Skafidas E, Testa R, Zantomio D, Chana G, Everall I P, Pantelis C
Centre for Neural Engineering, The University of Melbourne, Parkville, VIC, Australia.
1] Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Parkville, VIC, Australia [2] Department of Psychology, Monash University, Clayton, VIC, Australia.
Mol Psychiatry. 2014 Apr;19(4):504-10. doi: 10.1038/mp.2012.126. Epub 2012 Sep 11.
Autism spectrum disorder (ASD) depends on a clinical interview with no biomarkers to aid diagnosis. The current investigation interrogated single-nucleotide polymorphisms (SNPs) of individuals with ASD from the Autism Genetic Resource Exchange (AGRE) database. SNPs were mapped to Kyoto Encyclopedia of Genes and Genomes (KEGG)-derived pathways to identify affected cellular processes and develop a diagnostic test. This test was then applied to two independent samples from the Simons Foundation Autism Research Initiative (SFARI) and Wellcome Trust 1958 normal birth cohort (WTBC) for validation. Using AGRE SNP data from a Central European (CEU) cohort, we created a genetic diagnostic classifier consisting of 237 SNPs in 146 genes that correctly predicted ASD diagnosis in 85.6% of CEU cases. This classifier also predicted 84.3% of cases in an ethnically related Tuscan cohort; however, prediction was less accurate (56.4%) in a genetically dissimilar Han Chinese cohort (HAN). Eight SNPs in three genes (KCNMB4, GNAO1, GRM5) had the largest effect in the classifier with some acting as vulnerability SNPs, whereas others were protective. Prediction accuracy diminished as the number of SNPs analyzed in the model was decreased. Our diagnostic classifier correctly predicted ASD diagnosis with an accuracy of 71.7% in CEU individuals from the SFARI (ASD) and WTBC (controls) validation data sets. In conclusion, we have developed an accurate diagnostic test for a genetically homogeneous group to aid in early detection of ASD. While SNPs differ across ethnic groups, our pathway approach identified cellular processes common to ASD across ethnicities. Our results have wide implications for detection, intervention and prevention of ASD.
自闭症谱系障碍（ASD）的诊断依赖于临床访谈，且没有生物标志物辅助诊断。当前的研究对来自自闭症遗传资源交换库（AGRE）数据库的自闭症患者的单核苷酸多态性（SNP）进行了研究。将SNP映射到源自京都基因与基因组百科全书（KEGG）的通路，以识别受影响的细胞过程并开发一种诊断测试。然后将该测试应用于来自西蒙斯基金会自闭症研究计划（SFARI）和惠康信托1958年正常出生队列（WTBC）的两个独立样本进行验证。利用来自中欧（CEU）队列的AGRE SNP数据，我们创建了一个由146个基因中的237个SNP组成的遗传诊断分类器，该分类器在85.6%的CEU病例中正确预测了ASD诊断。该分类器在与CEU种族相关的托斯卡纳队列中也预测了84.3%的病例；然而，在遗传上不相似的汉族队列（HAN）中，预测准确性较低（56.4%）。三个基因（KCNMB4、GNAO1、GRM5）中的八个SNP在分类器中具有最大影响，其中一些作为易感性SNP，而其他则具有保护作用。随着模型中分析的SNP数量减少，预测准确性降低。我们的诊断分类器在来自SFARI（ASD）和WTBC（对照）验证数据集的CEU个体中，以71.7%的准确率正确预测了ASD诊断。总之，我们为一个基因同质群体开发了一种准确的诊断测试，以帮助早期检测ASD。虽然不同种族的SNP不同，但我们的通路方法确定了不同种族ASD共有的细胞过程。我们的结果对ASD的检测、干预和预防具有广泛的意义。
