Finding the missing heritability of complex diseases
Open accessAbstract
Genome-wide association studies have identified hundreds of genetic variants associated with complex human diseases and traits, and have provided valuable insights into their genetic architecture. Most variants identified so far confer relatively small increments in risk, and explain only a small proportion of familial clustering, leading many to question how the remaining, 'missing' heritability can be explained. Here we examine potential sources of missing heritability and propose research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment.
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T2D-associated genetic variants explain only a small proportion of total genetic risk.
“In any case, these variants explain only a small proportion of total genetic risk ( 11 ).”
From β-Cell Failure in Type 2 Diabetes: Postulated Mechanisms and Prospects for Prevention and Treatment (2014) · cites this paper as [11]
Known causal variants for many complex disorders, including ASD, generally confer less risk than heritability estimates suggest.
“the causal genetic variants thus far identified generally confer less risk than expected from empirical estimates of heritability6.”
From Genome-wide detection of tandem DNA repeats that are expanded in autism (2020) · cites this paper as [6]
The disparity between observed effects of variants first identified by GWAS and estimates of overall trait heritability (the missing heritability conundrum) is now largely resolved.
“The disparity between the observed effects of the variants first identified by GWAS and estimates of overall trait heritability (the ‘missing heritability’ conundrum) is now largely resolved47.”
From A brief history of human disease genetics (2020) · cites this paper as [47]
Loci detected by GWAS almost always explain only a small minority of the inferred genetic variance.
“loci detected by GWAS almost without exception explain a small minority of the inferred genetic variance5,6”
From Rare and common variants: twenty arguments (2012) · cites this paper as [6]
The common disease-common variant hypothesis has been refuted by the missing heritability problem.
“When GWAS began the field was dominated by the simple common disease-common variant (CD-CV) hypothesis1–4 has been refuted in light of the so-called ‘missing heritability problem’”
From Rare and common variants: twenty arguments (2012) · cites this paper as [6]
The simplest explanation for GWAS failing to find missing heritability is that expectations were based on unrealistic prior assumptions about effect sizes.
“While there has been a very public focus on the failure of GWAS to find the missing heritability5,6, the simplest explanation for this is that the expectations were based on unrealistic prior assumption of effect sizes.”
From Rare and common variants: twenty arguments (2012) · cites this paper as [6]
Genome-wide association studies focused on common single nucleotide variants have identified some disease-associated variants, but most genetic variants contributing to complex disease susceptibility remain undiscovered.
“Despite the success of genome wide association (GWA) studies in identifying common single nucleotide variants (SNVs) that contribute to complex diseases1, the vast majority of genetic variants contributing to disease susceptibility are yet to be discovered.”
From Statistical analysis strategies for association studies involving rare variants (2010) · cites this paper as [2]
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 [48]
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THE QTN PROGRAM AND THE ALLELES THAT MATTER FOR EVOLUTION: ALL THAT'S GOLD DOES NOT GLITTER
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Pan-genome analysis highlights the extent of genomic variation in cultivated and wild rice
Zhao, Q., Feng, Q., Lu, H., Li, Y., Wang, A., Tian, Q., Zhan, Q., Lu, Y., Zhang, L., Huang, T., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0041-z · Cited by 676 · see citing works
- Authors
- Manolio, T. A., Collins, F. S., Cox, N. J., Goldstein, D. B., Hindorff, L. A., Hunter, D. J., McCarthy, M. I., Ramos, E. M., Cardon, L. R., Chakravarti, A., Cho, J. H., Guttmacher, A. E., Kong, A., Kruglyak, L., Mardis, E., Rotimi, C. N., Slatkin, M., Valle, D., Whittemore, A. S., Boehnke, M., Clark, A. G., Eichler, E. E., Gibson, G., Haines, J. L., Mackay, T. F. C., McCarroll, S. A., & Visscher, P. M.
- Affiliations
- National Institutes of Health (US)
- University of Chicago (US)
- Duke University (US)
- Harvard University (US)
- Centre for Human Genetics (GB)
- GlaxoSmithKline (United Kingdom) (GB)
- Johns Hopkins University (US)
- Yale University (US)
- deCODE Genetics (Iceland) (IS)
- Howard Hughes Medical Institute (US)
- Washington University in St. Louis (US)
- University of California, Berkeley (US)
- Stanford University (US)
- University of Michigan (US)
- Cornell University (US)
- The University of Queensland (AU)
- Vanderbilt University (US)
- North Carolina State University (US)
- QIMR Berghofer Medical Research Institute (AU)
- Corresponding author
- Manolio, Teri A.
- ORCID
- Manolio, Teri A.
- Collins, Francis S.
- Cox, Nancy J.
- Goldstein, David B.
- Hindorff, Lucia A.
- McCarthy, Mark I.
- Ramos, Erin M.
- Chakravarti, Aravinda
- Cho, Judy H.
- Kong, Augustine
- Kruglyak, Leonid
- Mardis, Elaine
- Rotimi, Charles N.
- Slatkin, Montgomery
- Valle, David
- Whittemore, Alice S.
- Boehnke, Michael
- Clark, Andrew G.
- Eichler, Evan E.
- Gibson, Greg
- Haines, Jonathan L.
- Mackay, Trudy F. C.
- McCarroll, Steven A.
- Visscher, Peter M.
- Venue
- Nature
- Published
- 2009-10
- Volume
- 461
- Issue
- 7265
- Pages
- 747-753
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC2831613
- OpenAlex
- W1980991473
- Cited by
- 8,336
- References
- 84
- Citations by year
- 2026: 203 · 2025: 285 · 2024: 318 · 2023: 335 · 2022: 409 · 2021: 482 · 2020: 456 · 2019: 494 · 2018: 460 · 2017: 509 · 2016: 544 · 2015: 593 · 2014: 683 · 2013: 650 · 2012: 781
- FWCI
- 58.06
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Institutes of Health (5p50gm065509-10)
- National Heart, Lung, and Blood Institute (U01HL084706, R01HL072904)
- National Institute of Mental Health (R01MH084695)
- National Human Genome Research Institute (R01HG003229)
- National Institute of General Medical Sciences (P50-GM065509)
- National Center for Research Resources (UL1RR024992)
- 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, genetic architecture, epigenetic variation, gene-environment interaction, gene-gene interaction, polygenic risk, familial aggregation, disease prevention
- MeSH terms
- Genetics, Medical, Humans, Pedigree, Genetic Predisposition to Disease, Genetic Diseases, Inborn, Inheritance Patterns, Genome-Wide Association Study
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