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Reproducible sex differences in personalised functional network topography in youth.

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Title: Reproducible sex differences in personalised functional network topography in youth.
Authors: Keller, Arielle S. (AUTHOR), Sun, Kevin Y. (AUTHOR), Francisco, Ashley (AUTHOR), Robinson, Heather (AUTHOR), Beydler, Emily (AUTHOR), Bassett, Dani S. (AUTHOR), Cieslak, Matthew (AUTHOR), Cui, Zaixu (AUTHOR), Davatzikos, Christos (AUTHOR), Fan, Yong (AUTHOR), Gardner, Margaret (AUTHOR), Kishton, Rachel (AUTHOR), Kornfield, Sara L. (AUTHOR), Larsen, Bart (AUTHOR), Li, Hongming (AUTHOR), Linder, Isabella (AUTHOR), Pines, Adam (AUTHOR), Pritschet, Laura (AUTHOR), Raznahan, Armin (AUTHOR), Roalf, David R. (AUTHOR)
Source: British Journal of Psychiatry. Jun2025, Vol. 226 Issue 6, p383-391. 9p.
Subjects: Gender differences (Psychology), Adolescent development, Brain anatomy, Machine learning, Child psychopathology, Functional connectivity, Teenagers
Abstract: Background: A key step toward understanding psychiatric disorders that disproportionately impact female mental health is delineating the emergence of sex-specific patterns of brain organisation at the critical transition from childhood to adolescence. Prior work suggests that individual differences in the spatial organisation of functional brain networks across the cortex are associated with psychopathology and differ systematically by sex. Aims: We aimed to evaluate the impact of sex on the spatial organisation of person-specific functional brain networks. Method: We leveraged person-specific atlases of functional brain networks, defined using non-negative matrix factorisation, in a sample of n = 6437 youths from the Adolescent Brain Cognitive Development Study. Across independent discovery and replication samples, we used generalised additive models to uncover associations between sex and the spatial layout (topography) of personalised functional networks (PFNs). We also trained support vector machines to classify participants' sex from multivariate patterns of PFN topography. Results: Sex differences in PFN topography were greatest in association networks including the frontoparietal, ventral attention and default mode networks. Machine learning models trained on participants' PFNs were able to classify participant sex with high accuracy. Conclusions: Sex differences in PFN topography are robust, and replicate across large-scale samples of youth. These results suggest a potential contributor to the female-biased risk in depressive and anxiety disorders that emerge at the transition from childhood to adolescence. [ABSTRACT FROM AUTHOR]
Copyright of British Journal of Psychiatry is the property of Cambridge University Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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DbLabel: Psychology and Behavioral Sciences Collection
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Reproducible sex differences in personalised functional network topography in youth.
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  Data: <searchLink fieldCode="AR" term="%22Keller%2C+Arielle+S%2E%22">Keller, Arielle S.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Sun%2C+Kevin+Y%2E%22">Sun, Kevin Y.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Francisco%2C+Ashley%22">Francisco, Ashley</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Robinson%2C+Heather%22">Robinson, Heather</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Beydler%2C+Emily%22">Beydler, Emily</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Bassett%2C+Dani+S%2E%22">Bassett, Dani S.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cieslak%2C+Matthew%22">Cieslak, Matthew</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cui%2C+Zaixu%22">Cui, Zaixu</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Davatzikos%2C+Christos%22">Davatzikos, Christos</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Fan%2C+Yong%22">Fan, Yong</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Gardner%2C+Margaret%22">Gardner, Margaret</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kishton%2C+Rachel%22">Kishton, Rachel</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kornfield%2C+Sara+L%2E%22">Kornfield, Sara L.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Larsen%2C+Bart%22">Larsen, Bart</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Hongming%22">Li, Hongming</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Linder%2C+Isabella%22">Linder, Isabella</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pines%2C+Adam%22">Pines, Adam</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pritschet%2C+Laura%22">Pritschet, Laura</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Raznahan%2C+Armin%22">Raznahan, Armin</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Roalf%2C+David+R%2E%22">Roalf, David R.</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22British+Journal+of+Psychiatry%22">British Journal of Psychiatry</searchLink>. Jun2025, Vol. 226 Issue 6, p383-391. 9p.
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  Data: <searchLink fieldCode="DE" term="%22Gender+differences+%28Psychology%29%22">Gender differences (Psychology)</searchLink><br /><searchLink fieldCode="DE" term="%22Adolescent+development%22">Adolescent development</searchLink><br /><searchLink fieldCode="DE" term="%22Brain+anatomy%22">Brain anatomy</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br /><searchLink fieldCode="DE" term="%22Child+psychopathology%22">Child psychopathology</searchLink><br /><searchLink fieldCode="DE" term="%22Functional+connectivity%22">Functional connectivity</searchLink><br /><searchLink fieldCode="DE" term="%22Teenagers%22">Teenagers</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Background: A key step toward understanding psychiatric disorders that disproportionately impact female mental health is delineating the emergence of sex-specific patterns of brain organisation at the critical transition from childhood to adolescence. Prior work suggests that individual differences in the spatial organisation of functional brain networks across the cortex are associated with psychopathology and differ systematically by sex. Aims: We aimed to evaluate the impact of sex on the spatial organisation of person-specific functional brain networks. Method: We leveraged person-specific atlases of functional brain networks, defined using non-negative matrix factorisation, in a sample of n = 6437 youths from the Adolescent Brain Cognitive Development Study. Across independent discovery and replication samples, we used generalised additive models to uncover associations between sex and the spatial layout (topography) of personalised functional networks (PFNs). We also trained support vector machines to classify participants' sex from multivariate patterns of PFN topography. Results: Sex differences in PFN topography were greatest in association networks including the frontoparietal, ventral attention and default mode networks. Machine learning models trained on participants' PFNs were able to classify participant sex with high accuracy. Conclusions: Sex differences in PFN topography are robust, and replicate across large-scale samples of youth. These results suggest a potential contributor to the female-biased risk in depressive and anxiety disorders that emerge at the transition from childhood to adolescence. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of British Journal of Psychiatry is the property of Cambridge University Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1192/bjp.2025.135
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      – Code: eng
        Text: English
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        Type: general
      – SubjectFull: Adolescent development
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      – SubjectFull: Brain anatomy
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      – SubjectFull: Child psychopathology
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      – SubjectFull: Functional connectivity
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      – SubjectFull: Teenagers
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              Text: Jun2025
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