objective: To investigate any correlation between BMI and brain gray matter volume, we analyzed 1,428 healthy Japanese subjects by applying volumetric analysis and voxel-based morphometry (VBM) using brain magnetic resonance (MR) imaging, which enables a global analysis of brain structure without a priori identification of a region of interest. Methods and Procedures:We collected brain MR images from 690 men and 738 women, and their height, weight, and other clinical information. The collected images were automatically normalized into a common standard space for an objective assessment of neuroanatomical correlations in volumetric analysis and VBM with BMI. Results: Volumetric analysis revealed a significant negative correlation in men (P < 0.001, adjusting for age, lifetime alcohol intake, history of hypertension, and diabetes mellitus), although not in women, between BMI and the gray matter ratio, which represents the percentage of gray matter volume in the intracranial volume. VBM revealed that, in men, the regional gray matter volume of the bilateral medial temporal lobes, anterior lobe of the cerebellum, occipital lobe, frontal lobe, precuneus, and midbrain showed significant negative correlations with BMI, while those of the bilateral inferior frontal gyri, posterior lobe of the cerebellum, frontal lobes, temporal lobes, thalami, and caudate heads showed significant positive correlations with BMI. Discussion: Global loss and regional alterations in gray matter volume occur in obese male subjects, suggesting that male subjects with a high BMI are at greater risk for future declines in cognition or other brain functions.
The aim of this study was to examine structural brain networks using regional gray matter volume, as well as to investigate changes in small-world and modular organization with normal aging. We constructed structural brain networks composed of 90 regions in young, middle, and old age groups. We randomly selected 350 healthy subjects for each group from a Japanese magnetic resonance image database. Structural brain networks in three age groups showed economical small-world properties, providing high global and local efficiency for parallel information processing at low connection cost. The small-world efficiency and node betweenness varied significantly and revealed a U- or inverted U-curve model tendency among three age groups. Results also demonstrated that structural brain networks exhibited a modular organization in which the connections between regions are much denser within modules than between them. The modular organization of structural brain networks was similar between the young and middle age groups, but quite different from the old group. In particular, the old group showed a notable decrease in the connector ratio and the intermodule connections. Combining the results of small-world efficiency, node betweenness and modular organization, we concluded that the brain network changed slightly, developing into a more distributed organization from young to middle age. The organization eventually altered greatly, shifting to a more localized organization in old age. Our findings provided quantitative insights into topological principles of structural brain networks and changes related to normal aging.
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