Brain metabolism across the lifespan using multi-parametric MRS

全球预期寿命正在增长，预计到2050年，世界上16%的人口--北美将达到25%--至少65岁。老龄化社会暴露于越来越多与年龄有关的疾病的出现，如阿尔茨海默病和相关痴呆症(AD/ADRD)。使用新的病理生理变化标记物识别高危个体将成为21世纪医学的关键挑战，以实现预防和早期干预。建立这些标记物在生命周期内的标准范围对于早期诊断和提高我们对健康衰老和AD机制的理解是必不可少的。 质子磁共振波谱(1H-MRS)是一种非侵入性的体内定量内源性代谢产物、脂质和大分子(MM)信号的方法。MRS信号的幅度分别由这些化合物的浓度和MR弛豫时间决定，即局部生化指标和细胞微观结构的指示物。不幸的是，使用传统的MRS方法，特定对象的代谢物松弛和MM估计非常耗时，研究人员被迫使用平均文献值和假设。这种做法存在很大问题，因为代谢物水平、松弛时间和MM背景的变化反映了不同的生物过程，这些过程在整个生命周期内独立进化，但不能用传统的MRS区分(例如，信号随着年龄的增加而减少可能反映代谢物水平较低或横向松弛时间较短)。因此，目前的MRS方法在健康衰老和神经退行性疾病(如ADRD)中的可解释性大大降低。这项研究建议将通过开发新的MRS方法来解决这一关键的知识差距，该方法允许同时进行特定对象的代谢物浓度、松弛时间和MM背景估计。通过分离这三个候选生物标志物，可以获得比以前更具特异性的局部神经化学和细胞微结构的全面概况。在20岁至80岁的健康志愿者队列中的应用将建立候选生物标记物在正常衰老中的年龄轨迹。 开发这些新技术需要在磁共振序列开发和数据分析方面的大量专业知识。这项建议建立在我开发我们的开源MRS软件包Osprey的特殊记录的基础上，并从该领域的世界领先专家那里获得了新的脉冲序列开发培训。 约翰霍普金斯大学提供出色的职业发展资源和来自世界知名专家的培训，这些培训是成功指导我在MRS、PULSE编程以及老龄和AD/ADRD队列中的临床研究设计领域所必需的。该项目将开发新的技术来表征重要的神经生物学过程及其在健康老龄化中的作用，为识别AD/ADRD的新的早期生物标志物奠定基础。

Global life expectancy is rising, and 16% of the world’s population – up to 25% in North America – is predicted to be at least 65 years of age by 2050. Aging societies are exposed to increasing emergence of age-related diseases such as Alzheimer’s Disease and related dementias (AD/ADRD). Identifying individuals at risk using new markers of pathophysiological changes will become a key challenge of 21st century medicine to enable prevention and early intervention. Establishing normative ranges of these markers across the lifespan is imperative for early diagnostics and to improve our understanding of healthy aging and AD mechanisms. Proton magnetic resonance spectroscopy (1H-MRS) is a non-invasive in-vivo method quantifying signals from endogenous metabolites, lipids and macromolecules (MM). MRS signal amplitudes are determined by the concentrations and MR relaxation times of these compounds, i.e. indicators of local biochemistry and cellular microstructure, respectively. Unfortunately, subject-specific metabolite relaxation and MM estimation is prohibitively time-consuming with conventional MRS methods, and researchers are forced to use averaged literature values and assumptions instead. This practice is highly problematic as changes in metabolite levels, relaxation times and the MM background reflect different biological processes that evolve independently across the lifespan, but cannot be distinguished using conventional MRS (e.g., signal decreases with age could reflect lower metabolite levels or shorter transverse relaxation times). Current MRS methods therefore have substantially diminished interpretability in healthy aging and neurodegenerative diseases such as ADRD. This research proposal will address this critical knowledge gap by developing novel MRS methods allowing simultaneous subject-specific metabolite concentration, relaxation time, and MM background estimation. By separating those three candidate biomarkers, a comprehensive profile of local neurochemistry and cellular microstructure with greater specificity than previously possible can be achieved. Application in a cohort of healthy volunteers between 20 and 80 years of age will establish age trajectories of the candidate biomarkers in normal aging. Developing these novel techniques requires substantial expertise both in MR sequence development and in data analysis. This proposal builds upon my exceptional record in developing our open-source MRS software package Osprey with new training in pulse sequence development from world-leading experts in the field. The Johns Hopkins University provides outstanding career development resources and training from world-renowned experts necessary to successfully mentor me in the field of MRS, pulse programming, and clinical research design in aging and AD/ADRD cohorts. This project will develop novel techniques to characterize important neurobiological processes and their role in healthy aging, laying the foundation to identify new early biomarkers of AD/ADRD.