A general exposome factor explains individual differences in functional brain network topography and cognition in youth

Arielle S Keller; Tyler M Moore; Audrey Luo; Elina Visoki; Mārtiņš M Gataviņš; Alisha Shetty; Zaixu Cui; Yong Fan; Eric Feczko; Audrey Houghton; Hongming Li; Allyson P Mackey; Oscar Miranda-Dominguez; Adam Pines; Russell T Shinohara; Kevin Y Sun; Damien A Fair; Theodore D Satterthwaite; Ran Barzilay

doi:10.1016/j.dcn.2024.101370

A general exposome factor explains individual differences in functional brain network topography and cognition in youth

Dev Cogn Neurosci. 2024 Apr:66:101370. doi: 10.1016/j.dcn.2024.101370. Epub 2024 Apr 2.

Authors

Arielle S Keller¹, Tyler M Moore², Audrey Luo¹, Elina Visoki³, Mārtiņš M Gataviņš⁴, Alisha Shetty¹, Zaixu Cui⁵, Yong Fan⁶, Eric Feczko⁷, Audrey Houghton⁷, Hongming Li⁶, Allyson P Mackey⁸, Oscar Miranda-Dominguez⁷, Adam Pines⁹, Russell T Shinohara¹⁰, Kevin Y Sun¹, Damien A Fair¹¹, Theodore D Satterthwaite¹², Ran Barzilay¹³

Affiliations

¹ Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
² 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.
³ 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.
⁴ 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, Philadelphia, PA, USA.
⁵ Chinese Institute for Brain Research, Beijing, China.
⁶ Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
⁷ Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA.
⁸ Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA.
⁹ Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.
¹⁰ Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, USA.
¹¹ 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.
¹² 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, Philadelphia, PA, USA. Electronic address: sattertt@pennmedicine.upenn.edu.
¹³ 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, Children's Hospital of Philadelphia, Philadelphia, PA, USA.

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.

Keywords: Cognition; Development; Environment; Exposome; Functional networks; Topography.

Abstract

Grants and funding