Phenotypic complexity, measurement bias, and poor phenotypic resolution contribute to the missing heritability problem in genetic association studies.

<h4>Background</h4>The variance explained by genetic variants as identified in (genome-wide) genetic association studies is typically small compared to family-based heritability estimates. Explanations of this 'missing heritability' have been mainly genetic, such as genetic het...

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Autores principales:	Sophie van der Sluis, Matthijs Verhage, Danielle Posthuma, Conor V Dolan
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2010
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/52714df5db22411f8dfb9f66444138ba
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spelling	oai:doaj.org-article:52714df5db22411f8dfb9f66444138ba2021-11-18T07:37:00ZPhenotypic complexity, measurement bias, and poor phenotypic resolution contribute to the missing heritability problem in genetic association studies.1932-620310.1371/journal.pone.0013929https://doaj.org/article/52714df5db22411f8dfb9f66444138ba2010-11-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/21085666/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Background</h4>The variance explained by genetic variants as identified in (genome-wide) genetic association studies is typically small compared to family-based heritability estimates. Explanations of this 'missing heritability' have been mainly genetic, such as genetic heterogeneity and complex (epi-)genetic mechanisms.<h4>Methodology</h4>We used comprehensive simulation studies to show that three phenotypic measurement issues also provide viable explanations of the missing heritability: phenotypic complexity, measurement bias, and phenotypic resolution. We identify the circumstances in which the use of phenotypic sum-scores and the presence of measurement bias lower the power to detect genetic variants. In addition, we show how the differential resolution of psychometric instruments (i.e., whether the instrument includes items that resolve individual differences in the normal range or in the clinical range of a phenotype) affects the power to detect genetic variants.<h4>Conclusion</h4>We conclude that careful phenotypic data modelling can improve the genetic signal, and thus the statistical power to identify genetic variants by 20-99%.Sophie van der SluisMatthijs VerhageDanielle PosthumaConor V DolanPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 5, Iss 11, p e13929 (2010)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Sophie van der Sluis Matthijs Verhage Danielle Posthuma Conor V Dolan Phenotypic complexity, measurement bias, and poor phenotypic resolution contribute to the missing heritability problem in genetic association studies.
description	<h4>Background</h4>The variance explained by genetic variants as identified in (genome-wide) genetic association studies is typically small compared to family-based heritability estimates. Explanations of this 'missing heritability' have been mainly genetic, such as genetic heterogeneity and complex (epi-)genetic mechanisms.<h4>Methodology</h4>We used comprehensive simulation studies to show that three phenotypic measurement issues also provide viable explanations of the missing heritability: phenotypic complexity, measurement bias, and phenotypic resolution. We identify the circumstances in which the use of phenotypic sum-scores and the presence of measurement bias lower the power to detect genetic variants. In addition, we show how the differential resolution of psychometric instruments (i.e., whether the instrument includes items that resolve individual differences in the normal range or in the clinical range of a phenotype) affects the power to detect genetic variants.<h4>Conclusion</h4>We conclude that careful phenotypic data modelling can improve the genetic signal, and thus the statistical power to identify genetic variants by 20-99%.
format	article
author	Sophie van der Sluis Matthijs Verhage Danielle Posthuma Conor V Dolan
author_facet	Sophie van der Sluis Matthijs Verhage Danielle Posthuma Conor V Dolan
author_sort	Sophie van der Sluis
title	Phenotypic complexity, measurement bias, and poor phenotypic resolution contribute to the missing heritability problem in genetic association studies.
title_short	Phenotypic complexity, measurement bias, and poor phenotypic resolution contribute to the missing heritability problem in genetic association studies.
title_full	Phenotypic complexity, measurement bias, and poor phenotypic resolution contribute to the missing heritability problem in genetic association studies.
title_fullStr	Phenotypic complexity, measurement bias, and poor phenotypic resolution contribute to the missing heritability problem in genetic association studies.
title_full_unstemmed	Phenotypic complexity, measurement bias, and poor phenotypic resolution contribute to the missing heritability problem in genetic association studies.
title_sort	phenotypic complexity, measurement bias, and poor phenotypic resolution contribute to the missing heritability problem in genetic association studies.
publisher	Public Library of Science (PLoS)
publishDate	2010
url	https://doaj.org/article/52714df5db22411f8dfb9f66444138ba
work_keys_str_mv	AT sophievandersluis phenotypiccomplexitymeasurementbiasandpoorphenotypicresolutioncontributetothemissingheritabilityproblemingeneticassociationstudies AT matthijsverhage phenotypiccomplexitymeasurementbiasandpoorphenotypicresolutioncontributetothemissingheritabilityproblemingeneticassociationstudies AT danielleposthuma phenotypiccomplexitymeasurementbiasandpoorphenotypicresolutioncontributetothemissingheritabilityproblemingeneticassociationstudies AT conorvdolan phenotypiccomplexitymeasurementbiasandpoorphenotypicresolutioncontributetothemissingheritabilityproblemingeneticassociationstudies
_version_	1718423159614472192

Phenotypic complexity, measurement bias, and poor phenotypic resolution contribute to the missing heritability problem in genetic association studies.

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