Predicting the multi-omic impact of psychiatric GWAS associations

预测精神病学 GWAS 关联的多组学影响

基本信息

批准号：
10735004
负责人：
Laura Marianne Huckins
金额：
$ 58.62万
依托单位：
YALE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-12-01 至 2024-11-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10735004
关键词：
Address Algorithms Anorexia Nervosa Anterior Autopsy Biological Bipolar Disorder Brain Bypass Cell Line Collection Complex Data Data Set Development Disease Emotional Etiology Family Financial Hardship Gene Expression Genes Genetic Genetic Polymorphism Genetic study Genotype Goals High Prevalence Human Impairment Measures Mental disorders Methodology Methods Modeling Morbidity - disease rate Multiomic Data Neurons Pharmaceutical Preparations Pluripotent Stem Cells Prefrontal Cortex Public Health Regulation Research Research Personnel Risk Role Sample Size Sampling Schizophrenia Statistical Models Testing Therapeutic Intervention Time Tissue Banks Tissue Sample Tissues Translating Update Variant beta diversity brain tissue cell type cingulate cortex disorder risk effective therapy epigenome falls genome wide association study genome-wide genomic locus gut microbiota histone modification improved induced pluripotent stem cell innovation insight microbial microbial composition microbiome mortality multiple omics novel predictive modeling prenatal sample collection social success trait transcriptome transcriptomics

项目摘要

PROJECT SUMMARY / ABSTRACT Our understanding of schizophrenia (SCZ), bipolar disorder (BPD) and anorexia nervosa (AN) is advancing rapidly. We have identified polymorphisms and genes associated with all three disorders, although AN is still understudied compared to SCZ and BPD. As sample sizes for genome-wide association studies increase, larger numbers of associated variants will surely be identified, particularly for AN, which is projected to increase to 50,000 cases from ~3,500 currently, by 2019. However, such studies provide, at best, long lists of associated loci, which are not easily biologically interpretable. Consequently, we do not yet understand the key biological mechanisms underlying these diseases, and few effective treatments or medications are available. Methods that provide insight into the associations from these studies will be vital to furthering our understanding of disease etiology, and will have substantial public health impacts. We propose to develop statistical models to translate existing associations from these studies into biologically relevant information. These models are an innovative approach that capitalize on existing successful genetic studies. We use large, publicly available ‘multi-omic’ datasets with proven relevance to SCZ, BPD, and AN (for example brain gene expression, cell-type specific histone modifications, and gut microbiota) to build powerful multi-omic predictors. These may be used to predict higher-level measures (for example gene expression) from genotype, and test for association with disease. These types of associations may lead to increased understanding of underlying biological mechanisms, and opportunities for development of medications and therapeutic interventions. In specific aim 1, we will update and improve on our existing brain gene expression prediction models, using a large collection of post-mortem brain samples from the dorso-lateral pre-frontal cortex and anterior cingulate cortex. These samples will allow us to build large, well-powered, highly accurate prediction models. We will apply these models to existing studies of SCZ, BPD, and AN to provide disease-associated genes. In specific aim 2, we will extend our approach to include prediction of developmental brain gene expression, and again will apply our models to studies of SCZ, BPD, and AN. These analyses will provide trajectories of gene expression throughout development, and will identify genes associated with SCZ, BPD and AN at distinct developmental stages. In specific aim 3, we will create models predicting cell-type specific histone modifications and gut microbial composition from genotype, and will apply these to studies of SCZ, BPD, and AN. These analyses will elucidate the role of specific histone modifications (H3K4me3 and H3K27ac), in neurons and non-neurons, as well as the role of microbial diversity and specific bacterial species, in SCZ, BPD, and AN.

项目概要/摘要我们对精神分裂症 (SCZ)、双向情感障碍 (BPD) 和神经性厌食症 (AN) 的理解是尽管进展迅速，但我们已经确定了与所有三种疾病相关的多态性和基因。与 SCZ 和 BPD 相比，AN 在全基因组关联研究的样本量方面仍待研究。增加，肯定会识别出更多数量的相关变体，特别是对于 AN，预计到 2019 年，病例数将从目前的约 3,500 例增加到 50,000 例。然而，此类研究最多只能提供一长串清单相关位点的生物学解释不易，我们尚不了解。这些疾病背后的关键生物学机制，并且很少有有效的治疗方法或药物提供深入了解这些研究中的关联的方法对于进一步推进我们的研究至关重要。了解疾病病因，将对公共卫生产生重大影响。我们建议开发统计模型，将这些研究中的现有关联转化为这些模型是一种利用现有信息的创新方法。我们使用大型、公开的“多组学”数据集，并已证明与相关性相关。 SCZ、BPD 和 AN（例如脑基因表达、细胞类型特异性组蛋白修饰和肠道微生物群）来构建强大的多组学预测因子，这些可用于预测更高级别的测量（例如基因型的示例基因表达），并测试与疾病的关联。可能会增加对潜在生物机制的了解，并带来机会药物和治疗干预措施的开发。在具体目标1中，我们将更新和改进现有的大脑基因表达预测模型，使用来自背外侧前额叶皮层和前额皮质的大量死后大脑样本这些样本将使我们能够构建大型、功能强大、高度准确的预测模型。我们将把这些模型应用到 SCZ、BPD 和 AN 的现有研究中，以提供疾病相关基因。在具体目标 2 中，我们将扩展我们的方法以包括对发育大脑基因的预测表达，并再次将我们的模型应用于 SCZ、BPD 和 AN 的研究。这些分析将提供。整个发育过程中基因表达的轨迹，并将识别与 SCZ、BPD 相关的基因和 AN 处于不同的发展阶段。在具体目标 3 中，我们将创建预测细胞类型特异性组蛋白修饰和肠道的模型微生物组成，并将其应用于 SCZ、BPD 和 AN 的研究。将阐明特定组蛋白修饰（H3K4me3 和 H3K27ac）在神经元和非神经元中的作用，以及微生物多样性和特定细菌种类在 SCZ、BPD 和 AN 中的作用。

项目成果

期刊论文数量（49）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Genetically Regulated Gene Expression in the Brain Associated With Chronic Pain: Relationships With Clinical Traits and Potential for Drug Repurposing.

与慢性疼痛相关的大脑中基因调控的基因表达：与临床特征和药物再利用潜力的关系。

DOI：
发表时间：
2024-04-15
期刊：
影响因子：
10.6
作者：
Johnston, Keira J A;Cote, Alanna C;Hicks, Emily;Johnson, Jessica;Huckins, Laura M
通讯作者：
Huckins, Laura M

The impact of genetic risk for schizophrenia on eating disorder clinical presentations.

精神分裂症遗传风险对饮食失调临床表现的影响。

DOI：
发表时间：
2023-11-29
期刊：
影响因子：
6.8
作者：
Zhang, Ruyue;Kuja;Borg, Stina;Leppä, Virpi;Thornton, Laura M;Birgegård, Andreas;Bulik, Cynthia M;Bergen, Sarah E
通讯作者：
Bergen, Sarah E

Eating disorders: are gut microbiota to blame?

饮食失调：肠道微生物群是罪魁祸首吗？

DOI：
发表时间：
2024-04
期刊：
影响因子：
13.6
作者：
Xu, Jiayi;Carroll, Ian M;Huckins, Laura M
通讯作者：
Huckins, Laura M

Recommendations to encourage participation of individuals from diverse backgrounds in psychiatric genetic studies.

鼓励不同背景的个人参与精神病遗传学研究的建议。

DOI：
发表时间：
2022-07
期刊：
影响因子：
0
作者：
MacDermod, Casey;Pettie, Michaela A;Carrino, Emily A;Garcia, Susana Cruz;Padalecki, Sophie;Finch, Jody E;Sanzari, Christina;Kennedy, Hannah L;Pawar, Pratiksha S;Mcgough, Makenna M;Iwashita, Ava;Takgbajouah, Mary;Coan, Danielle;Szakasits, Lind
通讯作者：
Szakasits, Lind

Exploring the clinical and genetic associations of adult weight trajectories using electronic health records in a racially diverse biobank: a phenome-wide and polygenic risk study.

使用种族多样化生物库中的电子健康记录探索成人体重轨迹的临床和遗传关联：一项全表组和多基因风险研究。

DOI：
发表时间：
2022-08
期刊：
影响因子：
0
作者：
Xu, Jiayi;Johnson, Jessica S;Signer, Rebecca;Eating Disorders Working Group of the Psychiatric Genomics Consortium;Birgegård, Andreas;Jordan, Jennifer;Kennedy, Martin A;Landén, Mikael;Maguire, Sarah L;Martin, Nicholas G;Mortensen, Preben Bo;Pet
通讯作者：
Pet