Poster No:
995
Submission Type:
Late-Breaking Abstract Submission
Authors:
Lorenza Dall'Aglio1, Ryan Muetzel2, Yingzhe Zhang3, Serena Defina2, Fernando Estevez-Lopez4, Jordan Smoller1, Henning Tiemeier3, Karmel Choi5
Institutions:
1Massachusetts General Hospital, Harvard Medical School, Boston, MA, 2Erasmus Medical Center, Rotterdam, Zuid-Holland, 3Harvard School of Public Health, Boston, MA, 4Almeria University, Almeria, Andalusia, 5Massachusetts General Hospital, Boston, MA
First Author:
Co-Author(s):
Jordan Smoller
Massachusetts General Hospital, Harvard Medical School
Boston, MA
Introduction:
The role of physical activity (PA) in preventing neurodegeneration has been established (Augusto-Oliveira et al., 2023), yet little is known about its role in neurodevelopment. During adolescence, morphological changes occur and PA habits are consolidated (Larsen & Luna, 2018; Estévez-López et al., 2023). A greater understanding of the relation of PA with neuroanatomy in adolescents is needed. Moreover, prior literature has been predominantly confined to small samples, self-reported measures of PA, and region-of-interest (ROI) approaches focused on subcortical areas. Here, we examined the brain-wide morphology of objectively assessed PA in a large sample of adolescents.
Methods:
From the Adolescent Brain Cognitive Development Study, we included adolescents with Fitbit and MRI data at 12 years (N=4,409) (Garavan et al., 2018). Individuals with failed processing or quality assurance, or substantial incidental findings were excluded. PA was assessed with FitBit data collected for 21 days. The total number of daily steps and the time spent in different intensity levels (light and moderate-to-vigorous PA) were derived. T1-weighted structural images were acquired from 3T scanners (Casey et al., 2018), processed with FreeSurfer v6.0 (Fischl, 2012), and underwent manual and automated quality assurance. Surface-based measures for cortical volume and area at each vertex were obtained, together with data on ROIs (amygdala and hippocampus volume). We adjusted for age, race/ethnicity, sex, parental education, self-perceived pubertal status, study site (main model), and internalizing problems (sensitivity analysis). We ran vertex-wise analyses with QDECR (Lamballais & Muetzel, 2021) for each PA measure (total steps, light PA, moderate-to-vigorous PA) with each morphological measure (each vertex's cortical surface area, thickness, and ROI volumes). Cluster-wise corrections based on Monte Carlo simulations were used (Lamballais & Muetzel, 2021).
Results:
Adolescents were on average 12 years-old (SD = 0.64), the sample was gender-balanced (47% females), and predominantly White (59%). They generally took 9,252 steps per day (SD = 3,118). They spent 4.6 hours (SD=0.9) and 0.6 hours (SD=0.5) engaged in light and moderate-to-vigorous PA, respectively. Higher total step count related to higher cortical thickness, bilaterally (Figure 1). Areas of association were predominantly located in the superior parietal, paracentral, superior frontal, and inferior temporal areas bilaterally, in the precuneus in the left hemisphere, and the medial orbitofrontal, superior frontal, and caudal anterior cingulate areas in the right hemisphere. Results were similar after adjustments for concurrent internalizing problems. Total step count did not relate to surface area or ROIs.
With more time spent in light PA, both patterns of greater and lower cortical thickness were observed (Figure 2). Lower surface area in the medial orbitofrontal, superior frontal areas, and lower amygdala volume (estimate=0.03, SE=0.01, p=0.027) were also found. With more time spent in moderate-to-vigorous levels of PA, higher cortical thickness was shown in a small cluster in the cuneus, superior parietal, and lateral occipital in the right hemisphere (Figure 2). No relationships were observed for moderate-to-vigorous PA with cortical surface area or ROI volumes.

·Figure 1. Vertex-wise results for daily total steps and cortical thickness in adolescents. L = left hemisphere. R = right hemisphere. Colored clusters indicate statistically significant associations.

·Figure 2 Vertex-wise results for time spent in moderate-to-vigorous and light PA and cortical thickness in adolescents
Conclusions:
A greater total number of daily steps correlates with higher cortical thickness in adolescence, predominantly at frontal and temporal areas. When decomposing activity levels of PA, time spent in moderate-to-vigorous PA localized in visuomotor and sensorimotor areas, while light PA in areas involved in cognitive, emotional, sensory, and motor functions. To better elucidate how PA in adolescence might confer morphological changes, longitudinal studies with repeated PA and imaging assessments as well as randomized controlled trials are needed.
Lifespan Development:
Early life, Adolescence, Aging 1
Normal Brain Development: Fetus to Adolescence
Modeling and Analysis Methods:
Univariate Modeling
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Anatomy and Functional Systems
Subcortical Structures
Perception, Attention and Motor Behavior:
Visuo-Motor Functions
Motor Behavior Other 2
Keywords:
Motor
MRI
PEDIATRIC
STRUCTURAL MRI
Other - physical activity
1|2Indicates the priority used for review
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Free Surfer
Provide references using APA citation style.
Augusto-Oliveira, M., Arrifano, G. P., Leal-Nazaré, C. G., Santos-Sacramento, L., Lopes-Araújo, A., Royes, L. F. F., & Crespo-Lopez, M. E. (2023). Exercise Reshapes the Brain: Molecular, Cellular, and Structural Changes Associated with Cognitive Improvements. Molecular Neurobiology, 60(12), 6950–6974. https://doi.org/10.1007/s12035-023-03492-8
Casey, B. J., Cannonier, T., Conley, M. I., Cohen, A. O., Barch, D. M., Heitzeg, M. M., Soules, M. E., Teslovich, T., Dellarco, D. V., Garavan, H., Orr, C. A., Wager, T. D., Banich, M. T., Speer, N. K., Sutherland, M. T., Riedel, M. C., Dick, A. S., Bjork, J. M., Thomas, K. M., … Dale, A. M. (2018). The Adolescent Brain Cognitive Development (ABCD) study: Imaging acquisition across 21 sites. Developmental Cognitive Neuroscience, 32, 43–54. https://doi.org/10.1016/j.dcn.2018.03.001
Estévez-López, F., Dall’Aglio, L., Rodriguez-Ayllon, M., Xu, B., You, Y., Hillman, C. H., Muetzel, R. L., & Tiemeier, H. (2023). Levels of Physical Activity at Age 10 Years and Brain Morphology Changes From Ages 10 to 14 Years. JAMA Network Open, 6(10), e2333157. https://doi.org/10.1001/jamanetworkopen.2023.33157
Fischl, B. (2012). FreeSurfer. NeuroImage, 62(2), 774–781. https://doi.org/10.1016/j.neuroimage.2012.01.021
Garavan, H., Bartsch, H., Conway, K., Decastro, A., Goldstein, R. Z., Heeringa, S., Jernigan, T., Potter, A., Thompson, W., & Zahs, D. (2018). Recruiting the ABCD sample: Design considerations and procedures. Developmental Cognitive Neuroscience, 32, 16–22. https://doi.org/10.1016/j.dcn.2018.04.004
Lamballais, S., & Muetzel, R. L. (2021). QDECR: A Flexible, Extensible Vertex-Wise Analysis Framework in R. Frontiers in Neuroinformatics, 15. https://doi.org/10.3389/fninf.2021.561689
Larsen, B., & Luna, B. (2018). Adolescence as a neurobiological critical period for the development of higher-order cognition. Neuroscience and Biobehavioral Reviews, 94, 179–195. https://doi.org/10.1016/j.neubiorev.2018.09.005
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