Impact of Puberty Age Gap on Resting-state Functional Connectivity
Poster No:
1019
Submission Type:
Abstract Submission
Authors:
Soudeh Ashrafipour1, Nandita Vijayakumar1, Niousha Dehestani2, Samuel Berkins1, Timothy Silk1
Institutions:
1Centre for Social and Early Emotional Development and School of Psychology, Deakin University, Melbourne, Australia, 2School of Medicine, National University of Singapore, Singapore, Singapore, Singapore
First Author:
Soudeh Ashrafipour
Centre for Social and Early Emotional Development and School of Psychology, Deakin University
Melbourne, Australia
Centre for Social and Early Emotional Development and School of Psychology, Deakin University
Melbourne, Australia
Co-Author(s):
Nandita Vijayakumar
Centre for Social and Early Emotional Development and School of Psychology, Deakin University
Melbourne, Australia
Centre for Social and Early Emotional Development and School of Psychology, Deakin University
Melbourne, Australia
Niousha Dehestani
School of Medicine, National University of Singapore, Singapore
Singapore, Singapore
School of Medicine, National University of Singapore, Singapore
Singapore, Singapore
Samuel Berkins
Centre for Social and Early Emotional Development and School of Psychology, Deakin University
Melbourne, Australia
Centre for Social and Early Emotional Development and School of Psychology, Deakin University
Melbourne, Australia
Timothy Silk
Centre for Social and Early Emotional Development and School of Psychology, Deakin University
Melbourne, Australia
Centre for Social and Early Emotional Development and School of Psychology, Deakin University
Melbourne, Australia
Introduction:
Puberty is a key developmental milestone, driven by the release of pubertal hormones that lead to observable physical changes. Puberty unfolds in two phases: adrenarche and gonadarche, each reflecting unique aspects of pubertal development and exerting profound impacts on the brain [3,6]. Although adolescents progress through the same stages of puberty, there is significant interindividual variability regarding the timing of these stages [2]. Pubertal timing (PT)– pubertal status of an individual relative to their same-sex and same-age peers, has important implications for social and emotional outcomes, as well as the underlying brain structure. However, the influence of PT on brain functional connectivity (FC) remains understudied [5]. Investigating how PT affects changes of FC can provide insights into mechanisms underlying social and emotional outcomes [1]. This study aims to identify changes of resting-state FC (rs-FC) linked to PT, including the timing of adrenarche and gonadarche.
Methods:
Participants were drawn from the Adolescent Brain Cognitive Development (ABCD) study [4] which follows a diverse cohort of nearly 12,000 children, recruited from 21 sites across the United States. Participants were aged 9-10 years at baseline, and have since completed annual assessments of mental and physical health, and bi-annual MRI scans. To ensure a comprehensive representation of age and pubertal development, we examined development from baseline to 2nd-year follow-up for half the sample, and 2nd-year follow-up to 4th-year follow up for the other half of the sample. The final sample comprised 1164 females and 1374 males. PT was calculated using Puberty Age Gap (PAG), a recent novel approach that applies principles from brain ageing [2]. Refer to Figure 1 for details on different PAGs calculated. It was calculated at either baseline or 2nd year follow-up for each individual. We utilized preprocessed, tabulated FC of cortical resting-state (rs) networks based on the Gordon atlas. Correlations between cortical networks were calculated, providing measures of inter-network and intra-network connectivity, and the difference of these correlations between two timepoints were utilized as an estimate of the change. Ordinary least squares (OLS) regression was used to examine the relationship between different PAGs and rs-FC changes among 12 networks. Separate models were run for each sex, with age included as a covariate. False Discovery Rate (FDR) correction was applied to adjust for multiple comparisons.
Results:
In females, greater Physical PAG was associated with decreased rs-FC between the Auditory (AD) and Dorsal Attention Networks (DLA, p = 0.036) and increased rs-FC between the Salience (SA) and Sensorimotor Mouth Networks (SMM, p = 0.036). Combined (PDS and hormone) PAG was also positively associated with rs-FC changes between the SA and Sensorimotor Mouth Networks (SMM, p = 0.017). PAG based on hormones did not reveal significant findings. When breaking puberty into the two phases, higher Gonadarche_PDS PAG was significantly associated with two Ventral Attention Network (VTA) connectivity patterns: decrease with the Sensorimotor Hand Network (SMH, p = 0.001) and increase with the Frontoparietal Network (FO, p = 0.001), however no significant patterns emerged for adrenarche. No significant main effect of PAG on rs-FC changes were found in males following FDR correction.
Conclusions:
The findings suggest that PT uniquely influences rs-FC patterns in females. The lack of significant effects in males may reflect their later puberty onset (1-2 years later than females). Effects in females appear to be driven by physical changes rather than hormones, with earlier PT linked to increased connectivity of higher-order networks. Significant results mainly involve connections between cognitive control and primary processing networks.
Lifespan Development:
Normal Brain Development: Fetus to Adolescence 1
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural) 2
Keywords:
Development
FUNCTIONAL MRI
Other - Resting-state Functional Connectivity, Puberty, Pubertal Timing
1|2Indicates the priority used for review
Abstract Information
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2. Dehestani, N., Vijayakumar, N., Ball, G., Mansour L, S., Whittle, S., & Silk, T. J. (2023). “Puberty age gap”: New method of assessing pubertal timing and its association with mental health problems. Molecular Psychiatry. https://doi.org/10.1038/s41380-023-02316-4
3. Dorn, L. D., & Biro, F. M. (2011). Puberty and Its Measurement: A Decade in Review. Journal of Research on Adolescence (Wiley-Blackwell), 21(1), 180–195. https://doi.org/10.1111/j.1532-7795.2010.00722.x
4. 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
5. Mendle, J., Beltz, A. M., Carter, R., & Dorn, L. D. (2019). Understanding Puberty and Its Measurement: Ideas for Research in a New Generation. Journal of Research on Adolescence: The Official Journal of the Society for Research on Adolescence, 29(1), 82–95. https://doi.org/10.1111/jora.12371
6. Vijayakumar, N., Op de Macks, Z., Shirtcliff, E. A., & Pfeifer, J. H. (2018). Puberty and the human brain: Insights into adolescent development. Neuroscience & Biobehavioral Reviews, 92, 417–436. https://doi.org/10.1016/j.neubiorev.2018.06.004