Researchers at Carnegie Mellon University, the University of Pittsburgh, and the University of Washington have mapped how 3D genome architecture differs in brain cells affected by Alzheimer’s disease. According to a study published in Science, the research team linked genome folding to gene activity and brain tissue organization using single-cell technology, spatial mapping, and a deep learning model named Hicformer.
Uncovering 3D Genome Alterations in Alzheimer’s Disease
The 3D structure of the genome acts as a fundamental regulatory layer connecting DNA sequence to gene activity, according to Jian Ma, the Ray and Stephanie Lane Professor of Computational Biology at Carnegie Mellon University who led and supervised the study. By integrating genome folding, cell state, and tissue context, the team moved beyond simply cataloging disease-associated changes to understanding how they fit together.
To build this multi-scale view, researchers analyzed postmortem tissue from the prefrontal cortex. Samples came from individuals with and without Alzheimer’s who participated in a long-term dementia study and donated their brains after death. The team deployed GAGE-seq, a method that measures gene expression and 3D genome contacts inside the exact same cell. They then integrated these measurements with spatial transcriptomic maps of intact tissue.
Did you know? Alzheimer’s disease currently affects seven million Americans, a number that continues to grow.
How Hicformer and Single-Cell Technology Map Brain Cells
A key computational advance in the project was Hicformer, an AI model that combines DNA sequence, broad genome-folding features, and local 3D contact maps to predict gene activity across different kinds of cells. Xinyue Lu, a doctoral student in computational biology who co-led the research, described Hicformer as a computational test bed for asking how altered genome folding may change gene activity.
Yang Zhang, a project scientist in the Computational Biology Department who co-led the research, noted that measuring gene activity and genome folding in the same cell allows scientists to directly connect chromosome structure with disease-related gene programs. Across several kinds of brain cells, this paired view revealed a consistent signature of 3D genome reorganization.
Compartment Mingling and Its Effect on Gene Activity
Researchers found that large active and inactive regions of the genome, known as compartments, were less clearly separated in cells from people with Alzheimer’s. The team calls this pattern “increased compartment mingling.” According to the findings, multiple kinds of brain cells showed fewer short-range contacts and more long-range contacts, while greater compartment mingling associated with lower overall gene activity.
Furthermore, contacts between genes and nearby regulatory elements that help control gene activity weakened, while some midrange contacts strengthened. Hansruedi Mathys, assistant professor of neurobiology at the University of Pittsburgh’s Department of Neurobiology who directed the Pitt arm of the study, emphasized that these results establish higher-order chromatin alterations as a component of molecular pathology alongside classic hallmarks like amyloid-beta plaques and tau tangles.
These architectural alterations linked directly to reduced neuronal and synaptic programs, altered metabolic and stress responses, and senescence-related programs in microglia. By mapping these changes across intact brain tissue, the team provided a framework for future experiments to determine which structural changes contribute directly to the disease and whether they reveal new therapeutic targets.
Frequently Asked Questions
What is 3D genome architecture in Alzheimer’s disease?
According to the published research, 3D genome architecture refers to how DNA is folded inside a cell nucleus. In Alzheimer’s disease, this folding is organized differently, leading to “compartment mingling” that alters gene activity in brain cells.
What technology did researchers use to study the genome?
Researchers used GAGE-seq to measure gene expression and 3D genome contacts in the same cell, combined it with spatial transcriptomic maps, and utilized an AI model named Hicformer to predict gene activity.
Who funded this research?
The research was supported by grants from the National Institutes of Health, with contributions from scientists across Carnegie Mellon University, the University of Pittsburgh, the University of Washington, the Broad Institute of MIT and Harvard, the University of California, Los Angeles, and the Rush Alzheimer’s Disease Center.
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