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Sibling recurrence risk ratio analysis of the metabolic syndrome and its components over time
BACKGROUND: The purpose of this study was to estimate both cross-sectional sibling recurrence risk ratio (λ(s)) and lifetime λ(s )for the metabolic syndrome and its individual components over time among sibships in the prospectively followed-up cohorts provided by the Genetic Analysis Workshop 13. F...
Autores principales: | , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2003
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866469/ https://www.ncbi.nlm.nih.gov/pubmed/14975101 http://dx.doi.org/10.1186/1471-2156-4-S1-S33 |
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author | Chen, Wei J Liu, Pi-Hua Ho, Yen-Yi Chien, Kuo-Liong Lo, Min-Tzu Shih, Wei-Liang Yen, Yu-Chun Lee, Wen-Chung |
author_facet | Chen, Wei J Liu, Pi-Hua Ho, Yen-Yi Chien, Kuo-Liong Lo, Min-Tzu Shih, Wei-Liang Yen, Yu-Chun Lee, Wen-Chung |
author_sort | Chen, Wei J |
collection | PubMed |
description | BACKGROUND: The purpose of this study was to estimate both cross-sectional sibling recurrence risk ratio (λ(s)) and lifetime λ(s )for the metabolic syndrome and its individual components over time among sibships in the prospectively followed-up cohorts provided by the Genetic Analysis Workshop 13. Five measures included in the operational criteria of the metabolic syndrome by the Adult Treatment Panel III were examined. A method for estimating sibling recurrence risk with correction for complete ascertainment was used to estimate the numerator, and the prevalence in the whole cohort was used as the denominator of λ(s). RESULTS: Considerable variability in the λ(s )was found in terms of different time-points for the cross-sectional definition, the times of fulfilling the criterion for lifetime definition, and different components. Obesity and hyperglycemia had the highest cross-sectional λ(s )of the five components. Both components also had the largest slopes in the linear trend of the lifetime λ(s). However, the magnitudes of the lifetime λ(s )were similar to that of the mean cross-sectional λ(s), which were <2. The results of nonparametric linkage analysis showed only suggestive evidence of linkage between one marker and lifetime diagnosis of low high-density lipoprotein cholesterol and metabolic syndrome, respectively. CONCLUSION: The λ(s )of the metabolic syndrome and its components varies substantially across time, and the λ(s )of lifetime diagnosis was not necessarily larger than that of a cross-sectional diagnosis. The magnitude of λ(s )does not predict well the maximum LOD score of linkage analysis. |
format | Text |
id | pubmed-1866469 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2003 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-18664692007-05-11 Sibling recurrence risk ratio analysis of the metabolic syndrome and its components over time Chen, Wei J Liu, Pi-Hua Ho, Yen-Yi Chien, Kuo-Liong Lo, Min-Tzu Shih, Wei-Liang Yen, Yu-Chun Lee, Wen-Chung BMC Genet Proceedings BACKGROUND: The purpose of this study was to estimate both cross-sectional sibling recurrence risk ratio (λ(s)) and lifetime λ(s )for the metabolic syndrome and its individual components over time among sibships in the prospectively followed-up cohorts provided by the Genetic Analysis Workshop 13. Five measures included in the operational criteria of the metabolic syndrome by the Adult Treatment Panel III were examined. A method for estimating sibling recurrence risk with correction for complete ascertainment was used to estimate the numerator, and the prevalence in the whole cohort was used as the denominator of λ(s). RESULTS: Considerable variability in the λ(s )was found in terms of different time-points for the cross-sectional definition, the times of fulfilling the criterion for lifetime definition, and different components. Obesity and hyperglycemia had the highest cross-sectional λ(s )of the five components. Both components also had the largest slopes in the linear trend of the lifetime λ(s). However, the magnitudes of the lifetime λ(s )were similar to that of the mean cross-sectional λ(s), which were <2. The results of nonparametric linkage analysis showed only suggestive evidence of linkage between one marker and lifetime diagnosis of low high-density lipoprotein cholesterol and metabolic syndrome, respectively. CONCLUSION: The λ(s )of the metabolic syndrome and its components varies substantially across time, and the λ(s )of lifetime diagnosis was not necessarily larger than that of a cross-sectional diagnosis. The magnitude of λ(s )does not predict well the maximum LOD score of linkage analysis. BioMed Central 2003-12-31 /pmc/articles/PMC1866469/ /pubmed/14975101 http://dx.doi.org/10.1186/1471-2156-4-S1-S33 Text en Copyright © 2003 Chen 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 Chen, Wei J Liu, Pi-Hua Ho, Yen-Yi Chien, Kuo-Liong Lo, Min-Tzu Shih, Wei-Liang Yen, Yu-Chun Lee, Wen-Chung Sibling recurrence risk ratio analysis of the metabolic syndrome and its components over time |
title | Sibling recurrence risk ratio analysis of the metabolic syndrome and its components over time |
title_full | Sibling recurrence risk ratio analysis of the metabolic syndrome and its components over time |
title_fullStr | Sibling recurrence risk ratio analysis of the metabolic syndrome and its components over time |
title_full_unstemmed | Sibling recurrence risk ratio analysis of the metabolic syndrome and its components over time |
title_short | Sibling recurrence risk ratio analysis of the metabolic syndrome and its components over time |
title_sort | sibling recurrence risk ratio analysis of the metabolic syndrome and its components over time |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866469/ https://www.ncbi.nlm.nih.gov/pubmed/14975101 http://dx.doi.org/10.1186/1471-2156-4-S1-S33 |
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