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Exome-wide rare variant analyses of two bone mineral density phenotypes: the challenges of analyzing rare genetic variation

Performance of a recently developed test for association between multivariate phenotypes and sets of genetic variants (MURAT) is demonstrated using measures of bone mineral density (BMD). By combining individual-level whole genome sequenced data from the UK10K study, and imputed genome-wide genetic...

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Autores principales: Sun, Jianping, Oualkacha, Karim, Forgetta, Vincenzo, Zheng, Hou-Feng, Richards, J. Brent, Evans, Daniel S., Orwoll, Eric, Greenwood, Celia M. T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5760616/
https://www.ncbi.nlm.nih.gov/pubmed/29317680
http://dx.doi.org/10.1038/s41598-017-18385-9
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author Sun, Jianping
Oualkacha, Karim
Forgetta, Vincenzo
Zheng, Hou-Feng
Richards, J. Brent
Evans, Daniel S.
Orwoll, Eric
Greenwood, Celia M. T.
author_facet Sun, Jianping
Oualkacha, Karim
Forgetta, Vincenzo
Zheng, Hou-Feng
Richards, J. Brent
Evans, Daniel S.
Orwoll, Eric
Greenwood, Celia M. T.
author_sort Sun, Jianping
collection PubMed
description Performance of a recently developed test for association between multivariate phenotypes and sets of genetic variants (MURAT) is demonstrated using measures of bone mineral density (BMD). By combining individual-level whole genome sequenced data from the UK10K study, and imputed genome-wide genetic data on individuals from the Study of Osteoporotic Fractures (SOF) and the Osteoporotic Fractures in Men Study (MrOS), a data set of 8810 individuals was assembled; tests of association were performed between autosomal gene-sets of genetic variants and BMD measured at lumbar spine and femoral neck. Distributions of p-values obtained from analyses of a single BMD phenotype are compared to those from the multivariate tests, across several region definitions and variant weightings. There is evidence of increased power with the multivariate test, although no new loci for BMD were identified. Among 17 genes highlighted either because there were significant p-values in region-based association tests or because they were in well-known BMD genes, 4 windows in 2 genes as well as 6 single SNPs in one of these genes showed association at genome-wide significant thresholds with the multivariate phenotype test but not with the single-phenotype test, Sequence Kernel Association Test (SKAT).
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spelling pubmed-57606162018-01-17 Exome-wide rare variant analyses of two bone mineral density phenotypes: the challenges of analyzing rare genetic variation Sun, Jianping Oualkacha, Karim Forgetta, Vincenzo Zheng, Hou-Feng Richards, J. Brent Evans, Daniel S. Orwoll, Eric Greenwood, Celia M. T. Sci Rep Article Performance of a recently developed test for association between multivariate phenotypes and sets of genetic variants (MURAT) is demonstrated using measures of bone mineral density (BMD). By combining individual-level whole genome sequenced data from the UK10K study, and imputed genome-wide genetic data on individuals from the Study of Osteoporotic Fractures (SOF) and the Osteoporotic Fractures in Men Study (MrOS), a data set of 8810 individuals was assembled; tests of association were performed between autosomal gene-sets of genetic variants and BMD measured at lumbar spine and femoral neck. Distributions of p-values obtained from analyses of a single BMD phenotype are compared to those from the multivariate tests, across several region definitions and variant weightings. There is evidence of increased power with the multivariate test, although no new loci for BMD were identified. Among 17 genes highlighted either because there were significant p-values in region-based association tests or because they were in well-known BMD genes, 4 windows in 2 genes as well as 6 single SNPs in one of these genes showed association at genome-wide significant thresholds with the multivariate phenotype test but not with the single-phenotype test, Sequence Kernel Association Test (SKAT). Nature Publishing Group UK 2018-01-09 /pmc/articles/PMC5760616/ /pubmed/29317680 http://dx.doi.org/10.1038/s41598-017-18385-9 Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Sun, Jianping
Oualkacha, Karim
Forgetta, Vincenzo
Zheng, Hou-Feng
Richards, J. Brent
Evans, Daniel S.
Orwoll, Eric
Greenwood, Celia M. T.
Exome-wide rare variant analyses of two bone mineral density phenotypes: the challenges of analyzing rare genetic variation
title Exome-wide rare variant analyses of two bone mineral density phenotypes: the challenges of analyzing rare genetic variation
title_full Exome-wide rare variant analyses of two bone mineral density phenotypes: the challenges of analyzing rare genetic variation
title_fullStr Exome-wide rare variant analyses of two bone mineral density phenotypes: the challenges of analyzing rare genetic variation
title_full_unstemmed Exome-wide rare variant analyses of two bone mineral density phenotypes: the challenges of analyzing rare genetic variation
title_short Exome-wide rare variant analyses of two bone mineral density phenotypes: the challenges of analyzing rare genetic variation
title_sort exome-wide rare variant analyses of two bone mineral density phenotypes: the challenges of analyzing rare genetic variation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5760616/
https://www.ncbi.nlm.nih.gov/pubmed/29317680
http://dx.doi.org/10.1038/s41598-017-18385-9
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