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SumHer better estimates the SNP heritability of complex traits from summary statistics
Open accessPublished version of a preprint
Abstract
LD Score Regression (LDSC) has been widely applied to the results of genome-wide association studies. However, its estimates of SNP heritability are derived from an unrealistic model in which each SNP is expected to contribute equal heritability. As a consequence, LDSC tends to over-estimate confounding bias, under-estimate the total phenotypic variation explained by SNPs, and provide misleading estimates of the heritability enrichment of SNP categories. Therefore, we present SumHer, software for estimating SNP heritability from summary statistics using more realistic heritability models. After demonstrating its superiority over LDSC, we apply SumHer to the results of 24 large-scale association studies (average sample size 121 000). First we show that these studies have tended to substantially over-correct for confounding, and as a result the number of genome-wide significant loci has under-reported by about 20%. Next we estimate enrichment for 24 categories of SNPs defined by functional annotations. A previous study using LDSC reported that conserved regions were 13-fold enriched, and found a further twelve categories with above 2-fold enrichment. By contrast, our analysis using SumHer finds that conserved regions are only 1.6-fold (SD 0.06) enriched, and that no category has enrichment above 1.7-fold. SumHer provides an improved understanding of the genetic architecture of complex traits, which enables more efficient analysis of future genetic data.
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“Fourth, recent analyses have demonstrated that estimates of heritability enrichment are sensitive to the assumed heritability model and that variation in heritability estimates from different statistical methods are influenced by demographic factors75,76.”
From Quantifying the contribution of Neanderthal introgression to the heritability of complex traits (2021) · cites this paper as [75]
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Metadata
- Authors
- Speed, D., & Balding, D. J.
- Affiliations
- Aarhus University (DK)
- The University of Melbourne (AU)
- Corresponding author
- Speed, Doug
- Venue
- Nature Genetics
- Published
- 2018-12-03
- Volume
- 51
- Issue
- 2
- Pages
- 277-284
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- PMC
- PMC6485398
- OpenAlex
- W2901957554
- Cited by
- 254
- References
- 67
- Citations by year
- 2026: 30 · 2025: 31 · 2024: 37 · 2023: 33 · 2022: 24 · 2021: 37 · 2020: 33 · 2019: 26 · 2018: 3
- FWCI
- 15.18
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- cc-by-nc
- www.springer.com/tdm (tdm)
- Locations
- Nature Genetics (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Minerva Access (University of Melbourne) (submittedVersion)
- Funders
- Vanderbilt University (U01HG006378)
- Northwestern University (U01HG006378, U01HG006388)
- University of Michigan (U01 AG009740, RC2AG036495, RC4AG039029)
- Aarhus Universitet
- Wellcome Trust (754513)
- Vanderbilt University Medical Center (U01HG006378, U01HG006385)
- Aarhus Universitets Forskningsfond (7025- 00094B, 754513)
- Medical Research Council (MR/L012561/1)
- National Institute on Aging (U01AG009740, RC2AG036495, and RC4AG039029, RC2AG036495, and RC4AG039029, RC4AG039029, U01AG009740)
- National Human Genome Research Institute (U01HG006385, U01HG006379, U01HG006830, U01HG006375, U01HG006380, U01HG006382, U01HG006828, U01HG006378, U01HG006388, U01HG006389)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- SNP heritability, confounding, genetic correlation, complex traits, genome-wide association study, summary statistics, genetic architecture, LD score regression
- MeSH terms
- Humans, Models, Genetic, Phenotype, Software, Quantitative Trait, Heritable, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Inheritance Patterns, Genome-Wide Association Study
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