A cross-campus collaboration between statisticians and clinicians reveals signs of Huntington’s disease many years before symptoms begin.
Huntington’s disease often unfolds in slow motion. For people who inherit the gene responsible for Huntington’s, symptoms such as involuntary movements, cognitive decline, and personality changes may not appear until midlife. Yet the biological changes driving the disease begin many years earlier.
By the time symptoms emerge, damage has already occurred in parts of the brain that control movement and thinking. And although some therapies can help manage symptoms, no treatments exist to slow or stop the progression of Huntington’s. Many scientists believe treatments will be most effective if introduced earlier, before damage occurs, fueling an urgent search for biological markers that can reveal the disease long before symptoms appear.
A new study led by faculty at the School of Computer, Data & Information Sciences and the School of Medicine and Public Health suggests researchers may be getting closer to that goal. Professor Michael Newton (Department of Statistics and Chair of the Department of Biostatistics and Medical Informatics) and Professor Jane Paulsen (Department of Neurology, School of Medicine and Public Health) collaborated to analyze data from one of the largest studies of early Huntington’s ever conducted. Together, their research teams identified two proteins that decline as Huntington’s develops, revealing the disease years before symptoms appear; providing a path for families to weigh treatment, and even life, options. “This is exciting to see new proteins emerge for Huntington’s,” says Paulsen. “It’s sure to launch new research and provide hope to families.” By combining clinical experience with statistical expertise, their work detects the earliest signs of an otherwise silent disease and brings researchers closer to intervening before its damage begins.
Watching for the disease before symptoms appear
Their findings draw on data from PREDICT-HD, a long-term study supported by the National Institutes of Health. Launched in 2002, the study followed over 1,100 people who carry the Huntington’s gene but had not yet developed symptoms.
For 15 years, researchers monitored participants through neurological exams, cognitive testing, magnetic resonance imaging (MRI) brain scans, and analysis of cerebrospinal fluid (the clear liquid surrounding the brain and spinal cord that can reveal chemical traces of neurological change). During that time, more than 250 participants were diagnosed with Huntington’s, allowing researchers to compare early biological signals with the later emergence of symptoms.
A collaborative approach to complex data
Identifying those signs requires analyzing an incredible amount of data. To tackle that challenge, Paulsen and Newton combined their respective expertise in Huntington’s disease and statistical analysis. “The data in this study is particularly complex,” Newton says. “We’re looking at measurements collected over many years from many different individuals, with hundreds of signs to consider. Figuring out which patterns actually matter becomes something of an art form.”
By combining clinical expertise with advanced statistical modeling, the team was able to detect subtle patterns across years of patient data, signals that would be nearly impossible to identify through clinical observation alone. The work highlights the role of statistics in making sense of large, complex datasets in medical research. “True collaboration between statisticians and medical researchers,” Newton says, “opens the door to broader thinking about the scientific questions themselves.” For Paulsen, such a partnership is critical in rare disease research. “When statisticians get to know the clinical questions and the realities of a rare disease, they can help uncover patterns in the data that might otherwise be missed.”
Uncovering these early signs could accelerate the development of treatments for Huntington’s. For example, researchers are exploring gene-based approaches, as well as molecular treatments aimed at slowing damage in the brain.
For people who know they carry the Huntington’s gene, early signals could provide a picture of how the disease is progressing. “Looking for biomarkers for Huntington’s becomes really critical for patients,” Paulsen says. “They help people weigh treatment options and even make life decisions. Biomarkers can also identify new targets that could be developed for new treatments.”
A rare disease with a unique scientific impact
Huntington’s, with its single genetic cause and relatively predictable progression, has become a uniquely valuable focus for medical researchers. Insights from Huntington’s research are influencing studies of other neurological conditions, including Parkinson’s, dementia, and Alzheimer’s, and Huntington’s research has been recently hailed as “the best investment in neuroscience today.”
As scientists continue searching for ways to slow or prevent Huntington’s, biomarkers that reveal its earliest biological signals may become an essential tool. By revealing how the disease unfolds long before symptoms appear, they could help researchers identify new opportunities to intervene and improve the lives of people affected.
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