Predicting Disease Onset from Mutation Status Using Proband and Relative Data with Applications to Huntington's Disease
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...
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| Format: | Article |
| Language: | English |
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Wiley
2012-01-01
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| Series: | Journal of Probability and Statistics |
| Online Access: | http://dx.doi.org/10.1155/2012/375935 |
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| author | Tianle Chen Yuanjia Wang Yanyuan Ma Karen Marder Douglas R. Langbehn |
| author_facet | Tianle Chen Yuanjia Wang Yanyuan Ma Karen Marder Douglas R. Langbehn |
| author_sort | Tianle Chen |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-7702cf7245524fe5aace4a4a4c32c07a |
| institution | Kabale University |
| issn | 1687-952X 1687-9538 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Probability and Statistics |
| spelling | doaj-art-7702cf7245524fe5aace4a4a4c32c07a2025-02-03T06:12:09ZengWileyJournal of Probability and Statistics1687-952X1687-95382012-01-01201210.1155/2012/375935375935Predicting Disease Onset from Mutation Status Using Proband and Relative Data with Applications to Huntington's DiseaseTianle Chen0Yuanjia Wang1Yanyuan Ma2Karen Marder3Douglas R. Langbehn4Department of Biostatistics, Mailman School of Public Health, Columbia University, 722 West 168th Street, New York, NY 10032, USADepartment of Biostatistics, Mailman School of Public Health, Columbia University, 722 West 168th Street, New York, NY 10032, USADepartment of Statistics, Texas A&M University, College Station, TX 77843, USADepartments of Neurology and Psychiatry and Sergievsky Center and the Taub Institute, Columbia University Medical Center, New York, NY 10032, USADepartment of Psychiatry and Biostatistics (Secondary), University of Iowa, Iowa City, IA 52242, USAHuntington'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.http://dx.doi.org/10.1155/2012/375935 |
| spellingShingle | Tianle Chen Yuanjia Wang Yanyuan Ma Karen Marder Douglas R. Langbehn Predicting Disease Onset from Mutation Status Using Proband and Relative Data with Applications to Huntington's Disease Journal of Probability and Statistics |
| title | Predicting Disease Onset from Mutation Status Using Proband and Relative Data with Applications to Huntington's Disease |
| title_full | Predicting Disease Onset from Mutation Status Using Proband and Relative Data with Applications to Huntington's Disease |
| title_fullStr | Predicting Disease Onset from Mutation Status Using Proband and Relative Data with Applications to Huntington's Disease |
| title_full_unstemmed | Predicting Disease Onset from Mutation Status Using Proband and Relative Data with Applications to Huntington's Disease |
| title_short | Predicting Disease Onset from Mutation Status Using Proband and Relative Data with Applications to Huntington's Disease |
| title_sort | predicting disease onset from mutation status using proband and relative data with applications to huntington s disease |
| url | http://dx.doi.org/10.1155/2012/375935 |
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