3D pattern of brain abnormalities in Fragile X syndrome visualized using tensor-based morphometry.

Neuroimage

Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, 635 Charles E. Young Drive South, Suite 225E, Los Angeles, CA 90095-7332, USA.

Published: February 2007

Fragile X syndrome (FraX), a genetic neurodevelopmental disorder, results in impaired cognition with particular deficits in executive function and visuo-spatial skills. Here we report the first detailed 3D maps of the effects of the Fragile X mutation on brain structure, using tensor-based morphometry. TBM visualizes structural brain deficits automatically, without time-consuming specification of regions-of-interest. We compared 36 subjects with FraX (age: 14.66+/-1.58 S.D., 18 females/18 males), and 33 age-matched healthy controls (age: 14.67+/-2.2 S.D., 17 females/16 males), using high-dimensional elastic image registration. All 69 subjects' 3D T1-weighted brain MRIs were spatially deformed to match a high-resolution single-subject average MRI scan in ICBM space, whose geometry was optimized to produce a minimal deformation target. Maps of the local Jacobian determinant (expansion factor) were computed from the deformation fields. Statistical maps showed increased caudate (10% higher; p = 0.001) and lateral ventricle volumes (19% higher; p = 0.003), and trend-level parietal and temporal white matter excesses (10% higher locally; p = 0.04). In affected females, volume abnormalities correlated with reduction in systemically measured levels of the Fragile X mental retardation protein (FMRP; Spearman's r < -0.5 locally). Decreased FMRP correlated with ventricular expansion (p = 0.042; permutation test), and anterior cingulate tissue reductions (p = 0.0026; permutation test) supporting theories that FMRP is required for normal dendritic pruning in fronto-striatal-limbic pathways. No sex differences were found; findings were confirmed using traditional volumetric measures in regions of interest. Deficit patterns were replicated by performing statistics after logarithmic transformation, which may be more appropriate for tensor-valued data. Investigation of how these anomalies emerge over time will accelerate our understanding of FraX and its treatment.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1995408PMC
http://dx.doi.org/10.1016/j.neuroimage.2006.09.043DOI Listing

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