Genetic Architecture of Pure Alzheimer's Disease and Mixed Pathology
- PI
- Fardo, David
- DAR ID
- 11945
- Initial Approval Date
- September 17, 2025
- Current DAR Status
- Expired
- PI Institution
- University of Kentucky
- PI Institution Country
- United States
- PI Institution Type
- Non-Profit
Requested Datasets (1)
Research Use Statement
Objectives
Alzheimer's disease and related dementias (ADRD) present challenges to healthcare systems worldwide, affecting millions of individuals. We aim to unravel mechanisms driving ADRD. Integrating data from diverse omics offers a comprehensive view of the molecular landscape associated with ADRD. This holistic understanding could revolutionize diagnosis, treatment, and prevention. In particular, longitudinal omics analysis has unique characteristics that merit evaluating current and novel methods.
Study design & analysis plan
We will perform genome-wide association studies on ADRD and also examine previously associated loci associated with clinical phenotypes and/or neuropathologies. We will examine how associations are driven by particular neuropathological features, furthering our understanding of underlying mechanisms. The corresponding transcriptome-wide data from Seattle Alzheimer’s Disease Brain Cell Atlas (SEA-AD) will be used to infer possible mechanisms by integrating biological knowledge.
We will explore models to harmonize extensive multi-omics data, including transcriptome, epigenome, genome, and clinical data, to capture informative factors and associations for ADRD. We will harness data generated by SEA-AD to characterize the molecular changes linked to phenotypes at cell-type resolution. We will perform abundance analyses, differential gene expression, differential chromatin accessibility, eQTL in each cell type across multiple brain regions to help identify biological drivers of brain pathology.
Alzheimer's disease and related dementias (ADRD) present challenges to healthcare systems worldwide, affecting millions of individuals. We aim to unravel mechanisms driving ADRD. Integrating data from diverse omics offers a comprehensive view of the molecular landscape associated with ADRD. This holistic understanding could revolutionize diagnosis, treatment, and prevention. In particular, longitudinal omics analysis has unique characteristics that merit evaluating current and novel methods.
Study design & analysis plan
We will perform genome-wide association studies on ADRD and also examine previously associated loci associated with clinical phenotypes and/or neuropathologies. We will examine how associations are driven by particular neuropathological features, furthering our understanding of underlying mechanisms. The corresponding transcriptome-wide data from Seattle Alzheimer’s Disease Brain Cell Atlas (SEA-AD) will be used to infer possible mechanisms by integrating biological knowledge.
We will explore models to harmonize extensive multi-omics data, including transcriptome, epigenome, genome, and clinical data, to capture informative factors and associations for ADRD. We will harness data generated by SEA-AD to characterize the molecular changes linked to phenotypes at cell-type resolution. We will perform abundance analyses, differential gene expression, differential chromatin accessibility, eQTL in each cell type across multiple brain regions to help identify biological drivers of brain pathology.
Non-Technical Summary
Alzheimer’s disease and related dementias affect millions of people worldwide. Our research aims to better understand the underlying causes of these diseases by looking closely at how genes and other biological factors contribute to their development.
We will analyze a wide range of biological information—including data from DNA and RNA—collected from multiple brain regions of research participants / donors. We hope to discover new ways to identify the disease earlier, understand how it progresses, and find more effective treatments.
This research is a collaborative effort with scientists from the Allen Institute for Brain Science and the University of Washington. Together, we aim to bring new insights that could lead to improved care and hope for those affected by Alzheimer’s and related dementias.
We will analyze a wide range of biological information—including data from DNA and RNA—collected from multiple brain regions of research participants / donors. We hope to discover new ways to identify the disease earlier, understand how it progresses, and find more effective treatments.
This research is a collaborative effort with scientists from the Allen Institute for Brain Science and the University of Washington. Together, we aim to bring new insights that could lead to improved care and hope for those affected by Alzheimer’s and related dementias.
Reported Publications
Publications shown are those reported by investigators through NIAGADS DAR reporting and renewal processes and may not represent a complete list of publications associated with the project.
No publications have been reported for this DAR.