Assessing the association between global structural brain age and polygenic risk for schizophrenia in early adulthood: A recall-by-genotype study

Constantinos Constantinides; Vilte Baltramonaityte; Doretta Caramaschi; Laura K.M.  Han; Tom Lancaster; Stanley Zammit; Tom Freeman; Esther Walton

doi:10.1016/j.cortex.2023.11.015

Assessing the association between global structural brain age and polygenic risk for schizophrenia in early adulthood: A recall-by-genotype study

Constantinos Constantinides, Vilte Baltramonaityte, Doretta Caramaschi, Laura K.M. Han, Tom Lancaster, Stanley Zammit, Tom Freeman, Esther Walton

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

2 Citations (SciVal)

Abstract

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.

Original language	English
Pages (from-to)	1-13
Number of pages	13
Journal	Cortex
Volume	172
Early online date	8 Dec 2023
DOIs	https://doi.org/10.1016/j.cortex.2023.11.015
Publication status	Published - 31 Mar 2024

Bibliographical note

Data availability
The authors do not have permission to share data. Researchers can request the original dataset used directly from ALSPAC (https://www.bristol.ac.uk/alspac/researchers/).

Funding

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. 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.

Funders	Funder number
European Union's Horizon Europe/2020 research and innovation programme
Wellcome Sanger Institute
National Institutes of Health	MR/N0137941/1, R01MH113930
National Institute of Mental Health
The Wellcome Trust	217065/Z/19/Z
University Hospitals Bristol NHS Foundation Trust
UK Research and Innovation	452020227
Medical Research Council
National Institute for Health and Care Research
European Research Council	P/Y015037/1, 848158
University of Bristol	MR/K004360/1, G0800509
Nederlandse Organisatie voor Wetenschappelijk Onderzoek

Keywords

ALSPAC
Ageing
Brain age
Genetic risk
Schizophrenia

ASJC Scopus subject areas

Experimental and Cognitive Psychology
Neuropsychology and Physiological Psychology
Cognitive Neuroscience

Access to Document

10.1016/j.cortex.2023.11.015Licence: CC BY

Cite this

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title = "Assessing the association between global structural brain age and polygenic risk for schizophrenia in early adulthood: A recall-by-genotype study",

abstract = "Neuroimaging studies consistently show advanced brain age in schizophrenia, suggesting that brain structure is often {\textquoteleft}older{\textquoteright} 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.",

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note = "Data availability The authors do not have permission to share data. Researchers can request the original dataset used directly from ALSPAC (https://www.bristol.ac.uk/alspac/researchers/).",

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AU - Constantinides, Constantinos

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AU - Caramaschi, Doretta

AU - Han, Laura K.M.

AU - Lancaster, Tom

AU - Zammit, Stanley

AU - Freeman, Tom

AU - Walton, Esther

N1 - Data availability The authors do not have permission to share data. Researchers can request the original dataset used directly from ALSPAC (https://www.bristol.ac.uk/alspac/researchers/).

PY - 2024/3/31

Y1 - 2024/3/31

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.

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JO - Cortex

JF - Cortex

ER -

Assessing the association between global structural brain age and polygenic risk for schizophrenia in early adulthood: A recall-by-genotype study

Abstract

Bibliographical note

Funding

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

BrainHealth - Decoding life course pathways of mental ageing - Frontier Research Guarantee

EarlyCause

Cite this

Assessing the association between global structural brain age and polygenic risk for schizophrenia in early adulthood: A recall-by-genotype study

Abstract

Bibliographical note

Funding

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Projects

BrainHealth - Decoding life course pathways of mental ageing - Frontier Research Guarantee

EarlyCause

Cite this