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A general exposome factor explains individual differences in functional brain network topography and cognition in youth.
Keller, Arielle S; Moore, Tyler M; Luo, Audrey; Visoki, Elina; Gatavins, Martins M; Shetty, Alisha; Cui, Zaixu; Fan, Yong; Feczko, Eric; Houghton, Audrey; Li, Hongming; Mackey, Allyson P; Miranda-Dominguez, Oscar; Pines, Adam; Shinohara, Russell T; Sun, Kevin Y; Fair, Damien A; Satterthwaite, Theodore D; Barzilay, Ran.
Afiliação
  • Keller AS; Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
  • Moore TM; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA; Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Luo A; Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
  • Visoki E; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA; Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
  • Gatavins MM; Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA; Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania
  • Shetty A; Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
  • Cui Z; Chinese Institute for Brain Research, Beijing, China.
  • Fan Y; Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
  • Feczko E; Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA.
  • Houghton A; Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA.
  • Li H; Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
  • Mackey AP; Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA.
  • Miranda-Dominguez O; Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA.
  • Pines A; Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.
  • Shinohara RT; Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, USA.
  • Sun KY; Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
  • Fair DA; Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA; Institute of Child Development, College of Education and Human Development, Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, MN 55414, USA.
  • Satterthwaite TD; Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA; Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania
  • Barzilay R; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA; Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Child and Adolescent Psychiatry and Behavioral Science, Childre
Dev Cogn Neurosci ; 66: 101370, 2024 Apr.
Article em En | MEDLINE | ID: mdl-38583301
ABSTRACT
Childhood environments are critical in shaping cognitive neurodevelopment. With the increasing availability of large-scale neuroimaging datasets with deep phenotyping of childhood environments, we can now build upon prior studies that have considered relationships between one or a handful of environmental and neuroimaging features at a time. Here, we characterize the combined effects of hundreds of inter-connected and co-occurring features of a child's environment ("exposome") and investigate associations with each child's unique, multidimensional pattern of functional brain network organization ("functional topography") and cognition. We apply data-driven computational models to measure the exposome and define personalized functional brain networks in pre-registered analyses. Across matched discovery (n=5139, 48.5% female) and replication (n=5137, 47.1% female) samples from the Adolescent Brain Cognitive Development study, the exposome was associated with current (ages 9-10) and future (ages 11-12) cognition. Changes in the exposome were also associated with changes in cognition after accounting for baseline scores. Cross-validated ridge regressions revealed that the exposome is reflected in functional topography and can predict performance across cognitive domains. Importantly, a single measure capturing a child's exposome could more accurately and parsimoniously predict cognition than a wealth of personalized neuroimaging data, highlighting the importance of children's complex, multidimensional environments in cognitive neurodevelopment.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos