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

基本信息

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
项目类别：
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

项目摘要

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.

项目概要：自身免疫性疾病，如类风湿性关节炎和系统性红斑狼疮，使人衰弱以及由致病性炎症反应引起的高度流行的慢性疾病。 6 号染色体上的组织相容性 (MHC) 区域，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最强的遗传关联，但确切的 MHC 疾病风险背后的分子机制尚未得到解决。编码变异如何影响 HLA 蛋白质结构和抗原结合，但最近的研究强调了其潜力非编码变异在调节 HLA 表达中的作用可能在 HLA 表达增加中发挥因果作用。通过向自身反应性 T 细胞呈递更高水平的抗原来治疗疾病，迫切需要更好的方法。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 MHC 区域的遗传变异调节 HLA 的假设申请人将开发创新的细胞状态依赖性和疾病相关的表达方式。整合从炎症样本中采集的遗传和单细胞转录组数据的计算方法跨多种人类免疫介导疾病背景的组织和对照，包含 >1,088,000 个细胞具体而言，该研究旨在 (1) 量化遗传变异对 HLA 的影响。在关键免疫和基质细胞状态（T、B、成纤维细胞和骨髓细胞）中的表达，(2) 识别表达调节 HLA 调节变体效果的程序和转录调节因子，以及 (3) 连接 HLA 自身免疫性疾病风险位点的监管变异这项工作将生成详细介绍 HLA 的资源。跨不同细胞状态的表达并确定遗传变异调节 HLA 的特定环境这将加深我们对自身免疫性疾病机制的基本理解。风险，并可能为更明智的治疗策略铺平道路。拟议的培训计划将使申请人能够： (A) 加强对遗传的理解和人类疾病的免疫基础，（B）培养强大的计算基因组学方法技能发展，(C) 发展统计遗传学和计算免疫学方面的数据科学技能，(D) 提高对自身免疫性疾病临床方面的了解，以及 (E) 发展专业科学沟通技巧。丰富和支持性的培训环境以及专家的密切指导。复杂性状遗传学、免疫学和单细胞方法开发将使申请人具备成为一名有效的医师科学家的知识和技能，可以为疾病领域做出贡献重点计算免疫基因组学。