Gene-Network Analysis Identifies Susceptibility Genes Related to Glycobiology in Autism

The recent identification of copy-number variation in the human genome has opened up new avenues for the discovery of positional candidate genes underlying complex genetic disorders, especially in the field of psychiatric disease. One major challenge that remains is pinpointing the susceptibility genes in the multitude of disease-associated loci. This challenge may be tackled by reconstruction of functional gene-networks from the genes residing in these loci. We applied this approach to autism spectrum disorder (ASD), and identified the copy-number changes in the DNA of 105 ASD patients and 267 healthy individuals with Illumina Humanhap300 Beadchips. Subsequently, we used a human reconstructed gene-network, Prioritizer, to rank candidate genes in the segmental gains and losses in our autism cohort. This analysis highlighted several candidate genes already known to be mutated in cognitive and neuropsychiatric disorders, including RAI1, BRD1, and LARGE. In addition, the LARGE gene was part of a sub-network of seven genes functioning in glycobiology, present in seven copy-number changes specifically identified in autism patients with limited co-morbidity. Three of these seven copy-number changes were de novo in the patients. In autism patients with a complex phenotype and healthy controls no such sub-network was identified. An independent systematic analysis of 13 published autism susceptibility loci supports the involvement of genes related to glycobiology as we also identified the same or similar genes from those loci. Our findings suggest that the occurrence of genomic gains and losses of genes associated with glycobiology are important contributors to the development of ASD

A co-segregating microduplication of chromosome 15q11.2 pinpoints two risk genes for autism spectrum disorder

High resolution genomic copy-number analysis has shown that inherited and de novo copy-number variations contribute significantly to autism pathology, and that identification of small chromosomal aberrations related to autism will expedite the discovery of risk genes involved. Here, we report a microduplication of chromosome 15q11.2, spanning only four genes, co-segregating with autism in a Dutch pedigree, identified by SNP microarray analysis, and independently confirmed by FISH and MLPA analysis. Quantitative RT-PCR analysis revealed over 70% increase in peripheral blood mRNA levels for the four genes present in the duplicated region in patients, and RNA in situ hybridization on mouse embryonic and adult brain sections revealed that two of the four genes, CYFIP1 and NIPA1, were highly expressed in the developing mouse brain. These findings point towards a contribution of microduplications at chromosome 15q11.2 to autism, and highlight CYFIP1 and NIPA1 as autism risk genes functioning in axonogenesis and synaptogenesis. Thereby, these findings further implicate defects in dosage-sensitive molecular control of neuronal connectivity in autism. However, the prevalence of this microduplication in patient samples was statistically not significantly different from control samples (0.94%in patients vs. 0.42%controls, P=0.247), which suggests that our findings should be interpreted with caution and indicates the need for studies that include large numbers of control subjects to ascertain the impact of these changes on a population scale

Gene-network analysis identifies susceptibility genes related to glycobiology in autism.

The recent identification of copy-number variation in the human genome has opened up new avenues for the discovery of positional candidate genes underlying complex genetic disorders, especially in the field of psychiatric disease. One major challenge that remains is pinpointing the susceptibility genes in the multitude of disease-associated loci. This challenge may be tackled by reconstruction of functional gene-networks from the genes residing in these loci. We applied this approach to autism spectrum disorder (ASD), and identified the copy-number changes in the DNA of 105 ASD patients and 267 healthy individuals with Illumina Humanhap300 Beadchips. Subsequently, we used a human reconstructed gene-network, Prioritizer, to rank candidate genes in the segmental gains and losses in our autism cohort. This analysis highlighted several candidate genes already known to be mutated in cognitive and neuropsychiatric disorders, including RAI1, BRD1, and LARGE. In addition, the LARGE gene was part of a sub-network of seven genes functioning in glycobiology, present in seven copy-number changes specifically identified in autism patients with limited co-morbidity. Three of these seven copy-number changes were de novo in the patients. In autism patients with a complex phenotype and healthy controls no such sub-network was identified. An independent systematic analysis of 13 published autism susceptibility loci supports the involvement of genes related to glycobiology as we also identified the same or similar genes from those loci. Our findings suggest that the occurrence of genomic gains and losses of genes associated with glycobiology are important contributors to the development of ASD