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

怀孕期间的孕产妇健康和自闭症风险 - 遗传和非遗传机制

• 批准号: 10531594
• 负责人: MAGDALENA JANECKA
• 金额: $ 63.41万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-12-01 至 2025-10-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10531594
• 关键词: Accounting; Affect; American; Birth; Brothers; California; Child; Circulation; Coupled; Data; Data Set; Data Sources; Denmark; Development; Diabetes Mellitus; Diagnosis; Disease; Early identification; Ensure; Environmental Risk Factor; Epidemiology; Etiology; Exposure to; Extended Family; Family; Family Relationship; Female; Fetus; Genetic; Genetic Risk; Goals; Health Status; Individual; Infection; Intellectual functioning disability; International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10); Intervention; Knowledge; Link; Live Birth; Maps; Maternal Exposure; Maternal Health; Medical; Medical Records; Mental Depression; Methodology; Molecular Genetics; Mothers; Outcome; Output; Parents; Partner in relationship; Pathway interactions; Permeability; Pregnancy; Prevention; Preventive; Process; Public Health; Registries; Risk; Risk Factors; Sampling; Sister; Testing; Time; Vertical Disease Transmission; Woman; Work; autism spectrum disorder; autistic children; cohort; comorbidity; design; disorder risk; experience; family genetics; genetic pedigree; high risk; indexing; innovation; insight; male; modifiable risk; non-genetic; novel; offspring; polygenic risk score; population based; prenatal; recurrent infection; response; sex; transmission process

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.

自闭症谱系障碍（ASD）影响59个儿童中的1个，是由遗传和环境引起的 因素。然而，这种疾病的可修改风险因素仍然未知，创造了一个紧迫的公众 健康需求。由于ASD可能在产前发展的早期出现，因此在确定此类方面做出了巨大努力 可修改的危险因素集中在孕妇的孕妇暴露上。其中一些研究表明 例如糖尿病，抑郁或复发性感染。然而， （1）妇女在怀孕中经历许多其他疾病，其中大多数在上下文中尚未进行研究 后代ASD风险； （2）Mater诊断与ASD之间关联的基础机制 仍然未知。而母体循环中多种因素的胎盘渗透性导致直接影响 胎儿对胎儿的健康是合理的，这种解释尚未受到严格评估 孕产妇诊断和儿童ASD都是由重叠的遗传因素引起的，从母亲传播到 孩子。作为回应，我们提案的关键目标是（1）测试母校健康之间的关联 系统地，ASD在整个孕产妇诊断方面，并考虑其相关性， （2）阐明这些关联的遗传和/或非遗传机制。为此， 我们提出独立但协同的旨在提高结果的可靠性和概括性。 AIM 1：系统地识别与后代ASD相关的妊娠孕妇诊断。目标2： 确定Mater诊断和ASD之间的关联是否是由于传播的遗传因素引起的 有关丹麦的家庭关系的信息。 AIM 3：测试Mater Diagnostics之间的关联 在怀孕和儿童对ASD的遗传责任中，使用分子遗传数据。我们将使用大型，有力的 来自丹麦的> 723k活产样本，并提供完整的人群，医学和谱系信息以及 这些个体子集的遗传数据（n〜26K）。所有重要的关联将在 美国数据集（Kaiser Permanente North California），分娩约320K，确保我们的外部有效性 结果。该项目的创新是三个方面：（1）它有可能识别新的风险因素（如图所示 我们的初步数据），（2）它引入了ASD流行病学的方法论转变，并具有大规模的暴露 - 广泛而严格的推理过程，类似于已经应用于遗传学领域的推理过程； （3）第一次 它将来自北欧注册机构的国家数据与美国最大的同伙之一（Kaiser Permanente）集成在一起。 该项目将提供系统的系统列表，围绕妊娠有关 具有两者的ASD风险，独立队列以及有关遗传和非遗传的三角剖分证据 将怀孕诊断与后代ASD风险联系起来的机制。总的来说，这些输出将 对ASD病因贡献新的见解，提出潜在的预防性因素，并帮助尽早努力 识别高风险家庭。