Translating Genetic Risk Factors to Therapies: From Big Data to Druggable Targets

将遗传风险因素转化为治疗方法:从大数据到可药物靶点

基本信息

  • 批准号:
    10604891
  • 负责人:
  • 金额:
    $ 8.45万
  • 依托单位:
  • 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:
    2021-07-01 至 2026-06-30
  • 项目状态:
    未结题

项目摘要

PROJECT SUMMARY Genome-wide association studies (GWAS) provide insight to underlying etiologies of disease not obvious through clinical evaluation or pathophysiology alone. Genetic variants associated with complex, often refractory diseases such as Alzheimer’s Disease (AD) and Multiple Sclerosis (MS) may hold the key for the next generation of treatment options. Leveraging genetic data with current standards of care and known pathophysiology can provide a strong premise for mechanistic studies and novel drug targets. My current work studies the molecular genetics of CD33 in AD under Dr. Steve Estus. CD33 normally acts to inhibit microglial activation in the brain, suppressing amyloid clearance. We are investigating how the AD-protective single nucleotide polymorphism (SNP) in CD33 modulates protein, and thereby cellular, function. This SNP leads to an increase in an alternative CD33 protein isoform which, based on our recent genetic data, may promote—rather than suppress—microglial activation. I will learn new technical skills during the F99 phase of this award, and I will use these skills as I switch focus to MS and progress into the K00 phase to acquire additional, powerful techniques and models including work with patient samples, pluripotent stem cells, single-cell sequencing technologies, and animal models. In Specific Aim 1, I detail how my training in molecular biology and genetic concepts has allowed me to conceive independent hypotheses and carry out complex experiments. My doctoral work on the molecular genetics of CD33 and its association with reduced AD risk has provided training in GWAS interpretation, quantitative PCR, immunoassays such as Western blotting and co-immunoprecipitation, and genetic techniques including transfection and genome editing strategies in cell culture. In Specific Aim 2, I will continue to develop as a scientist and finish my doctoral work, carrying out increasingly complex studies to include high-resolution confocal imaging and subcellular localization, measuring time- and dose-dependent protein phosphorylation in situ, gene expression arrays, and functional assays including phagocytosis in vitro. I will also continue developing my professional skills such as oral and written communication, networking, and mentorship. In Specific Aim 3, I will extend my doctoral training to include work with human tissue samples and mouse models of MS. I have not yet identified a specific postdoctoral mentor, but my ideal mentor will have experience conducting human subjects research, using mouse models of MS, and have a strong track record of training fellows to become tenure-track faculty. I will identify a mentorship team to guide my technical and professional development during this phase. I will leverage my current training in molecular genetics to identify MS-associated functional SNPs, my training-in-progress to identify the mechanism behind these SNPs at the protein and intracellular signaling levels, and my future training with murine models and human subjects to establish a high- impact, translational career, combining genetic, clinical, and pathology findings for pharmacological breakthroughs in neuroimmune diseases.
项目摘要 全基因组关联研究(GWAS)为不明显的疾病的潜在病因提供了见解 仅通过临床评估或病理生理学。与复杂的,通常是难治性的 阿尔茨海默病(AD)和多发性硬化症(MS)等疾病可能是下一代的关键 治疗方案。利用遗传数据与当前的护理标准和已知的病理生理学, 为机理研究和新的药物靶点提供了强有力的前提。我目前的工作是研究 在Steve Estus博士的领导下,研究AD中的CD 33遗传学。CD 33通常用于抑制脑中的小胶质细胞活化, 抑制淀粉样蛋白清除。我们正在研究AD保护性单核苷酸多态性 (SNP)在CD 33调节蛋白质,从而细胞,功能。这种SNP导致替代性的增加。 根据我们最近的遗传数据,CD 33蛋白亚型可能促进而不是抑制小胶质细胞 activation.我将在F99阶段学习新的技术技能,并在切换时使用这些技能 专注于MS并进入K 00阶段,以获得更多强大的技术和模型,包括 与患者样本、多能干细胞、单细胞测序技术和动物模型一起工作。 在具体目标1中,我详细介绍了我在分子生物学和遗传概念方面的训练如何使我能够 构思独立的假设并进行复杂的实验。我的博士论文是关于 CD 33的遗传学及其与AD风险降低的相关性提供了GWAS解释的培训, 定量PCR、免疫测定如Western印迹和免疫共沉淀以及遗传技术 包括细胞培养中的转染和基因组编辑策略。在《目标2》中,我将继续开发 作为一名科学家,我完成了我的博士论文,进行越来越复杂的研究,包括高分辨率 共聚焦成像和亚细胞定位,测量时间和剂量依赖性蛋白磷酸化, 原位,基因表达阵列和功能测定,包括体外吞噬作用。我也会继续发展 我的专业技能,如口头和书面沟通,网络和指导。具体目标3: 我将扩展我的博士课程,包括研究人体组织样本和MS. I小鼠模型 我还没有确定一个具体的博士后导师,但我的理想导师将有经验进行 人类受试者的研究,使用小鼠模型的MS,并有良好的记录,培训研究员, 成为终身教职我将确定一个导师团队,指导我的技术和专业 在这个阶段的发展。我将利用我目前在分子遗传学方面的训练来鉴定MS相关的 功能性SNPs,我正在进行的培训,以确定这些SNPs背后的蛋白质和 细胞内信号水平,我未来的训练与小鼠模型和人类受试者,以建立一个高- 影响,翻译生涯,结合遗传,临床和病理学发现,药理学 神经免疫疾病的突破

项目成果

期刊论文数量(0)
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Benjamin C. Shaw其他文献

Pseudogene-mediated gene conversion after CRISPR-Cas9 editing demonstrated by partial CD33 conversion with SIGLEC22P
通过使用 SIGLEC22P 进行部分 CD33 转换证明了 CRISPR-Cas9 编辑后的假基因介导的基因转换
  • DOI:
    10.1101/2021.04.20.440641
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Benjamin C. Shaw;S. Estus
  • 通讯作者:
    S. Estus

Benjamin C. Shaw的其他文献

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{{ truncateString('Benjamin C. Shaw', 18)}}的其他基金

Translating Genetic Risk Factors to Therapies: From Big Data to Druggable Targets
将遗传风险因素转化为治疗方法:从大数据到可药物靶点
  • 批准号:
    10318416
  • 财政年份:
    2021
  • 资助金额:
    $ 8.45万
  • 项目类别:
Translating Genetic Risk Factors to Therapies: From Big Data to Druggable Targets
将遗传风险因素转化为治疗方法:从大数据到可药物靶点
  • 批准号:
    10668535
  • 财政年份:
    2021
  • 资助金额:
    $ 8.45万
  • 项目类别:

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