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.

项目概要 心脏代谢疾病 (CMD)，包括肥胖、2 型糖尿病、心脏病、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引起的。在过去的十年里，有 CMD 急剧增加，是全世界发病率和死亡率的重要原因。 因此，人们对了解 CMD 的病因学和病理生理学非常感兴趣。最近的基因组- 广泛关联研究 (GWAS) 加深了对 CMD 及相关疾病遗传基础的了解 特征。尽管 GWAS 已经确定了 CMD 及其相关基因位点的强且高度重复的关联。 相关性状，GWAS 结果只能表明相关变异的位置，而不能直接联系任何一个 某个区域内的基因导致疾病。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域，它们对疾病的影响可能在于调节 RNA 通过充当表达数量性状基因座（eQTL）来表达。脂肪组织过多，尤其是中枢脂肪组织 腹部储库，与 CMD 风险增加相关。皮下脂肪组织储存额外的 脂质并充当脂质能量平衡的缓冲系统，从而为 CMD 提供保护作用。 先前对皮下脂肪组织的 eQTL 研究表明，基因与肥胖和肥胖相关。 代谢特征。然而，GWAS 中确定的候选基因的作用仍不清楚，因为 已发表的 eQTL 研究基于脂肪中的大量组织基因表达。脂肪组织是松散的 结缔组织主要由脂肪细胞组成。除了脂肪细胞外，脂肪组织还 含有脂肪细胞祖细胞、内皮细胞、成纤维细胞和各种免疫细胞，例如 巨噬细胞。由此产生的样本之间的异质性可能会混淆大量组织数据的分析。到 为了克服这些限制，我们建议对公开可用的二次数据进行综合分析 来自人类脂肪的批量 RNA 测序 (RNA-seq) 和单细胞 RNA-seq (scRNA-seq) 数据。我们将测试 脂肪中发生可测量的分子缺陷（包括细胞类型和基因表达）的假设 对于命令。我们将进一步整合 CMD 上公开的 GWAS 数据，以推进后 GWAS CMD 遗传结果的解释。通过细胞类型组成和细胞类型的详细表征 人类脂肪中特定基因表达的变化，我们的结果将阐明 GWAS 的功能作用 这些发现仍然知之甚少，但可以为 CMD 的精准治疗提供动力。

项目成果

MuSiC2: cell-type deconvolution for multi-condition bulk RNA-seq data.

MuSiC2：多条件批量 RNA-seq 数据的细胞类型反卷积。

• 发表时间: 2022-11-19
• 影响因子: 9.5
• 作者: Fan, Jiaxin;Lyu, Yafei;Zhang, Qihuang;Wang, Xuran;Li, Mingyao;Xiao, Rui
• 通讯作者: Xiao, Rui

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。

• 发表时间: 2024-04
• 作者: Bashore, Alexander C;Yan, Hanying;Xue, Chenyi;Zhu, Lucie Y;Kim, Eunyoung;Mawson, Thomas;Coronel, Johana;Chung, Allen;Sachs, Nadja;Ho, Sebastian;Ross, Leila S;Kissner, Michael;Passegué, Emmanuelle;Bauer, Robert C;Maegdefessel, Lars;Li, Mingy
• 通讯作者: Li, Mingy