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Background Angelman syndrome (AS) is a severe neurodevelopmental disorder caused by either disruptions of the gene UBE3A or deletion of chromosome 15 at 15q11-q13, which encompasses UBE3A and several other genes, including GABRB3, GABRA5, GABRG3, encoding gamma-aminobutyric acid type A receptor subunits ( β 3, α 5, γ 3). Individuals with deletions are generally more impaired than those with other genotypes, but the underlying pathophysiology remains largely unknown. Here, we used electroencephalography (EEG) to test the hypothesis that genes other than UBE3A located on 15q11-q13 cause differences in pathophysiology between AS genotypes. Methods We compared spectral power of clinical EEG recordings from children (1–18 years of age) with a deletion genotype (n = 37) or a nondeletion genotype (n = 21) and typically developing children without Angelman syndrome (n = 48). Results We found elevated theta power (peak frequency: 5.3 Hz) and diminished beta power (peak frequency: 23 Hz) in the deletion genotype compared with the nondeletion genotype as well as excess broadband EEG power (1–32 Hz) peaking in the delta frequency range (peak frequency: 2.8 Hz), shared by both genotypes but stronger for the deletion genotype at younger ages. Conclusions Our results provide strong evidence for the contribution of non-UBE3A neuronal pathophysiology in deletion AS and suggest that hemizygosity of the GABRB3-GABRA5-GABRG3 gene cluster causes abnormal theta and beta EEG oscillations that may underlie the more severe clinical phenotype. Our work improves the understanding of AS pathophysiology and has direct implications for the development of AS treatments and biomarkers.

Normal-appearing white matter has been shown via diffusion tensor imaging to be affected in tuberous sclerosis complex. Under the hypothesis that some systems might be differentially affected, including the visual pathways and systems of social cognition, diffusion properties of various regions of white matter were compared. For 10 patients and 6 age-matched control subjects, 3 T magnetic resonance imaging was assessed using diffusion tensor imaging obtained in 35 directions. Three-dimensional volumes corresponding to the geniculocalcarine tracts were extracted via tractography, and two-dimensional regions of interest were used to sample other regions. Regression analysis indicated lower fractional anisotropy in the splenium of corpus callosum and geniculocalcarine tracts in tuberous sclerosis complex group, as well as lower axial diffusivity in the internal capsule, superior temporal gyrus, and geniculocalcarine tracts. Mean and radial diffusivity of the splenium of corpus callosum were higher in the tuberous sclerosis complex group. The differences in diffusion properties of white matter between tuberous sclerosis complex patients and control subjects suggest disorganized and structurally compromised axons with poor myelination. The visual and social cognition systems appear to be differentially involved, which might in part explain the behavioral and cognitive characteristics of the tuberous sclerosis complex population. © 2010 Elsevier Inc. All rights reserved.

Background We have previously identified an association between lipids and features of diffusion tensor imaging in preterm infants, highlighting the KEGG peroxisome proliferator-activated receptor pathway (PPAR) as the most highly ranked in association with a white matter phenotype. Here we applied a penalised linear regression model—the graph-guided group lasso (GGGL)—to select single nucleotide polymorphisms within functionally related genes associated with the imaging trait. The GGGL model utilises network-based prior knowledge to improve the selection of variables of interest. Methods Images acquired with a 3T MR scanner were collected along with saliva for 72 preterm infants (mean gestational age 28 weeks [+4 days], mean postmenstrual age at scan 40 weeks [+3 days]). Salivary DNA was extracted and genotyped with HumanOmniExpress-12 arrays (Illumina, San Diego, CA, USA). Fractional anisotropy maps were constructed from diffusion tensor imaging, and tract-based spatial statistics were used to obtain a group white matter skeleton varying with degree of prematurity, adjusting for age at scan. GGGL was applied to the genes in the PPAR pathway. Findings The GGGL method selected five of the 69 genes in the PPAR pathway, and these were functionally related in terms of Gene Ontology Biological Process and linearly correlated with white matter fractional anisotropy ( AQP7, ME1, PLIN1, SLC27A1 , and ACAA1 ). Analysis of transcriptional regulation with the PASTAA algorithm indicated that ACAA1, AQP7, ME1 , and SLC27A1 were jointly regulated by the EGR4 transcription factor (adjusted p=7·7×10 −4 ). Interpretation Our GGGL analysis of genes in the PPAR pathway identified five highly ranked genes involved in neuronal growth, myelinogenesis, and nervous system response to inflammation, and jointly transcriptionally regulated. Since preterm infants are at increased risk of mental illness and cardiovascular morbidity in later life, this work uses an integrative data-driven strategy to propose a unifying mechanism for these systemic effects, suggesting a promising avenue for intervention. Funding Medical Research Council, National Institute for Health Research Biomedical Research Centre.