. Mapping genomic loci implicates genes and synaptic biology in schizophrenia. Nature 2022, 604: 502–508.PubMedPubMedCentralCrossRef Trubetskoy V, Pardiñas AF, Qi T, Panagiotaropoulou G, Awasthi S, Bigdeli TB, et al. Mapping genomic loci implicates genes and synaptic biology in schizophrenia. Nature 2022, 604: 502–508.PubMedPubMedCentralCrossRef
5.
go back to reference Xu MQ, Sun WS, Liu BX, Feng GY, Yu L, Yang L, et al. Prenatal malnutrition and adult schizophrenia: Further evidence from the 1959–1961 Chinese famine. Schizophr Bull 2009, 35: 568–576.PubMedPubMedCentralCrossRef Xu MQ, Sun WS, Liu BX, Feng GY, Yu L, Yang L, et al. Prenatal malnutrition and adult schizophrenia: Further evidence from the 1959–1961 Chinese famine. Schizophr Bull 2009, 35: 568–576.PubMedPubMedCentralCrossRef
6.
go back to reference Wu Q, Wang X, Wang Y, Long YJ, Zhao JP, Wu RR. Developments in biological mechanisms and treatments for negative symptoms and cognitive dysfunction of schizophrenia. Neurosci Bull 2021, 37: 1609–1624.PubMedPubMedCentralCrossRef Wu Q, Wang X, Wang Y, Long YJ, Zhao JP, Wu RR. Developments in biological mechanisms and treatments for negative symptoms and cognitive dysfunction of schizophrenia. Neurosci Bull 2021, 37: 1609–1624.PubMedPubMedCentralCrossRef
7.
go back to reference Saugstad LF. Social class, marriage, and fertility in schizophrenia. Schizophr Bull 1989, 15: 9–43.PubMedCrossRef Saugstad LF. Social class, marriage, and fertility in schizophrenia. Schizophr Bull 1989, 15: 9–43.PubMedCrossRef
8.
go back to reference Abi-Dargham A, Moeller SJ, Ali F, DeLorenzo C, Domschke K, Horga G, et al. Candidate biomarkers in psychiatric disorders: State of the field. World Psychiatry 2023, 22: 236–262.PubMedPubMedCentralCrossRef Abi-Dargham A, Moeller SJ, Ali F, DeLorenzo C, Domschke K, Horga G, et al. Candidate biomarkers in psychiatric disorders: State of the field. World Psychiatry 2023, 22: 236–262.PubMedPubMedCentralCrossRef
9.
go back to reference Konopaske GT, Lange N, Coyle JT, Benes FM. Prefrontal cortical dendritic spine pathology in schizophrenia and bipolar disorder. JAMA Psychiatry 2014, 71: 1323–1331.PubMedPubMedCentralCrossRef Konopaske GT, Lange N, Coyle JT, Benes FM. Prefrontal cortical dendritic spine pathology in schizophrenia and bipolar disorder. JAMA Psychiatry 2014, 71: 1323–1331.PubMedPubMedCentralCrossRef
11.
go back to reference Abi-Dargham A, Horga G. The search for imaging biomarkers in psychiatric disorders. Nat Med 2016, 22: 1248–1255.PubMedCrossRef Abi-Dargham A, Horga G. The search for imaging biomarkers in psychiatric disorders. Nat Med 2016, 22: 1248–1255.PubMedCrossRef
12.
go back to reference Meyer-Lindenberg A, Weinberger DR. Intermediate phenotypes and genetic mechanisms of psychiatric disorders. Nat Rev Neurosci 2006, 7: 818–827.PubMedCrossRef Meyer-Lindenberg A, Weinberger DR. Intermediate phenotypes and genetic mechanisms of psychiatric disorders. Nat Rev Neurosci 2006, 7: 818–827.PubMedCrossRef
13.
go back to reference Alfaro-Almagro F, Jenkinson M, Bangerter NK, Andersson JLR, Griffanti L, Douaud G, et al. Image processing and quality control for the first 10, 000 brain imaging datasets from UK Biobank. Neuroimage 2018, 166: 400–424.PubMedCrossRef Alfaro-Almagro F, Jenkinson M, Bangerter NK, Andersson JLR, Griffanti L, Douaud G, et al. Image processing and quality control for the first 10, 000 brain imaging datasets from UK Biobank. Neuroimage 2018, 166: 400–424.PubMedCrossRef
14.
go back to reference Miller KL, Alfaro-Almagro F, Bangerter NK, Thomas DL, Yacoub E, Xu J, et al. Multimodal population brain imaging in the UK Biobank prospective epidemiological study. Nat Neurosci 2016, 19: 1523–1536.PubMedPubMedCentralCrossRef Miller KL, Alfaro-Almagro F, Bangerter NK, Thomas DL, Yacoub E, Xu J, et al. Multimodal population brain imaging in the UK Biobank prospective epidemiological study. Nat Neurosci 2016, 19: 1523–1536.PubMedPubMedCentralCrossRef
15.
go back to reference 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.PubMedPubMedCentralCrossRef 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.PubMedPubMedCentralCrossRef
17.
go back to reference Silbereis JC, Pochareddy S, Zhu Y, Li M, Sestan N. The cellular and molecular landscapes of the developing human central nervous system. Neuron 2016, 89: 248–268.PubMedPubMedCentralCrossRef Silbereis JC, Pochareddy S, Zhu Y, Li M, Sestan N. The cellular and molecular landscapes of the developing human central nervous system. Neuron 2016, 89: 248–268.PubMedPubMedCentralCrossRef
20.
go back to reference Smith SM, Jenkinson M, Johansen-Berg H, Rueckert D, Nichols TE, MacKay CE, et al. Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data. Neuroimage 2006, 31: 1487–1505.PubMedCrossRef Smith SM, Jenkinson M, Johansen-Berg H, Rueckert D, Nichols TE, MacKay CE, et al. Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data. Neuroimage 2006, 31: 1487–1505.PubMedCrossRef
21.
go back to reference Behrens TEJ, Berg HJ, Jbabdi S, Rushworth MFS, Woolrich MW. Probabilistic diffusion tractography with multiple fibre orientations: What can we gain? Neuroimage 2007, 34: 144–155.PubMedCrossRef Behrens TEJ, Berg HJ, Jbabdi S, Rushworth MFS, Woolrich MW. Probabilistic diffusion tractography with multiple fibre orientations: What can we gain? Neuroimage 2007, 34: 144–155.PubMedCrossRef
22.
23.
go back to reference Zhang H, Schneider T, Wheeler-Kingshott CA, Alexander DC. NODDI: Practical in vivo neurite orientation dispersion and density imaging of the human brain. Neuroimage 2012, 61: 1000–1016.PubMedCrossRef Zhang H, Schneider T, Wheeler-Kingshott CA, Alexander DC. NODDI: Practical in vivo neurite orientation dispersion and density imaging of the human brain. Neuroimage 2012, 61: 1000–1016.PubMedCrossRef
24.
go back to reference Heeger DJ, Ress D. What does fMRI tell us about neuronal activity? Nat Rev Neurosci 2002, 3: 142–151.PubMedCrossRef Heeger DJ, Ress D. What does fMRI tell us about neuronal activity? Nat Rev Neurosci 2002, 3: 142–151.PubMedCrossRef
25.
26.
go back to reference Spreng RN, Mar RA, Kim ASN. The common neural basis of autobiographical memory, prospection, navigation, theory of mind, and the default mode: A quantitative meta-analysis. J Cogn Neurosci 2009, 21: 489–510.PubMedCrossRef Spreng RN, Mar RA, Kim ASN. The common neural basis of autobiographical memory, prospection, navigation, theory of mind, and the default mode: A quantitative meta-analysis. J Cogn Neurosci 2009, 21: 489–510.PubMedCrossRef
27.
go back to reference Raichle ME, Snyder AZ. A default mode of brain function: A brief history of an evolving idea. Neuroimage 2007, 37: 1083–1090;discussion 1097–1099. Raichle ME, Snyder AZ. A default mode of brain function: A brief history of an evolving idea. Neuroimage 2007, 37: 1083–1090;discussion 1097–1099.
28.
go back to reference Damoiseaux JS. Effects of aging on functional and structural brain connectivity. Neuroimage 2017, 160: 32–40.PubMedCrossRef Damoiseaux JS. Effects of aging on functional and structural brain connectivity. Neuroimage 2017, 160: 32–40.PubMedCrossRef
30.
go back to reference Scholtens LH, van den Heuvel MP. Multimodal connectomics in psychiatry: Bridging scales from micro to macro. Biol Psychiatry Cogn Neurosci Neuroimaging 2018, 3: 767–776.PubMed Scholtens LH, van den Heuvel MP. Multimodal connectomics in psychiatry: Bridging scales from micro to macro. Biol Psychiatry Cogn Neurosci Neuroimaging 2018, 3: 767–776.PubMed
31.
go back to reference 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: 2382–2395.PubMedPubMedCentralCrossRef 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: 2382–2395.PubMedPubMedCentralCrossRef
32.
go back to reference Griffa A, Baumann PS, Thiran JP, Hagmann P. Structural connectomics in brain diseases. NeuroImage 2013, 80: 515–526.PubMedCrossRef Griffa A, Baumann PS, Thiran JP, Hagmann P. Structural connectomics in brain diseases. NeuroImage 2013, 80: 515–526.PubMedCrossRef
33.
go back to reference Elam JS, Glasser MF, Harms MP, Sotiropoulos SN, Andersson JLR, Burgess GC, et al. The human connectome project: A retrospective. Neuroimage 2021, 244: 118543.PubMedCrossRef Elam JS, Glasser MF, Harms MP, Sotiropoulos SN, Andersson JLR, Burgess GC, et al. The human connectome project: A retrospective. Neuroimage 2021, 244: 118543.PubMedCrossRef
34.
go back to reference Bazinet V, Hansen JY, Misic B. Towards a biologically annotated brain connectome. Nat Rev Neurosci 2023, 24: 747–760.PubMedCrossRef Bazinet V, Hansen JY, Misic B. Towards a biologically annotated brain connectome. Nat Rev Neurosci 2023, 24: 747–760.PubMedCrossRef
35.
go back to reference de Reus MA, Saenger VM, Kahn RS, van den Heuvel MP. An edge-centric perspective on the human connectome: Link communities in the brain. Philos Trans R Soc Lond B Biol Sci 2014, 369: 20130527.PubMedPubMedCentralCrossRef de Reus MA, Saenger VM, Kahn RS, van den Heuvel MP. An edge-centric perspective on the human connectome: Link communities in the brain. Philos Trans R Soc Lond B Biol Sci 2014, 369: 20130527.PubMedPubMedCentralCrossRef
36.
go back to reference van den Heuvel MP, Kahn RS, Goñi J, Sporns O. High-cost, high-capacity backbone for global brain communication. Proc Natl Acad Sci U S A 2012, 109: 11372–11377.PubMedPubMedCentralCrossRef van den Heuvel MP, Kahn RS, Goñi J, Sporns O. High-cost, high-capacity backbone for global brain communication. Proc Natl Acad Sci U S A 2012, 109: 11372–11377.PubMedPubMedCentralCrossRef
37.
go back to reference Ge J, Yang G, Han M, Zhou S, Men W, Qin L, et al. Increasing diversity in connectomics with the Chinese human connectome project. Nat Neurosci 2023, 26: 163–172.PubMedCrossRef Ge J, Yang G, Han M, Zhou S, Men W, Qin L, et al. Increasing diversity in connectomics with the Chinese human connectome project. Nat Neurosci 2023, 26: 163–172.PubMedCrossRef
38.
go back to reference Chiang MC, Barysheva M, Shattuck DW, Lee AD, Madsen SK, Avedissian C, et al. Genetics of brain fiber architecture and intellectual performance. J Neurosci 2009, 29: 2212–2224.PubMedPubMedCentralCrossRef Chiang MC, Barysheva M, Shattuck DW, Lee AD, Madsen SK, Avedissian C, et al. Genetics of brain fiber architecture and intellectual performance. J Neurosci 2009, 29: 2212–2224.PubMedPubMedCentralCrossRef
39.
go back to reference Bearden CE, van Erp TGM, Thompson PM, Toga AW, Cannon TD. Cortical mapping of genotype-phenotype relationships in schizophrenia. Hum Brain Mapp 2007, 28: 519–532.PubMedPubMedCentralCrossRef Bearden CE, van Erp TGM, Thompson PM, Toga AW, Cannon TD. Cortical mapping of genotype-phenotype relationships in schizophrenia. Hum Brain Mapp 2007, 28: 519–532.PubMedPubMedCentralCrossRef
40.
go back to reference Blokland GA, McMahon KL, Hoffman J, Zhu G, Meredith M, Martin NG, et al. Quantifying the heritability of task-related brain activation and performance during the N-back working memory task: A twin fMRI study. Biol Psychol 2008, 79: 70–79.PubMedPubMedCentralCrossRef Blokland GA, McMahon KL, Hoffman J, Zhu G, Meredith M, Martin NG, et al. Quantifying the heritability of task-related brain activation and performance during the N-back working memory task: A twin fMRI study. Biol Psychol 2008, 79: 70–79.PubMedPubMedCentralCrossRef
41.
go back to reference Glahn DC, Winkler AM, Kochunov P, Almasy L, Duggirala R, Carless MA, et al. Genetic control over the resting brain. Proc Natl Acad Sci U S A 2010, 107: 1223–1228.PubMedPubMedCentralCrossRef Glahn DC, Winkler AM, Kochunov P, Almasy L, Duggirala R, Carless MA, et al. Genetic control over the resting brain. Proc Natl Acad Sci U S A 2010, 107: 1223–1228.PubMedPubMedCentralCrossRef
42.
go back to reference Meda SA, Ruaño G, Windemuth A, O’Neil K, Berwise C, Dunn SM, et al. Multivariate analysis reveals genetic associations of the resting default mode network in psychotic bipolar disorder and schizophrenia. Proc Natl Acad Sci U S A 2014, 111: E2066–E2075.PubMedPubMedCentralCrossRef Meda SA, Ruaño G, Windemuth A, O’Neil K, Berwise C, Dunn SM, et al. Multivariate analysis reveals genetic associations of the resting default mode network in psychotic bipolar disorder and schizophrenia. Proc Natl Acad Sci U S A 2014, 111: E2066–E2075.PubMedPubMedCentralCrossRef
43.
go back to reference Bohlken MM, Mandl RCW, Brouwer RM, van den Heuvel MP, Hedman AM, Kahn RS, et al. Heritability of structural brain network topology: A DTI study of 156 twins. Hum Brain Mapp 2014, 35: 5295–5305.PubMedPubMedCentralCrossRef Bohlken MM, Mandl RCW, Brouwer RM, van den Heuvel MP, Hedman AM, Kahn RS, et al. Heritability of structural brain network topology: A DTI study of 156 twins. Hum Brain Mapp 2014, 35: 5295–5305.PubMedPubMedCentralCrossRef
44.
go back to reference van den Heuvel MP, van Soelen IL, Stam CJ, Kahn RS, Boomsma DI, Hulshoff Pol HE. Genetic control of functional brain network efficiency in children. Eur Neuropsychopharmacol 2013, 23: 19–23.PubMedCrossRef van den Heuvel MP, van Soelen IL, Stam CJ, Kahn RS, Boomsma DI, Hulshoff Pol HE. Genetic control of functional brain network efficiency in children. Eur Neuropsychopharmacol 2013, 23: 19–23.PubMedCrossRef
45.
go back to reference Romme IAC, de Reus MA, Ophoff RA, Kahn RS, van den Heuvel MP. Connectome disconnectivity and cortical gene expression in patients with schizophrenia. Biol Psychiatry 2017, 81: 495–502.PubMedCrossRef Romme IAC, de Reus MA, Ophoff RA, Kahn RS, van den Heuvel MP. Connectome disconnectivity and cortical gene expression in patients with schizophrenia. Biol Psychiatry 2017, 81: 495–502.PubMedCrossRef
46.
go back to reference Wheeler AL, Felsky D, Viviano JD, Stojanovski S, Ameis SH, Szatmari P, et al. BDNF-dependent effects on amygdala-cortical circuitry and depression risk in children and youth. Cereb Cortex 2018, 28: 1760–1770.PubMedCrossRef Wheeler AL, Felsky D, Viviano JD, Stojanovski S, Ameis SH, Szatmari P, et al. BDNF-dependent effects on amygdala-cortical circuitry and depression risk in children and youth. Cereb Cortex 2018, 28: 1760–1770.PubMedCrossRef
47.
go back to reference Paul LK, Brown WS, Adolphs R, Tyszka JM, Richards LJ, Mukherjee P, et al. Agenesis of the corpus callosum: Genetic, developmental and functional aspects of connectivity. Nat Rev Neurosci 2007, 8: 287–299.PubMedCrossRef Paul LK, Brown WS, Adolphs R, Tyszka JM, Richards LJ, Mukherjee P, et al. Agenesis of the corpus callosum: Genetic, developmental and functional aspects of connectivity. Nat Rev Neurosci 2007, 8: 287–299.PubMedCrossRef
48.
go back to reference Gong X, Lu W, Kendrick KM, Pu W, Wang C, Jin L, et al. A brain-wide association study of DISC1 genetic variants reveals a relationship with the structure and functional connectivity of the precuneus in schizophrenia. Hum Brain Mapp 2014, 35: 5414–5430.PubMedPubMedCentralCrossRef Gong X, Lu W, Kendrick KM, Pu W, Wang C, Jin L, et al. A brain-wide association study of DISC1 genetic variants reveals a relationship with the structure and functional connectivity of the precuneus in schizophrenia. Hum Brain Mapp 2014, 35: 5414–5430.PubMedPubMedCentralCrossRef
49.
go back to reference Liu B, Fan L, Cui Y, Zhang X, Hou B, Li Y, et al. DISC1 Ser704Cys impacts thalamic-prefrontal connectivity. Brain Struct Funct 2015, 220: 91–100.PubMedCrossRef Liu B, Fan L, Cui Y, Zhang X, Hou B, Li Y, et al. DISC1 Ser704Cys impacts thalamic-prefrontal connectivity. Brain Struct Funct 2015, 220: 91–100.PubMedCrossRef
50.
go back to reference Liu B, Zhang X, Hou B, Li J, Qiu C, Qin W, et al. The impact of MIR137 on dorsolateral prefrontal-hippocampal functional connectivity in healthy subjects. Neuropsychopharmacology 2014, 39: 2153–2160.PubMedPubMedCentralCrossRef Liu B, Zhang X, Hou B, Li J, Qiu C, Qin W, et al. The impact of MIR137 on dorsolateral prefrontal-hippocampal functional connectivity in healthy subjects. Neuropsychopharmacology 2014, 39: 2153–2160.PubMedPubMedCentralCrossRef
51.
go back to reference Egan MF, Goldberg TE, Kolachana BS, Callicott JH, Mazzanti CM, Straub RE, et al. Effect of COMT Val108/158 Met genotype on frontal lobe function and risk for schizophrenia. Proc Natl Acad Sci U S A 2001, 98: 6917–6922.PubMedPubMedCentralCrossRef Egan MF, Goldberg TE, Kolachana BS, Callicott JH, Mazzanti CM, Straub RE, et al. Effect of COMT Val108/158 Met genotype on frontal lobe function and risk for schizophrenia. Proc Natl Acad Sci U S A 2001, 98: 6917–6922.PubMedPubMedCentralCrossRef
52.
go back to reference Donohoe G, Morris DW, Clarke S, McGhee KA, Schwaiger S, Nangle JM, et al. Variance in neurocognitive performance is associated with dysbindin-1 in schizophrenia: A preliminary study. Neuropsychologia 2007, 45: 454–458.PubMedCrossRef Donohoe G, Morris DW, Clarke S, McGhee KA, Schwaiger S, Nangle JM, et al. Variance in neurocognitive performance is associated with dysbindin-1 in schizophrenia: A preliminary study. Neuropsychologia 2007, 45: 454–458.PubMedCrossRef
53.
go back to reference Donohoe G, Rose E, Frodl T, Morris D, Spoletini I, Adriano F, et al. ZNF804A risk allele is associated with relatively intact gray matter volume in patients with schizophrenia. Neuroimage 2011, 54: 2132–2137.PubMedCrossRef Donohoe G, Rose E, Frodl T, Morris D, Spoletini I, Adriano F, et al. ZNF804A risk allele is associated with relatively intact gray matter volume in patients with schizophrenia. Neuroimage 2011, 54: 2132–2137.PubMedCrossRef
54.
go back to reference Egan MF, Straub RE, Goldberg TE, Yakub I, Callicott JH, Hariri AR, et al. Variation in GRM3 affects cognition, prefrontal glutamate, and risk for schizophrenia. Proc Natl Acad Sci U S A 2004, 101: 12604–12609.PubMedPubMedCentralCrossRef Egan MF, Straub RE, Goldberg TE, Yakub I, Callicott JH, Hariri AR, et al. Variation in GRM3 affects cognition, prefrontal glutamate, and risk for schizophrenia. Proc Natl Acad Sci U S A 2004, 101: 12604–12609.PubMedPubMedCentralCrossRef
55.
go back to reference Otnaess MK, Djurovic S, Rimol LM, Kulle B, Kähler AK, Jönsson EG, et al. Evidence for a possible association of neurotrophin receptor (NTRK-3) gene polymorphisms with hippocampal function and schizophrenia. Neurobiol Dis 2009, 34: 518–524.PubMedCrossRef Otnaess MK, Djurovic S, Rimol LM, Kulle B, Kähler AK, Jönsson EG, et al. Evidence for a possible association of neurotrophin receptor (NTRK-3) gene polymorphisms with hippocampal function and schizophrenia. Neurobiol Dis 2009, 34: 518–524.PubMedCrossRef
56.
go back to reference Nicodemus KK, Law AJ, Radulescu E, Luna A, Kolachana B, Vakkalanka R, et al. Biological validation of increased schizophrenia risk with NRG1, ERBB4, and AKT1 epistasis via functional neuroimaging in healthy controls. Arch Gen Psychiatry 2010, 67: 991–1001.PubMedPubMedCentralCrossRef Nicodemus KK, Law AJ, Radulescu E, Luna A, Kolachana B, Vakkalanka R, et al. Biological validation of increased schizophrenia risk with NRG1, ERBB4, and AKT1 epistasis via functional neuroimaging in healthy controls. Arch Gen Psychiatry 2010, 67: 991–1001.PubMedPubMedCentralCrossRef
57.
go back to reference Lin Z, Long Y, Wu Z, Xiang Z, Ju Y, Liu Z. Associations between brain abnormalities and common genetic variants for schizophrenia: A narrative review of structural and functional neuroimaging findings. Ann Palliat Med 2021, 10: 10031–10052.PubMedCrossRef Lin Z, Long Y, Wu Z, Xiang Z, Ju Y, Liu Z. Associations between brain abnormalities and common genetic variants for schizophrenia: A narrative review of structural and functional neuroimaging findings. Ann Palliat Med 2021, 10: 10031–10052.PubMedCrossRef
58.
go back to reference Taquet M, Smith SM, Prohl AK, Peters JM, Warfield SK, Scherrer B, et al. A structural brain network of genetic vulnerability to psychiatric illness. Mol Psychiatry 2021, 26: 2089–2100.PubMedCrossRef Taquet M, Smith SM, Prohl AK, Peters JM, Warfield SK, Scherrer B, et al. A structural brain network of genetic vulnerability to psychiatric illness. Mol Psychiatry 2021, 26: 2089–2100.PubMedCrossRef
59.
go back to reference Gong Q, Hu X, Pettersson-Yeo W, Xu X, Lui S, Crossley N, et al. Network-level dysconnectivity in drug-Naïve first-episode psychosis: Dissociating transdiagnostic and diagnosis-specific alterations. Neuropsychopharmacology 2017, 42: 933–940.PubMedCrossRef Gong Q, Hu X, Pettersson-Yeo W, Xu X, Lui S, Crossley N, et al. Network-level dysconnectivity in drug-Naïve first-episode psychosis: Dissociating transdiagnostic and diagnosis-specific alterations. Neuropsychopharmacology 2017, 42: 933–940.PubMedCrossRef
60.
go back to reference Smith SM, Douaud G, Chen W, Hanayik T, Alfaro-Almagro F, Sharp K, et al. An expanded set of genome-wide association studies of brain imaging phenotypes in UK Biobank. Nat Neurosci 2021, 24: 737–745.PubMedPubMedCentralCrossRef Smith SM, Douaud G, Chen W, Hanayik T, Alfaro-Almagro F, Sharp K, et al. An expanded set of genome-wide association studies of brain imaging phenotypes in UK Biobank. Nat Neurosci 2021, 24: 737–745.PubMedPubMedCentralCrossRef
61.
go back to reference Elliott LT, Sharp K, Alfaro-Almagro F, Shi S, Miller KL, Douaud G, et al. Genome-wide association studies of brain imaging phenotypes in UK Biobank. Nature 2018, 562: 210–216.PubMedPubMedCentralCrossRef Elliott LT, Sharp K, Alfaro-Almagro F, Shi S, Miller KL, Douaud G, et al. Genome-wide association studies of brain imaging phenotypes in UK Biobank. Nature 2018, 562: 210–216.PubMedPubMedCentralCrossRef
62.
go back to reference Hibar DP, Stein JL, Renteria ME, Arias-Vasquez A, Desrivières S, Jahanshad N, et al. Common genetic variants influence human subcortical brain structures. Nature 2015, 520: 224–229.PubMedPubMedCentralCrossRef Hibar DP, Stein JL, Renteria ME, Arias-Vasquez A, Desrivières S, Jahanshad N, et al. Common genetic variants influence human subcortical brain structures. Nature 2015, 520: 224–229.PubMedPubMedCentralCrossRef
63.
go back to reference Hibar DP, Adams HHH, Jahanshad N, Chauhan G, Stein JL, Hofer E, et al. Novel genetic loci associated with hippocampal volume. Nat Commun 2017, 8: 13624.PubMedPubMedCentralCrossRef Hibar DP, Adams HHH, Jahanshad N, Chauhan G, Stein JL, Hofer E, et al. Novel genetic loci associated with hippocampal volume. Nat Commun 2017, 8: 13624.PubMedPubMedCentralCrossRef
64.
go back to reference Satizabal CL, Adams HHH, Hibar DP, White CC, Knol MJ, Stein JL, et al. Genetic architecture of subcortical brain structures in 38, 851 individuals. Nat Genet 2019, 51: 1624–1636.PubMedPubMedCentralCrossRef Satizabal CL, Adams HHH, Hibar DP, White CC, Knol MJ, Stein JL, et al. Genetic architecture of subcortical brain structures in 38, 851 individuals. Nat Genet 2019, 51: 1624–1636.PubMedPubMedCentralCrossRef
65.
go back to reference Flint J, Timpson N, Munafò M. Assessing the utility of intermediate phenotypes for genetic mapping of psychiatric disease. Trends Neurosci 2014, 37: 733–741.PubMedPubMedCentralCrossRef Flint J, Timpson N, Munafò M. Assessing the utility of intermediate phenotypes for genetic mapping of psychiatric disease. Trends Neurosci 2014, 37: 733–741.PubMedPubMedCentralCrossRef
67.
go back to reference Cohen MX, Young J, Baek JM, Kessler C, Ranganath C. Individual differences in extraversion and dopamine genetics predict neural reward responses. Brain Res Cogn Brain Res 2005, 25: 851–861.PubMedCrossRef Cohen MX, Young J, Baek JM, Kessler C, Ranganath C. Individual differences in extraversion and dopamine genetics predict neural reward responses. Brain Res Cogn Brain Res 2005, 25: 851–861.PubMedCrossRef
68.
go back to reference Vogeley K, Schneider-Axmann T, Pfeiffer U, Tepest R, Bayer TA, Bogerts B, et al. Disturbed gyrification of the prefrontal region in male schizophrenic patients: A morphometric postmortem study. Am J Psychiatry 2000, 157: 34–39.PubMedCrossRef Vogeley K, Schneider-Axmann T, Pfeiffer U, Tepest R, Bayer TA, Bogerts B, et al. Disturbed gyrification of the prefrontal region in male schizophrenic patients: A morphometric postmortem study. Am J Psychiatry 2000, 157: 34–39.PubMedCrossRef
69.
go back to reference James AC, James S, Smith DM, Javaloyes A. Cerebellar, prefrontal cortex, and thalamic volumes over two time points in adolescent-onset schizophrenia. Am J Psychiatry 2004, 161: 1023–1029.PubMedCrossRef James AC, James S, Smith DM, Javaloyes A. Cerebellar, prefrontal cortex, and thalamic volumes over two time points in adolescent-onset schizophrenia. Am J Psychiatry 2004, 161: 1023–1029.PubMedCrossRef
70.
go back to reference Jou RJ, Hardan AY, Keshavan MS. Reduced cortical folding in individuals at high risk for schizophrenia: A pilot study. Schizophr Res 2005, 75: 309–313.PubMedCrossRef Jou RJ, Hardan AY, Keshavan MS. Reduced cortical folding in individuals at high risk for schizophrenia: A pilot study. Schizophr Res 2005, 75: 309–313.PubMedCrossRef
71.
go back to reference 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: 547–553.PubMedCrossRef 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: 547–553.PubMedCrossRef
72.
go back to reference 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: 644–654.PubMedPubMedCentralCrossRef 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: 644–654.PubMedPubMedCentralCrossRef
73.
go back to reference Brugger SP, Howes OD. Heterogeneity and homogeneity of regional brain structure in schizophrenia: A meta-analysis. JAMA Psychiatry 2017, 74: 1104–1111.PubMedPubMedCentralCrossRef Brugger SP, Howes OD. Heterogeneity and homogeneity of regional brain structure in schizophrenia: A meta-analysis. JAMA Psychiatry 2017, 74: 1104–1111.PubMedPubMedCentralCrossRef
74.
go back to reference Zalesky A, Fornito A, Seal ML, Cocchi L, Westin CF, Bullmore ET, et al. Disrupted axonal fiber connectivity in schizophrenia. Biol Psychiatry 2011, 69: 80–89.PubMedCrossRef Zalesky A, Fornito A, Seal ML, Cocchi L, Westin CF, Bullmore ET, et al. Disrupted axonal fiber connectivity in schizophrenia. Biol Psychiatry 2011, 69: 80–89.PubMedCrossRef
75.
go back to reference Kelly S, Jahanshad N, Zalesky A, Kochunov P, Agartz I, Alloza C, et al. Widespread white matter microstructural differences in schizophrenia across 4322 individuals: Results from the ENIGMA Schizophrenia DTI Working Group. Mol Psychiatry 2018, 23: 1261–1269.PubMedCrossRef Kelly S, Jahanshad N, Zalesky A, Kochunov P, Agartz I, Alloza C, et al. Widespread white matter microstructural differences in schizophrenia across 4322 individuals: Results from the ENIGMA Schizophrenia DTI Working Group. Mol Psychiatry 2018, 23: 1261–1269.PubMedCrossRef
76.
go back to reference Balevich EC, Haznedar MM, Wang E, Newmark RE, Bloom R, Schneiderman JS, et al. Corpus callosum size and diffusion tensor anisotropy in adolescents and adults with schizophrenia. Psychiatry Res 2015, 231: 244–251.PubMedPubMedCentralCrossRef Balevich EC, Haznedar MM, Wang E, Newmark RE, Bloom R, Schneiderman JS, et al. Corpus callosum size and diffusion tensor anisotropy in adolescents and adults with schizophrenia. Psychiatry Res 2015, 231: 244–251.PubMedPubMedCentralCrossRef
77.
go back to reference Perlstein WM, Carter CS, Noll DC, Cohen JD. Relation of prefrontal cortex dysfunction to working memory and symptoms in schizophrenia. Am J Psychiatry 2001, 158: 1105–1113.PubMedCrossRef Perlstein WM, Carter CS, Noll DC, Cohen JD. Relation of prefrontal cortex dysfunction to working memory and symptoms in schizophrenia. Am J Psychiatry 2001, 158: 1105–1113.PubMedCrossRef
78.
go back to reference Anticevic A, Repovs G, Krystal JH, Barch DM. A broken filter: Prefrontal functional connectivity abnormalities in schizophrenia during working memory interference. Schizophr Res 2012, 141: 8–14.PubMedCrossRef Anticevic A, Repovs G, Krystal JH, Barch DM. A broken filter: Prefrontal functional connectivity abnormalities in schizophrenia during working memory interference. Schizophr Res 2012, 141: 8–14.PubMedCrossRef
79.
go back to reference Hua M, Peng Y, Zhou Y, Qin W, Yu C, Liang M. Disrupted pathways from limbic areas to thalamus in schizophrenia highlighted by whole-brain resting-state effective connectivity analysis. Prog Neuropsychopharmacol Biol Psychiatry 2020, 99: 109837.PubMedCrossRef Hua M, Peng Y, Zhou Y, Qin W, Yu C, Liang M. Disrupted pathways from limbic areas to thalamus in schizophrenia highlighted by whole-brain resting-state effective connectivity analysis. Prog Neuropsychopharmacol Biol Psychiatry 2020, 99: 109837.PubMedCrossRef
80.
go back to reference Martino M, Magioncalda P, Yu H, Li X, Wang Q, Meng Y, et al. Abnormal resting-state connectivity in a substantia nigra-related striato-thalamo-cortical network in a large sample of first-episode drug-Naïve patients with schizophrenia. Schizophr Bull 2018, 44: 419–431.PubMedCrossRef Martino M, Magioncalda P, Yu H, Li X, Wang Q, Meng Y, et al. Abnormal resting-state connectivity in a substantia nigra-related striato-thalamo-cortical network in a large sample of first-episode drug-Naïve patients with schizophrenia. Schizophr Bull 2018, 44: 419–431.PubMedCrossRef
81.
go back to reference Li A, Zalesky A, Yue W, Howes O, Yan H, Liu Y, et al. A neuroimaging biomarker for striatal dysfunction in schizophrenia. Nat Med 2020, 26: 558–565.PubMedCrossRef Li A, Zalesky A, Yue W, Howes O, Yan H, Liu Y, et al. A neuroimaging biomarker for striatal dysfunction in schizophrenia. Nat Med 2020, 26: 558–565.PubMedCrossRef
82.
go back to reference Liang S, Li T. Functional striatal abnormalities: A distinct brain signature of schizophrenia. Neurosci Bull 2021, 37: 284–286.PubMedCrossRef Liang S, Li T. Functional striatal abnormalities: A distinct brain signature of schizophrenia. Neurosci Bull 2021, 37: 284–286.PubMedCrossRef
83.
go back to reference Fornito A, Harrison BJ, Goodby E, Dean A, Ooi C, Nathan PJ, et al. Functional dysconnectivity of corticostriatal circuitry as a risk phenotype for psychosis. JAMA Psychiatry 2013, 70: 1143–1151.PubMedCrossRef Fornito A, Harrison BJ, Goodby E, Dean A, Ooi C, Nathan PJ, et al. Functional dysconnectivity of corticostriatal circuitry as a risk phenotype for psychosis. JAMA Psychiatry 2013, 70: 1143–1151.PubMedCrossRef
84.
go back to reference Whitfield-Gabrieli S, Ford JM. Default mode network activity and connectivity in psychopathology. Annu Rev Clin Psychol 2012, 8: 49–76.PubMedCrossRef Whitfield-Gabrieli S, Ford JM. Default mode network activity and connectivity in psychopathology. Annu Rev Clin Psychol 2012, 8: 49–76.PubMedCrossRef
85.
go back to reference Hu ML, Zong XF, Mann JJ, Zheng JJ, Liao YH, Li ZC, et al. A review of the functional and anatomical default mode network in schizophrenia. Neurosci Bull 2017, 33: 73–84.PubMedCrossRef Hu ML, Zong XF, Mann JJ, Zheng JJ, Liao YH, Li ZC, et al. A review of the functional and anatomical default mode network in schizophrenia. Neurosci Bull 2017, 33: 73–84.PubMedCrossRef
86.
go back to reference Garrity AG, Pearlson GD, McKiernan K, Lloyd D, Kiehl KA, Calhoun VD. Aberrant “default mode” functional connectivity in schizophrenia. Am J Psychiatry 2007, 164: 450–457.PubMedCrossRef Garrity AG, Pearlson GD, McKiernan K, Lloyd D, Kiehl KA, Calhoun VD. Aberrant “default mode” functional connectivity in schizophrenia. Am J Psychiatry 2007, 164: 450–457.PubMedCrossRef
87.
go back to reference Dauvermann MR, Mothersill D, Rokita KI, King S, Holleran L, Ruan K, et al. Changes in default-mode network associated with childhood trauma in schizophrenia. Schizophr Bull 2021, 47: 1482–1494.PubMedPubMedCentralCrossRef Dauvermann MR, Mothersill D, Rokita KI, King S, Holleran L, Ruan K, et al. Changes in default-mode network associated with childhood trauma in schizophrenia. Schizophr Bull 2021, 47: 1482–1494.PubMedPubMedCentralCrossRef
88.
go back to reference Sendi MSE, Zendehrouh E, Ellis CA, Liang Z, Fu Z, Mathalon DH, et al. Aberrant dynamic functional connectivity of default mode network in schizophrenia and links to symptom severity. Front Neural Circuits 2021, 15: 649417.PubMedPubMedCentralCrossRef Sendi MSE, Zendehrouh E, Ellis CA, Liang Z, Fu Z, Mathalon DH, et al. Aberrant dynamic functional connectivity of default mode network in schizophrenia and links to symptom severity. Front Neural Circuits 2021, 15: 649417.PubMedPubMedCentralCrossRef
89.
go back to reference Jamea AA, Alblowi M, Alghamdi J, Alosaimi FD, Albadr F, Abualait T, et al. Altered default mode network activity and cortical thickness as vulnerability indicators for SCZ: A preliminary resting state MRI study. Eur Rev Med Pharmacol Sci 2021, 25: 669–677.PubMed Jamea AA, Alblowi M, Alghamdi J, Alosaimi FD, Albadr F, Abualait T, et al. Altered default mode network activity and cortical thickness as vulnerability indicators for SCZ: A preliminary resting state MRI study. Eur Rev Med Pharmacol Sci 2021, 25: 669–677.PubMed
90.
go back to reference Liu H, Kaneko Y, Ouyang X, Li L, Hao Y, Chen EY, et al. Schizophrenic patients and their unaffected siblings share increased resting-state connectivity in the task-negative network but not its anticorrelated task-positive network. Schizophr Bull 2012, 38: 285–294.PubMedCrossRef Liu H, Kaneko Y, Ouyang X, Li L, Hao Y, Chen EY, et al. Schizophrenic patients and their unaffected siblings share increased resting-state connectivity in the task-negative network but not its anticorrelated task-positive network. Schizophr Bull 2012, 38: 285–294.PubMedCrossRef
91.
go back to reference Whitfield-Gabrieli S, Thermenos HW, Milanovic S, Tsuang MT, Faraone SV, McCarley RW, et al. Hyperactivity and hyperconnectivity of the default network in schizophrenia and in first-degree relatives of persons with schizophrenia. Proc Natl Acad Sci U S A 2009, 106: 1279–1284.PubMedPubMedCentralCrossRef Whitfield-Gabrieli S, Thermenos HW, Milanovic S, Tsuang MT, Faraone SV, McCarley RW, et al. Hyperactivity and hyperconnectivity of the default network in schizophrenia and in first-degree relatives of persons with schizophrenia. Proc Natl Acad Sci U S A 2009, 106: 1279–1284.PubMedPubMedCentralCrossRef
92.
go back to reference Sasabayashi D, Takahashi T, Takayanagi Y, Nemoto K, Ueno M, Furuichi A, et al. Resting state hyperconnectivity of the default mode network in schizophrenia and clinical high-risk state for psychosis. Cereb Cortex 2023, 33: 8456–8464.PubMedCrossRef Sasabayashi D, Takahashi T, Takayanagi Y, Nemoto K, Ueno M, Furuichi A, et al. Resting state hyperconnectivity of the default mode network in schizophrenia and clinical high-risk state for psychosis. Cereb Cortex 2023, 33: 8456–8464.PubMedCrossRef
94.
go back to reference Li H, Tang J, Chen L, Liao Y, Zhou B, He Y, et al. Reduced middle cingulate gyrus volume in late-onset schizophrenia in a Chinese Han population: A voxel-based structural MRI study. Neurosci Bull 2015, 31: 626–627.PubMedPubMedCentralCrossRef Li H, Tang J, Chen L, Liao Y, Zhou B, He Y, et al. Reduced middle cingulate gyrus volume in late-onset schizophrenia in a Chinese Han population: A voxel-based structural MRI study. Neurosci Bull 2015, 31: 626–627.PubMedPubMedCentralCrossRef
95.
go back to reference Marino M, Spironelli C, Mantini D, Craven AR, Ersland L, Angrilli A, et al. Default mode network alterations underlie auditory verbal hallucinations in schizophrenia. J Psychiatr Res 2022, 155: 24–32.PubMedCrossRef Marino M, Spironelli C, Mantini D, Craven AR, Ersland L, Angrilli A, et al. Default mode network alterations underlie auditory verbal hallucinations in schizophrenia. J Psychiatr Res 2022, 155: 24–32.PubMedCrossRef
96.
go back to reference Diederen KMJ, Neggers SFW, de Weijer AD, van Lutterveld R, Daalman K, Eickhoff SB, et al. Aberrant resting-state connectivity in non-psychotic individuals with auditory hallucinations. Psychol Med 2013, 43: 1685–1696.PubMedCrossRef Diederen KMJ, Neggers SFW, de Weijer AD, van Lutterveld R, Daalman K, Eickhoff SB, et al. Aberrant resting-state connectivity in non-psychotic individuals with auditory hallucinations. Psychol Med 2013, 43: 1685–1696.PubMedCrossRef
98.
go back to reference Friston KJ, Frith CD. Schizophrenia: A disconnection syndrome? Clin Neurosci 1995, 3: 89–97.PubMed Friston KJ, Frith CD. Schizophrenia: A disconnection syndrome? Clin Neurosci 1995, 3: 89–97.PubMed
99.
go back to reference van den Heuvel MP, Sporns O, Collin G, Scheewe T, Mandl RCW, Cahn W, et al. Abnormal rich club organization and functional brain dynamics in schizophrenia. JAMA Psychiatry 2013, 70: 783–792.PubMedCrossRef van den Heuvel MP, Sporns O, Collin G, Scheewe T, Mandl RCW, Cahn W, et al. Abnormal rich club organization and functional brain dynamics in schizophrenia. JAMA Psychiatry 2013, 70: 783–792.PubMedCrossRef
100.
go back to reference Bassett DS, Bullmore E, Verchinski BA, Mattay VS, Weinberger DR, Meyer-Lindenberg A. Hierarchical organization of human cortical networks in health and schizophrenia. J Neurosci 2008, 28: 9239–9248.PubMedPubMedCentralCrossRef Bassett DS, Bullmore E, Verchinski BA, Mattay VS, Weinberger DR, Meyer-Lindenberg A. Hierarchical organization of human cortical networks in health and schizophrenia. J Neurosci 2008, 28: 9239–9248.PubMedPubMedCentralCrossRef
101.
go back to reference Lynall ME, Bassett DS, Kerwin R, McKenna PJ, Kitzbichler M, Muller U, et al. Functional connectivity and brain networks in schizophrenia. J Neurosci 2010, 30: 9477–9487.PubMedPubMedCentralCrossRef Lynall ME, Bassett DS, Kerwin R, McKenna PJ, Kitzbichler M, Muller U, et al. Functional connectivity and brain networks in schizophrenia. J Neurosci 2010, 30: 9477–9487.PubMedPubMedCentralCrossRef
102.
go back to reference Cocchi L, Harding IH, Lord A, Pantelis C, Yucel M, Zalesky A. Disruption of structure-function coupling in the schizophrenia connectome. Neuroimage Clin 2014, 4: 779–787.PubMedPubMedCentralCrossRef Cocchi L, Harding IH, Lord A, Pantelis C, Yucel M, Zalesky A. Disruption of structure-function coupling in the schizophrenia connectome. Neuroimage Clin 2014, 4: 779–787.PubMedPubMedCentralCrossRef
103.
go back to reference van den Heuvel MP, Mandl RCW, Stam CJ, Kahn RS, Hulshoff Pol HE. Aberrant frontal and temporal complex network structure in schizophrenia: A graph theoretical analysis. J Neurosci 2010, 30: 15915–15926.PubMedPubMedCentralCrossRef van den Heuvel MP, Mandl RCW, Stam CJ, Kahn RS, Hulshoff Pol HE. Aberrant frontal and temporal complex network structure in schizophrenia: A graph theoretical analysis. J Neurosci 2010, 30: 15915–15926.PubMedPubMedCentralCrossRef
104.
go back to reference Cui LB, Wei Y, Xi YB, Griffa A, De Lange SC, Kahn RS, et al. Connectome-based patterns of first-episode medication-Naïve patients with schizophrenia. Schizophr Bull 2019, 45: 1291–1299.PubMedPubMedCentralCrossRef Cui LB, Wei Y, Xi YB, Griffa A, De Lange SC, Kahn RS, et al. Connectome-based patterns of first-episode medication-Naïve patients with schizophrenia. Schizophr Bull 2019, 45: 1291–1299.PubMedPubMedCentralCrossRef
105.
go back to reference Cui LB, Liu K, Li C, Wang LX, Guo F, Tian P, et al. Putamen-related regional and network functional deficits in first-episode schizophrenia with auditory verbal hallucinations. Schizophr Res 2016, 173: 13–22.PubMedCrossRef Cui LB, Liu K, Li C, Wang LX, Guo F, Tian P, et al. Putamen-related regional and network functional deficits in first-episode schizophrenia with auditory verbal hallucinations. Schizophr Res 2016, 173: 13–22.PubMedCrossRef
106.
go back to reference Li B, Cui LB, Xi YB, Friston KJ, Guo F, Wang HN, et al. Abnormal effective connectivity in the brain is involved in auditory verbal hallucinations in schizophrenia. Neurosci Bull 2017, 33: 281–291.PubMedPubMedCentralCrossRef Li B, Cui LB, Xi YB, Friston KJ, Guo F, Wang HN, et al. Abnormal effective connectivity in the brain is involved in auditory verbal hallucinations in schizophrenia. Neurosci Bull 2017, 33: 281–291.PubMedPubMedCentralCrossRef
107.
go back to reference Damaraju E, Allen EA, Belger A, Ford JM, McEwen S, Mathalon DH, et al. Dynamic functional connectivity analysis reveals transient states of dysconnectivity in schizophrenia. Neuroimage Clin 2014, 5: 298–308.PubMedPubMedCentralCrossRef Damaraju E, Allen EA, Belger A, Ford JM, McEwen S, Mathalon DH, et al. Dynamic functional connectivity analysis reveals transient states of dysconnectivity in schizophrenia. Neuroimage Clin 2014, 5: 298–308.PubMedPubMedCentralCrossRef
108.
go back to reference Woodward ND, Karbasforoushan H, Heckers S. Thalamocortical dysconnectivity in schizophrenia. Am J Psychiatry 2012, 169: 1092–1099.PubMedCrossRef Woodward ND, Karbasforoushan H, Heckers S. Thalamocortical dysconnectivity in schizophrenia. Am J Psychiatry 2012, 169: 1092–1099.PubMedCrossRef
110.
go back to reference Roiz-Santiañez R, Suarez-Pinilla P, Crespo-Facorro B. Brain structural effects of antipsychotic treatment in schizophrenia: A systematic review. Curr Neuropharmacol 2015, 13: 422–434.PubMedPubMedCentralCrossRef Roiz-Santiañez R, Suarez-Pinilla P, Crespo-Facorro B. Brain structural effects of antipsychotic treatment in schizophrenia: A systematic review. Curr Neuropharmacol 2015, 13: 422–434.PubMedPubMedCentralCrossRef
111.
go back to reference Deakin B, Suckling J, Barnes TRE, Byrne K, Chaudhry IB, Dazzan P, et al. The benefit of minocycline on negative symptoms of schizophrenia in patients with recent-onset psychosis (BeneMin): A randomised, double-blind, placebo-controlled trial. Lancet Psychiatry 2018, 5: 885–894.PubMedPubMedCentralCrossRef Deakin B, Suckling J, Barnes TRE, Byrne K, Chaudhry IB, Dazzan P, et al. The benefit of minocycline on negative symptoms of schizophrenia in patients with recent-onset psychosis (BeneMin): A randomised, double-blind, placebo-controlled trial. Lancet Psychiatry 2018, 5: 885–894.PubMedPubMedCentralCrossRef
112.
go back to reference Voineskos AN, Mulsant BH, Dickie EW, Neufeld NH, Rothschild AJ, Whyte EM, et al. Effects of antipsychotic medication on brain structure in patients with major depressive disorder and psychotic features: Neuroimaging findings in the context of a randomized placebo-controlled clinical trial. JAMA Psychiatry 2020, 77: 674–683.PubMedCrossRef Voineskos AN, Mulsant BH, Dickie EW, Neufeld NH, Rothschild AJ, Whyte EM, et al. Effects of antipsychotic medication on brain structure in patients with major depressive disorder and psychotic features: Neuroimaging findings in the context of a randomized placebo-controlled clinical trial. JAMA Psychiatry 2020, 77: 674–683.PubMedCrossRef
113.
go back to reference Woodward ML, Gicas KM, Warburton DE, White RF, Rauscher A, Leonova O, et al. Hippocampal volume and vasculature before and after exercise in treatment-resistant schizophrenia. Schizophr Res 2018, 202: 158–165.PubMedCrossRef Woodward ML, Gicas KM, Warburton DE, White RF, Rauscher A, Leonova O, et al. Hippocampal volume and vasculature before and after exercise in treatment-resistant schizophrenia. Schizophr Res 2018, 202: 158–165.PubMedCrossRef
114.
go back to reference Morimoto T, Matsuda Y, Matsuoka K, Yasuno F, Ikebuchi E, Kameda H, et al. Computer-assisted cognitive remediation therapy increases hippocampal volume in patients with schizophrenia: A randomized controlled trial. BMC Psychiatry 2018, 18: 83.PubMedPubMedCentralCrossRef Morimoto T, Matsuda Y, Matsuoka K, Yasuno F, Ikebuchi E, Kameda H, et al. Computer-assisted cognitive remediation therapy increases hippocampal volume in patients with schizophrenia: A randomized controlled trial. BMC Psychiatry 2018, 18: 83.PubMedPubMedCentralCrossRef
115.
go back to reference Yang M, He H, Duan M, Chen X, Chang X, Lai Y, et al. The effects of music intervention on functional connectivity strength of the brain in schizophrenia. Neural Plast 2018, 2018: 2821832.PubMedPubMedCentralCrossRef Yang M, He H, Duan M, Chen X, Chang X, Lai Y, et al. The effects of music intervention on functional connectivity strength of the brain in schizophrenia. Neural Plast 2018, 2018: 2821832.PubMedPubMedCentralCrossRef
116.
go back to reference Consortium IS, Purcell SM, Wray NR, Stone JL, Visscher PM, O’Donovan MC, et al. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature 2009, 460: 748–752.CrossRef Consortium IS, Purcell SM, Wray NR, Stone JL, Visscher PM, O’Donovan MC, et al. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature 2009, 460: 748–752.CrossRef
117.
go back to reference Chen Q, Ursini G, Romer AL, Knodt AR, Mezeivtch K, Xiao E, et al. Schizophrenia polygenic risk score predicts mnemonic hippocampal activity. Brain 2018, 141: 1218–1228.PubMedPubMedCentralCrossRef Chen Q, Ursini G, Romer AL, Knodt AR, Mezeivtch K, Xiao E, et al. Schizophrenia polygenic risk score predicts mnemonic hippocampal activity. Brain 2018, 141: 1218–1228.PubMedPubMedCentralCrossRef
118.
go back to reference Neilson E, Bois C, Gibson J, Duff B, Watson A, Roberts N, et al. Effects of environmental risks and polygenic loading for schizophrenia on cortical thickness. Schizophr Res 2017, 184: 128–136.PubMedCrossRef Neilson E, Bois C, Gibson J, Duff B, Watson A, Roberts N, et al. Effects of environmental risks and polygenic loading for schizophrenia on cortical thickness. Schizophr Res 2017, 184: 128–136.PubMedCrossRef
119.
go back to reference Kauppi K, Westlye LT, Tesli M, Bettella F, Brandt CL, Mattingsdal M, et al. Polygenic risk for schizophrenia associated with working memory-related prefrontal brain activation in patients with schizophrenia and healthy controls. Schizophr Bull 2015, 41: 736–743.PubMedCrossRef Kauppi K, Westlye LT, Tesli M, Bettella F, Brandt CL, Mattingsdal M, et al. Polygenic risk for schizophrenia associated with working memory-related prefrontal brain activation in patients with schizophrenia and healthy controls. Schizophr Bull 2015, 41: 736–743.PubMedCrossRef
120.
go back to reference Alnæs D, Kaufmann T, van der Meer D, Córdova-Palomera A, Rokicki J, Moberget T, et al. Brain heterogeneity in schizophrenia and its association with polygenic risk. JAMA Psychiatry 2019, 76: 739–748.PubMedPubMedCentralCrossRef Alnæs D, Kaufmann T, van der Meer D, Córdova-Palomera A, Rokicki J, Moberget T, et al. Brain heterogeneity in schizophrenia and its association with polygenic risk. JAMA Psychiatry 2019, 76: 739–748.PubMedPubMedCentralCrossRef
121.
go back to reference Stauffer EM, Bethlehem RAI, Warrier V, Murray GK, Romero-Garcia R, Seidlitz J, et al. Grey and white matter microstructure is associated with polygenic risk for schizophrenia. Mol Psychiatry 2021, 26: 7709–7718.PubMedPubMedCentralCrossRef Stauffer EM, Bethlehem RAI, Warrier V, Murray GK, Romero-Garcia R, Seidlitz J, et al. Grey and white matter microstructure is associated with polygenic risk for schizophrenia. Mol Psychiatry 2021, 26: 7709–7718.PubMedPubMedCentralCrossRef
122.
go back to reference Qi S, Sui J, Pearlson G, Bustillo J, Perrone-Bizzozero NI, Kochunov P, et al. Derivation and utility of schizophrenia polygenic risk associated multimodal MRI frontotemporal network. Nat Commun 2022, 13: 4929.PubMedPubMedCentralCrossRef Qi S, Sui J, Pearlson G, Bustillo J, Perrone-Bizzozero NI, Kochunov P, et al. Derivation and utility of schizophrenia polygenic risk associated multimodal MRI frontotemporal network. Nat Commun 2022, 13: 4929.PubMedPubMedCentralCrossRef
123.
go back to reference Liu B, Zhang X, Cui Y, Qin W, Tao Y, Li J, et al. Polygenic risk for schizophrenia influences cortical gyrification in 2 independent general populations. Schizophr Bull 2017, 43: 673–680.PubMed Liu B, Zhang X, Cui Y, Qin W, Tao Y, Li J, et al. Polygenic risk for schizophrenia influences cortical gyrification in 2 independent general populations. Schizophr Bull 2017, 43: 673–680.PubMed
124.
go back to reference Liu S, Li A, Liu Y, Li J, Wang M, Sun Y, et al. MIR137 polygenic risk is associated with schizophrenia and affects functional connectivity of the dorsolateral prefrontal cortex. Psychol Med 2020, 50: 1510–1518.PubMedCrossRef Liu S, Li A, Liu Y, Li J, Wang M, Sun Y, et al. MIR137 polygenic risk is associated with schizophrenia and affects functional connectivity of the dorsolateral prefrontal cortex. Psychol Med 2020, 50: 1510–1518.PubMedCrossRef
125.
go back to reference Liu S, Li A, Liu Y, Yan H, Wang M, Sun Y, et al. Polygenic effects of schizophrenia on hippocampal grey matter volume and hippocampus-medial prefrontal cortex functional connectivity. Br J Psychiatry 2020, 216: 267–274.PubMedCrossRef Liu S, Li A, Liu Y, Yan H, Wang M, Sun Y, et al. Polygenic effects of schizophrenia on hippocampal grey matter volume and hippocampus-medial prefrontal cortex functional connectivity. Br J Psychiatry 2020, 216: 267–274.PubMedCrossRef
126.
go back to reference Cao H, Zhou H, Cannon TD. Functional connectome-wide associations of schizophrenia polygenic risk. Mol Psychiatry 2021, 26: 2553–2561.PubMedCrossRef Cao H, Zhou H, Cannon TD. Functional connectome-wide associations of schizophrenia polygenic risk. Mol Psychiatry 2021, 26: 2553–2561.PubMedCrossRef
127.
go back to reference Franke B, Stein JL, Ripke S, Anttila V, Hibar DP, van Hulzen KJE, et al. Genetic influences on schizophrenia and subcortical brain volumes: Large-scale proof of concept. Nat Neurosci 2016, 19: 420–431.PubMedPubMedCentralCrossRef Franke B, Stein JL, Ripke S, Anttila V, Hibar DP, van Hulzen KJE, et al. Genetic influences on schizophrenia and subcortical brain volumes: Large-scale proof of concept. Nat Neurosci 2016, 19: 420–431.PubMedPubMedCentralCrossRef
128.
go back to reference Caseras X, Tansey KE, Foley S, Linden D. Association between genetic risk scoring for schizophrenia and bipolar disorder with regional subcortical volumes. Transl Psychiatry 2015, 5: e692.PubMedPubMedCentralCrossRef Caseras X, Tansey KE, Foley S, Linden D. Association between genetic risk scoring for schizophrenia and bipolar disorder with regional subcortical volumes. Transl Psychiatry 2015, 5: e692.PubMedPubMedCentralCrossRef
129.
go back to reference Grama S, Willcocks I, Hubert JJ, Pardiñas AF, Legge SE, Bracher-Smith M, et al. Polygenic risk for schizophrenia and subcortical brain anatomy in the UK Biobank cohort. Transl Psychiatry 2020, 10: 309.PubMedPubMedCentralCrossRef Grama S, Willcocks I, Hubert JJ, Pardiñas AF, Legge SE, Bracher-Smith M, et al. Polygenic risk for schizophrenia and subcortical brain anatomy in the UK Biobank cohort. Transl Psychiatry 2020, 10: 309.PubMedPubMedCentralCrossRef
130.
go back to reference van der Merwe C, Passchier R, Mufford M, Ramesar R, Dalvie S, Stein DJ. Polygenic risk for schizophrenia and associated brain structural changes: A systematic review. Compr Psychiatry 2019, 88: 77–82.PubMedCrossRef van der Merwe C, Passchier R, Mufford M, Ramesar R, Dalvie S, Stein DJ. Polygenic risk for schizophrenia and associated brain structural changes: A systematic review. Compr Psychiatry 2019, 88: 77–82.PubMedCrossRef
131.
go back to reference Burgess S, Butterworth A, Thompson SG. Mendelian randomization analysis with multiple genetic variants using summarized data. Genet Epidemiol 2013, 37: 658–665.PubMedPubMedCentralCrossRef Burgess S, Butterworth A, Thompson SG. Mendelian randomization analysis with multiple genetic variants using summarized data. Genet Epidemiol 2013, 37: 658–665.PubMedPubMedCentralCrossRef
132.
133.
go back to reference Price AL, Weale ME, Patterson N, Myers SR, Need AC, Shianna KV, et al. Long-range LD can confound genome scans in admixed populations. Am J Hum Genet 2008, 83: 132–135.PubMedPubMedCentralCrossRef Price AL, Weale ME, Patterson N, Myers SR, Need AC, Shianna KV, et al. Long-range LD can confound genome scans in admixed populations. Am J Hum Genet 2008, 83: 132–135.PubMedPubMedCentralCrossRef
134.
go back to reference Hemani G, Bowden J, Davey Smith G. Evaluating the potential role of pleiotropy in Mendelian randomization studies. Hum Mol Genet 2018, 27: R195–R208.PubMedPubMedCentralCrossRef Hemani G, Bowden J, Davey Smith G. Evaluating the potential role of pleiotropy in Mendelian randomization studies. Hum Mol Genet 2018, 27: R195–R208.PubMedPubMedCentralCrossRef
135.
go back to reference Burgess S, Daniel RM, Butterworth AS, Thompson SG, Consortium EI. Network Mendelian randomization: Using genetic variants as instrumental variables to investigate mediation in causal pathways. Int J Epidemiol 2015, 44: 484–495.CrossRef Burgess S, Daniel RM, Butterworth AS, Thompson SG, Consortium EI. Network Mendelian randomization: Using genetic variants as instrumental variables to investigate mediation in causal pathways. Int J Epidemiol 2015, 44: 484–495.CrossRef
136.
go back to reference Wendt FR, Pathak GA, Lencz T, Krystal JH, Gelernter J, Polimanti R. Multivariate genome-wide analysis of education, socioeconomic status and brain phenome. Nat Hum Behav 2021, 5: 482–496.PubMedCrossRef Wendt FR, Pathak GA, Lencz T, Krystal JH, Gelernter J, Polimanti R. Multivariate genome-wide analysis of education, socioeconomic status and brain phenome. Nat Hum Behav 2021, 5: 482–496.PubMedCrossRef
137.
go back to reference Luby J, Belden A, Botteron K, Marrus N, Harms MP, Babb C, et al. The effects of poverty on childhood brain development: The mediating effect of caregiving and stressful life events. JAMA Pediatr 2013, 167: 1135–1142.PubMedPubMedCentralCrossRef Luby J, Belden A, Botteron K, Marrus N, Harms MP, Babb C, et al. The effects of poverty on childhood brain development: The mediating effect of caregiving and stressful life events. JAMA Pediatr 2013, 167: 1135–1142.PubMedPubMedCentralCrossRef
138.
go back to reference MacKey AP, Finn AS, Leonard JA, Jacoby-Senghor DS, West MR, Gabrieli CFO, et al. Neuroanatomical correlates of the income-achievement gap. Psychol Sci 2015, 26: 925–933.PubMedCrossRef MacKey AP, Finn AS, Leonard JA, Jacoby-Senghor DS, West MR, Gabrieli CFO, et al. Neuroanatomical correlates of the income-achievement gap. Psychol Sci 2015, 26: 925–933.PubMedCrossRef
139.
go back to reference Noble KG, Houston SM, Brito NH, Bartsch H, Kan E, Kuperman JM, et al. Family income, parental education and brain structure in children and adolescents. Nat Neurosci 2015, 18: 773–778.PubMedPubMedCentralCrossRef Noble KG, Houston SM, Brito NH, Bartsch H, Kan E, Kuperman JM, et al. Family income, parental education and brain structure in children and adolescents. Nat Neurosci 2015, 18: 773–778.PubMedPubMedCentralCrossRef
140.
go back to reference Walters RK, Polimanti R, Johnson EC, McClintick JN, Adams MJ, Adkins AE, et al. Transancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders. Nat Neurosci 2018, 21: 1656–1669.PubMedPubMedCentralCrossRef Walters RK, Polimanti R, Johnson EC, McClintick JN, Adams MJ, Adkins AE, et al. Transancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders. Nat Neurosci 2018, 21: 1656–1669.PubMedPubMedCentralCrossRef
141.
go back to reference Hjorthøj C, Østergaard MLD, Benros ME, Toftdahl NG, Erlangsen A, Andersen JT, et al. Association between alcohol and substance use disorders and all-cause and cause-specific mortality in schizophrenia, bipolar disorder, and unipolar depression: A nationwide, prospective, register-based study. Lancet Psychiatry 2015, 2: 801–808.PubMedCrossRef Hjorthøj C, Østergaard MLD, Benros ME, Toftdahl NG, Erlangsen A, Andersen JT, et al. Association between alcohol and substance use disorders and all-cause and cause-specific mortality in schizophrenia, bipolar disorder, and unipolar depression: A nationwide, prospective, register-based study. Lancet Psychiatry 2015, 2: 801–808.PubMedCrossRef
142.
go back to reference Li L, Yu H, Liu Y, Meng YJ, Li XJ, Zhang C, et al. Lower regional grey matter in alcohol use disorders: Evidence from a voxel-based meta-analysis. BMC Psychiatry 2021, 21: 247.PubMedPubMedCentralCrossRef Li L, Yu H, Liu Y, Meng YJ, Li XJ, Zhang C, et al. Lower regional grey matter in alcohol use disorders: Evidence from a voxel-based meta-analysis. BMC Psychiatry 2021, 21: 247.PubMedPubMedCentralCrossRef
143.
go back to reference Jones SA, Nagel BJ. Altered frontostriatal white matter microstructure is associated with familial alcoholism and future binge drinking in adolescence. Neuropsychopharmacology 2019, 44: 1076–1083.PubMedPubMedCentralCrossRef Jones SA, Nagel BJ. Altered frontostriatal white matter microstructure is associated with familial alcoholism and future binge drinking in adolescence. Neuropsychopharmacology 2019, 44: 1076–1083.PubMedPubMedCentralCrossRef
144.
go back to reference Zahr NM, Pitel AL, Chanraud S, Sullivan EV. Contributions of studies on alcohol use disorders to understanding cerebellar function. Neuropsychol Rev 2010, 20: 280–289.PubMedPubMedCentralCrossRef Zahr NM, Pitel AL, Chanraud S, Sullivan EV. Contributions of studies on alcohol use disorders to understanding cerebellar function. Neuropsychol Rev 2010, 20: 280–289.PubMedPubMedCentralCrossRef
145.
go back to reference Gurillo P, Jauhar S, Murray RM, MacCabe JH. Does tobacco use cause psychosis? Systematic review meta-analysis. Lancet Psychiatr 2015, 2: 718–725.CrossRef Gurillo P, Jauhar S, Murray RM, MacCabe JH. Does tobacco use cause psychosis? Systematic review meta-analysis. Lancet Psychiatr 2015, 2: 718–725.CrossRef
146.
go back to reference Schneider CE, White T, Hass J, Geisler D, Wallace SR, Roessner V, et al. Smoking status as a potential confounder in the study of brain structure in schizophrenia. J Psychiatr Res 2014, 50: 84–91.PubMedCrossRef Schneider CE, White T, Hass J, Geisler D, Wallace SR, Roessner V, et al. Smoking status as a potential confounder in the study of brain structure in schizophrenia. J Psychiatr Res 2014, 50: 84–91.PubMedCrossRef
147.
go back to reference Pierce BL, Burgess S. Efficient design for Mendelian randomization studies: Subsample and 2-sample instrumental variable estimators. Am J Epidemiol 2013, 178: 1177–1184.PubMedPubMedCentralCrossRef Pierce BL, Burgess S. Efficient design for Mendelian randomization studies: Subsample and 2-sample instrumental variable estimators. Am J Epidemiol 2013, 178: 1177–1184.PubMedPubMedCentralCrossRef
148.
149.
go back to reference Guo J, Yu K, Dong SS, Yao S, Rong Y, Wu H, et al. Mendelian randomization analyses support causal relationships between brain imaging-derived phenotypes and risk of psychiatric disorders. Nat Neurosci 2022, 25: 1519–1527.PubMedCrossRef Guo J, Yu K, Dong SS, Yao S, Rong Y, Wu H, et al. Mendelian randomization analyses support causal relationships between brain imaging-derived phenotypes and risk of psychiatric disorders. Nat Neurosci 2022, 25: 1519–1527.PubMedCrossRef
150.
go back to reference Williams JA, Burgess S, Suckling J, Lalousis PA, Batool F, Griffiths SL, et al. Inflammation and brain structure in schizophrenia and other neuropsychiatric disorders: A Mendelian randomization study. JAMA Psychiatry 2022, 79: 498–507.PubMedPubMedCentralCrossRef Williams JA, Burgess S, Suckling J, Lalousis PA, Batool F, Griffiths SL, et al. Inflammation and brain structure in schizophrenia and other neuropsychiatric disorders: A Mendelian randomization study. JAMA Psychiatry 2022, 79: 498–507.PubMedPubMedCentralCrossRef
151.
go back to reference Bulik-Sullivan B, Finucane HK, Anttila V, Gusev A, Day FR, Loh PR, et al. An atlas of genetic correlations across human diseases and traits. Nat Genet 2015, 47: 1236–1241.PubMedPubMedCentralCrossRef Bulik-Sullivan B, Finucane HK, Anttila V, Gusev A, Day FR, Loh PR, et al. An atlas of genetic correlations across human diseases and traits. Nat Genet 2015, 47: 1236–1241.PubMedPubMedCentralCrossRef
152.
go back to reference Xiao Y, Yan Z, Zhao Y, Tao B, Sun H, Li F, et al. Support vector machine-based classification of first episode drug-naïve schizophrenia patients and healthy controls using structural MRI. Schizophr Res 2019, 214: 11–17.PubMedCrossRef Xiao Y, Yan Z, Zhao Y, Tao B, Sun H, Li F, et al. Support vector machine-based classification of first episode drug-naïve schizophrenia patients and healthy controls using structural MRI. Schizophr Res 2019, 214: 11–17.PubMedCrossRef
153.
go back to reference Yassin W, Nakatani H, Zhu Y, Kojima M, Owada K, Kuwabara H, et al. Machine-learning classification using neuroimaging data in schizophrenia, autism, ultra-high risk and first-episode psychosis. Transl Psychiatry 2020, 10: 278.PubMedPubMedCentralCrossRef Yassin W, Nakatani H, Zhu Y, Kojima M, Owada K, Kuwabara H, et al. Machine-learning classification using neuroimaging data in schizophrenia, autism, ultra-high risk and first-episode psychosis. Transl Psychiatry 2020, 10: 278.PubMedPubMedCentralCrossRef
154.
go back to reference Guo Y, Qiu J, Lu W. Support vector machine-based schizophrenia classification using morphological information from amygdaloid and hippocampal subregions. Brain Sci 2020, 10: 562.PubMedPubMedCentralCrossRef Guo Y, Qiu J, Lu W. Support vector machine-based schizophrenia classification using morphological information from amygdaloid and hippocampal subregions. Brain Sci 2020, 10: 562.PubMedPubMedCentralCrossRef
155.
go back to reference Koutsouleris N, Riecher-Rössler A, Meisenzahl EM, Smieskova R, Studerus E, Kambeitz-Ilankovic L, et al. Detecting the psychosis prodrome across high-risk populations using neuroanatomical biomarkers. Schizophr Bull 2015, 41: 471–482.PubMedCrossRef Koutsouleris N, Riecher-Rössler A, Meisenzahl EM, Smieskova R, Studerus E, Kambeitz-Ilankovic L, et al. Detecting the psychosis prodrome across high-risk populations using neuroanatomical biomarkers. Schizophr Bull 2015, 41: 471–482.PubMedCrossRef
156.
go back to reference Zang J, Huang Y, Kong L, Lei B, Ke P, Li H, et al. Effects of brain atlases and machine learning methods on the discrimination of schizophrenia patients: A multimodal MRI study. Front Neurosci 2021, 15: 697168.PubMedPubMedCentralCrossRef Zang J, Huang Y, Kong L, Lei B, Ke P, Li H, et al. Effects of brain atlases and machine learning methods on the discrimination of schizophrenia patients: A multimodal MRI study. Front Neurosci 2021, 15: 697168.PubMedPubMedCentralCrossRef
157.
go back to reference Ardekani BA, Tabesh A, Sevy S, Robinson DG, Bilder RM, Szeszko PR. Diffusion tensor imaging reliably differentiates patients with schizophrenia from healthy volunteers. Hum Brain Mapp 2011, 32: 1–9.PubMedCrossRef Ardekani BA, Tabesh A, Sevy S, Robinson DG, Bilder RM, Szeszko PR. Diffusion tensor imaging reliably differentiates patients with schizophrenia from healthy volunteers. Hum Brain Mapp 2011, 32: 1–9.PubMedCrossRef
158.
go back to reference Zhu Y, Nakatani H, Yassin W, Maikusa N, Okada N, Kunimatsu A, et al. Application of a machine learning algorithm for structural brain images in chronic schizophrenia to earlier clinical stages of psychosis and autism spectrum disorder: A multiprotocol imaging dataset study. Schizophr Bull 2022, 48: 563–574.PubMedPubMedCentralCrossRef Zhu Y, Nakatani H, Yassin W, Maikusa N, Okada N, Kunimatsu A, et al. Application of a machine learning algorithm for structural brain images in chronic schizophrenia to earlier clinical stages of psychosis and autism spectrum disorder: A multiprotocol imaging dataset study. Schizophr Bull 2022, 48: 563–574.PubMedPubMedCentralCrossRef
159.
go back to reference Sun H, Lui S, Yao L, Deng W, Xiao Y, Zhang W, et al. Two patterns of white matter abnormalities in medication-naive patients with first-episode schizophrenia revealed by diffusion tensor imaging and cluster analysis. JAMA Psychiatry 2015, 72: 678–686.PubMedCrossRef Sun H, Lui S, Yao L, Deng W, Xiao Y, Zhang W, et al. Two patterns of white matter abnormalities in medication-naive patients with first-episode schizophrenia revealed by diffusion tensor imaging and cluster analysis. JAMA Psychiatry 2015, 72: 678–686.PubMedCrossRef
160.
go back to reference Cao B, Cho RY, Chen D, Xiu M, Wang L, Soares JC, et al. Treatment response prediction and individualized identification of first-episode drug-naïve schizophrenia using brain functional connectivity. Mol Psychiatry 2020, 25: 906–913.PubMedCrossRef Cao B, Cho RY, Chen D, Xiu M, Wang L, Soares JC, et al. Treatment response prediction and individualized identification of first-episode drug-naïve schizophrenia using brain functional connectivity. Mol Psychiatry 2020, 25: 906–913.PubMedCrossRef
161.
go back to reference Winterburn JL, Voineskos AN, Devenyi GA, Plitman E, de la Fuente-Sandoval C, Bhagwat N, et al. Can we accurately classify schizophrenia patients from healthy controls using magnetic resonance imaging and machine learning? A multi-method and multi-dataset study. Schizophr Res 2019, 214: 3–10.PubMedCrossRef Winterburn JL, Voineskos AN, Devenyi GA, Plitman E, de la Fuente-Sandoval C, Bhagwat N, et al. Can we accurately classify schizophrenia patients from healthy controls using magnetic resonance imaging and machine learning? A multi-method and multi-dataset study. Schizophr Res 2019, 214: 3–10.PubMedCrossRef
162.
go back to reference Keshavan MS, Collin G, Guimond S, Kelly S, Prasad KM, Lizano P. Neuroimaging in schizophrenia. Neuroimaging Clin N Am 2020, 30: 73–83.PubMedCrossRef Keshavan MS, Collin G, Guimond S, Kelly S, Prasad KM, Lizano P. Neuroimaging in schizophrenia. Neuroimaging Clin N Am 2020, 30: 73–83.PubMedCrossRef
163.
go back to reference Shi D, Li Y, Zhang H, Yao X, Wang S, Wang G, et al. Machine learning of schizophrenia detection with structural and functional neuroimaging. Dis Markers 2021, 2021: 9963824.PubMedPubMedCentralCrossRef Shi D, Li Y, Zhang H, Yao X, Wang S, Wang G, et al. Machine learning of schizophrenia detection with structural and functional neuroimaging. Dis Markers 2021, 2021: 9963824.PubMedPubMedCentralCrossRef
164.
go back to reference Kambeitz J, Kambeitz-Ilankovic L, Leucht S, Wood S, Davatzikos C, Malchow B, et al. Detecting neuroimaging biomarkers for schizophrenia: A meta-analysis of multivariate pattern recognition studies. Neuropsychopharmacology 2015, 40: 1742–1751.PubMedPubMedCentralCrossRef Kambeitz J, Kambeitz-Ilankovic L, Leucht S, Wood S, Davatzikos C, Malchow B, et al. Detecting neuroimaging biomarkers for schizophrenia: A meta-analysis of multivariate pattern recognition studies. Neuropsychopharmacology 2015, 40: 1742–1751.PubMedPubMedCentralCrossRef
165.
go back to reference Kraguljac NV, McDonald WM, Widge AS, Rodriguez CI, Tohen M, Nemeroff CB. Neuroimaging biomarkers in schizophrenia. Am J Psychiatry 2021, 178: 509–521.PubMedPubMedCentralCrossRef Kraguljac NV, McDonald WM, Widge AS, Rodriguez CI, Tohen M, Nemeroff CB. Neuroimaging biomarkers in schizophrenia. Am J Psychiatry 2021, 178: 509–521.PubMedPubMedCentralCrossRef
166.
go back to reference Goldsmith DR, Crooks CL, Walker EF, Cotes RO. An update on promising biomarkers in schizophrenia. Focus (Am Psychiatr Publ) 2018, 16: 153–163.PubMed Goldsmith DR, Crooks CL, Walker EF, Cotes RO. An update on promising biomarkers in schizophrenia. Focus (Am Psychiatr Publ) 2018, 16: 153–163.PubMed
167.
go back to reference Sarpal DK, Argyelan M, Robinson DG, Szeszko PR, Karlsgodt KH, John M, et al. Baseline striatal functional connectivity as a predictor of response to antipsychotic drug treatment. Am J Psychiatry 2016, 173: 69–77.PubMedCrossRef Sarpal DK, Argyelan M, Robinson DG, Szeszko PR, Karlsgodt KH, John M, et al. Baseline striatal functional connectivity as a predictor of response to antipsychotic drug treatment. Am J Psychiatry 2016, 173: 69–77.PubMedCrossRef
168.
go back to reference Blessing EM, Murty VP, Zeng B, Wang J, Davachi L, Goff DC. Anterior hippocampal-cortical functional connectivity distinguishes antipsychotic Naïve first-episode psychosis patients from controls and may predict response to second-generation antipsychotic treatment. Schizophr Bull 2020, 46: 680–689.PubMedCrossRef Blessing EM, Murty VP, Zeng B, Wang J, Davachi L, Goff DC. Anterior hippocampal-cortical functional connectivity distinguishes antipsychotic Naïve first-episode psychosis patients from controls and may predict response to second-generation antipsychotic treatment. Schizophr Bull 2020, 46: 680–689.PubMedCrossRef
169.
go back to reference Svancer P, Spaniel F. Brain ventricular volume changes in schizophrenia. A narrative review. Neurosci Lett 2021, 759: 136065.PubMedCrossRef Svancer P, Spaniel F. Brain ventricular volume changes in schizophrenia. A narrative review. Neurosci Lett 2021, 759: 136065.PubMedCrossRef
170.
go back to reference Ebdrup BH, Glenthøj B, Rasmussen H, Aggernaes B, Langkilde AR, Paulson OB, et al. Hippocampal and caudate volume reductions in antipsychotic-naive first-episode schizophrenia. J Psychiatry Neurosci 2010, 35: 95–104.PubMedPubMedCentralCrossRef Ebdrup BH, Glenthøj B, Rasmussen H, Aggernaes B, Langkilde AR, Paulson OB, et al. Hippocampal and caudate volume reductions in antipsychotic-naive first-episode schizophrenia. J Psychiatry Neurosci 2010, 35: 95–104.PubMedPubMedCentralCrossRef
171.
go back to reference Smucny J, Dienel SJ, Lewis DA, Carter CS. Mechanisms underlying dorsolateral prefrontal cortex contributions to cognitive dysfunction in schizophrenia. Neuropsychopharmacology 2022, 47: 292–308.PubMedCrossRef Smucny J, Dienel SJ, Lewis DA, Carter CS. Mechanisms underlying dorsolateral prefrontal cortex contributions to cognitive dysfunction in schizophrenia. Neuropsychopharmacology 2022, 47: 292–308.PubMedCrossRef
172.
go back to reference Jiang JB, Cao Y, An NY, Yang Q, Cui LB. Magnetic resonance imaging-based connectomics in first-episode schizophrenia: From preclinical study to clinical translation. Front Psychiatry 2020, 11: 565056.PubMedPubMedCentralCrossRef Jiang JB, Cao Y, An NY, Yang Q, Cui LB. Magnetic resonance imaging-based connectomics in first-episode schizophrenia: From preclinical study to clinical translation. Front Psychiatry 2020, 11: 565056.PubMedPubMedCentralCrossRef
173.
go back to reference 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: 100.PubMedPubMedCentralCrossRef 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: 100.PubMedPubMedCentralCrossRef
174.
175.
go back to reference Okada N, Fukunaga M, Yamashita F, Koshiyama D, Yamamori H, Ohi K, et al. Abnormal asymmetries in subcortical brain volume in schizophrenia. Mol Psychiatry 2016, 21: 1460–1466.PubMedPubMedCentralCrossRef Okada N, Fukunaga M, Yamashita F, Koshiyama D, Yamamori H, Ohi K, et al. Abnormal asymmetries in subcortical brain volume in schizophrenia. Mol Psychiatry 2016, 21: 1460–1466.PubMedPubMedCentralCrossRef
176.
go back to reference Koutsouleris N, Dwyer DB, Degenhardt F, Maj C, Urquijo-Castro MF, Sanfelici R, et al. Multimodal machine learning workflows for prediction of psychosis in patients with clinical high-risk syndromes and recent-onset depression. JAMA Psychiatry 2021, 78: 195–209.PubMedCrossRef Koutsouleris N, Dwyer DB, Degenhardt F, Maj C, Urquijo-Castro MF, Sanfelici R, et al. Multimodal machine learning workflows for prediction of psychosis in patients with clinical high-risk syndromes and recent-onset depression. JAMA Psychiatry 2021, 78: 195–209.PubMedCrossRef
177.
go back to reference Bodnar M, Harvey PO, Malla AK, Joober R, Lepage M. The parahippocampal gyrus as a neural marker of early remission in first-episode psychosis: A voxel-based morphometry study. Clin Schizophr Relat Psychoses 2011, 4: 217–228.PubMedCrossRef Bodnar M, Harvey PO, Malla AK, Joober R, Lepage M. The parahippocampal gyrus as a neural marker of early remission in first-episode psychosis: A voxel-based morphometry study. Clin Schizophr Relat Psychoses 2011, 4: 217–228.PubMedCrossRef
178.
go back to reference Takayanagi Y, Sasabayashi D, Takahashi T, Furuichi A, Kido M, Nishikawa Y, et al. Reduced cortical thickness in schizophrenia and schizotypal disorder. Schizophr Bull 2020, 46: 387–394.PubMed Takayanagi Y, Sasabayashi D, Takahashi T, Furuichi A, Kido M, Nishikawa Y, et al. Reduced cortical thickness in schizophrenia and schizotypal disorder. Schizophr Bull 2020, 46: 387–394.PubMed
179.
go back to reference Wible CG, Anderson J, Shenton ME, Kricun A, Hirayasu Y, Tanaka S, et al. Prefrontal cortex, negative symptoms, and schizophrenia: An MRI study. Psychiatry Res 2001, 108: 65–78.PubMedPubMedCentralCrossRef Wible CG, Anderson J, Shenton ME, Kricun A, Hirayasu Y, Tanaka S, et al. Prefrontal cortex, negative symptoms, and schizophrenia: An MRI study. Psychiatry Res 2001, 108: 65–78.PubMedPubMedCentralCrossRef
180.
go back to reference Kyriakopoulos M, Dima D, Roiser JP, Corrigall R, Barker GJ, Frangou S. Abnormal functional activation and connectivity in the working memory network in early-onset schizophrenia. J Am Acad Child Adolesc Psychiatry 2012, 51: 911-920.e2.PubMedCrossRef Kyriakopoulos M, Dima D, Roiser JP, Corrigall R, Barker GJ, Frangou S. Abnormal functional activation and connectivity in the working memory network in early-onset schizophrenia. J Am Acad Child Adolesc Psychiatry 2012, 51: 911-920.e2.PubMedCrossRef
181.
go back to reference Stoyanov D, Aryutova K, Kandilarova S, Paunova R, Arabadzhiev Z, Todeva-Radneva A, et al. Diagnostic task specific activations in functional MRI and aberrant connectivity of Insula with middle frontal gyrus can inform the differential diagnosis of psychosis. Diagnostics 2021, 11: 95.PubMedPubMedCentralCrossRef Stoyanov D, Aryutova K, Kandilarova S, Paunova R, Arabadzhiev Z, Todeva-Radneva A, et al. Diagnostic task specific activations in functional MRI and aberrant connectivity of Insula with middle frontal gyrus can inform the differential diagnosis of psychosis. Diagnostics 2021, 11: 95.PubMedPubMedCentralCrossRef
182.
go back to reference Nielsen MØ, Rostrup E, Wulff S, Glenthøj B, Ebdrup BH. Striatal reward activity and antipsychotic-associated weight change in patients with schizophrenia undergoing initial treatment. JAMA Psychiatry 2016, 73: 121–128.PubMedCrossRef Nielsen MØ, Rostrup E, Wulff S, Glenthøj B, Ebdrup BH. Striatal reward activity and antipsychotic-associated weight change in patients with schizophrenia undergoing initial treatment. JAMA Psychiatry 2016, 73: 121–128.PubMedCrossRef
183.
go back to reference Homan P, Argyelan M, Fales CL, Barber AD, DeRosse P, Szeszko PR, et al. Striatal volume and functional connectivity correlate with weight gain in early-phase psychosis. Neuropsychopharmacology 2019, 44: 1948–1954.PubMedPubMedCentralCrossRef Homan P, Argyelan M, Fales CL, Barber AD, DeRosse P, Szeszko PR, et al. Striatal volume and functional connectivity correlate with weight gain in early-phase psychosis. Neuropsychopharmacology 2019, 44: 1948–1954.PubMedPubMedCentralCrossRef
184.
go back to reference Harvey PD. Mood symptoms, cognition, and everyday functioning: In major depression, bipolar disorder, and schizophrenia. Innov Clin Neurosci 2011, 8: 14–18.PubMedPubMedCentral Harvey PD. Mood symptoms, cognition, and everyday functioning: In major depression, bipolar disorder, and schizophrenia. Innov Clin Neurosci 2011, 8: 14–18.PubMedPubMedCentral
185.
go back to reference Duff BJ, MacRitchie KAN, Moorhead TWJ, Lawrie SM, Blackwood DHR. Human brain imaging studies of DISC1 in schizophrenia, bipolar disorder and depression: A systematic review. Schizophr Res 2013, 147: 1–13.PubMedCrossRef Duff BJ, MacRitchie KAN, Moorhead TWJ, Lawrie SM, Blackwood DHR. Human brain imaging studies of DISC1 in schizophrenia, bipolar disorder and depression: A systematic review. Schizophr Res 2013, 147: 1–13.PubMedCrossRef
186.
go back to reference Kempton MJ, Salvador Z, Munafò MR, Geddes JR, Simmons A, Frangou S, et al. Structural neuroimaging studies in major depressive disorder. Meta-analysis and comparison with bipolar disorder. Arch Gen Psychiatry 2011, 68: 675–690. Kempton MJ, Salvador Z, Munafò MR, Geddes JR, Simmons A, Frangou S, et al. Structural neuroimaging studies in major depressive disorder. Meta-analysis and comparison with bipolar disorder. Arch Gen Psychiatry 2011, 68: 675–690.
187.
go back to reference Schmaal L, Pozzi E, Ho TC, van Velzen LS, Veer IM, Opel N, et al. ENIGMA MDD: Seven years of global neuroimaging studies of major depression through worldwide data sharing. Transl Psychiatry 2020, 10: 172.PubMedPubMedCentralCrossRef Schmaal L, Pozzi E, Ho TC, van Velzen LS, Veer IM, Opel N, et al. ENIGMA MDD: Seven years of global neuroimaging studies of major depression through worldwide data sharing. Transl Psychiatry 2020, 10: 172.PubMedPubMedCentralCrossRef
188.
go back to reference Ho NF, Chong PLH, Lee DR, Chew QH, Chen G, Sim K. The amygdala in schizophrenia and bipolar disorder: A synthesis of structural MRI, diffusion tensor imaging, and resting-state functional connectivity findings. Harv Rev Psychiatry 2019, 27: 150–164.PubMedCrossRef Ho NF, Chong PLH, Lee DR, Chew QH, Chen G, Sim K. The amygdala in schizophrenia and bipolar disorder: A synthesis of structural MRI, diffusion tensor imaging, and resting-state functional connectivity findings. Harv Rev Psychiatry 2019, 27: 150–164.PubMedCrossRef
189.
go back to reference Botvinik-Nezer R, Holzmeister F, Camerer CF, Dreber A, Huber J, Johannesson M, et al. Variability in the analysis of a single neuroimaging dataset by many teams. Nature 2020, 582: 84–88.PubMedPubMedCentralCrossRef Botvinik-Nezer R, Holzmeister F, Camerer CF, Dreber A, Huber J, Johannesson M, et al. Variability in the analysis of a single neuroimaging dataset by many teams. Nature 2020, 582: 84–88.PubMedPubMedCentralCrossRef
190.
go back to reference McCutcheon RA, Reis Marques T, Howes OD. Schizophrenia-an overview. JAMA. Psychiatry 2020, 77: 201–210. McCutcheon RA, Reis Marques T, Howes OD. Schizophrenia-an overview. JAMA. Psychiatry 2020, 77: 201–210.
192.
go back to reference van den Heuvel MP, Scholtens LH, de Reus MA, Kahn RS. Associated microscale spine density and macroscale connectivity disruptions in schizophrenia. Biol Psychiatry 2016, 80: 293–301.PubMedCrossRef van den Heuvel MP, Scholtens LH, de Reus MA, Kahn RS. Associated microscale spine density and macroscale connectivity disruptions in schizophrenia. Biol Psychiatry 2016, 80: 293–301.PubMedCrossRef
193.
go back to reference Price AJ, Jaffe AE, Weinberger DR. Cortical cellular diversity and development in schizophrenia. Mol Psychiatry 2021, 26: 203–217.PubMedCrossRef Price AJ, Jaffe AE, Weinberger DR. Cortical cellular diversity and development in schizophrenia. Mol Psychiatry 2021, 26: 203–217.PubMedCrossRef
194.
go back to reference Wang M, Yan H, Tian X, Yue W, Liu Y, Fan L, et al. Neuroimaging and multiomics reveal cross-scale circuit abnormalities in schizophrenia. Nat Ment Health 2023, 1: 633–654.CrossRef Wang M, Yan H, Tian X, Yue W, Liu Y, Fan L, et al. Neuroimaging and multiomics reveal cross-scale circuit abnormalities in schizophrenia. Nat Ment Health 2023, 1: 633–654.CrossRef
195.
go back to reference Whiting D, Gulati G, Geddes JR, Fazel S. Association of schizophrenia spectrum disorders and violence perpetration in adults and adolescents from 15 countries: A systematic review and meta-analysis. JAMA Psychiatry 2022, 79: 120–132.PubMedCrossRef Whiting D, Gulati G, Geddes JR, Fazel S. Association of schizophrenia spectrum disorders and violence perpetration in adults and adolescents from 15 countries: A systematic review and meta-analysis. JAMA Psychiatry 2022, 79: 120–132.PubMedCrossRef
196.
go back to reference Olfson M, Stroup TS, Huang C, Wall MM, Crystal S, Gerhard T. Suicide risk in medicare patients with schizophrenia across the life span. JAMA Psychiatry 2021, 78: 876–885.PubMedCrossRef Olfson M, Stroup TS, Huang C, Wall MM, Crystal S, Gerhard T. Suicide risk in medicare patients with schizophrenia across the life span. JAMA Psychiatry 2021, 78: 876–885.PubMedCrossRef
197.
go back to reference Widmayer S, Borgwardt S, Lang UE, Stieglitz RD, Huber CG. Functional neuroimaging correlates of aggression in psychosis: A systematic review with recommendations for future research. Front Psychiatry 2018, 9: 777.PubMedCrossRef Widmayer S, Borgwardt S, Lang UE, Stieglitz RD, Huber CG. Functional neuroimaging correlates of aggression in psychosis: A systematic review with recommendations for future research. Front Psychiatry 2018, 9: 777.PubMedCrossRef
Metadata
Title
Unveiling Promising Neuroimaging Biomarkers for Schizophrenia Through Clinical and Genetic Perspectives
Authors
Jing Guo
Changyi He
Huimiao Song
Huiwu Gao
Shi Yao
Shan-Shan Dong
Tie-Lin Yang
Publication date
04-05-2024
Publisher
Springer Nature Singapore
Published in
Neuroscience Bulletin
Print ISSN: 1673-7067
Electronic ISSN: 1995-8218
DOI
https://doi.org/10.1007/s12264-024-01214-1