Nature Communications (Jul 2024)

Investigating grey matter volumetric trajectories through the lifespan at the individual level

  • Runye Shi,
  • Shitong Xiang,
  • Tianye Jia,
  • Trevor W. Robbins,
  • Jujiao Kang,
  • Tobias Banaschewski,
  • Gareth J. Barker,
  • Arun L. W. Bokde,
  • Sylvane Desrivières,
  • Herta Flor,
  • Antoine Grigis,
  • Hugh Garavan,
  • Penny Gowland,
  • Andreas Heinz,
  • Rüdiger Brühl,
  • Jean-Luc Martinot,
  • Marie-Laure Paillère Martinot,
  • Eric Artiges,
  • Frauke Nees,
  • Dimitri Papadopoulos Orfanos,
  • Tomáš Paus,
  • Luise Poustka,
  • Sarah Hohmann,
  • Sabina Millenet,
  • Juliane H. Fröhner,
  • Michael N. Smolka,
  • Nilakshi Vaidya,
  • Henrik Walter,
  • Robert Whelan,
  • Gunter Schumann,
  • Xiaolei Lin,
  • Barbara J. Sahakian,
  • Jianfeng Feng,
  • IMAGEN Consortium

DOI
https://doi.org/10.1038/s41467-024-50305-0
Journal volume & issue
Vol. 15, no. 1
pp. 1 – 14

Abstract

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Abstract Adolescents exhibit remarkable heterogeneity in the structural architecture of brain development. However, due to limited large-scale longitudinal neuroimaging studies, existing research has largely focused on population averages, and the neurobiological basis underlying individual heterogeneity remains poorly understood. Here we identify, using the IMAGEN adolescent cohort followed up over 9 years (14–23 y), three groups of adolescents characterized by distinct developmental patterns of whole-brain gray matter volume (GMV). Group 1 show continuously decreasing GMV associated with higher neurocognitive performances than the other two groups during adolescence. Group 2 exhibit a slower rate of GMV decrease and lower neurocognitive performances compared with Group 1, which was associated with epigenetic differences and greater environmental burden. Group 3 show increasing GMV and lower baseline neurocognitive performances due to a genetic variation. Using the UK Biobank, we show these differences may be attenuated in mid-to-late adulthood. Our study reveals clusters of adolescent neurodevelopment based on GMV and the potential long-term impact.