Evaluating the heritability explained by known susceptibility variants: a survey of ten complex diseases
Abstract
Recently, an increasing number of susceptibility variants have been identified for complex diseases. At the same time, the concern of "missing heritability" has also emerged. There is however no unified way to assess the heritability explained by individual genetic variants for binary outcomes. A systemic and quantitative assessment of the degree of "missing heritability" for complex diseases is lacking. In this study, we measure the variance in liability explained by individual variants, which can be directly interpreted as the locus-specific heritability. The method is extended to deal with haplotypes, multi-allelic markers, multi-locus genotypes, and markers in linkage disequilibrium. Methods to estimate the standard error and confidence interval are proposed. To assess our current level of understanding of the genetic basis of complex diseases, we conducted a survey of 10 diseases, evaluating the total variance explained by the known variants. The diseases under evaluation included Alzheimer's disease, bipolar disorder, breast cancer, coronary artery disease, Crohn's disease, prostate cancer, schizophrenia, systemic lupus erythematosus (SLE), type 1 diabetes and type 2 diabetes. The median total variance explained across the 10 diseases was 9.81%, while the median variance explained per associated SNP was around 0.25%. Our results suggest that a substantial proportion of heritability remains unexplained for the diseases under study. Programs to implement the methodologies described in this paper are available at http://sites.google.com/site/honcheongso/software/varexp.
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Using a model that assumes an underlying normally distributed but unobserved disease risk score or liability, the nineteen loci described here account for between 10% (if AMD prevalence is close to 1%) and 30% (if AMD prevalence is closer to 10%) of the variability in disease risk (corresponding to 15-65% of the total genetic contribution to AMD).
“Using a model that assumes an underlying normally distributed but unobserved disease risk score or liability49, the nineteen loci described here account for between 10% (if AMD prevalence is close to 1%) and 30% (if AMD prevalence is closer to 10%) of the variability in disease risk (corresponding to 15–65% of the total genetic contribution to AMD).”
From Seven new loci associated with age-related macular degeneration (2013) · cites this paper as [49]
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- Authors
- So, H.-C., Gui, A. H. S., Cherny, S. S., & Sham, P. C.
- Affiliations
- University of Hong Kong (HK)
- Corresponding author
- Sham, Pak C.
- Venue
- Genetic Epidemiology
- Publisher
- Wiley
- Published
- 2011-03-03
- Volume
- 35
- Issue
- 5
- Pages
- 310-317
- ISSN
- 0741-0395 (ISSN-L)
- OpenAlex
- W2128416240
- Cited by
- 289
- References
- 32
- Citations by year
- 2026: 3 · 2025: 4 · 2024: 5 · 2023: 9 · 2022: 16 · 2021: 14 · 2020: 9 · 2019: 19 · 2018: 22 · 2017: 26 · 2016: 23 · 2015: 26 · 2014: 32 · 2013: 29 · 2012: 40
- FWCI
- 22.18
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Genetic Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- The HKU Scholars Hub (University of Hong Kong) (submittedVersion)
- Funders
- Wellcome Trust
- Croucher Foundation
- 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
- missing heritability, complex diseases, single nucleotide polymorphisms, haplotypes, linkage disequilibrium, multilocus genotypes, genetic risk variants, Alzheimer's disease, bipolar disorder, breast cancer, coronary artery disease, Crohn's disease, prostate cancer, schizophrenia, systemic lupus erythematosus, type 1 diabetes, type 2 diabetes
- MeSH terms
- Alleles, Female, Genetic Markers, Genotype, Haplotypes, Humans, Male, Models, Genetic, Genetic Variation, Models, Statistical, Linkage Disequilibrium, Statistics, Nonparametric, Genetic Predisposition to Disease, Genome-Wide Association Study
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