Cargando…

Genome-wide association analysis of cardiovascular-related quantitative traits in the Framingham Heart Study

Multivariate linear growth curves were used to model high-density lipoprotein (HDL), low-density lipoprotein (LDL), triglycerides (TG), and systolic blood pressure (SBP) measured during four exams from 1659 independent individuals from the Framingham Heart Study. The slopes and intercepts from each...

Descripción completa

Detalles Bibliográficos
Autores principales: Roslin, Nicole M, Hamid, Jemila S, Paterson, Andrew D, Beyene, Joseph
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2795889/
https://www.ncbi.nlm.nih.gov/pubmed/20017982
_version_ 1782175463098023936
author Roslin, Nicole M
Hamid, Jemila S
Paterson, Andrew D
Beyene, Joseph
author_facet Roslin, Nicole M
Hamid, Jemila S
Paterson, Andrew D
Beyene, Joseph
author_sort Roslin, Nicole M
collection PubMed
description Multivariate linear growth curves were used to model high-density lipoprotein (HDL), low-density lipoprotein (LDL), triglycerides (TG), and systolic blood pressure (SBP) measured during four exams from 1659 independent individuals from the Framingham Heart Study. The slopes and intercepts from each of two phenotype models were tested for association with 348,053 autosomal single-nucleotide polymorphisms from the Affymetrix Gene Chip 500 k set. Three regions were associated with LDL intercept, TG slope, and SBP intercept (p < 1.44 × 10(-7)). We observed results consistent with previously reported associations between rs599839, on chromosome 1p13, and LDL. We note that the association is significant with LDL intercept but not slope. Markers on chromosome 17q25 were associated with TG slope, and a single-nucleotide polymorphism on chromosome 7p11 was associated with SBP intercept. Growth curve models can be used to gain more insight on the relationships between SNPs and traits than traditional association analysis when longitudinal data has been collected. The power to detect association with changes over time may be limited if the subjects are not followed over a long enough time period.
format Text
id pubmed-2795889
institution National Center for Biotechnology Information
language English
publishDate 2009
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-27958892009-12-18 Genome-wide association analysis of cardiovascular-related quantitative traits in the Framingham Heart Study Roslin, Nicole M Hamid, Jemila S Paterson, Andrew D Beyene, Joseph BMC Proc Proceedings Multivariate linear growth curves were used to model high-density lipoprotein (HDL), low-density lipoprotein (LDL), triglycerides (TG), and systolic blood pressure (SBP) measured during four exams from 1659 independent individuals from the Framingham Heart Study. The slopes and intercepts from each of two phenotype models were tested for association with 348,053 autosomal single-nucleotide polymorphisms from the Affymetrix Gene Chip 500 k set. Three regions were associated with LDL intercept, TG slope, and SBP intercept (p < 1.44 × 10(-7)). We observed results consistent with previously reported associations between rs599839, on chromosome 1p13, and LDL. We note that the association is significant with LDL intercept but not slope. Markers on chromosome 17q25 were associated with TG slope, and a single-nucleotide polymorphism on chromosome 7p11 was associated with SBP intercept. Growth curve models can be used to gain more insight on the relationships between SNPs and traits than traditional association analysis when longitudinal data has been collected. The power to detect association with changes over time may be limited if the subjects are not followed over a long enough time period. BioMed Central 2009-12-15 /pmc/articles/PMC2795889/ /pubmed/20017982 Text en Copyright ©2009 Roslin 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
Roslin, Nicole M
Hamid, Jemila S
Paterson, Andrew D
Beyene, Joseph
Genome-wide association analysis of cardiovascular-related quantitative traits in the Framingham Heart Study
title Genome-wide association analysis of cardiovascular-related quantitative traits in the Framingham Heart Study
title_full Genome-wide association analysis of cardiovascular-related quantitative traits in the Framingham Heart Study
title_fullStr Genome-wide association analysis of cardiovascular-related quantitative traits in the Framingham Heart Study
title_full_unstemmed Genome-wide association analysis of cardiovascular-related quantitative traits in the Framingham Heart Study
title_short Genome-wide association analysis of cardiovascular-related quantitative traits in the Framingham Heart Study
title_sort genome-wide association analysis of cardiovascular-related quantitative traits in the framingham heart study
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2795889/
https://www.ncbi.nlm.nih.gov/pubmed/20017982
work_keys_str_mv AT roslinnicolem genomewideassociationanalysisofcardiovascularrelatedquantitativetraitsintheframinghamheartstudy
AT hamidjemilas genomewideassociationanalysisofcardiovascularrelatedquantitativetraitsintheframinghamheartstudy
AT patersonandrewd genomewideassociationanalysisofcardiovascularrelatedquantitativetraitsintheframinghamheartstudy
AT beyenejoseph genomewideassociationanalysisofcardiovascularrelatedquantitativetraitsintheframinghamheartstudy