Profiling the Functional Genetics of Health and Disease using BrainGENIE: The Brain Gene Expression and Network Imputation Engine

使用 BrainGENIE 分析健康和疾病的功能遗传学：大脑基因表达和网络插补引擎

• 批准号: 10435527
• 负责人: Stephen J Glatt
• 金额: $ 20.25万
• 依托单位: UPSTATE MEDICAL UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-06-21 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10435527
• 关键词: Address; Affect; Alzheimer' s Disease; Attention; Autopsy; Bayesian Modeling; Biological; Bipolar Disorder; Blood; Blood specimen; Brain; Brain Diseases; Brain region; Collection; Complex; Computer software; Computing Methodologies; Data; Data Set; Diagnostic; Disease; Etiology; Fostering; Functional disorder; Gene Expression; Gene Expression Profile; Genes; Genetic; Genomics; Genotype; Genotype-Tissue Expression Project; Goals; Gold; Health; Heritability; Human; Individual; Intervention; Knowledge; Light; Major Depressive Disorder; Maps; Mental disorders; Methods; Modeling; Molecular; Natural Immunity; Neural Network Simulation; Neurodegenerative Disorders; Parkinson Disease; Participant; Pathway interactions; Pattern; Persons; Post-Traumatic Stress Disorders; Quantitative Trait Loci; Regression Analysis; Research Personnel; Sampling; Schizophrenia; Source Code; Statistical Methods; Surrogate Markers; Testing; Tissues; Training; Validation; Variant; Work; autism spectrum disorder; base; brain tissue; cell type; chromatin remodeling; deep learning; deep neural network; gene discovery; gene network; genome wide association study; human subject; improved; mild cognitive impairment; neural network; neurodevelopment; neuropsychiatric disorder; neurotransmission; novel; peripheral blood; public repository; tool; trait; transcriptome; transcriptomics

Abstract The pathophysiology of brain disorders remains unknown because we cannot study the relevant tissue in living human subjects. Postmortem brain tissue is useful, but expensive, rare, and critically confounded by antemortem and agonal factors. These two facts have inspired the search for alternative strategies, such as the use of surrogate markers like blood-based gene expression. To improve the rigor of this widely used approach, we developed a novel computational method called the Brain Gene Expression and Network Imputation Engine (BrainGENIE) that leverages biological comparability between blood and brain gene expression to predict transcriptome profiles for brain tissue based on blood gene-expression profiles. BrainGENIE is fundamentally different from other transcriptome-imputation methods, and captures a much larger proportion of the variance in—and larger fraction of—the brain transcriptome. BrainGENIE is capable of predicting approximately 9–57% of the brain transcriptome, which yields an approximate 1.8-fold increase in coverage relative to the “gold standard” method PrediXcan, and which greatly improves our statistical power to detect genes and pathways associated with disease. Our proposal contains three Specific Aims to improve our method and shed light on biological pathways underlying neuropsychiatric disorders. Aim 1: Refine BrainGENIE to capture additional genes that are not currently well predicted by our method. Aim 2: Apply BrainGENIE to our collection of publicly available and in-house data to predict brain-region-specific gene expression profiles for over 8,000 living persons, and discover region-specific gene-expression patterns associated with neuropsychiatric disorders and neurodegenerative diseases. Aim 3: Disseminate BrainGENIE as stand-alone software for other researchers to use freely. Guided by recent genetic and genomic studies, we hypothesize that comparable patterns of gene dysregulation will be found across neuropsychiatric disorders among pathways involving innate immunity, chromatin remodeling, neurodevelopment, and neurotransmission. Inclusion of neurodegenerative disorders in our analysis will allow us to determine whether gene expression patterns are shared across a broader range of brain disorders. We also expect to identify disorder-specific and brain-region-specific transcriptomic associations. Our project will enable new lines of inquiry into biological changes that emerge in the brains of living persons, and create opportunities to improve diagnostics, intervention, and treatment.

摘要

项目成果

A polygenic resilience score moderates the genetic risk for schizophrenia: Replication in 18,090 cases and 28,114 controls from the Psychiatric Genomics Consortium.

多基因复原力评分可减轻精神分裂症的遗传风险：在精神病学基因组学联盟的 18,090 例病例和 28,114 例对照中进行复制。

• DOI: 10.1002/ajmg.b.32957
• 发表时间: 2024
• 期刊: American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics
• 作者: Hess,JonathanL;Mattheisen,Manuel;SchizophreniaWorkingGroupofthePsychiatricGenomicsConsortium;Greenwood,TiffanyA;Tsuang,MingT;Edenberg,HowardJ;Holmans,Peter;Faraone,StephenV;Glatt,StephenJ
• 通讯作者: Glatt,StephenJ