Genetic risk for schizophrenia is associated with increased proportion of indirect connections in brain networks revealed by a semi-metric analysis: evidence from population sample stratified for polygenic risk

S. I. Dimitriadis; G. Perry; T. M. Lancaster; K. E. Tansey; K. D. Singh; P. Holmans; A. Pocklington; G. Davey Smith; S. Zammit; J. Hall; M. C. O'Donovan; M. J. Owen; D. K. Jones; D. E. Linden

doi:10.1093/cercor/bhac256

Genetic risk for schizophrenia is associated with increased proportion of indirect connections in brain networks revealed by a semi-metric analysis: evidence from population sample stratified for polygenic risk

S. I. Dimitriadis, G. Perry, T. M. Lancaster, K. E. Tansey, K. D. Singh, P. Holmans, A. Pocklington, G. Davey Smith, S. Zammit, J. Hall, M. C. O'Donovan, M. J. Owen, D. K. Jones, D. E. Linden

Research output: Contribution to journal › Article › peer-review

2 Citations (SciVal)

Abstract

Research studies based on tractography have revealed a prominent reduction of asymmetry in some key white-matter tracts in schizophrenia (SCZ). However, we know little about the influence of common genetic risk factors for SCZ on the efficiency of routing on structural brain networks (SBNs). Here, we use a novel recall-by-genotype approach, where we sample young adults from a population-based cohort (ALSPAC:N genotyped = 8,365) based on their burden of common SCZ risk alleles as defined by polygenic risk score (PRS). We compared 181 individuals at extremes of low (N = 91) or high (N = 90) SCZ-PRS under a robust diffusion MRI-based graph theoretical SBN framework. We applied a semi-metric analysis revealing higher SMR values for the high SCZ-PRS group compared with the low SCZ-PRS group in the left hemisphere. Furthermore, a hemispheric asymmetry index showed a higher leftward preponderance of indirect connections for the high SCZ-PRS group compared with the low SCZ-PRS group (PFDR < 0.05). These findings might indicate less efficient structural connectivity in the higher genetic risk group. This is the first study in a population-based sample that reveals differences in the efficiency of SBNs associated with common genetic risk variants for SCZ.

Original language	English
Pages (from-to)	2997-3011
Number of pages	15
Journal	Cerebral cortex (New York, N.Y. : 1991)
Volume	33
Issue number	6
Early online date	14 Jul 2022
DOIs	https://doi.org/10.1093/cercor/bhac256
Publication status	Published - 15 Mar 2023

Bibliographical note

This research was funded explicitly by MRC grant MR/K004360/1( Behavioral and Neurophysiological Effects of Schizophrenia Risk Genes: A Multi-locus, Pathway Based Approach). A MARIE-CURIE COFUND EU-UK Research Fellowship also supported SID. DKJ is supported by a Wellcome Trust New Investigator Award (096646/Z/11/Z) and Wellcome Trust Strategic Award (104943/Z/14/Z).MJO, JH, DKJ, and DEL were supported by the Wellcome Trust Strategic Award’ Defining endopheno types from integrative neuroscience’(DEFINE). SZ is supported by the NIHR Biomedical Research Centre at University Hospitals Bristol N.H.S. Foundation Trust and the University of Bristol. We would like to thank Professor George Davey Smith and Professor Andrew Pocklington for their careful proof reading, their thoughtful comments based on their expertise that finally improved and shaped the final paper. This research was funded in part, by the Wellcome Trust (096646/Z/11/Z,104943/Z/14/Z). For the purpose of open access, the author has applied a CCBY public copyright license (where permitted by UKRI, “Open Government License” or “CC BY-ND public copyright license” may be stated instead) to any Author Accepted Manuscript version arising

Funding

This research was funded explicitly by MRC grant MR/K004360/1 (Behavioral and Neurophysiological Effects of Schizophrenia Risk Genes: A Multi-locus, Pathway Based Approach). A MARIE-CURIE COFUND EU-UK Research Fellowship also supported SID. DKJ is supported by a Wellcome Trust New Investigator Award (096646/Z/11/Z) and Wellcome Trust Strategic Award (104943/Z/14/Z). MJO, JH, DKJ, and DEL were supported by the Wellcome Trust Strategic Award' Defining endophenotypes from integrative neuroscience' (DEFINE). SZ is supported by the NIHR Biomedical Research Centre at University Hospitals Bristol N.H.S. Foundation Trust and the University of Bristol. We would like to thank Professor George Davey Smith and Professor Andrew Pocklington for their careful proofreading, their thoughtful comments based on their expertise that finally improved and shaped the final paper. This research was funded in part, by the Wellcome Trust (096646/Z/11/Z, 104943/Z/14/Z). For the purpose of open access, the author has applied a CC BY public copyright license (where permitted by UKRI, “Open Government License” or “CC BY-ND public copyright license” may be stated instead) to any Author Accepted Manuscript version arising. We are extremely grateful to all the families who took part in this study, the midwives for their help in recruiting them, and the whole ALSPAC team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists, and nurses. The UK Medical Research Council and Wellcome (Grant ref: 217065/Z/19/Z) and the University of Bristol provide core support for ALSPAC. This publication is the authors' work and will serve as guarantors for the contents of this paper. A comprehensive list of grants funding is available on the ALSPAC website ( http://www.bristol.ac.uk/alspac/external/documents/grant-acknowledgements.pdf ).

Keywords

Avon Longitudinal Study of Parents and Children (ALSPAC)
brain connectomics
diffusion magnetic resonance imaging (dMRI)
genetic risk for schizophrenia
schizophrenia
semi-metric percentage
structural brain networks
tractography

ASJC Scopus subject areas

Cognitive Neuroscience
Cellular and Molecular Neuroscience

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Dimitriadis, S. I., Perry, G., Lancaster, T. M., Tansey, K. E., Singh, K. D., Holmans, P., Pocklington, A., Davey Smith, G., Zammit, S., Hall, J., O'Donovan, M. C., Owen, M. J., Jones, D. K., & Linden, D. E. (2023). Genetic risk for schizophrenia is associated with increased proportion of indirect connections in brain networks revealed by a semi-metric analysis: evidence from population sample stratified for polygenic risk. Cerebral cortex (New York, N.Y. : 1991), 33(6), 2997-3011. https://doi.org/10.1093/cercor/bhac256

Genetic risk for schizophrenia is associated with increased proportion of indirect connections in brain networks revealed by a semi-metric analysis: evidence from population sample stratified for polygenic risk. / Dimitriadis, S. I.; Perry, G.; Lancaster, T. M. et al.
In: Cerebral cortex (New York, N.Y. : 1991), Vol. 33, No. 6, 15.03.2023, p. 2997-3011.

Research output: Contribution to journal › Article › peer-review

Dimitriadis, SI, Perry, G, Lancaster, TM, Tansey, KE, Singh, KD, Holmans, P, Pocklington, A, Davey Smith, G, Zammit, S, Hall, J, O'Donovan, MC, Owen, MJ, Jones, DK & Linden, DE 2023, 'Genetic risk for schizophrenia is associated with increased proportion of indirect connections in brain networks revealed by a semi-metric analysis: evidence from population sample stratified for polygenic risk', Cerebral cortex (New York, N.Y. : 1991), vol. 33, no. 6, pp. 2997-3011. https://doi.org/10.1093/cercor/bhac256

Dimitriadis SI, Perry G, Lancaster TM, Tansey KE, Singh KD, Holmans P et al. Genetic risk for schizophrenia is associated with increased proportion of indirect connections in brain networks revealed by a semi-metric analysis: evidence from population sample stratified for polygenic risk. Cerebral cortex (New York, N.Y. : 1991). 2023 Mar 15;33(6):2997-3011. Epub 2022 Jul 14. doi: 10.1093/cercor/bhac256

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title = "Genetic risk for schizophrenia is associated with increased proportion of indirect connections in brain networks revealed by a semi-metric analysis: evidence from population sample stratified for polygenic risk",

abstract = "Research studies based on tractography have revealed a prominent reduction of asymmetry in some key white-matter tracts in schizophrenia (SCZ). However, we know little about the influence of common genetic risk factors for SCZ on the efficiency of routing on structural brain networks (SBNs). Here, we use a novel recall-by-genotype approach, where we sample young adults from a population-based cohort (ALSPAC:N genotyped = 8,365) based on their burden of common SCZ risk alleles as defined by polygenic risk score (PRS). We compared 181 individuals at extremes of low (N = 91) or high (N = 90) SCZ-PRS under a robust diffusion MRI-based graph theoretical SBN framework. We applied a semi-metric analysis revealing higher SMR values for the high SCZ-PRS group compared with the low SCZ-PRS group in the left hemisphere. Furthermore, a hemispheric asymmetry index showed a higher leftward preponderance of indirect connections for the high SCZ-PRS group compared with the low SCZ-PRS group (PFDR < 0.05). These findings might indicate less efficient structural connectivity in the higher genetic risk group. This is the first study in a population-based sample that reveals differences in the efficiency of SBNs associated with common genetic risk variants for SCZ.",

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note = "This research was funded explicitly by MRC grant MR/K004360/1( Behavioral and Neurophysiological Effects of Schizophrenia Risk Genes: A Multi-locus, Pathway Based Approach). A MARIE-CURIE COFUND EU-UK Research Fellowship also supported SID. DKJ is supported by a Wellcome Trust New Investigator Award (096646/Z/11/Z) and Wellcome Trust Strategic Award (104943/Z/14/Z).MJO, JH, DKJ, and DEL were supported by the Wellcome Trust Strategic Award{\textquoteright} Defining endopheno types from integrative neuroscience{\textquoteright}(DEFINE). SZ is supported by the NIHR Biomedical Research Centre at University Hospitals Bristol N.H.S. Foundation Trust and the University of Bristol. We would like to thank Professor George Davey Smith and Professor Andrew Pocklington for their careful proof reading, their thoughtful comments based on their expertise that finally improved and shaped the final paper. This research was funded in part, by the Wellcome Trust (096646/Z/11/Z,104943/Z/14/Z). For the purpose of open access, the author has applied a CCBY public copyright license (where permitted by UKRI, “Open Government License” or “CC BY-ND public copyright license” may be stated instead) to any Author Accepted Manuscript version arising",

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AU - Lancaster, T. M.

AU - Tansey, K. E.

AU - Singh, K. D.

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Genetic risk for schizophrenia is associated with increased proportion of indirect connections in brain networks revealed by a semi-metric analysis: evidence from population sample stratified for polygenic risk

Abstract

Bibliographical note

Funding

Keywords

ASJC Scopus subject areas

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