Abstract
Schizophrenia (SCZ) is associated with structural brain changes, with considerable variation in the extent to which these cortical regions are influenced. We present a novel metric that summarises individual structural variation across the brain, while considering prior effect sizes, established via meta-analysis. We determine individual participant deviation from a within-sample-norm across structural MRI regions of interest (ROIs). For each participant, we weight the normalised deviation of each ROI by the effect size (Cohen's d) of the difference between SCZ/control for the corresponding ROI from the SCZ Enhancing Neuroimaging Genomics through Meta-Analysis working group. We generate a morphometric risk score (MRS) representing the average of these weighted deviations. We investigate if SCZ-MRS is elevated in a SCZ case/control sample (NCASE = 50; NCONTROL = 125), a replication sample (NCASE = 23; NCONTROL = 20) and a sample of asymptomatic young adults with extreme SCZ polygenic risk (NHIGH-SCZ-PRS = 95; NLOW-SCZ-PRS = 94). SCZ cases had higher SCZ-MRS than healthy controls in both samples (Study 1: β = 0.62, P < 0.001; Study 2: β = 0.81, P = 0.018). The high liability SCZ-PRS group also had a higher SCZ-MRS (Study 3: β = 0.29, P = 0.044). Furthermore, the SCZ-MRS was uniquely associated with SCZ status, but not attention-deficit hyperactivity disorder (ADHD), whereas an ADHD-MRS was linked to ADHD status, but not SCZ. This approach provides a promising solution when considering individual heterogeneity in SCZ-related brain alterations by identifying individual's patterns of structural brain-wide alterations.
Original language | English |
---|---|
Pages (from-to) | 524-532 |
Number of pages | 9 |
Journal | Schizophrenia Bulletin |
Volume | 48 |
Issue number | 2 |
Early online date | 18 Oct 2021 |
DOIs | |
Publication status | Published - 31 Mar 2022 |
Bibliographical note
Funding: This work was supported by grant MR/K004360/1 from the Medical Research Council: “Behavioural and neurophysiological effects of schizophrenia risk genes: a multi-locus, pathway-based approach”, we also grateful to co-investigators (Dr Tansey, Professor Derek Jones, Professor Krish Singh, Professor Peter Holmans, Dr Andrew Pocklington, Professor George Davey-Smith, Professor Jeremy Hall and Professor Michael Owen), the MRC Centre for Neuropsychiatric Genetics and Genomics (G0800509) and the NIHR Bristol Biomedical Research Centre. Avon Longitudinal Study of Parents and Children (ALSPAC): 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 ALSPACteam, 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 work of the authors and corresponding author Dr Thomas Lancaster will serve as guarantor for the contents of this paper. “GWAS data was generated by Sample Logistics and Genotyping Facilities at Wellcome Sanger Institute and LabCorp (Laboratory Corporation of America) using support from 23andMe.
Publisher Copyright:
© 2021 The Author(s). Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.
Keywords
- heterogeneity
- MRI
- multivariate
- normative modelling
- polygenic
- schizophrenia
ASJC Scopus subject areas
- Psychiatry and Mental health