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Comparison between two analytic strategies to detect linkage to obesity with genetically determined age of onset: the Framingham Heart Study

BACKGROUND: Genes have been found to influence the age of onset of several diseases and traits. The occurrence of many chronic diseases, obesity included, appears to be strongly age-dependent. However, an analysis of potential age of onset genes for obesity has yet to be reported. There are at least...

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Autores principales: Engelman, Corinne D, Brady, Heather L, Baron, Anna E, Norris, Jill M
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2003
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866531/
https://www.ncbi.nlm.nih.gov/pubmed/14975158
http://dx.doi.org/10.1186/1471-2156-4-S1-S90
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author Engelman, Corinne D
Brady, Heather L
Baron, Anna E
Norris, Jill M
author_facet Engelman, Corinne D
Brady, Heather L
Baron, Anna E
Norris, Jill M
author_sort Engelman, Corinne D
collection PubMed
description BACKGROUND: Genes have been found to influence the age of onset of several diseases and traits. The occurrence of many chronic diseases, obesity included, appears to be strongly age-dependent. However, an analysis of potential age of onset genes for obesity has yet to be reported. There are at least two analytic methods for determining an age of onset gene. The first is to consider a person affected if they possess the trait before a certain age (an early age of onset phenotype). The second is to define the phenotype based on the residual from a survival analysis. RESULTS: No regions provided evidence for linkage at the more stringent level of p < 0.001. However, five regions showed consistent suggestive evidence for linkage (one marker with p < 0.01 and a second contiguous marker at p < 0.05). These regions were chromosome 1 (280–294 cM) and chromosome 16 (56–64 cM) for overweight using the survival analysis residual method and chromosome 13 (102–122 cM), chromosome 17 (127–138 cM), and chromosome 19 (23–47 cM) for obese before age 35. CONCLUSION: Only one region (chromosome 19 at 23–47 cM) showed somewhat consistent results between the two analytic methods. Potential reasons for inconsistent results between the two methods, as well as their strengths and weaknesses, are discussed. The use of both methods together to explore the genetics of the age of onset of a trait may prove to be beneficial in determining a gene that is linked only to an early age of onset phenotype versus one that determines age of onset through all age groups.
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spelling pubmed-18665312007-05-11 Comparison between two analytic strategies to detect linkage to obesity with genetically determined age of onset: the Framingham Heart Study Engelman, Corinne D Brady, Heather L Baron, Anna E Norris, Jill M BMC Genet Proceedings BACKGROUND: Genes have been found to influence the age of onset of several diseases and traits. The occurrence of many chronic diseases, obesity included, appears to be strongly age-dependent. However, an analysis of potential age of onset genes for obesity has yet to be reported. There are at least two analytic methods for determining an age of onset gene. The first is to consider a person affected if they possess the trait before a certain age (an early age of onset phenotype). The second is to define the phenotype based on the residual from a survival analysis. RESULTS: No regions provided evidence for linkage at the more stringent level of p < 0.001. However, five regions showed consistent suggestive evidence for linkage (one marker with p < 0.01 and a second contiguous marker at p < 0.05). These regions were chromosome 1 (280–294 cM) and chromosome 16 (56–64 cM) for overweight using the survival analysis residual method and chromosome 13 (102–122 cM), chromosome 17 (127–138 cM), and chromosome 19 (23–47 cM) for obese before age 35. CONCLUSION: Only one region (chromosome 19 at 23–47 cM) showed somewhat consistent results between the two analytic methods. Potential reasons for inconsistent results between the two methods, as well as their strengths and weaknesses, are discussed. The use of both methods together to explore the genetics of the age of onset of a trait may prove to be beneficial in determining a gene that is linked only to an early age of onset phenotype versus one that determines age of onset through all age groups. BioMed Central 2003-12-31 /pmc/articles/PMC1866531/ /pubmed/14975158 http://dx.doi.org/10.1186/1471-2156-4-S1-S90 Text en Copyright © 2003 Engelman et al; licensee BioMed Central Ltd http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Proceedings
Engelman, Corinne D
Brady, Heather L
Baron, Anna E
Norris, Jill M
Comparison between two analytic strategies to detect linkage to obesity with genetically determined age of onset: the Framingham Heart Study
title Comparison between two analytic strategies to detect linkage to obesity with genetically determined age of onset: the Framingham Heart Study
title_full Comparison between two analytic strategies to detect linkage to obesity with genetically determined age of onset: the Framingham Heart Study
title_fullStr Comparison between two analytic strategies to detect linkage to obesity with genetically determined age of onset: the Framingham Heart Study
title_full_unstemmed Comparison between two analytic strategies to detect linkage to obesity with genetically determined age of onset: the Framingham Heart Study
title_short Comparison between two analytic strategies to detect linkage to obesity with genetically determined age of onset: the Framingham Heart Study
title_sort comparison between two analytic strategies to detect linkage to obesity with genetically determined age of onset: the framingham heart study
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866531/
https://www.ncbi.nlm.nih.gov/pubmed/14975158
http://dx.doi.org/10.1186/1471-2156-4-S1-S90
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