The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
A new model for prediction of the age of onset and penetrance for Huntington's disease based on CAG length
Abstract
Huntington's disease (HD) is a neurodegenerative disorder caused by an unstable CAG repeat. For patients at risk, participating in predictive testing and learning of having CAG expansion, a major unanswered question shifts from “Will I get HD?” to “When will it manifest?” Using the largest cohort of HD patients analyzed to date (2913 individuals from 40 centers worldwide), we developed a parametric survival model based on CAG repeat length to predict the probability of neurological disease onset (based on motor neurological symptoms rather than psychiatric onset) at different ages for individual patients. We provide estimated probabilities of onset associated with CAG repeats between 36 and 56 for individuals of any age with narrow confidence intervals. For example, our model predicts a 91% chance that a 40‐year‐old individual with 42 repeats will have onset by the age of 65, with a 95% confidence interval from 90 to 93%. This model also defines the variability in HD onset that is not attributable to CAG length and provides information concerning CAG‐related penetrance rates.
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MACDONALD, M. (1993) · Cell · doi:10.1016/0092-8674(93)90585-e · Cited by 8,366
Trinucleotide repeat length instability and age of onset in Huntington's disease
Duyao, M., Ambrose, C., Myers, R., Novelletto, A., Persichetti, F., Frontali, M., Folstein, S., Ross, C., Franz, M., Abbott, M., et al. (1993) · Nature Genetics · doi:10.1038/ng0893-387 · Cited by 1,089
Cited by
Within-subject template estimation for unbiased longitudinal image analysis
Reuter, M., Schmansky, N. J., Rosas, H. D., & Fischl, B. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.02.084 · Cited by 2,356
Huntington disease: natural history, biomarkers and prospects for therapeutics
Ross, C. A., Aylward, E. H., Wild, E. J., Langbehn, D. R., Long, J. D., Warner, J. H., Scahill, R. I., Leavitt, B. R., Stout, J. C., Paulsen, J. S., et al. (2014) · Nature Reviews Neurology · doi:10.1038/nrneurol.2014.24 · Cited by 1,016
Self-citationTabrizi, S. J., Langbehn, D. R., Leavitt, B. R., Roos, R. A., Durr, A., Craufurd, D., Kennard, C., Hicks, S. L., Fox, N. C., Scahill, R. I., et al. (2009) · The Lancet Neurology · doi:10.1016/s1474-4422(09)70170-x · Cited by 984
Self-citationDetection of Huntington's disease decades before diagnosis: the Predict-HD study
Paulsen, J. S., Langbehn, D. R., Stout, J. C., Aylward, E., Ross, C. A., Nance, M., Guttman, M., Johnson, S., MacDonald, M., Beglinger, L. J., et al. (2008) · Journal of Neurology, Neurosurgery & Psychiatry · doi:10.1136/jnnp.2007.128728 · Cited by 804
Self-citationA chaperome subnetwork safeguards proteostasis in aging and neurodegenerative disease
Brehme, M., Voisine, C., Rolland, T., Wachi, S., Soper, J. H., Zhu, Y., Orton, K., Villella, A., Garza, D., Vidal, M., et al. (2014) · Cell Reports · doi:10.1016/j.celrep.2014.09.042 · Cited by 584
Metadata
- Authors
- Langbehn, D., Brinkman, R., Falush, D., Paulsen, J., Hayden, M., & on behalf of an International Huntington's Disease Collaborative Group
- Venue
- Clinical Genetics
- Publisher
- Wiley
- Published
- 2004-03-12
- Volume
- 65
- Issue
- 4
- Pages
- 267-277
- ISSN
- 0009-9163 (ISSN-L)
- 1399-0004
- OpenAlex
- W2163671213
- Cited by
- 817
- References
- 2
- FWCI
- 6.78
- Type
- journal article
- Language
- en
- Open access
- closed
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- Langbehn, D., Brinkman, R., Falush, D., Paulsen, J., Hayden, M., & on behalf of an International Huntington's Disease Collaborative Group. (2004). A new model for prediction of the age of onset and penetrance for Huntington's disease based on CAG length. Clinical Genetics. https://doi.org/10.1111/j.1399-0004.2004.00241.x
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
