Estimation and partitioning of polygenic variation captured by common SNPs for Alzheimer's disease, multiple sclerosis and endometriosis
Open accessAbstract
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.
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Endometriosis has an estimated total heritability of 0.47-0.51 based on twin studies and a common SNP-based heritability of 0.26.
“The condition has an estimated total heritability of 0.47–0.51 based on twin studies13, and a common SNP-based heritability of 0.26 (ref. 4).”
From Meta-analysis identifies five novel loci associated with endometriosis highlighting key genes involved in hormone metabolism (2017) · cites this paper as [4]
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- Authors
- Lee, S. H., Harold, D., Nyholt, D. R., ANZGene Consortium, International Endogene Consortium, the Genetic and Environmental Risk for Alzheimer's disease (GERAD1) Consortium, Goddard, M. E., Zondervan, K. T., Williams, J., Montgomery, G. W., Wray, N. R., & Visscher, P. M.
- Affiliations
- The University of Queensland (AU)
- Cardiff University (GB)
- QIMR Berghofer Medical Research Institute (AU)
- The University of Melbourne (AU)
- John Radcliffe Hospital (GB)
- Corresponding author
- Lee, S. H.
- ORCID
- Venue
- Human Molecular Genetics
- Publisher
- Oxford University Press (OUP)
- Published
- 2012-11-28
- Volume
- 22
- Issue
- 4
- Pages
- 832-841
- ISSN
- 0964-6906 (ISSN-L)
- 1460-2083
- PMC
- PMC3554206
- OpenAlex
- W2123971761
- Cited by
- 217
- References
- 45
- Citations by year
- 2026: 4 · 2025: 15 · 2024: 10 · 2023: 15 · 2022: 18 · 2021: 15 · 2020: 19 · 2019: 13 · 2018: 14 · 2017: 12 · 2016: 21 · 2015: 23 · 2014: 24 · 2013: 14
- FWCI
- 11.76
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc
- Locations
- Human Molecular Genetics (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion, cc-by-nc)
- QUT ePrints (Queensland University of Technology) (submittedVersion, other-oa)
- Minerva Access (University of Melbourne) (submittedVersion, cc-by)
- EPubDev Repository (submittedVersion)
- eCite Digital Repository (University of Tasmania) (submittedVersion, cc-by-nc)
- UWA Profiles and Research Repository (UWA) (submittedVersion)
- Murdoch University Research Portal (submittedVersion)
- Universitätsbibliographie, Universität Duisburg-Essen (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Figshare (submittedVersion, cc-by-nc)
- ORCA Online Research @Cardiff (Cardiff University) (submittedVersion)
- Bristol Research (University of Bristol) (submittedVersion)
- Griffith Research Online (submittedVersion, cc-by-nc)
- RUNE (Research UNE) (submittedVersion)
- NOVA (University of Newcastle Australia) (submittedVersion)
- Funders
- Wellcome Trust (085235, 084766, WT085235/Z/08/Z, 090532, WT085235, 076113, 095317)
- University of Queensland
- Medical Research Council (MR/K013041/1)
- Australian Research Council (FT0991360, FT0991022)
- National Health and Medical Research Council (613674, 613601, 613602, 619667, 339462, 1011506)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
- Keywords
- Alzheimer's disease, multiple sclerosis, endometriosis, polygenic risk, heritability, genetic variance partitioning, liability scale, linear mixed models, genetic architecture, minor allele frequency, genome-wide association study
- MeSH terms
- Alzheimer Disease, Chromosomes, Human, Endometriosis, Female, Gene Frequency, Genotype, Humans, Male, Models, Genetic, Multiple Sclerosis, Genetic Variation, Case-Control Studies, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Molecular Sequence Annotation
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