Estimation and partitioning of polygenic variation captured by common SNPs for Alzheimer's disease, multiple sclerosis and endometriosis

Common diseases such as endometriosis (ED), Alzheimer's disease (AD) and multiple sclerosis (MS) account for a significant proportion of the health care burden in many countries. Genome-wide association studies (GWASs) for these diseases have identified a number of individual genetic variants c...

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Main Authors:	Lee, S. Hong, Harold, Denise, Nyholt, Dale R., Goddard, Michael E., Zondervan, Krina T., Williams, Julie, Montgomery, Grant W., Wray, Naomi R., Visscher, Peter M.
Format:	Online
Language:	English
Published:	Oxford University Press 2013
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3554206/

id	pubmed-3554206
recordtype	oai_dc
spelling	pubmed-35542062013-01-24 Estimation and partitioning of polygenic variation captured by common SNPs for Alzheimer's disease, multiple sclerosis and endometriosis Lee, S. Hong Harold, Denise Nyholt, Dale R. Goddard, Michael E. Zondervan, Krina T. Williams, Julie Montgomery, Grant W. Wray, Naomi R. Visscher, Peter M. Association Studies Articles Common diseases such as endometriosis (ED), Alzheimer's disease (AD) and multiple sclerosis (MS) account for a significant proportion of the health care burden in many countries. Genome-wide association studies (GWASs) for these diseases have identified a number of individual genetic variants contributing to the risk of those diseases. However, the effect size for most variants is small and collectively the known variants explain only a small proportion of the estimated heritability. We used a linear mixed model to fit all single nucleotide polymorphisms (SNPs) simultaneously, and estimated genetic variances on the liability scale using SNPs from GWASs in unrelated individuals for these three diseases. For each of the three diseases, case and control samples were not all genotyped in the same laboratory. We demonstrate that a careful analysis can obtain robust estimates, but also that insufficient quality control (QC) of SNPs can lead to spurious results and that too stringent QC is likely to remove real genetic signals. Our estimates show that common SNPs on commercially available genotyping chips capture significant variation contributing to liability for all three diseases. The estimated proportion of total variation tagged by all SNPs was 0.26 (SE 0.04) for ED, 0.24 (SE 0.03) for AD and 0.30 (SE 0.03) for MS. Further, we partitioned the genetic variance explained into five categories by a minor allele frequency (MAF), by chromosomes and gene annotation. We provide strong evidence that a substantial proportion of variation in liability is explained by common SNPs, and thereby give insights into the genetic architecture of the diseases. Oxford University Press 2013-02-15 2012-11-28 /pmc/articles/PMC3554206/ /pubmed/23193196 http://dx.doi.org/10.1093/hmg/dds491 Text en © The Author 2012. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial reuse, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Lee, S. Hong Harold, Denise Nyholt, Dale R. Goddard, Michael E. Zondervan, Krina T. Williams, Julie Montgomery, Grant W. Wray, Naomi R. Visscher, Peter M.
spellingShingle	Lee, S. Hong Harold, Denise Nyholt, Dale R. Goddard, Michael E. Zondervan, Krina T. Williams, Julie Montgomery, Grant W. Wray, Naomi R. Visscher, Peter M. Estimation and partitioning of polygenic variation captured by common SNPs for Alzheimer's disease, multiple sclerosis and endometriosis
author_facet	Lee, S. Hong Harold, Denise Nyholt, Dale R. Goddard, Michael E. Zondervan, Krina T. Williams, Julie Montgomery, Grant W. Wray, Naomi R. Visscher, Peter M.
author_sort	Lee, S. Hong
title	Estimation and partitioning of polygenic variation captured by common SNPs for Alzheimer's disease, multiple sclerosis and endometriosis
title_short	Estimation and partitioning of polygenic variation captured by common SNPs for Alzheimer's disease, multiple sclerosis and endometriosis
title_full	Estimation and partitioning of polygenic variation captured by common SNPs for Alzheimer's disease, multiple sclerosis and endometriosis
title_fullStr	Estimation and partitioning of polygenic variation captured by common SNPs for Alzheimer's disease, multiple sclerosis and endometriosis
title_full_unstemmed	Estimation and partitioning of polygenic variation captured by common SNPs for Alzheimer's disease, multiple sclerosis and endometriosis
title_sort	estimation and partitioning of polygenic variation captured by common snps for alzheimer's disease, multiple sclerosis and endometriosis
description	Common diseases such as endometriosis (ED), Alzheimer's disease (AD) and multiple sclerosis (MS) account for a significant proportion of the health care burden in many countries. Genome-wide association studies (GWASs) for these diseases have identified a number of individual genetic variants contributing to the risk of those diseases. However, the effect size for most variants is small and collectively the known variants explain only a small proportion of the estimated heritability. We used a linear mixed model to fit all single nucleotide polymorphisms (SNPs) simultaneously, and estimated genetic variances on the liability scale using SNPs from GWASs in unrelated individuals for these three diseases. For each of the three diseases, case and control samples were not all genotyped in the same laboratory. We demonstrate that a careful analysis can obtain robust estimates, but also that insufficient quality control (QC) of SNPs can lead to spurious results and that too stringent QC is likely to remove real genetic signals. Our estimates show that common SNPs on commercially available genotyping chips capture significant variation contributing to liability for all three diseases. The estimated proportion of total variation tagged by all SNPs was 0.26 (SE 0.04) for ED, 0.24 (SE 0.03) for AD and 0.30 (SE 0.03) for MS. Further, we partitioned the genetic variance explained into five categories by a minor allele frequency (MAF), by chromosomes and gene annotation. We provide strong evidence that a substantial proportion of variation in liability is explained by common SNPs, and thereby give insights into the genetic architecture of the diseases.
publisher	Oxford University Press
publishDate	2013
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3554206/
_version_	1611949270012788736

Estimation and partitioning of polygenic variation captured by common SNPs for Alzheimer's disease, multiple sclerosis and endometriosis

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