Patterns of brain-wide associations reflect socioeconomics.
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| Title: | Patterns of brain-wide associations reflect socioeconomics. |
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| Authors: | Marek, Scott (AUTHOR), Donohue, Meghan Rose (AUTHOR), Karcher, Nicole R. (AUTHOR), Hoyniak, Caroline P. (AUTHOR), Chauvin, Roselyne J. (AUTHOR), Meyer, Ashley C. (AUTHOR), Miller, John (AUTHOR), Van, Andrew N. (AUTHOR), Wang, Anxu (AUTHOR), Baden, Noah J. (AUTHOR), Suljic, Vahdeta (AUTHOR), Scheidter, Kristen M. (AUTHOR), Monk, Julia (AUTHOR), Whiting, Forrest I. (AUTHOR), Ramirez-Perez, Nadeshka J. (AUTHOR), Krimmel, Samuel R. (AUTHOR), Metoki, Athanasia (AUTHOR), Paul, Sarah E. (AUTHOR), Gorelik, Aaron J. (AUTHOR), Hendrickson, Timothy J. (AUTHOR) |
| Source: | Science. 6/11/2026, Vol. 392 Issue 6803, p1-17. 17p. |
| Subjects: | Socioeconomic status, Sleep deprivation, Physiological stress, Perceptual-motor processes, Intelligence levels, Child development, Brain imaging |
| Abstract: | Previous brain-wide association studies (BWAS) have linked specific environmental and behavioral variables to brain variability. In this work, we mapped 649 variables to children's brains and compared the resultant BWAS maps with each other and with neurobiological reference patterns. Socioeconomic status (SES) showed the strongest brain-wide associations. The SES associations were strongest in motor and sensory but not cognitive regions, a pattern shared across many BWAS maps, including intelligence quotient (IQ). A single, common BWAS brain pattern existed across variables that was most reflective of a child's socioeconomics. Adjusting for SES weakened brain-IQ associations, eliminating the BWAS motor and sensory pattern. Brain-with-IQ associations also did not generalize when trained on higher-SES subsamples. Thus, children's brains vary the most with SES, potentially through SES-dependent sleep deprivation and stress. Editor's summary: Brain function and structure are known to be affected by environmental conditions. Marek et al. mapped brain-wide association studies (BWAS) of 649 phenotypes and exposures to brain function and structure using imaging data from many sources (see the Perspective by Sisk and Satterthwaite). Across adolescents, neighborhood-level socioeconomics showed the strongest brain-wide association, representing a single exposome pattern that explains 34% of all BWAS variance. In their datasets, the classic brain-IQ association largely disappeared when socioeconomic status was properly accounted for. These results provide valuable insights for understanding the effects of the environment on brain development. —Mattia Maroso INTRODUCTION: Brain-wide association studies (BWAS) link individual differences in behavioral traits [e.g., intelligence quotient (IQ)] or living conditions (e.g., socioeconomic status) to variability in our brain function and structure. Widely used BWAS measures include magnetic resonance imaging (MRI)–derived resting-state functional connectivity, which successfully maps networks based on spontaneous neural fluctuations, and cortical thickness. Prior BWAS have associated brain imaging data with single traits, most commonly IQ or psychopathology, prioritizing association strength over spatial patterns. Although large samples improve BWAS replicability, the relative importance of different environmental and behavioral variables, their relationships to each other, and the interpretation of the underlying brain patterns remain unclear. RATIONALE: Datasets with many thousands of participants enable us to simultaneously map hundreds of nonimaging variables to the brain and to compare them both with each other and with well-established neurobiological reference patterns (non-BWAS). This framework leverages existing knowledge of brain biology for abductive pattern-based inference. For example, higher-order cognition relies on the frontal and parietal cortices, whereas the effects of sleep deprivation and stress manifest in primary motor and sensory regions. With such neurobiological patterns as a guiding light, we can robustly infer meaning from the BWAS patterns and identify which brain-wide associations may reflect confounding or are only valid for certain subsets of people. RESULTS: Across 649 nonimaging variables, in a large sample of 9 to 10 year olds, socioeconomic measures had the strongest and most replicable brain-wide associations. The single strongest brain association was with the socioeconomic opportunities afforded by a child's zip code. This socioeconomic brain pattern was dominant and permeated many of the other BWAS maps. Socioeconomic associations were concentrated in primary motor and sensory regions, with strong spatial similarity to arousal and stress patterns, including norepinephrine receptor density, sleep duration, and stimulant medication effects, while being negatively correlated with task functional MRI maps of higher-order cognition. Unexpectedly, the BWAS map of IQ closely matched the socioeconomic pattern. Adjusting for socioeconomics reduced brain-IQ associations and shifted them away from arousal and toward a pattern more similar to cognition, consistent with confounding by socioeconomics. Multivariate brain-IQ models failed when trained on samples from higher socioeconomic strata lacking a correlation between socioeconomics and IQ. Brain-IQ models could only detect associations when the training sample included children from neighborhoods with lower socioeconomic status. However, these were misleading, because the IQ-trained models still predicted socioeconomics better than IQ, consistent with shortcut learning. CONCLUSION: Socioeconomic circumstances are more powerfully associated with brain function and structure than other variables. The dominant socioeconomic brain pattern matches the known effects of sleep deprivation and stress (primary motor and sensory) while sparing higher-order cognitive regions in the frontal and parietal cortices. Thus, it appears most likely that environmental factors indexed by neighborhood socioeconomic status, including sleep and stress, strongly shape childhood brain organization. This stands in contrast to brain-IQ associations that are confounded and reflect shortcut learning of socioeconomics rather than brain-based differences. Accounting for socioeconomics improves BWAS interpretation and generalizability. In summary, neighborhood socioeconomics represent the principal axis shaping brain organization during childhood and beyond, potentially through sleep and stress. Socioeconomics is the dominant axis of childhood brain organization.: Brain-wide associations in the Adolescent Brain Cognitive Development (ABCD) Study revealed that socioeconomic status exhibited the strongest associations with brain organization. Socioeconomic status dominated population-level variation through arousal-related patterns linked to sleep and stress, specifically norepinephrine and stimulant effect maps. Socioeconomic status models demonstrated robust generalizability across different groups, highlighting its importance as the primary variable in childhood BWAS. [Figure created by Lucy Reading-Ikkanda] [ABSTRACT FROM AUTHOR] |
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| Database: | Psychology and Behavioral Sciences Collection |
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| Abstract: | Previous brain-wide association studies (BWAS) have linked specific environmental and behavioral variables to brain variability. In this work, we mapped 649 variables to children's brains and compared the resultant BWAS maps with each other and with neurobiological reference patterns. Socioeconomic status (SES) showed the strongest brain-wide associations. The SES associations were strongest in motor and sensory but not cognitive regions, a pattern shared across many BWAS maps, including intelligence quotient (IQ). A single, common BWAS brain pattern existed across variables that was most reflective of a child's socioeconomics. Adjusting for SES weakened brain-IQ associations, eliminating the BWAS motor and sensory pattern. Brain-with-IQ associations also did not generalize when trained on higher-SES subsamples. Thus, children's brains vary the most with SES, potentially through SES-dependent sleep deprivation and stress. Editor's summary: Brain function and structure are known to be affected by environmental conditions. Marek et al. mapped brain-wide association studies (BWAS) of 649 phenotypes and exposures to brain function and structure using imaging data from many sources (see the Perspective by Sisk and Satterthwaite). Across adolescents, neighborhood-level socioeconomics showed the strongest brain-wide association, representing a single exposome pattern that explains 34% of all BWAS variance. In their datasets, the classic brain-IQ association largely disappeared when socioeconomic status was properly accounted for. These results provide valuable insights for understanding the effects of the environment on brain development. —Mattia Maroso INTRODUCTION: Brain-wide association studies (BWAS) link individual differences in behavioral traits [e.g., intelligence quotient (IQ)] or living conditions (e.g., socioeconomic status) to variability in our brain function and structure. Widely used BWAS measures include magnetic resonance imaging (MRI)–derived resting-state functional connectivity, which successfully maps networks based on spontaneous neural fluctuations, and cortical thickness. Prior BWAS have associated brain imaging data with single traits, most commonly IQ or psychopathology, prioritizing association strength over spatial patterns. Although large samples improve BWAS replicability, the relative importance of different environmental and behavioral variables, their relationships to each other, and the interpretation of the underlying brain patterns remain unclear. RATIONALE: Datasets with many thousands of participants enable us to simultaneously map hundreds of nonimaging variables to the brain and to compare them both with each other and with well-established neurobiological reference patterns (non-BWAS). This framework leverages existing knowledge of brain biology for abductive pattern-based inference. For example, higher-order cognition relies on the frontal and parietal cortices, whereas the effects of sleep deprivation and stress manifest in primary motor and sensory regions. With such neurobiological patterns as a guiding light, we can robustly infer meaning from the BWAS patterns and identify which brain-wide associations may reflect confounding or are only valid for certain subsets of people. RESULTS: Across 649 nonimaging variables, in a large sample of 9 to 10 year olds, socioeconomic measures had the strongest and most replicable brain-wide associations. The single strongest brain association was with the socioeconomic opportunities afforded by a child's zip code. This socioeconomic brain pattern was dominant and permeated many of the other BWAS maps. Socioeconomic associations were concentrated in primary motor and sensory regions, with strong spatial similarity to arousal and stress patterns, including norepinephrine receptor density, sleep duration, and stimulant medication effects, while being negatively correlated with task functional MRI maps of higher-order cognition. Unexpectedly, the BWAS map of IQ closely matched the socioeconomic pattern. Adjusting for socioeconomics reduced brain-IQ associations and shifted them away from arousal and toward a pattern more similar to cognition, consistent with confounding by socioeconomics. Multivariate brain-IQ models failed when trained on samples from higher socioeconomic strata lacking a correlation between socioeconomics and IQ. Brain-IQ models could only detect associations when the training sample included children from neighborhoods with lower socioeconomic status. However, these were misleading, because the IQ-trained models still predicted socioeconomics better than IQ, consistent with shortcut learning. CONCLUSION: Socioeconomic circumstances are more powerfully associated with brain function and structure than other variables. The dominant socioeconomic brain pattern matches the known effects of sleep deprivation and stress (primary motor and sensory) while sparing higher-order cognitive regions in the frontal and parietal cortices. Thus, it appears most likely that environmental factors indexed by neighborhood socioeconomic status, including sleep and stress, strongly shape childhood brain organization. This stands in contrast to brain-IQ associations that are confounded and reflect shortcut learning of socioeconomics rather than brain-based differences. Accounting for socioeconomics improves BWAS interpretation and generalizability. In summary, neighborhood socioeconomics represent the principal axis shaping brain organization during childhood and beyond, potentially through sleep and stress. Socioeconomics is the dominant axis of childhood brain organization.: Brain-wide associations in the Adolescent Brain Cognitive Development (ABCD) Study revealed that socioeconomic status exhibited the strongest associations with brain organization. Socioeconomic status dominated population-level variation through arousal-related patterns linked to sleep and stress, specifically norepinephrine and stimulant effect maps. Socioeconomic status models demonstrated robust generalizability across different groups, highlighting its importance as the primary variable in childhood BWAS. [Figure created by Lucy Reading-Ikkanda] [ABSTRACT FROM AUTHOR] |
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| ISSN: | 00368075 |
| DOI: | 10.1126/science.aee6213 |
