Integrative analysis of bulk and single-cell RNA-seq data for cardiometabolic disease

心脏代谢疾病的批量和单细胞 RNA-seq 数据的综合分析

• 批准号: 10448317
• 负责人: Mingyao Li
• 金额: $ 12.19万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 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 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10448317
• 关键词: Abdomen; Accounting; Adipocytes; Adipose tissue; Allelic Imbalance; Architecture; Atherosclerosis; Body mass index; Buffers; Candidate Disease Gene; Cardiometabolic Disease; Catalogs; Cells; Cholesterol; Complex; Computer software; Data; Data Analyses; Data Set; Disease; Elements; Endothelial Cells; Etiology; Fibroblasts; Foundations; Functional disorder; Funding; Gene Expression; Genes; Genetic; Genetic Diseases; Genetic Transcription; Genome; Genotype; Heterogeneity; High-Throughput RNA Sequencing; Human; Immune; Knowledge; Link; Lipids; Location; Loose connective tissue; Measurable; Metabolic; Methods; Molecular; Morbidity - disease rate; Muscle; Myocardial Infarction; National Heart, Lung, and Blood Institute; National Human Genome Research Institute; Needle biopsy procedure; Non-Insulin-Dependent Diabetes Mellitus; Obesity; Peripheral; Precision therapeutics; Publishing; Quantitative Trait Loci; Regulatory Element; Reporting; Resolution; Risk; Role; Sampling; Single Nucleotide Polymorphism; Statistical Data Interpretation; Statistical Methods; Stroke; System; Testing; Tissues; Triglycerides; Untranslated RNA; Variant; Waist-Hip Ratio; Whole Blood; adiponectin; base; cardiometabolic risk; cell type; energy balance; genetic association; genetic variant; genome wide association study; genomic locus; human data; insight; interest; lifestyle factors; macrophage; mortality; novel; open source; single-cell RNA sequencing; statistics; stem cells; subcutaneous; therapeutic target; trait; transcriptome; transcriptome sequencing; transcriptomics

PROJECT SUMMARY Cardiometabolic diseases (CMD), including obesity, type 2 diabetes, heart attack, stroke, and atherosclerosis, are caused by the effects and complex interplay of genetic and lifestyle factors. In the past decade, there has been a dramatic increase of CMD, which represents important causes of morbidity and mortality worldwide. Therefore, there is a great interest to understand the etiology and pathophysiology of CMD. Recent genome- wide association studies (GWAS) have provided increased insight into the genetic basis for CMD and related traits. Although GWAS have identified strong and highly replicated association of genetic loci for CMD and their related traits, GWAS findings can only suggest locations of associated variants and not directly link any one gene within a region to disease. Since most GWAS-identified single nucleotide polymorphisms (SNPs) are located in non-coding regions of the genome, their influence on disease is likely to be on modulating RNA expression by acting as expression quantitative trait loci (eQTL). Excess adipose tissue, especially in central abdominal depots, is associated with increased risk of CMD. Subcutaneous adipose tissue stores additional lipids and acts as a buffering system for lipid energy balance, thus providing a protective role for CMD. Previous eQTL studies in subcutaneous adipose tissue have implicated genes involved in obesity and metabolic traits. However, the role of candidate genes identified in GWAS is still not yet clear because published eQTL studies were based on bulk tissue gene expression in adipose. Adipose tissue is a loose connective tissue that is composed mostly of adipocytes. In addition to adipocytes, adipose tissue also contains adipocyte progenitor cells, endothelial cells, fibroblasts, and various immune cells such as macrophages. The resulting heterogeneity between samples can confound the analysis of bulk tissue data. To overcome these limitations, we propose to perform integrative secondary data analysis of publically available bulk RNA sequencing (RNA-seq) and single-cell RNA-seq (scRNA-seq) data from human adipose. We will test the hypothesis that measurable molecular deficits that include cell types and gene expression occur in adipose for CMD. We will further integrate with publically available GWAS data on CMD to advance post-GWAS interpretation of CMD genetic results. By detailed characterization of cell-type composition and cell-type- specific gene expression changes in human adipose, our results will elucidate the functional roles of GWAS findings that are still poorly understood and can power precision therapeutic targeting of CMD.

项目摘要 心脏代谢疾病（CMD），包括肥胖、2型糖尿病、心脏病发作、中风和动脉粥样硬化， 是由遗传和生活方式因素的影响和复杂的相互作用造成的。在过去的十年里， CMD急剧增加，这是世界范围内发病率和死亡率的重要原因。 因此，了解CMD的病因学和病理生理学具有极大的兴趣。最近的基因组- 广泛关联研究（GWAS）为CMD及其相关疾病的遗传基础提供了更多的见解。 性状尽管GWAS已经确定了CMD及其相关基因座的强且高度重复的关联， GWAS的发现只能表明相关变体的位置，而不能直接将任何一个 一个区域内的基因对疾病的影响。由于大多数GWAS鉴定的单核苷酸多态性（SNP）是 位于基因组的非编码区，它们对疾病的影响可能是调节RNA 作为表达数量性状基因座（eQTL）。脂肪组织过多，特别是在中央 腹部贮库与CMD风险增加有关。皮下脂肪组织储存额外的 脂质和作为一个缓冲系统的脂质能量平衡，从而为CMD提供保护作用。 先前在皮下脂肪组织中的eQTL研究已经涉及肥胖和肥胖相关基因。 代谢特征然而，在GWAS中鉴定的候选基因的作用仍然不清楚， 公开的eQTL研究是基于脂肪中的大量组织基因表达。脂肪组织是一种松散的 主要由脂肪细胞组成的结缔组织。除了脂肪细胞，脂肪组织也 含有脂肪祖细胞、内皮细胞、成纤维细胞和各种免疫细胞， 巨噬细胞样本之间产生的异质性可能会混淆大量组织数据的分析。到 为了克服这些局限性，我们建议对临床上可用的二手数据进行综合分析。 来自人脂肪的批量RNA测序（RNA-seq）和单细胞RNA-seq（scRNA-seq）数据。我们将测试 假设可测量的分子缺陷，包括细胞类型和基因表达发生在脂肪组织中， 关于CMD我们将进一步与CMD上的可用GWAS数据集成，以推进后GWAS CMD遗传结果的解释。通过对细胞类型组成和细胞类型的详细表征， 我们的结果将阐明GWAS在人类脂肪中的功能作用 这些发现仍然知之甚少，可以为CMD的精确治疗靶向提供动力。

项目成果

High-Dimensional Single-Cell Multimodal Landscape of Human Carotid Atherosclerosis.

人颈动脉粥样硬化的高维单细胞多模态景观。

• DOI: 10.1101/2023.07.13.23292633
• 发表时间: 2023
• 期刊: medRxiv : the preprint server for health sciences
• 作者: Bashore,AlexanderC;Yan,Hanying;Xue,Chenyi;Zhu,LucieY;Kim,Eunyoung;Mawson,Thomas;Coronel,Johana;Chung,Allen;Ho,Sebastian;Ross,LeilaS;Kissner,Michael;Passegué,Emmanuelle;Bauer,RobertC;Maegdefessel,Lars;Li,Mingyao;Reilly,Mu
• 通讯作者: Reilly,Mu