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Genomic Analyses for Elucidating Novel Targets for Symptoms Management

Genomic Analyses for Elucidating Novel Targets for Symptoms Management
用于阐明症状管理新目标的基因组分析
批准号:
8940019
负责人:
Ann Cashion
金额:
$93.23万
依托单位国家:
美国
项目类别:
财政年份:
--
资助国家:
美国
项目状态:
未结题
起止时间:
至

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中文摘要
翻译
大多数症状是多因素的,遗传和环境因素都会导致个体差异。候选基因研究已经在生物学假设的基础上进行,以确定复杂性状(如疼痛)的相关遗传变异。然而,影响因素的复杂网络和涉及不同症状的数千个分子使得很难检测出对个体独特的疾病易感性负责的遗传变异。单一基因的常见变异不太可能对复杂性状起主导作用;相反,每个基因的作用似乎是微妙的,作用于多种生物途径中的一种,使其信号难以检测。
英文摘要
Most symptoms are multifactorial in origin with both genetic and environmental factors contributing to individual variations. Candidate gene studies on the basis of biological hypotheses have been performed to identify relevant genetic variation in complex traits such as pain. However, the complicated mesh of contributing factors and the thousands of molecules involved in different symptoms makes it difficult to detect responsible genetic variations for an individuals unique susceptibility to disorders. It is unlikely that common variations in a single gene act dominantly on complex traits; rather, the contribution of each gene seems to be subtle, acting on one of multiple biological pathways, making its signal difficult to detect. The combined impact of the rapid increase in knowledge of diseases and the ability to apply powerful and high capacity technology has raised expectations for more effective and safer medicines for various types of symptoms management. Developing new treatment strategies for symptoms management is also critically dependent on identifying new target molecules and defining phenotypes for specific types of disorders. Therefore the first step of this project has been to define the characteristics of experimental and clinical phenotypes. Recently, we launched multiple projects with next generation sequencing (NGS) technology, which allows us to perform entire and/or targeted genome sequencing. The role of genetic and epigenetic factors on symptoms in various disorders and/or conditions will continue to be studied. For example, in neurological disorders such as acute pain, mild traumatic brain injury and PTSD, we are using genotyping, gene and protein expression, and patient reported outcomes to better understand the reciprocal interplay between these factors and the numerous biologic/mechanistic pathways including the inflammatory cascade. Gene expression profiles from the soldiers back from war zone were presented at the multiple meetings (CNRM and ASN meeting) and have been submitted for publication. Two epigenetic studies using DNA methylation chromatin immunoprecipitation followed by whole genome scale sequencing were conducted from civilian and military groups. Epigenetic changes in the sports related concussion patients will be presented at the ASHG meeting. The second epigenetic study in military PTSD patients finished sequencing of samples and the data are under the analysis. Using the targeted next generation sequencing technology, we also have 2 on-going microbiome projects to characterize population of microorganisms in human and/or animal body from different disease status. Using a next generation semiconductor sequencer, microbiome was analyzed with extensive sequencing of 16s rRNA region in an animal model of irritable bowel syndrome and human patients. The results were presented at the scientific meeting and submitted for publication. Another microbiome project was launched recently for oral microbiome from the aplastic anemia patients. So far, preliminary data analysis was finished and its result will be presented at the IADR meeting. Additional samples will be sequenced and analyzed. Mainly both projects found that the microbiome composition is altered in specific disease conditions. Developing new analyzing methods for the high throughput big data generated by the next generation sequencers is another goal of these projects. From these results along with biological knowledge of multiple pathways in neurological disorders, we will be able to suggest molecular-genetic mechanisms of those diseases at the level of the individual. Finally, we can suggest integrative genomic analysis to develop new drugs and test them based on individual genetic information.
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