Characteristics and predictive value of blood transcriptome signature in males with autism spectrum disorders.
Characteristics and predictive value of blood transcriptome signature in males with autism spectrum disorders.
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DOI：
10.1371/journal.pone.0049475
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发表时间：
2012
期刊：
影响因子：
3.7
通讯作者：
Kohane IS
中科院分区：
文献类型：
--
作者：
Kong SW;Collins CD;Shimizu-Motohashi Y;Holm IA;Campbell MG;Lee IH;Brewster SJ;Hanson E;Harris HK;Lowe KR;Saada A;Mora A;Madison K;Hundley R;Egan J;McCarthy J;Eran A;Galdzicki M;Rappaport L;Kunkel LM;Kohane IS
自闭症谱系障碍（ASD）是一种高度遗传的神经发育障碍，其中已知的突变在20%的病例中导致疾病风险。在这里，我们报告了迄今为止最大的血液转录组研究的结果，旨在确定170例ASD病例和115例年龄/性别匹配对照的差异，并评估基因表达谱作为辅助ASD诊断工具的实用性。差异表达的基因被富集为神经营养因子信号传导、长时程增强/抑制和notch信号传导途径。我们开发了一个55个基因的预测模型，使用交叉验证策略，对66名男性ASD病例和33名年龄匹配的男性对照（P1）的样本队列。随后，招募了104例ASD病例和82例对照，并用作验证集（P2）。该55个基因表达特征在验证组中实现了68%的分类准确度（受试者工作特征曲线下面积（AUC）：0.70 [95%置信区间[CI]：0.62-0.77]）。毫不奇怪，我们用男性样本构建和训练的预测模型对男性表现良好（AUC 0.73，95% CI 0.65-0.82），但对女性样本表现不佳（AUC 0.51，95% CI 0.36-0.67）。当用P2男性样本训练预测模型以对P1样本进行分类时，55个基因签名也表现稳健（AUC 0.69，95%CI 0.58-0.80）。我们的研究结果表明，使用血液表达谱检测ASD可能是可行的。需要进一步的研究来确定应该部署这种测试的年龄，以及可以识别ASD的遗传特征。
Autism Spectrum Disorders (ASD) is a spectrum of highly heritable neurodevelopmental disorders in which known mutations contribute to disease risk in 20% of cases. Here, we report the results of the largest blood transcriptome study to date that aims to identify differences in 170 ASD cases and 115 age/sex-matched controls and to evaluate the utility of gene expression profiling as a tool to aid in the diagnosis of ASD. The differentially expressed genes were enriched for the neurotrophin signaling, long-term potentiation/depression, and notch signaling pathways. We developed a 55-gene prediction model, using a cross-validation strategy, on a sample cohort of 66 male ASD cases and 33 age-matched male controls (P1). Subsequently, 104 ASD cases and 82 controls were recruited and used as a validation set (P2). This 55-gene expression signature achieved 68% classification accuracy with the validation cohort (area under the receiver operating characteristic curve (AUC): 0.70 [95% confidence interval [CI]: 0.62–0.77]). Not surprisingly, our prediction model that was built and trained with male samples performed well for males (AUC 0.73, 95% CI 0.65–0.82), but not for female samples (AUC 0.51, 95% CI 0.36–0.67). The 55-gene signature also performed robustly when the prediction model was trained with P2 male samples to classify P1 samples (AUC 0.69, 95% CI 0.58–0.80). Our result suggests that the use of blood expression profiling for ASD detection may be feasible. Further study is required to determine the age at which such a test should be deployed, and what genetic characteristics of ASD can be identified.
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影响因子：
14.9
作者：
Basu SN;Kollu R;Banerjee-Basu S
通讯作者：
Banerjee-Basu S
影响因子：
15.1
作者：
Enstrom, Amanda M.;Lit, Lisa;Onore, Charity E.;Gregg, Jeff P.;Hansen, Robin L.;Pessah, Isaac N.;Hertz-Picciotto, Irva;Van de Water, Judy A.;Sharp, Frank R.;Ashwood, Paul
通讯作者：
Ashwood, Paul
影响因子：
5.2
作者：
Castermans, Dries;Vermeesch, Joris R.;Devriendt, Koen
通讯作者：
Devriendt, Koen
影响因子：
4.5
作者：
Chow ML;Pramparo T;Winn ME;Barnes CC;Li HR;Weiss L;Fan JB;Murray S;April C;Belinson H;Fu XD;Wynshaw-Boris A;Schork NJ;Courchesne E
通讯作者：
Courchesne E
影响因子：
4.4
作者：
Griggs, Bradley L.;Ladd, Sydney;Srivastava, Arland K.
通讯作者：
Srivastava, Arland K.