Federal grant · project grant (b)
Single-cell Epigenome Analysis of the Alzheimer's Disease Brain - Project Summary Late Onset Ad (LOAD) Is a Heterogeneous Disease That Involves Complex Interactions Between Genetic, Epigenetic, and Environmental Risk Factors. Genome-wide Association Studies (GWAS) Have Identified Several Thousand Sequence Variants Linked to Increased or Decreased Risk of Ad, Most of Which Are Noncoding. the Current Paradigm Posits That Noncoding Variants Contribute to Disease Etiology by Perturbing Transcriptional Regulation in Disease-relevant Cell Types, While Environmental Risk Factors Contribute to Pathogenesis in Part via Alterations to the Epigenome. However, a Lack of Maps and Tools to Explore Gene Activities and Their Transcriptional Regulation at Cellular Resolution in the Brain Has Presented a Major Bottleneck to the Functional Interpretation of Noncoding Ad Risk Variants. in Prior Work, We Applied Droplet Paired-tag Multi-omic Profiling of Transcription and Histone Post-translational Modification to Post-mortem Ad and Control Parietal Cortex, Demonstrating Its Capacity to Profile Cellular Epigenetics and Transcription From Bulk Samples. This Technology Has Garnered Significant Interest Through Our Early-access Program. in the Proposed Study, We Will Develop a Manufacturing Quality Management System Incorporating References and Reference Measurements for the Production of Droplet Paired-tag Kits. We Will Optimize Our Protocols Specifically on Post-mortem Ad and Healthy Brain Tissue From Hippocampus, White Matter, and Cerebellum, as Well as on Peripheral Blood; and Further Optimize Droplet Paired-tag for Application to Sorted Nuclear Populations. We Will Publish the Resulting Data as a Comprehensive Cellular Encyclopedia of Dna Elements. If Successful, the Research Would Catalyze the Study of the Epigenetics of Ad, and Enable the Widespread Application of Next-generation Multi-omic Assays to Ad and Other Neurological Diseases.
Committed
$2.0 Million
Paid out
$1.8M
91%
Committed, not yet paid
$183.5K
9%
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