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

Author:

Dimitriadis S I1234ORCID,Perry G2ORCID,Lancaster T M125ORCID,Tansey K E6ORCID,Singh K D2ORCID,Holmans P3ORCID,Pocklington A3ORCID,Davey Smith G67ORCID,Zammit S37ORCID,Hall J13ORCID,O’Donovan M C13ORCID,Owen M J13ORCID,Jones D K2ORCID,Linden D E12378ORCID

Affiliation:

1. Neuroscience and Mental Health Research Institute (NMHI) , College of Biomedical and Life Sciences, Cardiff University, Maindy Road CF24 4HQ, Cardiff, Wales, UK

2. Cardiff University Brain Research Imaging Centre (CUBRIC) , School of Psychology, College of Biomedical and Life Sciences, Cardiff University, Maindy Road CF24 4HQ, Cardiff, Wales, UK

3. Division of Psychological Medicine and Clinical Neurosciences , MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff School of Medicine, Cardiff University, Maindy Road CF24 4HQ, Cardiff, Wales, UK

4. Neuroinformatics Group , School of Psychology, College of Biomedical and Life Sciences, Cardiff University, Maindy Road CF24 4HQ, Cardiff, Wales, UK

5. Department of Psychology , Bath University, Claverton Down BA2 7AY, Bath, Wales, UK

6. MRC Integrative Epidemiology Unit (IEU) , University of Bristol, Queens Road BS8 1QU, Bristol, Wales, UK

7. Population Health Sciences , Bristol Medical School, University of Bristol, 1-5 Whiteladies Road BS8 1NU, Bristol, Wales, UK

8. School for Mental Health and Neuroscience , Faculty of Health, Medicine and Life Sciences, Maastricht University, Universiteitssingel 40 UNS40 6229 ER, Maastricht, The Netherlands

Abstract

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.

Funder

Medical Research Council

Wellcome Trust New Investigator Award

Wellcome Trust Strategic Award

Wellcome Trust

Publisher

Oxford University Press (OUP)

Subject

Cellular and Molecular Neuroscience,Cognitive Neuroscience

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