TY - JOUR
T1 - Assessing the association between global structural brain age and polygenic risk for schizophrenia in early adulthood
T2 - A recall-by-genotype study
AU - Constantinides, Constantinos
AU - Baltramonaityte, Vilte
AU - Caramaschi, Doretta
AU - Han, Laura K. M.
AU - Lancaster, Thomas M.
AU - Zammit, Stanley
AU - Freeman, Tom P.
AU - Walton, Esther
N1 - Funding Information: The UK Medical Research Council (MRC) 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 CC and EW will serve as guarantors for the contents of this paper. A comprehensive list of grant funding is available on the ALSPAC website ( http://www.bristol.ac.uk/alspac/external/documents/grant-acknowledgements.pdf ). The recall-by genotype imaging sub-study was supported by grant MR/K004360/1 from the MRC titled: “Behavioural and neurophysiological effects of schizophrenia risk genes: a multi-locus, pathway based approach” and by the MRC Centre for Neuropsychiatric Genetics and Genomics ( G0800509 ). GWAS data were generated by Sample Logistics and Genotyping Facilities at Wellcome Sanger Institute and LabCorp (Laboratory Corporation of America) using support from 23andMe. The work reported in this publication was funded from the European Union's Horizon Europe/2020 research and innovation programme under the European Research Council grant agreement No 848158 (EarlyCause) and P/Y015037/1 (BrainHealth, fulfilled by UKRI) to EW. EW also received funding from the National Institute of Mental Health of the National Institutes of Health (award number R01MH113930 ). CC was supported by grant MR/N0137941/1 for the GW4 BIOMED Doctoral Training Partnership awarded to the Universities of Bath, Bristol, Cardiff and Exeter from the Medical Research Council (MRC)/ UK Research & Innovation (UKRI). LH was funded by the Rubicon award (grant number 452020227) from the Dutch Research Council (NWO). SZ is supported by the NIHR Biomedical Research Centre at University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol. Funding Information: The UK Medical Research Council (MRC) 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 CC and EW will serve as guarantors for the contents of this paper. A comprehensive list of grant funding is available on the ALSPAC website (http://www.bristol.ac.uk/alspac/external/documents/grant-acknowledgements.pdf). The recall-by genotype imaging sub-study was supported by grant MR/K004360/1 from the MRC titled: “Behavioural and neurophysiological effects of schizophrenia risk genes: a multi-locus, pathway based approach” and by the MRC Centre for Neuropsychiatric Genetics and Genomics (G0800509). GWAS data were generated by Sample Logistics and Genotyping Facilities at Wellcome Sanger Institute and LabCorp (Laboratory Corporation of America) using support from 23andMe. The work reported in this publication was funded from the European Union's Horizon Europe/2020 research and innovation programme under the European Research Council grant agreement No 848158 (EarlyCause) and P/Y015037/1 (BrainHealth, fulfilled by UKRI) to EW. EW also received funding from the National Institute of Mental Health of the National Institutes of Health (award number R01MH113930). CC was supported by grant MR/N0137941/1 for the GW4 BIOMED Doctoral Training Partnership awarded to the Universities of Bath, Bristol, Cardiff and Exeter from the Medical Research Council (MRC)/UK Research & Innovation (UKRI). LH was funded by the Rubicon award (grant number 452020227) from the Dutch Research Council (NWO). SZ is supported by the NIHR Biomedical Research Centre at University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol. Publisher Copyright: © 2023 The Author(s)
PY - 2024/3/1
Y1 - 2024/3/1
N2 - Neuroimaging studies consistently show advanced brain age in schizophrenia, suggesting that brain structure is often ‘older’ than expected at a given chronological age. Whether advanced brain age is linked to genetic liability for schizophrenia remains unclear. In this pre-registered secondary data analysis, we utilised a recall-by-genotype approach applied to a population-based subsample from the Avon Longitudinal Study of Parents and Children to assess brain age differences between young adults aged 21–24 years with relatively high (n = 96) and low (n = 93) polygenic risk for schizophrenia (SCZ-PRS). A global index of brain age (or brain-predicted age) was estimated using a publicly available machine learning model previously trained on a combination of region-wise gray-matter measures, including cortical thickness, surface area and subcortical volumes derived from T1-weighted magnetic resonance imaging (MRI) scans. We found no difference in mean brain-PAD (the difference between brain-predicted age and chronological age) between the high- and low-SCZ-PRS groups, controlling for the effects of sex and age at time of scanning (b = −.21; 95% CI −2.00, 1.58; p = .82; Cohen's d = −.034; partial R2 = .00029). These findings do not support an association between SCZ-PRS and brain-PAD based on global age-related structural brain patterns, suggesting that brain age may not be a vulnerability marker of common genetic risk for SCZ. Future studies with larger samples and multimodal brain age measures could further investigate global or localised effects of SCZ-PRS.
AB - Neuroimaging studies consistently show advanced brain age in schizophrenia, suggesting that brain structure is often ‘older’ than expected at a given chronological age. Whether advanced brain age is linked to genetic liability for schizophrenia remains unclear. In this pre-registered secondary data analysis, we utilised a recall-by-genotype approach applied to a population-based subsample from the Avon Longitudinal Study of Parents and Children to assess brain age differences between young adults aged 21–24 years with relatively high (n = 96) and low (n = 93) polygenic risk for schizophrenia (SCZ-PRS). A global index of brain age (or brain-predicted age) was estimated using a publicly available machine learning model previously trained on a combination of region-wise gray-matter measures, including cortical thickness, surface area and subcortical volumes derived from T1-weighted magnetic resonance imaging (MRI) scans. We found no difference in mean brain-PAD (the difference between brain-predicted age and chronological age) between the high- and low-SCZ-PRS groups, controlling for the effects of sex and age at time of scanning (b = −.21; 95% CI −2.00, 1.58; p = .82; Cohen's d = −.034; partial R2 = .00029). These findings do not support an association between SCZ-PRS and brain-PAD based on global age-related structural brain patterns, suggesting that brain age may not be a vulnerability marker of common genetic risk for SCZ. Future studies with larger samples and multimodal brain age measures could further investigate global or localised effects of SCZ-PRS.
KW - ALSPAC
KW - Ageing
KW - Brain age
KW - Genetic risk
KW - Schizophrenia
UR - http://www.scopus.com/inward/record.url?scp=85181512336&partnerID=8YFLogxK
U2 - https://doi.org/10.1016/j.cortex.2023.11.015
DO - https://doi.org/10.1016/j.cortex.2023.11.015
M3 - Article
C2 - 38154374
SN - 0010-9452
VL - 172
SP - 1
EP - 13
JO - Cortex
JF - Cortex
ER -