Maternal health in pregnancy and autism risk - genetic and non-genetic mechanisms

自闭症谱系障碍(ASD)影响59名儿童中的1名，由遗传和环境共同引起。 各种因素。然而，这种疾病的可改变的风险因素仍然未知，造成了一个紧迫的公众 健康需要。由于自闭症可能在产前发育早期出现，因此在识别此类疾病方面付出了大量努力 可修改的风险因素侧重于孕妇在怀孕期间的暴露。其中一些研究表明 患有糖尿病、抑郁症或反复感染的妇女的子女患自闭症的比例较高。然而， (1)妇女在怀孕期间经历了许多其他情况，其中大多数没有在背景下进行研究 子代ASD风险的关系；以及(2)母体诊断与ASD之间关联的潜在机制 仍然不为人所知。而胎盘对母体循环中多种因素的渗透性直接影响 孕妇的健康对胎儿的影响似乎是合理的，但这种解释并没有经过严格的评估，因为 母亲的诊断和儿童的ASD都是由重叠的遗传因素引起的，从母亲传染给 那个孩子。对此，我们建议的主要目标是：(1)检验产妇健康之间的联系 和自闭症系统地，跨越整个母体诊断的范围，并考虑到它们的相关性， 以及(2)阐明这些关联背后的遗传和/或非遗传机制。为了实现这一目标， 我们提出独立的，但协同的，旨在增加我们的结果的可靠性和普适性。 目的1：系统识别妊娠期与子代ASD相关的母体诊断。目标2： 确定母亲的诊断和自闭症之间的联系是否由于遗传因素传播，使用 丹麦有关于家庭关系的信息。目标3：测试产妇诊断之间的关联 利用分子遗传学数据研究妊娠和儿童对自闭症的遗传易感性。我们将使用大型、马力强大的 来自丹麦的72.3万名活产婴儿样本，包含完整的人口统计、医学和血统信息，以及 这些个体(N~26k)的子集的遗传数据。所有重要的关联都将在 美国数据集(Kaiser Permanente North California)，出生约32万，确保我们的外部有效性 结果。该项目的创新有三个方面：(1)它具有识别新风险因素的潜力(如图所示 我们的初步数据)，(2)它引入了ASD流行病学的方法转变，大规模的暴露- 广泛而严格的推理过程，类似于已经应用于遗传学领域的过程；以及(3)第一次， 它将来自北欧登记处的国家数据与美国最大的队列之一(Kaiser Permanente)整合在一起。 该项目将提供与怀孕相关的高信度、孕产妇诊断的系统清单 在两个独立的队列中存在ASD风险，以及关于遗传和非遗传的三角证据 将怀孕期间的这些诊断与后代患ASD的风险联系起来的机制。总体而言，这些产出将 对ASD的病因提出新的见解，提出潜在的预防因素，并帮助努力实现早期 识别高危家庭。

Autism spectrum disorder (ASD) affects 1 in 59 children1, and is caused by both genetic and environmental factors. Nevertheless, the modifiable risk factors for this disorder remain unknown, creating a pressing public health need. As ASD likely arises early in prenatal development considerable efforts in identifying such modifiable risk factors have focused on maternal exposures in pregnancy. Some of those studies have shown higher rates of ASD among children of women with e.g. diabetes, depression or recurrent infections. However, (1) women experience many other conditions in pregnancy, most of which have not been studied in the context of offspring ASD risk; and (2) the mechanisms underlying the association between maternal diagnoses and ASD remain unknown. While placental permeability to multiple factors in maternal circulation renders direct effects of maternal health on fetus plausible, this explanation has not been rigorously evaluated against the possibility that both maternal diagnosis and child’s ASD are caused by overlapping genetic factors, transmitted from mother to the child. In response, the key objectives of our proposal are to (1) test the associations between maternal health and ASD systematically, across the full spectrum of maternal diagnoses, and accounting for their correlation, and (2) elucidate the genetic and/or non-genetic mechanisms underlying those associations. To achieve this, we propose independent, but synergistic, aims to increase the reliability and generalizability of our results. Aim 1: Systematically identify maternal diagnoses in pregnancy associated with ASD in offspring. Aim 2: Determine if the association between maternal diagnoses and ASD is due to transmitted genetic factors, using information on family relations available in Denmark. Aim 3: Test the association between maternal diagnoses in pregnancy and child’s genetic liability for ASD using molecular genetic data. We will use large, well-powered sample of >723k live births from Denmark with full demographic, medical and pedigree information, as well as genetic data for a subset of those individuals (N~26k). All significant associations will be replicated in an American dataset (Kaiser Permanente Northern California) with ~320k births, ensuring external validity of our results. The innovation of this project is three-fold: (1) it has a potential to identify novel risk factors (shown in our preliminary data), (2) it introduces a methodological shift in ASD epidemiology, with large-scale, exposure- wide and rigorous inference process, akin to that already applied in the field of genetics; and (3) for the first time, it integrates national data from Nordic registries with one of the largest US-based cohorts (Kaiser Permanente). This project will deliver a systematic list of high-confidence, maternal diagnoses around pregnancy associated with ASD risk in two, independent cohorts, and triangulated evidence regarding genetic and non-genetic mechanisms linking those diagnoses in pregnancy with risk of ASD in offspring. Collectively, these outputs will contribute new insights into ASD etiology, suggest potential preventive factors and aid the efforts towards early identification of high-risk families.