Pinpointing how single-cell states affect genetic regulation of HLA expression in autoimmune diseases

查明单细胞状态如何影响自身免疫性疾病中 HLA 表达的遗传调控

• 批准号: 10535216
• 负责人: Joyce Blossom Kang
• 金额: $ 3.9万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10535216
• 关键词: Affect; Alleles; Antigen Presentation; Autoimmune Diseases; Autoimmunity; Automobile Driving; Binding Sites; Biological; Cells; Chromosome 6; Chronic; Clinical; Code; Communication; Complex Genetic Trait; Computing Methodologies; Data; Data Science; Data Set; Dendritic Cells; Disease; Environment; Fibroblasts; Funding; Gene Expression; Genes; Genetic; Genetic Transcription; Genetic Variation; Genome; Genomics; Genotype; Grain; HLA Antigens; Histocompatibility; Histocompatibility Antigens Class I; Histocompatibility Antigens Class II; Human; Human Genetics; Immune; Immune system; Immunogenomics; Immunology; Individual; Inflammatory; Inflammatory Bowel Diseases; Inflammatory Response; Interferon Type II; Knowledge; Label; Lead; Link; MHC Class II Genes; Mediating; Medicine; Mentorship; Methods; Modeling; Molecular; Myelogenous; Myeloid Cells; National Institute of Allergy and Infectious Disease; Pathogenicity; Patients; Peptides; Physicians; Play; Population; Process; Publishing; Quantitative Trait Loci; Regulation; Research; Resolution; Resources; Rheumatoid Arthritis; Risk; Role; Sampling; Scientist; Single Nucleotide Polymorphism; Statistical Models; Stromal Cells; Surface; Synovitis; Systemic Lupus Erythematosus; T-Cell Activation; T-Lymphocyte; T-Lymphocyte Subsets; Testing; Therapeutic; Tissues; Training; Transcription Coactivator; Untranslated RNA; Variant; Work; antigen binding; autoreactive T cell; base; cell type; cohort; disorder risk; genetic association; genetic variant; genomic data; high dimensionality; human disease; human model; human tissue; improved; innovation; macrophage; method development; multimodality; multiple datasets; novel strategies; personalized approach; programs; protein structure; reference genome; response; risk variant; single-cell RNA sequencing; skills; transcription factor; transcriptomics; treatment strategy

Project Summary: Autoimmune diseases, such as rheumatoid arthritis and systemic lupus erythematosus, are debilitating and highly prevalent chronic conditions that result from pathogenic inflammatory responses. The major histocompatibility (MHC) region on chromosome 6, which contains the human leukocyte antigen (HLA) and other immune-related genes, has the strongest genetic association with autoimmune diseases, but the exact molecular mechanisms behind MHC disease risk are yet unsolved. Previous research has primarily explored how coding variants affect HLA protein structure and antigen binding, but recent studies highlight the potential role of noncoding variants in regulating HLA expression. Increased HLA expression could play a causal role in disease through higher levels of antigen presentation to autoreactive T cells. There is a critical need to better understand how a cell’s biological state impacts genetic control of HLA expression. The proposed research will test the hypothesis that genetic variation in the MHC region modulates HLA expression in a cell-state-dependent and disease-relevant manner. The applicant will develop innovative computational methods to integrate both genetic and single-cell transcriptomic data sampled from inflamed tissues and controls across multiple human immune-mediated disease contexts, comprising >1,088,000 cells from 384 individuals. Specifically, the study aims to (1) quantify the effect of genetic variation on HLA expression in key immune and stromal cell states (T, B, fibroblast, and myeloid cells), (2) identify expression programs and transcriptional regulators that modulate the effect of HLA regulatory variants, and (3) link HLA regulatory variation to autoimmune disease risk loci. This work will generate a resource detailing HLA expression across diverse cell states and identify the specific contexts in which genetic variants regulate HLA expression. This will deepen our fundamental understanding of mechanisms underlying autoimmune disease risk and may pave the way for better informed therapeutic strategies. The proposed training plan will enable the applicant to: (A) strengthen an understanding of the genetic and immune basis of human diseases, (B) cultivate strong skills in computational genomics methods development, (C) develop data science skills in statistical genetics and computational immunology, (D) improve understanding of the clinical aspects of autoimmune diseases, and (E) develop professional scientific communication skills. An enriching and supportive training environment and close mentorship by experts in complex trait genetics, immunology, and single-cell methods development will equip the applicant with knowledge and skills to become an effective physician-scientist who can contribute to the field of disease- focused computational immunogenomics.

项目摘要： 自身免疫性疾病，例如类风湿关节炎和全身性红斑狼疮，正在使人衰弱 以及由致病性炎症反应引起的高度普遍的慢性病。专业 6染色体上的组织相容性（MHC）区域，其中包含人类白细胞抗原（HLA）和 其他免疫相关基因与自身免疫性疾病具有牢固的遗传关联，但确切的 MHC疾病风险背后的分子机制尚未解决。以前的研究已经探索了 编码变体如何影响HLA蛋白结构和抗原结合，但最近的研究突出了潜力 非编码变体在调节HLA表达中的作用。 HLA表达的增加可能在 通过更高水平的自动反应性T细胞的抗原呈递疾病。迫切需要更好 了解细胞的生物状态如何影响HLA表达的遗传控制。 拟议的研究将检验以下假设：MHC区域的遗传变异调节HLA 以依赖细胞状态和疾病的方式表达。申请人将发展创新 计算方法以整合从发炎中采样的遗传和单细胞转录组数据 多种人类免疫介导的疾病环境中的组织和对照，含量> 1,088,000个细胞 来自384个人。特别是，该研究的目的是（1）量化遗传变异对HLA的影响 在关键免疫和基质细胞态中的表达（T，B，成纤维细胞和髓样细胞），（2）识别表达 调节HLA调节变体效果的程序和转录调节器，以及（3）链接HLA 自身免疫性疾病风险基因座的调节变化。这项工作将生成一个详细的资源，详细介绍HLA 跨潜水细胞状态的表达并确定遗传变异调节HLA的特定环境 表达。这将加深我们对自身免疫性疾病潜在机制的基本理解 风险，可能为更好的知情治疗策略铺平道路。 拟议的培训计划将使申请能够：（a）加强对通用的理解 （b）在计算基因组学方法中培养强大技能的免疫基础 发展，（c）统计遗传学和计算免疫学方面的发展数据科学技能，（d） 提高对自身免疫性疾病的临床方面的了解，以及（e）发展专业科学 沟通技巧。丰富和支持培训环境以及专家的仔细思想 复杂的性状遗传学，免疫学和单细胞方法的发展将使申请人配备 知识和技能成为有效的身体科学家，可以为疾病的领域做出贡献 - 聚焦计算免疫基因组学。