# High-Throughput 3D Multiscale Mass Spectrometry Imaging for Understanding Neurochemical Heterogeneity in Alzheimer's Disease > **NIH NIH R01** · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · 2024 · $731,735 ## Abstract PROJECT ABSTRACT: Understanding Alzheimer’s disease (AD) and identifying effective interventions are among the most exciting scientific frontiers and most critical healthcare challenges. While the roles of several pathological hallmarks of AD have been extensively studied, the biochemical alterations associated with these hallmarks and the mechanisms underlying progressive neuron loss and neuronal vulnerability in AD are not fully understood. Neurogenesis, a unique characteristic of the hippocampal formation, has been shown to play important roles in aging and AD progression. Abnormal early declines in neurogenesis have been observed in AD brains in both human and animal models, but the molecular profile of alterations in vulnerable brain circuits and neurons associated with varied neurogenesis have not been documented. Fourier transform mass spectrometry imaging (MSI) and single cell analyses allow for mapping and profiling hundreds to thousands of molecules in biological samples and single cells, providing unparalleled chemical insights relevant to AD as discussed above. However, several major challenges exist: (1) the limited throughput that prohibits the analysis of many tissue slices and samples; (2) the challenges associated with high-resolution volumetric reconstruction of biomolecular distributions for regional analysis across samples and experimental groups; (3) the need for integrating multiscale tissue MSI and single-cell MS data to relate cellular neurochemistry to tissue chemical heterogeneity. The proposed research addresses these challenges by developing a suite of novel mass spectrometry-based technologies and uses these technologies to map biomolecules related to AD and neurogenesis. Aim 1 develops a new technology to significantly enhances the throughput of FT-MSI by synergizing compressed sensing and deep learning, and a multimodal approach to integrate many MSI slices for 3D chemical atlases of AD and wild type mouse brain. Aim 2 develops an experimental framework to generate multiscale tissue MSI and single-cell MS data, a computational framework to jointly analyze these data, and -omics based molecular libraries to aid in interpreting the MSI and single cell data. Aim 3 leverages the tools developed in Aims 1 & 2 to determine the temporal and spatial signature of vulnerable circuits and neurons in a FAD mouse model of AD. Aim 4 investigates the effects of hippocampal neurogenesis on neuronal vulnerability and AD progression using the new multiscale MSI technology, as well as creates 3D chemical atlas of the mouse brain. The proposed research, synergistic with both technology- and hypothesis- driven aims, will expand the technological envelop of MSI and transform how high-resolution MSI data are generated and analyzed. The proposed measurements will address critical knowledge gaps on the mechanism underlying neuronal vulnerability in AD, potentially identifying new biomarkers and therapeutic targets. ## Key facts - **NIH application ID:** 10898676 - **Project number:** 5R01AG078797-03 - **Recipient organization:** UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN - **Principal Investigator:** Fan Lam - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $731,735 - **Award type:** 5 - **Project period:** 2022-09-15 → 2027-05-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10898676 ## Citation > US National Institutes of Health, RePORTER application 10898676, High-Throughput 3D Multiscale Mass Spectrometry Imaging for Understanding Neurochemical Heterogeneity in Alzheimer's Disease (5R01AG078797-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10898676. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*