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Comparative Study
.2011 Mar;68(3):295-305.
doi: 10.1001/archgenpsychiatry.2010.153. Epub 2010 Nov 1.

Neuroanatomical differences in toddler boys with fragile x syndrome and idiopathic autism

Affiliations
Comparative Study

Neuroanatomical differences in toddler boys with fragile x syndrome and idiopathic autism

Fumiko Hoeft et al. Arch Gen Psychiatry.2011 Mar.

Abstract

Context: Autism is an etiologically heterogeneous neurodevelopmental disorder for which there is no known unifying etiology or pathogenesis. Many conditions of atypical development can lead to autism, including fragile X syndrome (FXS), which is presently the most common known single-gene cause of autism.

Objective: To examine whole-brain morphometric patterns that discriminate young boys with FXS from those with idiopathic autism (iAUT) as well as control participants.

Design: Cross-sectional, in vivo neuroimaging study.

Setting: Academic medical centers.

Patients: Young boys (n = 165; aged 1.57-4.15 years) diagnosed as having FXS or iAUT as well as typically developing and idiopathic developmentally delayed controls.

Main outcome measures: Univariate voxel-based morphometric analyses, voxel-based morphometric multivariate pattern classification (linear support vector machine), and clustering analyses (self-organizing map).

Results: We found that frontal and temporal gray and white matter regions often implicated in social cognition, including the medial prefrontal cortex, orbitofrontal cortex, superior temporal region, temporal pole, amygdala, insula, and dorsal cingulum, were aberrant in FXS and iAUT as compared with controls. However, these differences were in opposite directions for FXS and iAUT relative to controls; in general, greater volume was seen in iAUT compared with controls, who in turn had greater volume than FXS. Multivariate analysis showed that the overall pattern of brain structure in iAUT generally resembled that of the controls more than FXS, both with and without AUT.

Conclusions: Our findings demonstrate that FXS and iAUT are associated with distinct neuroanatomical patterns, further underscoring the neurobiological heterogeneity of iAUT.

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Figures

Figure 1
Figure 1. Differences in regional brain volumes between groups
a. Regions that show significant differences in regional grey matter volume (GMV) and white matter volume (WMV) between fragile X syndrome (FXS) and idiopathic autism (iAUT) (a-i), FXS and typically developing (TD) as well as idiopathic developmentally delayed (DD) controls (a-ii), and iAUT and TD/DD controls (a-iii).b-i. Brain regions that show similar regional brain volumes for iAUT and TD/DD controls compared to FXS. (GMV: red, WMV: violet), and for TD/DD and iAUT compared to FXS (GMV: blue, WMV: cyan).b-ii. Brain regions that show similar regional brain volumes for FXS and iAUT compared to TD/DD controls. (GMV: red, WMV: violet). Overlaid on custom T1 template.c. Brain regions that show opposite regional volume patterns for FXS and iAUT. Left side shows right hemisphere. Statistical threshold is set at p = 0.01 family-wise error (FWE) cluster-level corrected.
Figure 2
Figure 2. Pattern classification results
a. Whole-brain representation of pattern classification results from FXS vs. iAUT using GM and WM voxels. Warm colors represent voxels with positive weight for the classification FXS vs. iAUT (FXS > iAUT) and cool colors represent negative weights (iAUT > FXS). Left side shows right hemisphere.b. Support vector machine (SVM) between-group classification accuracy using a combination of all GM and WM as features. Black dots indicate accuracy, red dashes indicate sensitivity, blue dashes indicate specificity and green dashes indicate positive predictive value (PPV).c. SVM classification accuracy for various control analyses. ForFXS+A vs iAUT we show accuracy for whole brain with dimensionality reduction using PCA (open circle), all behavior (first filled circle), and behavior using recursive feature elimination (RFE) (second filled circle). ForFXS vs iAUT we show accuracy for whole brain with dimensionality reduction using PCA (open circle), and using only the caudate and cerebellar vermis as features (filled circle). ForiAUT classified as TD/DD using the classifier fromFXS vs TD/DD we show accuracy for whole brain with dimensionality reduction using PCA (filled circle). ForiAUT vs TD/DD we show accuracy for whole brain with dimensionality reduction using PCA (open circle), only those areas significant in univariate VBM analyses (first filled circle), and whole brain using RFE (second filled circle).d. Overlay of univariate and SVM analyses from the FXS vs. iAUT contrast for GM (SVM weights thresholded based on p = 0.05 permutation-based correction).e. Brain-based representations of the four groups (TD, DD, FXS and iAUT) using a self-organizing map (SOM). Solid lines: Euclidian distance > 1.
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Comment in

References

    1. Association AP. Diagnostic and Statistical Manual of Mental Disorders DSM-IV-TR. Fourth Edition (Text Revision) Author; Washington DC: 2000.
    1. Hall SS, Lightbody AA, Hirt M, Rezvani A, Reiss AL. Autism in Fragile X Syndrome: A Category Mistake? J Am Acad Child Adolesc Psychiatry. 2010 Sep;49(9):921–933. - PMC - PubMed
    1. Hazlett HC, Poe M, Lightbody AA, et al. Teasing apart the heterogeneity of autism: Same behavior, different brains in toddlers with fragile X syndome and autism. Jourlan of Neurodevelopmental Disorders. 2009;1:81–90. - PMC - PubMed
    1. Wilson LB, Tregellas JR, Hagerman RJ, Rogers SJ, Rojas DC. A voxel-based morphometry comparison of regional gray matter between fragile X syndrome and autism. Psychiatry Res. 2009 Nov 30;174(2):138–145. - PMC - PubMed
    1. Geschwind DH, Levitt P. Autism spectrum disorders: developmental disconnection syndromes. Curr Opin Neurobiol. 2007 Feb;17(1):103–111. - PubMed

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