Alzheimer variants: Propagation of shared functional changes across cellular networks

阿尔茨海默病变异：跨细胞网络共享功能变化的传播

• 批准号: 10689080
• 负责人: PHILIP L DE JAGER
• 金额: $ 164.51万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-15 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10689080
• 关键词: Address; Alzheimer' s Disease; Alzheimer' s disease pathology; Astrocytes; Biological Assay; Biological Models; Brain; CRISPR screen; Cell Culture Techniques; Cells; Cerebrospinal Fluid; Clinical; Clinical Data; Code; Cognition; Communities; Complex; DNA; Data; Data Analyses; Data Set; Databases; Dementia; Disease; Disease Progression; Disease susceptibility; Dissection; Epigenetic Process; Evaluation; Event; Future; Generations; Genes; Genetic Transcription; Genetic Variation; Genetic study; Genome; Goals; Heterogeneity; Human; Impaired cognition; In Situ; In Vitro; Individual; Intervention; Lead; Link; Location; Maps; Measures; Microglia; Modality; Modeling; Molecular; Multiomic Data; Natural Selections; Nerve Degeneration; Neurons; Nodal; Nucleic Acid Regulatory Sequences; Onset of illness; Outcome; Outcome Measure; Peptides; Predisposition; Proteins; Proteomics; Quantitative Trait Loci; Research; Risk Factors; Role; Sampling; Specific qualifier value; Susceptibility Gene; Symptoms; System; Time; Tissue Stains; Tissues; Variant; Work; brain cell; cell type; clinical phenotype; data and analysis portal; demented; endophenotype; epigenomics; experimental study; functional genomics; genetic variant; genomic locus; human DNA; human tissue; in silico; in vivo; induced pluripotent stem cell; intercellular communication; morphometry; multiple omics; network models; neural; novel; precision medicine; programs; stem cell model; synergism; trait; transcriptomics

Project Abstract Genetic studies of Alzheimer’s disease (AD) and related-diseases (ADRD) have identified over 72 loci associated with susceptibility. Although some of the most penetrant variants have been studied independently, the majority of sequence variants and features are unlikely to act in isolation. In addition, the range of susceptibility loci cover coding, epigenetic, and regulatory regions of the genome, suggesting complex relationships that cannot be captured by large-scale transcriptomic and proteomic profiling alone. With this in mind, we systematically interrogate combinations of variants across validated AD loci in a cell autonomous and non-autonomous manner using a combination of molecular, epigenetic, and functional assays. This allows to create a functional network across AD loci, and identify nodal points where the effects of individual loci interact to trigger the hallmarks of AD pathology and clinical phenotypes. As part of this effort, we propose to establish a novel AD Locus Annotator interface that synthesizes information about AD-associated sequence features from reference databases encompassing existing multi-omic and clinical data, as well as new data sets that capture quantitative proteoform and cellular functional data; these latter two data modalities have been under-characterized in AD research to date, but are crucial to identifying cross-loci interactions. From this synthesized data analysis and portal effort, we then establish a set of gene editing efforts to validate and extend our mechanistic understanding of multi- locus functional networks from these AD-associated sequence features. Taken together, these analyses and experiments allow us to link the heterogeneity of AD-associated genetic variation and clinical manifestations into a coherent framework that link AD loci with the temporal sequence of events in AD onset and progression.

项目摘要 阿尔茨海默氏病（AD）和相关疾病（ADRD）的遗传研究已确定超过72个基因座相关的 悬浮液。 序列变体和特征不太可能孤立起作用。 基因组的编码，表观遗传和调节区域，表明不可能是的复杂关系 仅由大规模转录组和蛋白质组学分析捕获。 以细胞自动及自主的方式质疑跨经过验证的AD基因座变体的组合 使用分子，表观遗传和功能测定的组合。 跨广告基因座，并识别淋巴结点，其中各个基因座的影响相互作用以触发标志 AD病理和临床表型。 从参考数据库中综合有关广告序列序列的信息的接口 涵盖了捕获定量蛋白质成型的新数据集，包括出of-OMIC和临床数据集 和细胞功能数据； 日期，但对于识别跨Loci相互作用至关重要。 我们建立了一组基因编辑编辑工作，以验证和扩展我们对多数的机械理解 来自AD相关序列特征的基因座功能网络。 实验使我们能够将广告量变异和临床表现的异质性联系到 一个连贯的框架，将AD基因座与AD OND进程中事件的时间序列联系起来。

项目成果

Using population-scale transcriptomic and genomic data to map 3' UTR alternative polyadenylation quantitative trait loci.

• DOI: 10.1016/j.xpro.2022.101566
• 发表时间: 2022-09-16
• 期刊: STAR PROTOCOLS
• 作者: Zou, Xudong;Ding, Ruofan;Chen, Wenyan;Wang, Gao;Cheng, Shumin;Wang, Qin;Li, Wei;Li, Lei
• 通讯作者: Li, Lei

Microglial function, INPP5D/SHIP1 signaling, and NLRP3 inflammasome activation: implications for Alzheimer's disease.

• DOI: 10.1186/s13024-023-00674-9
• 发表时间: 2023-11-29
• 期刊: Molecular neurodegeneration
• 影响因子: 15.1
• 作者: Terzioglu G;Young-Pearse TL
• 通讯作者: Young-Pearse TL

A single-nucleus transcriptome-wide association study implicates novel genes in depression pathogenesis.

一项单核全转录组关联研究表明新基因与抑郁症发病机制有关。

• DOI: 10.1101/2023.03.27.23286844
• 发表时间: 2023
• 期刊: medRxiv : the preprint server for health sciences
• 作者: Zeng,Lu;Fujita,Masashi;Gao,Zongmei;White,CharlesC;Green,GiladS;Habib,Naomi;Menon,Vilas;Bennett,DavidA;Boyle,PatriciaA;Klein,Hans-Ulrich;DeJager,PhilipL
• 通讯作者: DeJager,PhilipL

Translocator protein is a marker of activated microglia in rodent models but not human neurodegenerative diseases.

• DOI: 10.1038/s41467-023-40937-z
• 发表时间: 2023-08-28
• 期刊: NATURE COMMUNICATIONS
• 影响因子: 16.6
• 作者: Nutma, Erik;Fancy, Nurun;Weinert, Maria;Tsartsalis, Stergios;Marzin, Manuel C.;Muirhead, Robert C. J.;Falk, Irene;Breur, Marjolein;de Bruin, Joy;Hollaus, David;Pieterman, Robin;Anink, Jasper;Story, David;Chandran, Siddharthan;Tang, Jiabin;Trolese, Maria C.;Saito, Takashi;Saido, Takaomi C.;Wiltshire, Katharine H.;Beltran-Lobo, Paula;Phillips, Alexandra;Antel, Jack;Healy, Luke;Dorion, Marie-France;Galloway, Dylan A.;Benoit, Rochelle Y.;Amosse, Quentin;Ceyzeriat, Kelly;Badina, Aurelien M.;Koevari, Enikoe;Bendotti, Caterina;Aronica, Eleonora;Radulescu, Carola I.;Wong, Jia Hui;Barron, Anna M.;Smith, Amy M.;Barnes, Samuel J.;Hampton, David W.;van der Valk, Paul;Jacobson, Steven;Howell, Owain W.;Baker, David;Kipp, Markus;Kaddatz, Hannes;Tournier, Benjamin B.;Millet, Philippe;Matthews, Paul M.;Moore, Craig S.;Amor, Sandra;Owen, David R.
• 通讯作者: Owen, David R.

scMultiGAN: cell-specific imputation for single-cell transcriptomes with multiple deep generative adversarial networks.

scMultiGAN：具有多个深度生成对抗网络的单细胞转录组的细胞特异性插补。

• DOI: 10.1093/bib/bbad384
• 发表时间: 2023
• 期刊: Briefings in bioinformatics
• 影响因子: 9.5
• 作者: Wang,Tao;Zhao,Hui;Xu,Yungang;Wang,Yongtian;Shang,Xuequn;Peng,Jiajie;Xiao,Bing
• 通讯作者: Xiao,Bing