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Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3–90 years
Journal article   Open access

Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3–90 years

Danai Dima, Amirhossein Modabbernia, Efstathios Papachristou, Gaelle E Doucet, Ingrid Agartz, Moji Aghajani, Theophilus N Akudjedu, Anton Albajes Eizagirre, Dag Alnæs, Kathryn I Alpert, …
Human brain mapping, Vol.43(1), pp.452-469
02/11/2021
DOI: 10.1002/hbm.25320
PMCID: PMC8675429
PMID: 33570244
url
https://doi.org/10.1002/hbm.25320View
Published (Version of record) Open Access

Abstract

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.
Brain Edat Cervell Morphology (Biology) Morfologia (Biologia) Age ENIGMA brain morphometry longitudinal trajectories

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