Centre for Pattern Recognition and Data Analytics (PRaDA), Deakin University, Geelong, Australia.
Centre for Molecular and Medical Research, Deakin University, Geelong, Australia.
Am J Med Genet B Neuropsychiatr Genet. 2019 Sep;180(6):377-389. doi: 10.1002/ajmg.b.32701. Epub 2018 Dec 6.
Autism spectrum disorder (ASD) is a markedly heterogeneous condition with a varied phenotypic presentation. Its high concordance among siblings, as well as its clear association with specific genetic disorders, both point to a strong genetic etiology. However, the molecular basis of ASD is still poorly understood, although recent studies point to the existence of sex-specific ASD pathophysiologies and biomarkers. Despite this, little is known about how exactly sex influences the gene expression signatures of ASD probands. In an effort to identify sex-dependent biomarkers and characterize their function, we present an analysis of a single paired-end postmortem brain RNA-Seq data set and a meta-analysis of six blood-based microarray data sets. Here, we identify several genes with sex-dependent dysregulation, and many more with sex-independent dysregulation. Moreover, through pathway analysis, we find that these sex-independent biomarkers have substantially different biological roles than the sex-dependent biomarkers, and that some of these pathways are ubiquitously dysregulated in both postmortem brain and blood. We conclude by synthesizing the discovered biomarker profiles with the extant literature, by highlighting the advantage of studying sex-specific dysregulation directly, and by making a call for new transcriptomic data that comprise large female cohorts.
自闭症谱系障碍 (ASD) 是一种表现明显异质性的疾病。其在兄弟姐妹中的高一致性,以及与特定遗传疾病的明确关联,都指向强烈的遗传病因。然而,尽管最近的研究指出了存在性别特异性 ASD 病理生理学和生物标志物,但 ASD 的分子基础仍知之甚少。尽管如此,人们对性别究竟如何影响 ASD 患者的基因表达特征知之甚少。为了确定性别依赖性生物标志物并描述其功能,我们对一个单一的配对端死后大脑 RNA-Seq 数据集进行了分析,并对六个基于血液的微阵列数据集进行了荟萃分析。在这里,我们确定了几个具有性别依赖性失调的基因,还有更多的基因具有性别独立性失调。此外,通过途径分析,我们发现这些性别独立性生物标志物的生物学作用与性别依赖性生物标志物有很大的不同,而且这些途径中的一些在死后大脑和血液中普遍失调。最后,我们通过将发现的生物标志物谱与现有文献综合起来,通过强调直接研究性别特异性失调的优势,并呼吁包含大量女性队列的新转录组数据,来结束这篇文章。