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PMID: 15025718 Published · ppublish English Journal Article Multicenter Study Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, P.H.S.

A new model for prediction of the age of onset and penetrance for Huntington's disease based on CAG length.

Clinical genetics ·Vol. 65 ·No. 4 ·2004-04-00 ·Pages 267-77

Langbehn DR, Brinkman RR, Falush D, Paulsen JS, Hayden MR, International Huntington's Disease Collaborative Group

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.

MeSH Terms
Age of Onset DNA Sequence, Unstable Humans Huntington Disease/genetics Likelihood Functions Logistic Models Models, Genetic Penetrance Predictive Value of Tests Trinucleotide Repeats
Authors & Affiliations
6 authors, click to expand affiliations / ORCID
Langbehn D R
Department of Psychiatry, University of Iowa College of Medicine, Iowa City, IA, USA.
Brinkman R R
Falush D
Paulsen J S
Hayden M R
International Huntington's Disease Collaborative Group
Article Info
Journal
Clinical genetics
Abbr.
Clin Genet
ISSN
0009-9163
Published
2004-04-00
Pages
267-77
Language
English
Region
Denmark
NLM ID
0253664
Subset
IM
Grants
NINDS NIH HHS · 1 R01 NS40068-01A1 · United States
Corrections
ErratumIn
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