A meta-analysis of the corpus callosum in autism

Biol Psychiatry. 2009 Nov 15;66(10):935-41. doi: 10.1016/j.biopsych.2009.07.022. Epub 2009 Sep 12.


Background: Previous magnetic resonance imaging (MRI) studies have reported reductions in corpus callosum (CC) total area and CC regions in individuals with autism. However, studies have differed concerning the magnitude and/or region contributing to CC reductions. The present study determined the significance and magnitude of reductions in CC total and regional area measures in autism.

Method: PubMed and PsycINFO databases were searched to identify MRI studies examining corpus callosum area in autism. Ten studies contributed data from 253 patients with autism (mean age = 14.58, SD = 6.00) and 250 healthy control subjects (mean age = 14.47, SD = 5.31). Of these 10 studies, 8 reported area measurements for corpus callosum regions (anterior, mid/body, and posterior), and 6 reported area for Witelson subdivisions. Meta-analytic procedures were used to quantify differences in total and region CC area measurements.

Results: Total CC area was reduced in autism and the magnitude of the reduction was medium (weighted mean d = .48, 95% confidence interval [CI] = .30-.66). All regions showed reductions in size with the magnitude of the effect decreasing caudally (anterior d = .49, mid/body d = .43, posterior d = .37). Witelson subdivision 3 (rostral body) showed the largest effect, indicating greatest reduction in the region containing premotor/supplementary motor neurons.

Conclusions: Corpus callosum reductions are present in autism and support the aberrant connectivity hypothesis. Future diffusion tensor imaging studies examining specific fiber tracts connecting the hemispheres are needed to identify the cortical regions most affected by CC reductions.

Publication types

  • Meta-Analysis
  • Research Support, N.I.H., Extramural

MeSH terms

  • Adolescent
  • Autistic Disorder / pathology*
  • Child
  • Corpus Callosum / pathology*
  • Databases, Factual / statistics & numerical data
  • Female
  • Humans
  • Image Processing, Computer-Assisted / methods
  • Magnetic Resonance Imaging / methods
  • Male