Defining lipid droplet homeostasis in Alzheimer's disease and aging with high molecular specificity using mass spectrometry imaging and isomer resolved lipidomics

使用质谱成像和异构体解析脂质组学以高分子特异性定义阿尔茨海默病和衰老中的脂滴稳态

• 批准号: 10645746
• 负责人: Alison J Scott
• 金额: $ 59.96万
• 依托单位: UNIVERSITY OF MARYLAND BALTIMORE
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-15 至 2028-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10645746
• 关键词: Adoption; Affect; Age; Aging; Alzheimer disease prevention; Alzheimer' s Disease; Alzheimer' s disease model; Alzheimer' s disease patient; Alzheimer' s disease related dementia; Atlases; Awareness; Biological Assay; Brain; Brain Mapping; Brain region; Cells; Characteristics; Cholesterol; Cholesterol Esters; Communities; Data; Diabetes Mellitus; Disease; Disease model; Dose; Elements; Endotoxins; Failure; Female; Fingerprint; Gaucher Disease; Health; Hippocampal Formation; Histologic; Histology; Homeostasis; Human; Image; Immunohistochemistry; Individual; Inflammation; Intervention; Isomerism; Knowledge; Life; Link; Lipids; Liver Failure; Machine Learning; Maintenance; Maps; Mass Spectrum Analysis; Methods; Modeling; Molecular; Mus; Neighborhoods; Neurons; Organelles; Organism; Parkinson Disease; Pathology; Persons; Phospholipids; Physiologic pulse; Population; Production; Protein Isoforms; Proteins; Recycling; Regulation; Research; Resolution; Resources; Role; Specificity; Sphingolipids; Stains; Surveys; Testing; Time; Tissues; Transcriptional Regulation; Triglycerides; United States; Wild Type Mouse; aging brain; brain cell; brain tissue; cell type; combinatorial; healthspan; healthy aging; interest; lipid metabolism; lipid transport; lipidomics; machine learning method; male; mass spectrometric imaging; meter; mouse model; multimodality; normal aging; novel; phenotypic data; pi bond; preservation; sex; stable isotope; tool; transcriptomics; translational therapeutics

SUMMARY Loss of healthspan - declining health and function as we age – impacts nearly every living organism and is a pronounced feature of Alzheimer’s disease and related dementias (ADRD), affecting nearly 6 million people in the United States. Lipids are poorly understood central components of aging, having roles in healthy aging and diseases of aging. The gap in lipid knowledge begins with a missing definition of ‘normal’ and extends to a lack of understanding surrounding lipid fluctuations throughout life. Lipid homeostasis is an important component of the healthy brain and both aging and multiple diseases are associated with alterations in lipid populations and lipid droplet (LD) volume and count. Dysregulated lipid homeostasis is linked to inflammation, diabetes, forms of liver failure, Gaucher disease, Parkinson’s disease, ADRD, and untold more pathologies. The failure to understand lipids in health and disease can be explained by a lack of adequate tools to study lipids. With the wide adoption of mass spectrometry tools, we recently entered the lipidomic era in which lipids can be characterized in fine structural detail across a range of lipid classes with spatial sensitivity and relative or absolute quantity. Spatial lipidomics using multimodal mass spectrometry imaging (MSI) produces regio-, cell-, and organelle-specific lipid maps and reveals changes in tissue sections even when traditional, extracted lipidomic studies fail to show changes. While progress has been made in spatial mapping of brain lipids in aging and AD, these studies were limited by scope (lacking total lipid coverage, spatial resolution, and structural specificity). Here, we will use leading edge high specificity and resolution spatial lipidomics to describe the most thorough spatial lipid survey of aging brains possible, to date, using a combinatorial approach. We will produce characteristic lipid fingerprints based on age, sex, disease state, and brain region. These lipid fingerprints will be supported with phenotypic data and spatial transcriptomic data. These end result will be an important resource for the aging and lipid research communities and will lead to new, translational therapeutic approaches.

摘要 健康寿命的丧失--随着年龄的增长，健康和功能不断下降--几乎影响到每一个活着的有机体，是一种 阿尔茨海默病和相关痴呆症(ADRD)的明显特征，影响到 美国。脂质是衰老的核心成分，人们对此知之甚少，在健康的衰老和 老年性疾病。脂类知识的空白始于对正常的定义缺失，并延伸到缺乏 在整个生命中理解周围的脂肪波动。脂类动态平衡是 健康的大脑、衰老和多种疾病都与血脂人群和 脂滴(LD)体积和计数。脂质平衡失调与炎症、糖尿病、 肝功能衰竭、高谢病、帕金森氏病、多器官功能障碍综合症，以及更多的疾病。未能做到 理解脂类在健康和疾病中的作用可以通过缺乏足够的工具来研究脂类来解释。与 随着质谱学工具的广泛采用，我们最近进入了脂质体时代，在这个时代，脂类可以 具有精细结构细节的特征，跨越一系列具有空间敏感性和相对或 绝对量。使用多模质谱成像(MSI)的空间脂质组学产生区域、细胞和 和细胞器特有的脂类图谱并揭示组织切片的变化，即使在传统的、提取的 脂肪组学研究没有显示出变化。虽然在脑部脂质的空间图谱方面取得了进展 对于衰老和阿尔茨海默病，这些研究受到范围的限制(缺乏总的脂类覆盖率、空间分辨率和 结构专一性)。在这里，我们将使用前沿的高特异性和分辨率空间脂质组学来 描述到目前为止对老化大脑进行的最彻底的空间血脂调查，使用组合 接近。我们将根据年龄、性别、疾病状态和大脑区域制作具有特征的脂肪指纹。 这些脂类指纹将得到表型数据和空间转录数据的支持。这些最终结果 将是衰老和脂质研究社区的重要资源，并将导致新的，翻译的 治疗方法。