Summary: New analysis suggests Huntington’s disease advances largely because cells lose the homeostatic systems that maintain their health, rather than solely from increasing damage caused by the disease protein.
Source: Picower Institute of Learning and Memory
Researchers at MIT and Sorbonne Université used an innovative computational method to analyze large brain cell gene expression datasets and found that, in Huntington’s disease, the failure of cells’ maintenance systems appears to drive progression to advanced stages more than a direct increase in pathological damage.
The team’s analysis identified specific gene networks and molecular pathways that appear essential to sustaining neuronal and glial health during Huntington’s. Those pathways present potential targets for therapies aimed at preserving cellular function rather than attempting to correct individual genes one by one, said co-senior author Myriam Heiman, Associate Professor in MIT’s Department of Brain and Cognitive Sciences and an investigator at The Picower Institute for Learning and Memory. Christian Neri of Sorbonne Université’s Centre National de la Recherche Scientifique is co-senior and co-corresponding author of the study published in eLife.
“Maintaining the expression of compensatory mechanisms may be a more effective therapeutic strategy than trying to modify single genes in isolation,” said Heiman, who is also a Broad Institute member.
Led by co-corresponding author Lucile Megret, the researchers developed a process called “Geomic” to integrate two large datasets from Heiman’s lab with an additional dataset from UCLA researcher William Yang. Each dataset captured different dimensions of the disease: how gene expression changes over time, how those changes vary across cell types, and how cell survival correlates with expression dynamics.
Geomic mapped differences in expression for roughly 4,300 genes across dimensions such as mouse age, severity of the Huntington’s-causing mutation, and cell type—focusing on vulnerable cells in the striatum, including specific neuron classes and astrocytes. The method represented these multidimensional data as geometric shapes whose deformations could be compared quantitatively to identify the genes whose expression shifts had the most consequential effects on cellular health. From those comparisons, researchers examined how abnormal expression patterns might undermine cell function.
Major breakdowns in cellular maintenance
Geomic revealed a consistent pattern: many pathogenic responses to the mutant Huntingtin protein remain active over time, but the homeostatic, compensatory responses that protect cells decline. Vulnerable cell types progressively lose the ability to sustain gene programs that keep essential systems functioning. These compensatory mechanisms initially respond to disease stress but then weaken, leaving cells exposed to failure.
A prominent example was in Drd1-expressing neurons, which showed a marked decline in genes that preserve mitochondrial integrity. Heiman’s lab had previously shown that mitochondrial RNA leakage in some Huntington’s-affected neurons can trigger an aberrant immune response and cell death. The current analysis reinforces the central role of mitochondrial quality control and implicates genes such as Ndufb10, whose reduced expression may erode the broader network that supports mitochondrial function.
Another striking decline occurred in both Drd1 neurons and astrocytes within pathways that manage endosome regulation. Proper endosome function determines protein trafficking and degradation—processes essential for cellular housekeeping. Key genes in those networks, including Rab8b and Rab7, emerged as contributors to endosomal dysfunction when their expression fell.
The authors validated several top findings by confirming similar gene expression alterations in post-mortem brain tissue from human Huntington’s patients, lending support to the relevance of the mouse-model-derived networks to human disease.
Beyond mitochondrial and endosomal pathways, the study catalogues numerous additional homeostatic processes that decline across cell types. To accelerate follow-up work, the Geomic source code and the resulting data visualizations have been made publicly available by the authors as a resource for the research community.
Co-senior author Christian Neri noted that the resulting database establishes a precise foundation for testing ways to restore compensatory responses in Huntington’s disease and potentially in other neurodegenerative conditions that share similar homeostatic mechanisms.
Heiman emphasized that several of the implicated genes are transcriptional regulators. “Some of the genes we identified act as transcription factors,” she said. “Targeting these regulators could help reinstate the compensatory gene programs that decline during disease progression.”
A new systems-level approach to neurodegeneration
While Geomic and its “shape deformation analysis” were developed and applied here to Huntington’s disease, the authors expect the method to be broadly useful for studying other neurodegenerative disorders such as Alzheimer’s and Parkinson’s, and for exploring systems-level changes in many brain diseases. The approach shifts focus from single genes or isolated pathways to coordinated network dynamics that determine cellular resilience or failure.
“This represents a new way to study system-level responses rather than targeting individual pathways in isolation,” Heiman said. “It’s a strong proof of principle and a tool we hope will be applied to other genomic datasets across disease models.”
In addition to Heiman, Neri and Megret, the study’s authors include Barbara Gris, Satish Nair, Jasmin Cevost, Mary Wertz, Jeff Aaronson, Jim Rosinski, Thomas Vogt, and Hilary Wilkinson.
Funding: The research was supported by Sorbonne Université, the CHDI Foundation and the National Institutes of Health. Heiman’s laboratory also receives support from the JPB Foundation.
About this Huntington’s disease research news
Source: Picower Institute of Learning and Memory
Contact: David Orenstein – Picower Institute of Learning and Memory
Image: The image is credited to Sorbonne Université
Original Research: Open access. “Shape deformation analysis reveals the temporal dynamics of cell-type-specific homeostatic and pathogenic responses to mutant huntingtin” by Lucile Megret et al., eLife
Abstract
Shape deformation analysis reveals the temporal dynamics of cell-type-specific homeostatic and pathogenic responses to mutant huntingtin
Loss of cellular homeostasis has been implicated in the etiology of several neurodegenerative diseases. However, the molecular mechanisms that underlie this loss remain poorly understood at a systems level for each disease.
Using a novel computational approach that integrates dimensional RNA-seq with in vivo neuron survival data, the authors map the temporal dynamics of homeostatic and pathogenic responses in four striatal cell types in Huntington’s model mice.
The resulting map shows that many pathogenic responses are mitigated over time while most homeostatic responses decline, suggesting neuronal death in Huntington’s disease is driven primarily by loss of homeostatic mechanisms.
Different cell types may lose similar homeostatic processes—for example, endosome biogenesis and mitochondrial quality control in Drd1-expressing neurons and astrocytes. The study’s relevance to human disease is supported by human stem cell data, genome-wide association studies, and post-mortem brain analyses.
These findings establish a new paradigm and framework to guide therapeutic discovery in Huntington’s disease and other neurodegenerative disorders.