Using MR Spectroscopy to Measure Mammalian Neurogenesis in Vivo

使用磁共振波谱测量哺乳动物体内神经发生

• 批准号: 10627832
• 负责人: MIRJANA MALETIC-SAVATIC
• 金额: $ 77.29万
• 依托单位: BAYLOR COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-06-01 至 2027-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10627832
• 关键词: Address; Adolescent; Adopted; Adult; Age; Aging; Agreement; Alzheimer' s Disease; Alzheimer' s disease related dementia; Animal Model; Area; Attention; Autopsy; Behavioral; Biological Markers; Brain; Bromodeoxyuridine; Cells; Clinical; Data; Detection; Disease; Drops; Electroconvulsive Therapy; Excision; Foundations; Goals; Hippocampus; Human; Image; Impairment; In Vitro; Learning; Ligands; Lipids; Machine Learning; Magnetic Resonance Spectroscopy; Major Depressive Disorder; Measurement; Measures; Memory; Mental Depression; Methods; Modeling; Monounsaturated Fatty Acids; Moods; Mus; Natural regeneration; Network-based; Newly Diagnosed; Noise; Nuclear Receptors; Oleic Acids; Pathway Analysis; Pattern Recognition; Performance; Pharmaceutical Preparations; Process; Proliferating; Protocols documentation; Reproducibility; Resistance; Rodent; Scanning; Sensitivity and Specificity; Signal Transduction; Site; Specificity; Spectrometry; Statistical Data Interpretation; Techniques; Time; Tissues; Validation; Wild Type Mouse; Work; adult neurogenesis; age effect; aged; analytical method; biomarker validation; computerized data processing; convolutional neural network; data acquisition; deep learning; detection method; environmental enrichment for laboratory animals; gamma-Aminobutyric Acid; improved; in vivo; in vivo magnetic resonance spectroscopy; innovation; interest; learning strategy; model organism; nerve stem cell; neural; neural network; neurogenesis; newborn neuron; novel; novel strategies; repaired; response; stem; stem cell self renewal; stem cells; tool

PROJECT SUMMARY Since its discovery, adult mammalian hippocampal neurogenesis—particularly human—has attracted attention and controversy. Envisioned as a unique, intrinsic capacity of the brain center for learning and memory and mood control to repair and regenerate, over the past three decades it has been scrutinized in model organisms, which provided a wealth of data confirming its functional relevance. The case for human neurogenesis, however, has faced a much harder road to acceptance because the only means to study it has been by immunostaining of the postmortem tissue. It is thus of no surprise that we know very little about it. While most agree that adult human hippocampus harbors newborn neurons that decline with age and with diseases such as Alzheimer’s, their functional importance has proved elusive without a live and non-invasive measure. As noted in the RFA, developing a means of measuring neurogenesis rates in vivo in a non-invasive manner is of critical interest. Doing so in a technique that can be readily used in not only animal models, but also in humans would give us a vital tool in our effort to not only understand neurogenesis per se, but to also understand how neurogenesis may lead to impairments found in aging and in AD/ADRD. This proposal takes as its foundation the innovation by our group of the first and only in vivo magnetic resonance spectroscopy (MRS)-based marker of neurogenesis: a lipid-based signal resonating at 1.28 ppm. While our group’s initial work in this area has identified and validated this biomarker, several critical gaps exist that must be addressed before it can be widely adopted in human studies of aging and AD/ADRD. Our goal in this proposal is to adapt a number of existing techniques to the accurate measurement and quantification of the 1.28ppm signal and to further develop analytical methods based on deep machine learning so that it can be broadly and reliably used to assess levels of and changes in human adult neurogenesis. In particular, we will: 1) Acquire data from phantoms, in vivo and ex vivo mice, and humans using techniques that will allow for more reliable quantification and validation, 2) Adapt the MEGA-PRESS technique successfully used to quantify GABA to isolate the neurogenic-associated signal at 1.28ppm from the nearby lactate signal; 3) Adapt pre-processing tools we have developed in related studies that enhance signal-to-noise in MRS signals from the hippocampus; 4) Further develop time-domain based processing tools to isolate the neurogenic signal from overlapping components; and 5) Further develop a neural-network based approach to detect and quantify it. In each of these areas, we have existing solutions that are functional, but we believe can be improved upon to provide more reliable and robust quantification of the neurogenic signal. Here, we will formally evaluate the new approaches relative to the existing approaches to produce a final acquisition-through-quantification pipeline that can be used by the field.

项目摘要 自发现以来，成年哺乳动物海马神经发生（尤其是人类）引起了人们的注意 和争议。被设想为大脑学习和记忆中心的独特，内在的能力， 在过去的三十年中，情绪控制要修复和再生，在模型中已仔细检查 有机体提供了大量数据证实其功能相关性。人类的案例 然而，神经发生已经面临着更艰难的接受之路，因为研究它的唯一手段 我们是通过对死后组织的免疫染色。因此，我们对此一无所知，这不足为奇。 大多数人都同意成年人类海马藏有新生儿神经元，这些神经元随着年龄的增长而下降 诸如阿尔茨海默氏症之类的疾病，它们的功能重要性是在没有生命和无创的而难以捉摸的 措施。 如RFA所述，以非侵入性的方式开发一种在体内测量神经发生率的方法是 关键的关注。这样做的技术不仅可以在动物模型中，而且在 人类将为我们提供一个至关重要的工具，不仅要了解神经发生本身，还可以 了解神经发生如何导致衰老和AD/ADRD中的损害。该提议采取了 作为其基础，我们的第一个也是唯一的体内磁共振光谱的创新 （MRS）神经发生的标记：一种基于脂质的信号在1.28 ppm处共鸣。而我们小组的最初 该领域的工作已经确定并验证了该生物标志物，存在一些关键差距必须解决 在对衰老和AD/ADRD的人类研究中可以广泛采用之前。我们在此提案中的目标是适应 1.28ppm信号的准确测量和数量和数量的许多现有技术以及 进一步开发基于深度机器学习的分析方法，以便可以广泛使用 评估人类成人神经发生的水平和变化。特别是：1）从 幻影，体内和外体内小鼠以及人类使用将​​允许更可靠的技术 数量和验证，2）成功地使用用于量化GABA的大型压力技术 从附近的鞋底信号中分离出1.28ppm的神经源相关信号； 3）调整预处理 我们在相关研究中开发的工具可以增强海马MRS信号中的信号噪声； 4）进一步发展基于时间域的处理工具，以隔离神经源信号 成分; 5）进一步开发一种基于神经网络的方法来检测和量化它。在每个 在这些领域，我们拥有可行的现有解决方案，但我们认为可以改进 神经源信号的更可靠和稳健数量。在这里，我们将正式评估新的 相对于现有的方法，方法是生产最终收购量化管道的方法 该领域可以使用。