International Meeting for Autism Research: No Longer Massively Univariate: Quantifying Individual and Group Differences in White Matter Microstructure in Autism Vs. Typical Development

No Longer Massively Univariate: Quantifying Individual and Group Differences in White Matter Microstructure in Autism Vs. Typical Development

Friday, May 21, 2010
Franklin Hall B Level 4 (Philadelphia Marriott Downtown)
1:00 PM
J. Scott , Center for Biologics Evaluation and Research, U.S. Food and Drug Administration, Washington, DC
J. E. Lainhart , Psychiatry, University of Utah, Salt Lake City, UT
M. Lazar , Center for Biomedical Imaging, New York University School of Medicine, New York, NY
A. L. Alexander , Department of Medical Physics, Department of Psychiatry, Waisman Laboratory for Brain Imaging & Behavior, University of Wisconsin, Madison, WI
N. Lange , Departments of Psychiatry and Biostatistics, Harvard University, Belmont, MA
Background: Massively univariate voxel-based analysis unnecessarily limits the utility of diffusion tensor imaging to probe white matter microstructure (WMM) in autism. This method tests for a regional group difference first at a single voxel by ignoring all of its neighbors and then combines voxel-based statistics by simple averaging, ignoring spatial correlation and heterogeneity within subjects and between groups. Such disregard can increase false positive and false negative rates, yielding misleading conclusions regarding the fiber organization of the autistic brain.

Objectives: We sought to determine if and how spatial correlation and variance heterogeneity affect estimated individual and group differences in corpus callosum WMM in autism.

Methods: We examined the voxel-wise mean and variance of fractional anisotropy (FA) and a novel full tensor measure (MV) in the genu and splenium in a sample of N=80 children and young adults (mean age 14.1 years) with ASD and N=40 typically-developing matched controls (mean age 15.5 years). We compared results from models that assumed intra-subject, inter-subject and inter-group variances to be equal or unequal across subjects and between groups. All models accounted for inter-voxel correlation in each subject.

Results: After accounting for group mean differences, we found that inter-subject variance was significantly high in splenium FA (χ2=6.0, df=1, p=0.01 and genu MV (χ2=17.4, df=6, p<0.01). Second, we found that autism subjects had significantly greater intra-subject FA variance in these regions (χ2=16.7, df=1, p<0.0001; χ2= 44.2, df=1, p<0.0001) and significantly greater MV variance as well (χ2= 263.2, df=6, p<0.0001; χ2=117.2, df=6, p<0.0001) in autism. Last, we observed substantially more coherent clustering of FA, MV and their group differences by accounting for inter-voxel correlation compared to those derived by a massively univariate approach.

Conclusions: Our results suggest that WMM in the genu and splenium of the adolescent male with high-functioning autism is more heterogeneous than that of his typically developing counterpart. There is a high likelihood of decreased consistency of directional diffusion coherence in the corpus callosum of an individual with autism and between individuals with autism, perhaps due to genetic and/or epigenetic dysregulation in brain development. In addition to the first-order (mean) decreases in directional diffusion coherence between groups reported previously, these second-order (variance) deviations suggest that a variety of disruptions of fiber organization may affect the quality of inter-hemispheric information transfer and perhaps language and social functioning. Our novel method demonstrated that (1) when testing for group differences in WMM, particularly in the corpus callosum and possibly other brain regions, one should acknowledge the correlation and increased variance of voxel-wise tensor measures in autism relative to measures in healthy populations; and (2) the detection of a regional group difference at a single voxel that acknowledges regional voxel-wise correlations outperforms widely-used approaches that ignore them.

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