Identifying novel targets for cardioprotection with non-traditional animal models

利用非传统动物模型确定心脏保护的新靶点

基本信息

批准号：
10406111
负责人：
Linda Boettger Goodman
金额：
$ 17.73万
依托单位：
FAUNA BIO INCORPORATED
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-06-01 至 2023-01-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10406111
关键词：
Acute Liver Failure Age Aloral Alzheimer&apos s Disease Animal Disease Models Animal Model Animals Apoptosis Area BCL9 gene Biological Biology Brain Categories Collagen Data Data Set Decision Trees Diabetes Mellitus Disease Disease Resistance Etiology Event Exhibits Fibrosis Gene Expression Profile Genes Genetic Genetic Transcription Genomics Grant Health Hibernation Human Human Genome Hydrogen Peroxide In Vitro Ischemia Lead Liver Liver Failure Logistic Regressions Machine Learning Mammals Medical Methods Modeling Muscle Muscular Atrophy Myocardial Ischemia Neurodegenerative Disorders Neurofibrillary Tangles Obesity Osteoporosis Output Paralysed Pathology Pathway interactions Pharmaceutical Preparations Pharmacologic Substance Phase Phenotype RNA Interference Reperfusion Injury Reperfusion Therapy Resistance Resources Sampling Sequence Analysis Skeletal Muscle Small Business Technology Transfer Research Spermophilus Testing Time Training Transforming Growth Factor beta Translating Validation Vision Work animal data base cardioprotection cost drug discovery experience genome wide association study genomic data healing heart damage human data human disease hyperphosphorylated tau improved in vitro Model in vivo liver ischemia new therapeutic target novel novel therapeutic intervention novel therapeutics phenotypic data repaired screening tau phosphorylation therapeutic development therapeutic target transcriptome sequencing

项目摘要

Project Summary/Abstract: Low-cost sequencing has ushered in a new era of drug discovery that can that utilize genomic information from hundreds of thousands of people. However, humans are a limited resource for identifying novel drug targets, and attempts at therapeutic development often rely on an already well-known set of genes and pathways. Greater potential for discovery exists if we broaden our search throughout the animal kingdom. In particular, animal adaptations for disease resistance have great potential to unearth novel biological pathways to counteract human diseases. Hibernating mammals are an especially rich resource to inspire novel therapeutics as they exhibit numerous transient phenotypes that mirror critical human health problems such as ischemia-reperfusion injury, Alzheimer’s disease, osteoporosis, muscle atrophy, and obesity/diabetes, yet they are able to avoid or reverse pathologies. A systematic understanding of the gene networks utilized to generate the protective and healing phenotypes of hibernators has great potential to reveal novel therapeutic avenues; however, targets that reproduce across independent datasets, including associating with the same phenotype across multiple species have higher likelihood of translating to humans. In this proposal, specifically, we propose to (1) obtain high-throughput phenotypic data to test our platform (2) create a better model for identifying targets based on machine learning and (3) grow our approach into new disease areas. Our long-term vision is to develop a genomics discovery platform centered on hibernating animals for all of the diseases discussed above. We believe that our approach will identify novel therapeutic targets that will translate to humans, and we will advance our discoveries through strategic pharmaceutical partnerships.

项目摘要/摘要：低成本的测序已迎来了一个可以利用的药物发现的新时代来自成千上万人的基因组信息。但是，人类是有限的用于识别新型药物靶标的资源，并经常尝试治疗性开发依靠已经众所周知的基因和途径。存在更大的发现潜力如果我们在整个动物王国中扩大搜索。特别是动物适应抗病性具有发掘新的生物学途径的巨大潜力人类疾病。冬眠哺乳动物是一种激发小说的特别丰富的资源当他们暴露了许多反映关键人类健康的瞬时表型时的治疗诸如缺血 - 再灌注损伤，阿尔茨海默氏病，骨质疏松症，肌肉等问题萎缩和肥胖/糖尿病，但它们能够避免或逆转病理。系统了解用于生成受保护和愈合表型的基因网络冬眠的巨大潜力可以揭示新的治疗途径。但是，这是针对的跨独立数据集复制，包括与相同的表型相关联多种物种具有更高的转化为人类的可能性。在此提案中，特别是我们提案（1）获取高通量表型数据以测试我们的平台（2）创建更好的基于机器学习和（3）将我们的方法发展为新的模型疾病地区。我们的长期愿景是开发一个以中心为中心的基因组发现平台关于上述所有疾病的冬眠动物。我们相信我们的方法将确定将转化为人类的新型治疗靶标，我们将通过战略性药物合作伙伴关系提高我们的发现。