Cargando…

Multipoint association mapping for longitudinal family data: an application to hypertension phenotypes

It is essential to develop adequate statistical methods to fully utilize information from longitudinal family studies. We extend our previous multipoint linkage disequilibrium approach—simultaneously accounting for correlations between markers and repeat measurements within subjects, and the correla...

Descripción completa

Detalles Bibliográficos
Autores principales: Chiu, Yen-Feng, Lee, Chun-Yi, Hsu, Fang-Chi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5133529/
https://www.ncbi.nlm.nih.gov/pubmed/27980655
http://dx.doi.org/10.1186/s12919-016-0049-2
_version_ 1782471281995677696
author Chiu, Yen-Feng
Lee, Chun-Yi
Hsu, Fang-Chi
author_facet Chiu, Yen-Feng
Lee, Chun-Yi
Hsu, Fang-Chi
author_sort Chiu, Yen-Feng
collection PubMed
description It is essential to develop adequate statistical methods to fully utilize information from longitudinal family studies. We extend our previous multipoint linkage disequilibrium approach—simultaneously accounting for correlations between markers and repeat measurements within subjects, and the correlations between subjects in families—to detect loci relevant to disease through gene-based analysis. Estimates of disease loci and their genetic effects along with their 95 % confidence intervals (or significance levels) are reported. Four different phenotypes—ever having hypertension at 4 visits, incidence of hypertension, hypertension status at baseline only, and hypertension status at 4 visits—are studied using the proposed approach. The efficiency of estimates of disease locus positions (inverse of standard error) improves when using the phenotypes from 4 visits rather than using baseline only.
format Online
Article
Text
id pubmed-5133529
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-51335292016-12-15 Multipoint association mapping for longitudinal family data: an application to hypertension phenotypes Chiu, Yen-Feng Lee, Chun-Yi Hsu, Fang-Chi BMC Proc Proceedings It is essential to develop adequate statistical methods to fully utilize information from longitudinal family studies. We extend our previous multipoint linkage disequilibrium approach—simultaneously accounting for correlations between markers and repeat measurements within subjects, and the correlations between subjects in families—to detect loci relevant to disease through gene-based analysis. Estimates of disease loci and their genetic effects along with their 95 % confidence intervals (or significance levels) are reported. Four different phenotypes—ever having hypertension at 4 visits, incidence of hypertension, hypertension status at baseline only, and hypertension status at 4 visits—are studied using the proposed approach. The efficiency of estimates of disease locus positions (inverse of standard error) improves when using the phenotypes from 4 visits rather than using baseline only. BioMed Central 2016-10-18 /pmc/articles/PMC5133529/ /pubmed/27980655 http://dx.doi.org/10.1186/s12919-016-0049-2 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Proceedings
Chiu, Yen-Feng
Lee, Chun-Yi
Hsu, Fang-Chi
Multipoint association mapping for longitudinal family data: an application to hypertension phenotypes
title Multipoint association mapping for longitudinal family data: an application to hypertension phenotypes
title_full Multipoint association mapping for longitudinal family data: an application to hypertension phenotypes
title_fullStr Multipoint association mapping for longitudinal family data: an application to hypertension phenotypes
title_full_unstemmed Multipoint association mapping for longitudinal family data: an application to hypertension phenotypes
title_short Multipoint association mapping for longitudinal family data: an application to hypertension phenotypes
title_sort multipoint association mapping for longitudinal family data: an application to hypertension phenotypes
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5133529/
https://www.ncbi.nlm.nih.gov/pubmed/27980655
http://dx.doi.org/10.1186/s12919-016-0049-2
work_keys_str_mv AT chiuyenfeng multipointassociationmappingforlongitudinalfamilydataanapplicationtohypertensionphenotypes
AT leechunyi multipointassociationmappingforlongitudinalfamilydataanapplicationtohypertensionphenotypes
AT hsufangchi multipointassociationmappingforlongitudinalfamilydataanapplicationtohypertensionphenotypes