Study Finds Ways to Predict, Track Huntington’s Disease

Anticipating future clinical trials for Huntington’s disease, researchers are seeking sensitive measures that will predict onset and track progression. One large international collaboration led by Sarah Tabrizi, University College London, U.K., initiated the TRACK-HD study, which followed 300 people with pre-manifest (presymptomatic) or early Huntington’s disease (HD) for three years. The researchers reported the final 36-month data online May 9 in Lancet Neurology. It details imaging and behavioral patterns that either portend disease or mark its progress. While some of these outcomes need further study to assess their clinical relevance, they offer possible measurements for future clinical trials, said Douglas Langbehn, University of Iowa, Iowa City, a senior author on the study. “It’s critical to identify subtle changes that we can measure over a relatively short period of time, especially in the pre-manifest stage of disease,” he said.

HD studies typically rely on the Unified Huntington’s Disease Rating Scale (UHDRS) to estimate outcome. This battery of tests evaluates motor skills, cognition, behavior, daily function, and independence. It includes the Total Functional Capacity, which assesses components of daily living such as the ability to work and manage finances, and Total Motor Score, which examines motor features typically impaired in HD. However, these tests are too crude to detect small changes over the short term, agree researchers. “It would be nice to identify more sensitive measures so that we can conduct shorter studies with fewer individuals,” said Ray Dorsey, Johns Hopkins Hospital, Baltimore, Maryland. Many see sensitive tests as crucial for success in future clinical trials.

To address that need, Tabrizi and colleagues enrolled 366 subjects at study sites in the U.K., France, the Netherlands, and Canada starting in 2008. All patients carried a mutant HD gene. Some lacked symptoms, while others were in the early stages of disease. Almost 100 non-carriers served as healthy controls. Each year for three years, the researchers evaluated volunteers clinically and measured cognitive, motor, and neuropsychiatric performance. They also performed magnetic resonance imaging to detect structural changes in the brain. They found several markers that stood out as either predictors or trackers of disease.

Those who were more than 10.8 years away from their expected age of onset (designated the preHD-A group) exhibited only slight evidence of functional decline. In a speeded tapping task, which asks participants to tap their index finger as quickly and steadily as they can, preHD-A volunteers left a larger interval between taps than controls. They also experienced atrophy in whole brain, caudate, white matter, and putamen. Changes were more obvious in asymptomatic subjects within 10.8 years of their disease onset (the preHD-B group). In addition to the extended tap interval and brain atrophy, these individuals declined faster than controls on the Symbol Digital Modality Test (SDMT), a written test in which subjects convert numerals to symbols using a novel code. They also scored worse on measures of apathy. “These values may be important for screening potential subjects for a clinical trial, to get some idea of how close or far they are to developing disease,” Langbehn said. “This could improve trial efficiency and steer the most appropriate subjects to specific treatments.”

Did any outcomes predict progression to symptomatic HD? Less gray matter and reduced striatal volume at baseline distinguished 19 people who were eventually diagnosed with HD from those who stayed asymptomatic for the study duration. People who developed HD also performed more poorly than controls on baseline measures of finger tapping, SDMT, Stroop word reading task, and indirect circle tracing, which measures visuomotor integration and motor planning. Over three years, caudate and global brain volume shrank most in these 19 individuals, while inter-tap interval in the speeded tapping task lengthened.

The researchers also tracked disease in the early stages of HD. Whole brain and striatum atrophied, while declining performance on the Stroop word reading test and indirect circle tracing tracked with a decline in total functional capacity. In addition, neuropsychological symptoms such as irritability and apathy all rose as performance on that functional measure worsened.

These outcomes need to be validated for clinical relevance and treatment responsiveness before they can be used in clinical trials, said Langbehn. He added that this study suggests that all of the above-mentioned variables could be markers of disease in the future. Researchers should assess them alongside standard measures in the next generation of HD clinical trials to see how they relate to each other, he said. Dorsey agreed. “This gives us great guidance as to what outcome measures we should incorporate and enhances the tools we have available,” he said. Dorsey was especially struck by the ability of imaging, SDMT, and quantitative motor assessments, such as a simple tapping test, to measure disease progression. However, he pointed out that TRACK-HD included no people with advanced disease, so it is unclear how far these findings extend. This study “reassures us that we can accurately track disease progression over time, using multiple measures,” wrote Francis Walker, Wake Forest Medical School, Winston-Salem, North Carolina, in an accompanying editorial.

TRACK-HD “provides an enormous amount of important information” that gives researchers a better sense of how to select patients for clinical trials and which tests make the best outcome measures, said Christopher Ross, Johns Hopkins University, Baltimore, Maryland. It specifies baseline measures that predict disease onset and progression, as well as variables that track with disease, such as apathy, he explained. Imaging variables, especially of striatal volume, might be useful for Phase 2 trials to provide a rationale for conducting larger Phase 3 studies with clinical or functional outcomes, he said. He pointed out that TRACK-HD collected data for a relatively small number of subjects followed for just three years. This limited the opportunity to observe many incident cases. Ross is involved in the larger, longer PREDICT-HD study, which has a similar goal of finding HD markers in people with pre-manifest disease. It is following approximately 1,000 subjects for up to a decade and already has over 100 incident cases. Slated for completion in 2013, it already found motor abnormalities (see Biglan et al., 2009), and anatomical (see Klöppel et al., 2009) and behavioral changes (see Beglinger et al., 2008) that may predict HD onset.

Similar longitudinal studies are ongoing to find markers of other neurodegenerative diseases, including Alzheimer’s (see ARF related news story; ARF news story; and ARF news story) and Parkinson’s diseases (see ARF related news story). Paired with findings from the Dominantly Inherited Alzheimer Network (DIAN), which similarly looks for longitudinal changes in familial AD, these studies highlight that the clinically expressed disease stage is really an endpoint, said DIAN leader John Morris, Washington University, St. Louis, Missouri. TRACK-HD reinforces that pathological changes occur long before symptomatic disease onset, and the concept that researchers need to aim to intervene in the presymptomatic phase, said Morris.

TRACK-HD researchers will continue to follow their preHD participants for at least two additional years in Track-On HD. PREDICT-HD recently incorporated cerebrospinal fluid measures into its protocol, and Track-On will add functional imaging. Both of these have proven useful for AD diagnosis and tracking but remain largely untapped as biomarkers for HD.—Gwyneth Dickey Zakaib

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References

News Citations

  1. Wrapping Up Enrollment, ADNI 2, PPMI Focus on Earlier Disease
  2. Expanding the Network, DIAN Starts Showing Longitudinal Data
  3. API Echoes DIAN: Biomarker Changes Precede Symptoms by 20 Years
  4. PPMI: Parkinson's Field’s Answer to ADNI

Paper Citations

  1. Biglan KM, Ross CA, Langbehn DR, Aylward EH, Stout JC, Queller S, Carlozzi NE, Duff K, Beglinger LJ, Paulsen JS, . Motor abnormalities in premanifest persons with Huntington's disease: the PREDICT-HD study. Mov Disord. 2009 Sep 15;24(12):1763-72. PubMed.
  2. Klöppel S, Chu C, Tan GC, Draganski B, Johnson H, Paulsen JS, Kienzle W, Tabrizi SJ, Ashburner J, Frackowiak RS, . Automatic detection of preclinical neurodegeneration: presymptomatic Huntington disease. Neurology. 2009 Feb 3;72(5):426-31. PubMed.
  3. Beglinger LJ, Paulsen JS, Watson DB, Wang C, Duff K, Langbehn DR, Moser DJ, Paulson HL, Aylward EH, Carlozzi NE, Queller S, Stout JC. Obsessive and compulsive symptoms in prediagnosed Huntington's disease. J Clin Psychiatry. 2008 Nov;69(11):1758-65. PubMed.

External Citations

  1. PREDICT-HD
  2. Track-On HD

Further Reading

Papers

  1. Scahill RI, Wild EJ, Tabrizi SJ. Biomarkers for Huntington's disease: an update. Expert Opin Med Diagn. 2012 Sep;6(5):371-5. PubMed.
  2. Aylward EH, Nopoulos PC, Ross CA, Langbehn DR, Pierson RK, Mills JA, Johnson HJ, Magnotta VA, Juhl AR, Paulsen JS, . Longitudinal change in regional brain volumes in prodromal Huntington disease. J Neurol Neurosurg Psychiatry. 2011 Apr;82(4):405-10. PubMed.
  3. Long JD, Matson WR, Juhl AR, Leavitt BR, Paulsen JS, . 8OHdG as a marker for Huntington disease progression. Neurobiol Dis. 2012 Jun;46(3):625-634. PubMed.
  4. Borowsky B, Warner J, Leavitt BR, Tabrizi SJ, Roos RA, Durr A, Becker C, Sampaio C, Tobin AJ, Schulman H. 8OHdG is not a biomarker for Huntington disease state or progression. Neurology. 2013 May 21;80(21):1934-41. PubMed.
  5. Paulsen JS, Long JD. Neurodegenerative disease: Establishing a clinical trial battery for Huntington disease. Nat Rev Neurol. 2012 May;8(5):250-1. PubMed.
  6. Chaumeil MM, Valette J, Baligand C, Brouillet E, Hantraye P, Bloch G, Gaura V, Rialland A, Krystkowiak P, Verny C, Damier P, Remy P, Bachoud-Levi AC, Carlier P, Lebon V. pH as a biomarker of neurodegeneration in Huntington's disease: a translational rodent-human MRS study. J Cereb Blood Flow Metab. 2012 Feb 29; PubMed.
  7. Beste C, Stock AK, Ness V, Hoffmann R, Lukas C, Saft C. A novel cognitive-neurophysiological state biomarker in premanifest Huntington's disease validated on longitudinal data. Sci Rep. 2013 May 8;3:1797. PubMed.
  8. Shin H, Kim MH, Lee SJ, Lee KH, Kim MJ, Kim JS, Cho JW. Decreased Metabolism in the Cerebral Cortex in Early-Stage Huntington's Disease: A Possible Biomarker of Disease Progression?. J Clin Neurol. 2013 Jan;9(1):21-5. PubMed.
  9. Lambrecq V, Langbour N, Guehl D, Bioulac B, Burbaud P, Rotge JY. Evolution of brain gray matter loss in Huntington's disease: a meta-analysis. Eur J Neurol. 2013 Feb;20(2):315-21. PubMed.

Primary Papers

  1. Tabrizi SJ, Scahill RI, Owen G, Durr A, Leavitt BR, Roos RA, Borowsky B, Landwehrmeyer B, Frost C, Johnson H, Craufurd D, Reilmann R, Stout JC, Langbehn DR, . Predictors of phenotypic progression and disease onset in premanifest and early-stage Huntington's disease in the TRACK-HD study: analysis of 36-month observational data. Lancet Neurol. 2013 May 8; PubMed.
  2. Walker FO. Huntington's disease: the road to progress. Lancet Neurol. 2013 May 8; PubMed.

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