Validation of a Salivary RNA Test for Childhood Autism Spectrum Disorder
Validation of a Salivary RNA Test for Childhood Autism Spectrum Disorder
复制标题
DOI：
10.3389/fgene.2018.00534
复制
发表时间：
2018-11-09
影响因子：
3.7
通讯作者：
Middleton, Frank A.
中科院分区：
文献类型：
--
作者：
Hicks, Steven D.;Rajan, Alexander T.;Middleton, Frank A.
背景：自闭症谱系障碍（ASD）的诊断依赖于行为评估。确定ASD生物标志物的努力尚未导致客观，可靠的测试。ASD中RNA水平的研究已经证明了潜在的实用性，但受到关注单一RNA类型，小样本量和缺乏发育延迟控制的限制。我们假设，唾液为基础的多“组”RNA面板可以客观地区分ASD儿童从他们的神经典型的同龄人和儿童与非ASD developmentaldelay.Methods：这个多中心的横断面研究包括456名儿童，年龄19-83个月。儿童为神经典型（n = 134）或诊断为ASD（n = 238）或非ASD发育迟缓（n = 84）。使用无偏的下一代测序在所有参与者的唾液中测量了全面的人类和微生物RNA丰度。在分析之前，将样本随机分为训练集（82%的受试者）和独立验证测试集（18%的受试者）。训练集用于开发基于RNA的算法，以区分ASD和非ASD儿童。模型开发中未使用验证集（特征选择或训练），但仅用于验证经验准确性。结果：在训练集中（n = 372;平均年龄51个月; 75%为男性; 51%ASD），一组32个RNA特征（对照人口统计学和医学特征），确定ASD状态，交叉验证曲线下面积（AUC）为0.87（95% CI：0.86-0.88）。在完全独立的验证测试集中（n = 84;平均年龄50个月; 85%男性; 60% ASD），该算法保持AUC为0.88（82%灵敏度和88%特异性）。值得注意的是，RNA功能牵连在ASD（轴突导向，神经营养信号）相关的生理过程。结论：唾液多组RNA测量代表了一种新的，非侵入性的方法，可以准确地识别儿童ASD。该技术可以提高ASD评估转诊的特异性或为ASD诊断提供客观支持。
Background: The diagnosis of autism spectrum disorder (ASD) relies on behavioral assessment. Efforts to define biomarkers of ASD have not resulted in an objective, reliable test. Studies of RNA levels in ASD have demonstrated potential utility, but have been limited by a focus on single RNA types, small sample sizes, and lack of developmental delay controls. We hypothesized that a saliva-based poly-"omic" RNA panel could objectively distinguish children with ASD from their neurotypical peers and children with non-ASD developmental delay.Methods: This multi-center cross-sectional study included 456 children, ages 19-83 months. Children were either neurotypical (n = 134) or had a diagnosis of ASD (n = 238), or non-ASD developmental delay (n = 84). Comprehensive human and microbial RNA abundance was measured in the saliva of all participants using unbiased next generation sequencing. Prior to analysis, the sample was randomly divided into a training set (82% of subjects) and an independent validation test set (18% of subjects). The training set was used to develop an RNA-based algorithm that distinguished ASD and non-ASD children. The validation set was not used in model development (feature selection or training) but served only to validate empirical accuracy.Results: In the training set (n = 372; mean age 51 months; 75% male; 51% ASD), a set of 32 RNA features (controlled for demographic and medical characteristics), identified ASD status with a cross-validated area under the curve (AUC) of 0.87 (95% CI: 0.86-0.88). In the completely separate validation test set (n = 84; mean age 50 months; 85% male; 60% ASD), the algorithm maintained an AUC of 0.88 (82% sensitivity and 88% specificity). Notably, the RNA features were implicated in physiologic processes related to ASD (axon guidance, neurotrophic signaling).Conclusion: Salivary poly-omic RNA measurement represents a novel, non-invasive approach that can accurately identify children with ASD. This technology could improve the specificity of referrals for ASD evaluation or provide objective support for ASD diagnoses.