Bridging the gap between type 2 diabetes GWAS and therapeutic targets

缩小 2 型糖尿病 GWAS 与治疗目标之间的差距

基本信息

批准号：
10649602
负责人：
Melina C Claussnitzer
金额：
$ 186.37万
依托单位：
UNIV OF NORTH CAROLINA CHAPEL HILL
依托单位国家：
美国
项目类别：
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/10649602
关键词：
Acceleration Address Adipocytes Adipose tissue Affect African Alleles Animal Model Biological Biological Assay Catalogs Cell model Cells Chromatin Collaborations Collection Communities Complement Computer Analysis Computing Methodologies DNA DNA Sequence Data Data Set Disease Distant Drug Targeting East Asian Electrophysiology (science)Environment Ethnic Origin European Evaluation Frequencies Functional disorder Generations Genes Genetic Genetic Variation Genetic study Genome Genomics Genotype Gluconeogenesis Hepatic Tissue Hepatocyte Heritability Hispanic Human Human Genetics Impairment Individual Inherited Insulin Insulin deficiency International Investigation Islet Cell Latino Link Lipids Liver Maps Meta-Analysis Methods Mitochondria Molecular Morbidity - disease rate Muscle Muscle Cells Names Non-Insulin-Dependent Diabetes Mellitus Nucleic Acid Regulatory Sequences Nucleotides Pathway interactions Pharmaceutical Preparations Physiological Play Population Population Heterogeneity Regulation Regulatory Element Research Personnel Resistance Role Series Signal Pathway Signal Transduction South Asian Structure of beta Cell of islet System Testing Tissues Transcript Translating Untranslated RNA Validation Variant Vision Visualization analytical method candidate marker causal variant cell type clinical phenotype computerized tools diabetes mellitus genetics diabetes pathogenesis diabetes risk disease heterogeneity disorder risk epigenomics experimental study functional genomics gene regulatory network genetic architecture genetic association genetic variant genome annotation genome editing genome wide association study genome-wide genome-wide analysis genomic data glucose uptake improved in vivo insight insulin secretion islet lipid metabolism mortality multidisciplinary new therapeutic target novel novel therapeutic intervention pancreatic juice protein function risk variant skeletal tissue therapeutic target trait transcriptomics

项目摘要

Type 2 diabetes (T2D) is a heterogeneous disorder characterized by resistance of hepatic, skeletal muscle and adipose tissues to insulin and a relative deficiency of insulin secretion by pancreatic β cells. T2D has a substantial genetic component, and over the past decade human genetic studies have identified over 400 association signals across diverse populations. However, in most cases the specific variants and genes responsible for these association signals are not known. T2D signals include loci for which functions of the protein products encoded by nearby genes are poorly characterized, the closest known gene is distant, or more than one gene appears to be a plausible biological candidate. Identifying the causal variants, the regulatory gene networks affected by the change in DNA sequence, and the mechanisms by which such variation leads to disease are critical steps toward understanding the genetic architecture of T2D, validating potential drug targets, and developing novel therapeutic strategies. Here, we propose large-scale multi-disciplinary functional genomics projects in islet, liver, adipose and muscle cells to determine the contributions and mechanisms underlying T2D risk-associated variants and their downstream effector transcripts. Throughout the project, we leverage our prior and ongoing generation of genomic data sets and genome-wide and targeted screens for function of variants and genes. To complement these efforts, we will first collect genome-wide array and sequencing-based association study results, identify conditionally distinct association signals and construct credible sets of variants. We propose to link variants to effector transcripts through analyses of genome-wide transcriptomic and epigenomic data, perturbation assays that alter thousands of variant-containing regulatory elements and effector transcripts, perturbations of tens of specific variants, and integrative computational analyses. Next, we propose systematic evaluation of hundreds of potential effector transcripts through use of genome-wide and targeted screens of insulin secretion, lipid accumulation, mitochondrial function, glucose uptake, and differentiation state, with assay selection depending on cell type. Based on these results, we propose focused studies on tens to hundreds of potential effector transcripts to evaluate electrophysiology, gluconeogenesis, lipid metabolism and signaling pathways, and we propose thorough investigation the context-specific mechanism of action of individual genes. Finally, we propose to analyze, integrate, and visualize all data by placing effector transcripts into cell-type and environmental context-specific networks, selecting network nodes as candidate biomarkers and modulation points for drugs, and building a framework to understand the tissue-specific contribution of variants and transcripts to individual disease heterogeneity. Successful completion of these aims will translate T2D association signals into biological insights and therapeutic targets.

2 型糖尿病 (T2D) 是一种异质性疾病，其特征是肝脏、骨骼肌和糖尿病的抵抗力脂肪组织对胰岛素的抵抗力和胰腺β细胞分泌胰岛素的相对不足与T2D有显着的关系。过去十年人类遗传学研究已经确定了 400 多个关联然而，在大多数情况下，具体的变异和基因负责这些信号。 T2D 信号包括编码蛋白质产物功能的基因座尚不清楚。附近基因的特征很差，最近的已知基因很遥远，或者多个基因似乎是一个合理的生物学候选者，确定因果变异，即受变异影响的调控基因网络。 DNA 序列的变化以及这种变化导致疾病的机制是实现这一目标的关键步骤了解 T2D 的遗传结构、验证潜在的药物靶点并开发治疗新药在这里，我们提出了关于胰岛、肝脏、脂肪的大规模多学科功能基因组学项目。和肌肉细胞以确定 T2D 风险相关变异的贡献和机制在整个项目中，我们利用了我们之前和正在生成的下游效应器转录本。基因组数据集以及针对变体和基因功能的全基因组和靶向筛选。这些努力，我们将首先收集全基因组阵列和基于测序的关联研究结果，识别我们建议将变体与条件不同的关联信号联系起来并构建可信的变体集。通过分析全基因组转录组和表观基因组数据、微扰分析来分析效应转录本改变数千个包含变异的调控元件和效应转录本，数十个的扰动接下来，我们提出对数百个的系统评估。通过使用全基因组和胰岛素分泌、脂质的靶向筛选来筛选潜在的效应转录本积累、线粒体功能、葡萄糖摄取和分化状态，分析选择取决于基于这些结果，我们建议对数十至数百种潜在效应物进行重点研究。转录本来评估电生理学、糖异生、脂质代谢和信号通路，我们彻底研究个体基因的特定作用机制，最后，我们提出。通过将效应子转录物放入细胞类型和环境中来分析、整合和可视化所有数据特定于上下文的网络，选择网络节点作为候选生物标志物和药物调节点，并建立一个框架来了解变异和转录本对个体的组织特异性贡献成功完成这些目标将把 T2D 关联信号转化为生物学信号。见解和治疗目标。

项目成果

期刊论文数量（19）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Type 2 Diabetes risk alleles in Peptidyl-glycine Alpha-amidating Monooxygenase influence GLP-1 levels and response to GLP-1 Receptor Agonists.

肽基甘氨酸α-酰胺化单加氧酶中的 2 型糖尿病风险等位基因影响 GLP-1 水平和对 GLP-1 受体激动剂的反应。

DOI：
发表时间：
2023-04-12
期刊：
影响因子：
0
作者：
Umapathysivam, Mahesh M;Araldi, Elisa;Hastoy, Benoit;Dawed, Adem Y;Vatandaslar, Hasan;Sengupta, Shahana;Kaufmann, Adrian;Thomsen, Søren;Hartmann, Bolette;Jonsson, Anna E;Kabakci, Hasan;Thaman, Swaraj;Grarup, Niels;Have, Christian T;Færch, Kr
通讯作者：
Færch, Kr

Electrophysiological characterisation of iPSC-derived human β-like cells and an SLC30A8 disease model.

iPSC 衍生的人类 β 样细胞和 SLC30A8 疾病模型的电生理学特征。

DOI：
发表时间：
2023-10-18
期刊：
影响因子：
0
作者：
Jaffredo M;Krentz NAJ;Champon B;Duff CE;Nawaz S;Beer N;Honore C;Clark A;Rorsman P;Lang J;Gloyn AL;Raoux M;Hastoy B
通讯作者：
Hastoy B

Gaining insight into metabolic diseases from human genetic discoveries.

从人类基因发现中深入了解代谢疾病。

DOI：
发表时间：
2021-12
期刊：
影响因子：
0
作者：
Claussnitzer, Melina;Susztak, Katalin
通讯作者：
Susztak, Katalin

Rare variant association analysis in 51,256 type 2 diabetes cases and 370,487 controls informs the spectrum of pathogenicity of monogenic diabetes genes.

对 51,256 例 2 型糖尿病病例和 370,487 例对照进行的罕见变异关联分析揭示了单基因糖尿病基因的致病性谱。

DOI：
发表时间：
2023-09-29
期刊：
影响因子：
0
作者：
Schroeder, Philip;Mandla, Ravi;Huerta;Alkanak, Ahmed;Nagy, Dorka;Szczerbinski, Lukasz;Madsen, Jesper G S;Cole, Joanne B;Porneala, Bianca;Westerman, Kenneth;Li, Josephine H;Pollin, Toni I;Florez, Jose C;Gloyn, Anna L;Cebola, I
通讯作者：
Cebola, I

Multi-ancestry Polygenic Mechanisms of Type 2 Diabetes Elucidate Disease Processes and Clinical Heterogeneity.

2 型糖尿病的多祖先多基因机制阐明了疾病过程和临床异质性。

DOI：
发表时间：
2023-09-29
期刊：
影响因子：
0
作者：
Smith, Kirk;Deutsch, Aaron J;McGrail, Carolyn;Kim, Hyunkyung;Hsu, Sarah;Mandla, Ravi;Schroeder, Philip H;Westerman, Kenneth E;Szczerbinski, Lukasz;Majarian, Timothy D;Kaur, Varinderpal;Williamson, Alice;Claussnitzer, Melina;Florez, Jose C;Ma
通讯作者：
Ma