Dataset Information

Age-Related Variations in Regional White Matter Volumetry and Microstructure During the Post-adolescence Period: A Cross-Sectional Study of a Cohort of 1,713 University Students.

ABSTRACT: Human brain white matter undergoes a protracted maturation that continues well into adulthood. Recent advances in diffusion-weighted imaging (DWI) methods allow detailed characterizations of the microstructural architecture of white matter, and they are increasingly utilized to study white matter changes during development and aging. However, relatively little is known about the late maturational changes in the microstructural architecture of white matter during post-adolescence. Here we report on regional changes in white matter volume and microstructure in young adults undergoing university-level education. As part of the MRi-Share multi-modal brain MRI database, multi-shell, high angular resolution DWI data were acquired in a unique sample of 1,713 university students aged 18-26. We assessed the age and sex dependence of diffusion metrics derived from diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) in the white matter regions as defined in the John Hopkins University (JHU) white matter labels atlas. We demonstrate that while regional white matter volume is relatively stable over the age range of our sample, the white matter microstructural properties show clear age-related variations. Globally, it is characterized by a robust increase in neurite density index (NDI), and to a lesser extent, orientation dispersion index (ODI). These changes are accompanied by a decrease in diffusivity. In contrast, there is minimal age-related variation in fractional anisotropy. There are regional variations in these microstructural changes: some tracts, most notably cingulum bundles, show a strong age-related increase in NDI coupled with decreases in radial and mean diffusivity, while others, mainly cortico-spinal projection tracts, primarily show an ODI increase and axial diffusivity decrease. These age-related variations are not different between males and females, but males show higher NDI and ODI and lower diffusivity than females across many tracts. These findings emphasize the complexity of changes in white matter structure occurring in this critical period of late maturation in early adulthood.

SUBMITTER: Tsuchida A

PROVIDER: S-EPMC8369154 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundWhite matter hyperintensities (WMHs) and regional brain lobe atrophy coexist in the brain of patients with Alzheimer's disease (AD), but the association between them in patients with AD still lacks comprehensive investigation and solid imaging data support.ObjectiveWe explored whether WMHs can promote the pathological process of AD by aggravating atrophy in specific brain regions and tried to explain the regional specificity of these relationships.MethodsA sample of 240 adults including 180 normal controls (NCs) and 80 cases with AD were drawn from the ADNI database. T1-weighted magnetic resonance imaging (MRI) and T2-weighted fluid-attenuated MRI of the participants were downloaded and were analyzed using AccuBrain® to generate the quantitative ratio of WMHs (WMHr, WMH volumes corrected by intracranial volume) and regional brain atrophy. We also divided WMHr into periventricular WMHr (PVWMHr) and deep WMHr (DWMHr) for the purpose of this study. The Cholinergic Pathways Hyperintensities Scale (CHIPS) scores were conducted by two evaluators. Independent t-test, Mann-Whitney U test, or χ2 test were used to compare the demographic characteristics, and Spearman correlation coefficient values were used to determine the association between WMHs and different regions of brain atrophy.ResultsPositive association between WMHr and quantitative medial temporal lobe atrophy (QMTA) (r s = 0.281, p = 0.011), temporal lobe atrophy (r s = 0.285, p = 0.011), and insular atrophy (r s = 0.406, p < 0.001) was found in the AD group before Bonferroni correction. PVWMHr contributed to these correlations. By separately analyzing the relationship between PVWMHr and brain atrophy, we found that there were still positive correlations after correction in QMTA (r s = 0.325, p = 0.003), temporal lobe atrophy (r s = 0.298, p = 0.007), and insular atrophy (r s = 0.429, p < 0.001) in AD group.ConclusionWMH severity tends to be associated with regional brain atrophy in patients with AD, especially with medial temporal lobe, temporal lobe, and insular lobe atrophy. PVWMHs were devoted to these correlations.

Project description:BackgroundAdolescence is a critical time for brain development. Findings from previous studies have been inconsistent, failing to distinguish the influence of pubertal status and aging on brain maturation. The current study sought to address these inconsistencies, addressing the trajectories of pubertal development and aging by longitudinally tracking structural brain development during adolescence.MethodsTwo cohorts of healthy children were recruited (cohort 1: 9-10 years old; cohort 2: 12-13 years old at baseline). MRI data were acquired for gray matter volume and white matter tract measures. To determine whether age, pubertal status, both or their interaction best modelled longitudinal data, we compared four multi-level linear regression models to the null model (general brain growth indexed by total segmented volume) using Bayesian model selection.ResultsData were collected at baseline (n = 116), 12 months (n = 97) and 24 months (n = 84) after baseline. Findings demonstrated that the development of most regional gray matter volume, and white matter tract measures, were best modelled by age. Interestingly, precentral and paracentral regions of the cortex, as well as the accumbens demonstrated significant preference for the pubertal status model. None of the white matter tract measures were better modelled by pubertal status.LimitationsThe major limitation of this study is the two-cohort recruitment. Although this allowed a faster coverage of the age span, a complete per person trajectory over 6 years of development (9-15 years) could not be investigated.ConclusionsComparing the impact of age and pubertal status on regional gray matter volume and white matter tract measures, we found age to best predict longitudinal changes. Further longitudinal studies investigating the differential influence of puberty status and age on brain development in more diverse samples are needed to replicate the present results and address mechanisms underlying norm-variants in brain development.

Dataset Information

Age-Related Variations in Regional White Matter Volumetry and Microstructure During the Post-adolescence Period: A Cross-Sectional Study of a Cohort of 1,713 University Students.

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