Brain Chemistry in Adults with Autism Spectrum Disorder

Saturday, May 16, 2015: 11:30 AM-1:30 PM
Imperial Ballroom (Grand America Hotel)
N. M. Kleinhans1, N. M. Corrigan2, M. A. Reiter3, T. L. Richards3 and S. Dager1, (1)University of Washington, Seattle, WA, (2)Department of Radiology, University of Washington, Seattle, WA, (3)Radiology, University of Washington, Seattle, WA

Clinical research suggests that core ASD symptoms may be milder in adulthood than during early development.  An extant theory posits that behavioral improvements with age may be a result of maturation and the stabilization of disease processes. However, very little is known about the biochemical integrity of grey and white matter in adults with ASD, how these measures change with age, and how such indices of brain health are associated with the presentation of autism symptoms.  


1)    Determine whether abnormalities in white matter and grey matter are present in adults with ASD.

2)    Determine whether aberrant developmental trajectories are present in brain metabolites in ASD using a cross-sectional approach. 

3)    Determine whether grey matter and white matter integrity are associated with ASD symptomotology measured with the Autism Diagnostic Observation Schedule.


MRI (T1-weighted 3DMPRAGE and magnetic resonance spectroscopic imaging (MRSI; TE=19ms) data were acquired on a 3T Philips Achieva scanner for 18 adults with ASD and 22 age and IQ-matched typically developing controls (TD)[mean age: ASD=24.7(4.8), TD=24.2(3.8); mean FSIQ: ASD=114.1(9.7), TD=111.8(12.5)]. LCModel with water referencing and partial volume correction was used to obtain chemical estimates. T1-weighted images were segmented into gray matter, white matter, and cerebrospinal fluid compartments and coregistered with the spectroscopic images for computation of compartmental chemical concentrations.


MANOVAs for both compartments were conducted with diagnosis and age as independent variables, and with five metabolite concentrations as the dependent variables [choline (CHO), creatine (CRE), n-acetyl aspartate (NAA), myoinositol (INS), glutamate+glutamine (GLX)]. The grey matter analysis did not show a significant multivariate effect for the five metabolites in relation to diagnosis (ASD versus TD: p=.107), age (p=.057) or the age by diagnosis interaction (p=.094). The white matter analysis showed a significant multivariate effect for the five metabolites as a group in relation to diagnosis (ASD versus TD: Roy’s largest root = .556, F(6,30)=2.781,  p=.029) and the age of the participant (Roy’s largest root = .593, F(6,30)=2.965, p=.021). In addition, the interaction between age and diagnosis was significant (Roy’s largest root = .545, F(6,30)=2.727, p=.031). Follow-up univariate analyses of the metabolite concentrations in white matter indicated the interaction was significant for CHO (F(1,35)=5.758, p=.022) and INS (F(1,35)=7.975, p=.008), reflecting that for both CHO and INS, metabolite concentrations are increasing with age in the TD group but not in the ASD group.  Univariate analyses of the main effect of group also indicated that the ASD group had significantly higher levels of CHO (F(1,35)=5.854, p=.021) and INS (F(1,35)=8.780, p=.005), evaluated at age 24.4 years.  

Within the ASD group, individual differences in social dysfunction were correlated with CHO (r = .572, p = .013) and GLX (r = .497, p= .036), indicating that greater symptom severity was associated with higher metabolite levels in white matter.

Conclusions:  Adults with ASD appear to have white matter abnormalities characterized by elevated metabolite levels and an atypical developmental trajectory of metabolites associated with glial proliferation and membrane breakdown, inflammation, and demyelination. Concomitant changes in grey matter do not appear to be present.