Wall D P, Esteban F J, Deluca T F, Huyck M, Monaghan T, Velez de Mendizabal N, Goñí J, Kohane I S
Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA.
Genomics. 2009 Feb;93(2):120-9. doi: 10.1016/j.ygeno.2008.09.015. Epub 2008 Nov 12.
The behaviors of autism overlap with a diverse array of other neurological disorders, suggesting common molecular mechanisms. We conducted a large comparative analysis of the network of genes linked to autism with those of 432 other neurological diseases to circumscribe a multi-disorder subcomponent of autism. We leveraged the biological process and interaction properties of these multi-disorder autism genes to overcome the across-the-board multiple hypothesis corrections that a purely data-driven approach requires. Using prior knowledge of biological process, we identified 154 genes not previously linked to autism of which 42% were significantly differentially expressed in autistic individuals. Then, using prior knowledge from interaction networks of disorders related to autism, we uncovered 334 new genes that interact with published autism genes, of which 87% were significantly differentially regulated in autistic individuals. Our analysis provided a novel picture of autism from the perspective of related neurological disorders and suggested a model by which prior knowledge of interaction networks can inform and focus genome-scale studies of complex neurological disorders.
自闭症的行为与一系列其他神经疾病存在重叠，这表明存在共同的分子机制。我们对与自闭症相关的基因网络和其他432种神经疾病的基因网络进行了大规模比较分析，以界定自闭症的多疾病子成分。我们利用这些多疾病自闭症基因的生物学过程和相互作用特性，来克服纯数据驱动方法所需的全面多重假设校正。利用生物学过程的先验知识，我们鉴定出154个先前未与自闭症相关联的基因，其中42%在自闭症个体中显著差异表达。然后，利用来自与自闭症相关疾病的相互作用网络的先验知识，我们发现了334个与已发表的自闭症基因相互作用的新基因，其中87%在自闭症个体中显著差异调节。我们的分析从相关神经疾病的角度提供了自闭症的新图景，并提出了一个模型，通过该模型，相互作用网络的先验知识可以为复杂神经疾病的全基因组规模研究提供信息并聚焦研究重点。
