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Personalized functional brain network topography is associated with individual differences in youth cognition.

ABSTRACT: Individual differences in cognition during childhood are associated with important social, physical, and mental health outcomes in adolescence and adulthood. Given that cortical surface arealization during development reflects the brain's functional prioritization, quantifying variation in the topography of functional brain networks across the developing cortex may provide insight regarding individual differences in cognition. We test this idea by defining personalized functional networks (PFNs) that account for interindividual heterogeneity in functional brain network topography in 9-10 year olds from the Adolescent Brain Cognitive Development℠ Study. Across matched discovery (n = 3525) and replication (n = 3447) samples, the total cortical representation of fronto-parietal PFNs positively correlates with general cognition. Cross-validated ridge regressions trained on PFN topography predict cognition in unseen data across domains, with prediction accuracy increasing along the cortex's sensorimotor-association organizational axis. These results establish that functional network topography heterogeneity is associated with individual differences in cognition before the critical transition into adolescence.

SUBMITTER: Keller AS

PROVIDER: S-EPMC10728159 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

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Personalized functional brain network topography is associated with individual differences in youth cognition.

Keller Arielle S AS Pines Adam R AR Shanmugan Sheila S Sydnor Valerie J VJ Cui Zaixu Z Bertolero Maxwell A MA Barzilay Ran R Alexander-Bloch Aaron F AF Byington Nora N Chen Andrew A Conan Gregory M GM Davatzikos Christos C Feczko Eric E Hendrickson Timothy J TJ Houghton Audrey A Larsen Bart B Li Hongming H Miranda-Dominguez Oscar O Roalf David R DR Perrone Anders A Shetty Alisha A Shinohara Russell T RT Fan Yong Y Fair Damien A DA Satterthwaite Theodore D TD

Nature communications 20231218 1

Individual differences in cognition during childhood are associated with important social, physical, and mental health outcomes in adolescence and adulthood. Given that cortical surface arealization during development reflects the brain's functional prioritization, quantifying variation in the topography of functional brain networks across the developing cortex may provide insight regarding individual differences in cognition. We test this idea by defining personalized functional networks (PFNs) ...[more]

PMID: 38110396

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Project description:BackgroundA key step towards understanding psychiatric disorders that disproportionately impact female mental health is delineating the emergence of sex-specific patterns of brain organization at the critical transition from childhood to adolescence. Prior work suggests that individual differences in the spatial organization of functional brain networks across the cortex are associated with psychopathology and differ systematically by sex.AimsWe aimed to evaluate the impact of sex on the spatial organization of person-specific functional brain networks.MethodWe leveraged person-specific atlases of functional brain networks defined using nonnegative matrix factorization in a sample of n = 6437 youths from the Adolescent Brain Cognitive Development Study. Across independent discovery and replication samples, we used generalized additive models to uncover associations between sex and the spatial layout ("topography") of personalized functional networks (PFNs). Next, we trained support vector machines to classify participants' sex from multivariate patterns of PFN topography. Finally, we leveraged transcriptomic data from the Allen Human Brain Atlas to evaluate spatial correlations between sex differences in PFN topography and gene expression.ResultsSex differences in PFN topography were greatest in association networks including the fronto-parietal, ventral attention, and default mode networks. Machine learning models trained on participants' PFNs were able to classify participant sex with high accuracy. Brain regions with the greatest sex differences in PFN topography were enriched in expression of X-linked genes as well as genes expressed in astrocytes and excitatory neurons.ConclusionsSex differences in PFN topography are robust, replicate across large-scale samples of youth, and are associated with expression patterns of X-linked genes. 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.

Project description:ImportanceFunctional brain networks are associated with both behavior and genetic factors. To uncover clinically translatable mechanisms of psychopathology, it is critical to define how the spatial organization of these networks relates to genetic risk during development.ObjectiveTo determine the relationship between transdiagnostic polygenic risk scores (PRSs), personalized functional brain networks (PFNs), and overall psychopathology (p-factor) during early adolescence.DesignThe Adolescent Brain Cognitive Development (ABCD) Study is an ongoing longitudinal cohort study of 21 collection sites across the United States. Here, we conduct a cross-sectional analysis of ABCD baseline data, collected 2017-2018.SettingThe ABCD Study ® is a multi-site community-based study.ParticipantsThe sample is largely recruited through school systems. Exclusion criteria included severe sensory, intellectual, medical, or neurological issues that interfere with protocol and scanner contraindications. Split-half subsets were used for cross-validation, matched on age, ethnicity, family structure, handedness, parental education, site, sex, and anesthesia exposure.ExposuresPolygenic risk scores of transdiagnostic genetic factors F1 (PRS-F1) and F2 (PRS-F2) derived from adults in Psychiatric Genomic Consortium and UK Biobanks datasets. PRS-F1 indexes liability for common psychiatric symptoms and disorders related to mood disturbance; PRS-F2 indexes liability for rarer forms of mental illness characterized by mania and psychosis.Main outcomes and measures(1) P-factor derived from bifactor models of youth- and parent-reported mental health assessments. (2) Person-specific functional brain network topography derived from functional magnetic resonance imaging (fMRI) scans.ResultsTotal participants included 11,873 youths ages 9-10 years old; 5,678 (47.8%) were female, and the mean (SD) age was 9.92 (0.62) years. PFN topography was found to be heritable (N=7,459, 57.06% of vertices h 2 p FDR <0.05, mean h 2 =0.35). PRS-F1 was associated with p-factor (N=5,815, r=0.12, 95% CI [0.09-0.15], p<0.001). Interindividual differences in functional network topography were associated with p-factor (N=7,459, mean r=0.12), PRS-F1 (N=3,982, mean r=0.05), and PRS-F2 (N=3,982, mean r=0.08). Cortical maps of p-factor and PRS-F1 regression coefficients were highly correlated (r=0.7, p=0.003).Conclusions and relevancePolygenic risk for transdiagnostic adulthood psychopathology is associated with both p-factor and heritable PFN topography during early adolescence. These results advance our understanding of the developmental drivers of psychopathology.

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Personalized functional brain network topography is associated with individual differences in youth cognition.

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Personalized functional brain network topography is associated with individual differences in youth cognition.

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