Functional Interrogation of T2D-associated genes in human stem cell-derived models and mice

人类干细胞衍生模型和小鼠中 T2D 相关基因的功能研究

• 批准号: 10649538
• 负责人: Struan F A Grant
• 金额: $ 174.17万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-20 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10649538
• 关键词: ATAC-seq; Ablation; Adipocytes; Affect; Animals; Area; Biological; Biological Process; Biology; Biometry; Blindness; Candidate Disease Gene; Cardiovascular Diseases; Cause of Death; Cell model; Cells; Chronic; Collaborations; Collection; Communities; Complex; Data; Data Set; Diabetes Mellitus; Diabetic mouse; Disease; Disease model; Disease susceptibility; Engineering; Functional disorder; Funding; Genes; Genetic; Genetic Engineering; Genetic Predisposition to Disease; Genetic study; Genomic approach; Genomics; Goals; Health; Hepatocyte; Heterogeneity; Human; Human Genetics; Hyperglycemia; Individual; Insulin Resistance; Investigation; Kidney Failure; Knowledge; Liver; Malignant Neoplasms; Maps; Metabolic; Methods; Modeling; Molecular; Mus; Muscle Fibers; Mutant Strains Mice; Neuropathy; Non-Insulin-Dependent Diabetes Mellitus; Obesity; Pancreas; Pathway Analysis; Pathway interactions; Patients; Pediatric Hospitals; Pennsylvania; Phenotype; Philadelphia; Physiological; Population Genetics; Positioning Attribute; Predisposition; Prevalence; Process; Regulation; Research; Resources; Role; Skeletal Muscle; Source; Structure of beta Cell of islet; System; Testing; Therapeutic; Tissues; Transcript; United States National Institutes of Health; Universities; Untranslated RNA; Variant; Veterans; biobank; bioinformatics pipeline; candidate identification; causal variant; cell type; chromosome conformation capture; clinical translation; computational pipelines; conditional mutant; diabetes pathogenesis; follow-up; functional genomics; gain of function; gene interaction; gene network; gene regulatory network; genome wide association study; genome-wide; genomic data; genomic locus; human stem cells; human tissue; in vivo; induced pluripotent stem cell; loss of function; molecular phenotype; mouse model; multidisciplinary; multiple data sources; mutant; mutant mouse model; new therapeutic target; novel therapeutics; programs; stem cell model; stem cells; therapeutic target; trait; transcriptome sequencing

Functional Interrogation of T2D-associated genes in human stem cell-derived models and mice Type 2 Diabetes (T2D) is one of the fastest-growing diseases and a leading cause of death throughout the world. A better understanding of the disease process, including characterization of both the genetic etiology and the contribution of different cell types to disease initiation, progression and heterogeneity promises to reveal new therapeutic targets. Large-scale genome-wide association studies (GWAS) of this common complex trait have driven the rapid identification of hundreds of T2D-associated loci. However, the mechanism(s) through which most of these loci influence disease susceptibility remain poorly understood. Our interdisciplinary team at Penn brings together experts in population genetics, T2D GWAS, biostatistics, metabolic tissue biology, human cellular disease modeling and T2D pathophysiology to tackle this critical knowledge gap. In collaboration with other Consortium groups, we aim to accomplish the following goals. (1) Provide the diabetes research community with a robust pipeline for mapping T2D GWAS variants to effector genes and target tissues. (2) Identify new genes and biological pathways that modulate susceptibility to T2D. (3) Define gene regulatory networks relevant to T2D with the goal of uncovering therapeutic ‘entry points’ for developing new treatments. For (1), we will prioritize “candidate effector transcripts” for downstream functional analyses by integrating multiple sources of data to gain a ‘confluence of evidence’ as to their disease relevance and tissue of action. These sources include publically available datasets, a unique collection of internal resources from the Million Veteran Program, and our own functional genomics (RNA-seq, ATAC-seq, chromatin conformation capture etc.) data generated from stem cell-derived T2D relevant cell types. For (2), we will examine the biological function of prioritized T2D-effector transcripts in human cell models of T2D-relevant tissue types using gain- and loss-of- function methods combined with a battery of physiological, metabolic, molecular phenotyping and genomic approaches. These studies include the use of induced pluripotent stem cell (iPSC) models for pancreatic b cells, hepatocytes, adipocytes and skeletal muscle cells, enabling precise genetic engineering and establishment of multiple cell types in the same genetic background. Through this process, we will identify 10 high priority candidate effector genes, which we will advance for comprehensive in vivo analyses in conditional mutant mouse models. For (3), we will perform network analyses through the integration of our multiple data sources to identify molecular memberships in broader pathways and search for pathway components that are potentially amenable for therapeutic targeting.

人类干细胞衍生模型和小鼠中 T2D 相关基因的功能研究 2 型糖尿病 (T2D) 是全球增长最快的疾病之一，也是导致死亡的主要原因。 更好地了解疾病过程，包括遗传病因和疾病特征 不同细胞类型对疾病发生、进展和异质性的贡献有望揭示新的 针对这一常见复杂性状的大规模全基因组关联研究（GWAS）已取得进展。 推动了数百个 T2D 相关位点的快速识别，但是，其机制是什么？ 我们宾夕法尼亚大学的跨学科团队对大多数影响疾病易感性的基因座仍知之甚少。 汇集了群体遗传学、T2D GWAS、生物统计学、代谢组织生物学、人类细胞等领域的专家 疾病建模和 T2D 病理生理学，以解决这一关键的知识差距。 联合体团体，我们旨在完成以下目标。 (1) 为糖尿病研究界提供强大的管道，将 T2D GWAS 变异映射到 效应基因和靶组织。 (2) 识别调节 T2D 易感性的新基因和生物途径。 (3) 定义与 T2D 相关的基因调控网络，目标是发现治疗“入口” 为新疗法开发点。 对于（1），我们将通过整合优先考虑“候选效应转录本”以进行下游功能分析 多个数据源以获得关于其疾病相关性和作用组织的“证据汇合”。 这些来源包括公开可用的数据集，这是来自百万个内部资源的独特集合 Veteran Program，以及我们自己的功能基因组学（RNA-seq、ATAC-seq、染色质构象捕获等） 对于（2），我们将检查从干细胞衍生的 T2D 相关细胞类型生成的数据。 使用增益和丢失对 T2D 相关组织类型的人类细胞模型中的 T2D 效应子转录物进行优先排序 功能方法与一系列生理、代谢、分子表型和基因组相结合 这些研究包括使用胰腺 b 细胞的诱导多能干细胞 (iPSC) 模型， 肝细胞、脂肪细胞和骨骼肌细胞，实现精确的基因工程和建立 通过这个过程，我们将识别出 10 种高优先级的细胞类型。 候选效应基因，我们将在条件突变小鼠体内进行全面的分析 对于（3），我们将通过整合多个数据源进行网络分析来识别。 更广泛途径中的分子成员资格并寻找可能适合的途径成分 用于治疗靶向。

项目成果

Variant to gene mapping for carpal tunnel syndrome risk loci implicates skeletal muscle regulatory elements.

腕管综合征风险位点的基因图谱变异涉及骨骼肌调节元件。

• 发表时间: 2024-03
• 影响因子: 11.1
• 作者: Pahl, Matthew C;Liu, Lin;Pippin, James A;Wagley, Yadav;Boehm, Keith;Hankenson, Kurt D;Wells, Andrew D;Yang, Wenli;Grant, Struan F A
• 通讯作者: Grant, Struan F A

Awakening new sleep biology with machine learning.

通过机器学习唤醒新的睡眠生物学。

• 发表时间: 2023-02-08
• 影响因子: 5.6
• 作者: Hazuga, Mary Ann;Grant, Struan F A
• 通讯作者: Grant, Struan F A

Long-Term Body Mass Index Variability and Adverse Cardiovascular Outcomes.

长期体重指数变异和不良心血管后果。

• 发表时间: 2024-03-04
• 影响因子: 13.8
• 作者: Almuwaqqat, Zakaria;Hui, Qin;Liu, Chang;Zhou, Jin J;Voight, Benjamin F;Ho, Yuk;Posner, Daniel C;Vassy, Jason L;Gaziano, J Michael;Cho, Kelly;Wilson, Peter W F;Sun, Yan V
• 通讯作者: Sun, Yan V

The Diabetes Syndrome - A Collection of Conditions with Common, Interrelated Pathophysiologic Mechanisms.

糖尿病综合症 - 一系列具有共同、相互关联的病理生理机制的病症。

• 发表时间: 2021
• 作者: Rachfal, Amy W;Grant, Struan F A;Schwartz, Stanley S
• 通讯作者: Schwartz, Stanley S

Multi-phenotype analyses of hemostatic traits with cardiovascular events reveal novel genetic associations.

止血特性与心血管事件的多表型分析揭示了新的遗传关联。

• 发表时间: 2022-06
• 作者: Temprano;Sitlani, Colleen M;Bone, William P;Martin;Voight, Benjamin F;Morrison, Alanna C;Damrauer, Scott M;de Vries, Paul S;Smith, Nicholas L;Sabater
• 通讯作者: Sabater