Autism specific patterns of DNA methylation from birth to age 5

项目总结 自闭症谱系障碍(ASD)是一种神经发育疾病，影响多达2%的美国儿童。 自闭症残疾对患有自闭症的个人及其家人和 社区。与自闭症相关的残疾每年的估计成本超过2500亿美元。最近的研究结果表明 表明早期发现和干预可以最大限度地减少ASD残疾的影响，最大限度地提高儿童的 发展潜力，并最终改善长期成果。然而，目前还没有可靠的标记 存在在24个月以下儿童中检测ASD的情况，但ASD的平均诊断年龄仍在徘徊 这项研究的目标是通过评估早期生命DNA 血液中的甲基化(DNaM)模式反映了ASD的后期诊断。 我们和其他人之前的研究发现，年龄较大的儿童和患有ASD的成年人的dNaM发生了变化 诊断。然而，目前尚不清楚这些差异是否存在于婴儿期，并可能作为一种 早期生活自闭症风险生物标志物。此外，尽管有强有力的证据表明表观遗传学与自闭症有关，但大多数研究 专注于识别与自闭症相关的特定基因座--只有一项研究考虑了表观遗传学的变化 衰老途径，据我们所知，没有人研究过与ASD相关的全球dNaM变化。最后，不 研究已经测试了与ASD相关的dNaM的纵向变化。在这里，我们克服了以前的研究 利用一项独特的以美国人群为基础的自闭症婴儿医疗卡研究的局限性(Pre-the 并在5岁时采集血液(诊断后)。这使我们能够评估预期和 纵向dNaM与ASD的相关性。我们在210上使用现有的(n=968)和新生成的dNaM数据 受试者检验我们的假设，即婴儿血液dNaM模式与后来的ASD诊断有关，并且 纵向dNaM改变伴随着ASD征象的出现。使用收集到的样本 在接近出生时和5岁时，我们将估计差异：(1)出生时和出生时的医用棒状血斑dNaM (1B)在有ASD诊断的儿童和没有ASD的儿童之间，从出生到5岁的纵向dNaM模式 5岁。在目标2中，我们将测试表观遗传年龄加速/减速：(2A)出生时，(2B)纵向 从出生到5岁，在5岁时有ASD诊断的儿童和没有ASD的儿童之间有任何显著的联系 将接受二次分析，以测试已确定的dNaM变化是特定于ASD还是也 在有其他发育障碍的SEED儿童中存在。 这一R21机制提供了所需的早期概念支持，以确定这一领域是否 研究需要对更大的样本进行进一步检查，其中可能包括约4000个种子样本。这个 这项研究的结果可能最终会影响儿童的健康，因为它提供了一个早期生命DNA甲基化标记 ASD风险，为未来的干预策略提供信息。此外，我们在早期发现的动态dNaM变化 更广泛地说，生活可能对儿童的其他健康结果很重要。

PROJECT SUMMARY Autism spectrum disorder (ASD) is a neurodevelopmental condition that affects up to 2% of U.S. children. ASD disabilities have substantial adverse impacts on individuals living with ASD and their families and communities. The estimated annual cost of ASD related disabilities exceeds $250 billion. Recent findings have shown that early detection and intervention can minimize the impact of ASD disabilities, maximize children’s developmental potential, and ultimately improve long-term outcomes. However, no reliable markers currently exist to detect ASD in children under the age of 24 months and the mean age of ASD diagnosis still hovers around age 5. The goal of this study is to address this critical need by evaluating whether early life DNA methylation (DNAm) patterns in blood reflect later ASD diagnosis. Previous studies, by us and others, have found DNAm changes in older children and adults with an ASD diagnosis. However, it isn’t clear whether these differences are present during infancy and may serve as an early life ASD risk biomarker. In addition, despite strong evidence for epigenetic links to ASD most studies have focused on identifying specific loci related to ASD - only one study considered changes in the epigenetic aging pathway and none to our knowledge have examined global DNAm changes related to ASD. Finally, no studies have tested for longitudinal changes in DNAm related to ASD. Here, we overcome previous study limitations by leveraging a unique US population-based study of ASD with infant heal-stick cards (pre- diagnosis) and blood collected at age 5 (post-diagnosis). This enables us to assess prospective and longitudinal DNAm associations with ASD. We use extant (n=968) and newly generated DNAm data on 210 subjects to test our hypotheses that infant blood DNAm patterns are related to later ASD diagnoses and that longitudinal DNAm changes occur concomitant with the emergence of ASD signs. Using samples collected near birth and again at age 5, we will estimate differences: (1A) in heal-stick blood spot DNAm at birth and (1B) in longitudinal DNAm patterns from birth to age 5 between children with and without an ASD diagnosis at age 5. In Aim 2, we will test for epigenetic age acceleration/deceleration: (2A) at birth, and (2B) longitudinally from birth to age 5 between children with and without an ASD diagnosis at age 5. Any significant associations will undergo secondary analyses to test whether the identified DNAm changes are specific to ASD or are also present in SEED children with other developmental disabilities. This R21 mechanism provides the early conceptual support needed to determine whether this area of research warrants further examination in a larger sample, which could include ~4,000 SEED samples. The results of this study may, ultimately, impact child health by providing an early life DNA methylation marker of ASD risk to inform future intervention strategies. Further, the dynamic DNAm changes we identify during early life will likely be important for other childhood health outcomes, more broadly.