Predicting Disease Onset from Mutation Status Using Proband and Relative Data with Applications to Huntington's Disease

Tianle Chen; Yuanjia Wang; Yanyuan Ma; Karen Marder; Douglas R Langbehn

doi:10.1155/2012/375935

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Predicting Disease Onset from Mutation Status Using Proband and Relative Data with Applications to Huntington's Disease

Journal article

Open access

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Predicting Disease Onset from Mutation Status Using Proband and Relative Data with Applications to Huntington's Disease

Tianle Chen, Yuanjia Wang, Yanyuan Ma, Karen Marder and Douglas R Langbehn

Journal of probability and statistics, Vol.2012, pp.1-19

2012

DOI: 10.1155/2012/375935

PMCID: PMC3589804

PMID: 23476655

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Abstract

Huntington's disease (HD) is a progressive neurodegenerative disorder caused by an expansion of CAG repeats in the IT15 gene. The age-at-onset (AAO) of HD is inversely related to the CAG repeat length and the minimum length thought to cause HD is 36. Accurate estimation of the AAO distribution based on CAG repeat length is important for genetic counseling and the design of clinical trials. In the Cooperative Huntington's Observational Research Trial (COHORT) study, the CAG repeat length is known for the proband participants. However, whether a family member shares the huntingtin gene status (CAG expanded or not) with the proband is unknown. In this work, we use the expectation-maximization (EM) algorithm to handle the missing huntingtin gene information in first-degree family members in COHORT, assuming that a family member has the same CAG length as the proband if the family member carries a huntingtin gene mutation. We perform simulation studies to examine performance of the proposed method and apply the methods to analyze COHORT proband and family combined data. Our analyses reveal that the estimated cumulative risk of HD symptom onset obtained from the combined data is slightly lower than the risk estimated from the proband data alone.

Details

Title: Subtitle: Predicting Disease Onset from Mutation Status Using Proband and Relative Data with Applications to Huntington's Disease
Creators: Tianle Chen - Department of Biostatistics, Mailman School of Public Health, Columbia University, 722 West 168th Street, New York, NY 10032, USA
Yuanjia Wang - Department of Biostatistics, Mailman School of Public Health, Columbia University, 722 West 168th Street, New York, NY 10032, USA
Yanyuan Ma - Department of Statistics, Texas A&M University, College Station, TX 77843, USA
Karen Marder - Departments of Neurology and Psychiatry and Sergievsky Center and the Taub Institute, Columbia University Medical Center, New York, NY 10032, USA
Douglas R Langbehn - Department of Psychiatry and Biostatistics (Secondary), University of Iowa, Iowa City, IA 52242, USA
Resource Type: Journal article
Publication Details: Journal of probability and statistics, Vol.2012, pp.1-19
DOI: 10.1155/2012/375935
PMID: 23476655
PMCID: PMC3589804
NLM abbreviation: J Probab Stat
ISSN: 1687-952X
eISSN: 1687-9538
Grant note: DOI: 10.13039/100000002, name: National Institutes of Health, award: R03AG031113-01A2, R01NS073671-01
Language: English
Date published: 2012
Academic Unit: Psychiatry; Iowa Neuroscience Institute
Record Identifier: 9984003484202771

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