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Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
Published on: January 9, 2020
Beyond Bulk: Cell-Type-Resolved Epigenomics as the Path Forward in Alzheimer's Disease Research
Lucía Cañizares-Moscato1, Jose Ruiz-Iglesias1, Javier Isoler-Alcaraz1
1Molecular Neuropathology Unit, Physiological and Pathological Processes Program, Centro de Biología Molecular Severo Ochoa, CSIC-UAM, Madrid, Spain.
Abstract:
Alzheimer's disease (AD) is a complex neurodegenerative disorder in which most risk variants are noncoding and are enriched at gene regulatory regions, implicating epigenetic mechanisms as central mediators of disease pathogenesis. For most of the history of AD epigenetics research, bulk tissue analysis has dominated, obscuring the fundamentally distinct epigenomic landscapes of individual brain cell types and masking cell-type-specific contributions to disease. Advances in single-cell and single-nucleus sequencing, fluorescence-activated nuclei sorting and multiplexed epigenomic platforms have transformed this landscape, enabling cell-type-resolved profiling of chromatin accessibility, DNA methylation, histone modifications and transcription across the major neuronal, glial and neurovascular populations of the human brain. Here, we review these advances, structured around the argument that cell-type resolution is not a methodological refinement but a conceptual necessity. We describe the distinct epigenomic programs disrupted in neurons, microglia, astrocytes, oligodendrocytes and neurovascular cells in AD, highlighting how each cell type responds to pathology. We discuss the discovery of epigenomic erosion, the progressive loss of cell-type-specific epigenomic identity across virtually all brain cell populations as AD advances, as a unifying disease mechanism linking chromatin dysregulation to cognitive decline. Finally, we identify critical gaps in current knowledge, including the near-complete absence of cell-type-resolved histone modification and DNA methylation data for most brain cell types, the underrepresentation of rare populations in standard preparations and the untapped potential of metabolic acylation marks as indicators of the epigenome-metabolism interface in neurodegeneration.
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