Genome-wide association studies and the genetic dissection of complex traits
Open accessAbstract
The availability of affordable high throughput technology for parallel genotyping has opened the field of genetics to genome-wide association studies (GWAS), and in the last few years hundreds of articles reporting results of GWAS for a variety of heritable traits have been published. What do these results tell us? Although GWAS have discovered a few hundred reproducible associations, this number is underwhelming in relation to the huge amount of data produced, and challenges the conjecture that common variants may be the genetic causes of common diseases. We argue that the massive amount of genetic data that result from these studies remains largely unexplored and unexploited because of the challenge of mining and modeling enormous data sets, the difficulty of using nontraditional computational techniques and the focus of accepted statistical analyses on controlling the false positive rate rather than limiting the false negative rate. In this article, we will review the common approach to analysis of GWAS data and then discuss options to learn more from these data. We will use examples from our ongoing studies of sickle cell anemia and also GWAS in multigenic traits.
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Most GWAS are conducted using a standard additive model, where heterozygous variant carriers exhibit a phenotype approximately intermediate in severity relative to each homozygous genotype.
“most GWAS are conducted using a standard additive model [266], where it is hypothesized heterozygous variant carriers exhibit a phenotype approximately intermediate in severity relative to each homozygous genotype.”
From Genetic architecture of Alzheimer's disease (2020) · cites this paper as [266]
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Nonparametric Statistics with Applications to Science and Engineering
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Whole-genome association study identifies <i>STK39</i> as a hypertension susceptibility gene
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Genome-Wide Association Studies in Alzheimer Disease
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Sorl1 as an Alzheimer’s Disease Predisposition Gene?
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Genetics of exceptional longevity
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Genetic Variants Contributing to Daunorubicin-Induced Cytotoxicity
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Genetic Association Analysis Using Data from Triads and Unrelated Subjects
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Estimatingp-values in small microarray experiments
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Survival of Parents and Siblings of Supercentenarians
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The F7 Gene and Clotting Factor VII Levels: Dissection of a Human Quantitative Trait Locus
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A stochastic downhill search algorithm for estimating the local false discovery rate
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Platelet genomics and the risk of atherothrombosis
Ouwehand, W. H. (2007) · Journal of Thrombosis and Haemostasis · doi:10.1111/j.1538-7836.2007.02550.x · Cited by 34 · see citing works
The Molecular Biology of Aging
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Imputation of missing genotypes: an empirical evaluation of IMPUTE
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The F7 Gene and Clotting Factor VII Levels: Dissection of a Human Quantitative Trait Locus
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PedGenie: meta genetic association testing in mixed family and case-control designs
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Matching in case-control studies
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Robust Transmission/Disequilibrium Test for Incomplete Family Genotypes
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Predictive Genomics of Cardioembolic Stroke
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Genetic modifiers of sickle cell disease
Steinberg, M. H., & Sebastiani, P. (2012) · American Journal of Hematology · doi:10.1002/ajh.23232 · Cited by 315 · see citing works
Self-citationLeg ulcers in sickle cell disease
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Classification, Epidemiology, and Genetics of Orofacial Clefts
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History and Current Status of Newborn Screening for Hemoglobinopathies
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van der Sluis, S., Verhage, M., Posthuma, D., & Dolan, C. (2010) · PLoS ONE · doi:10.1371/journal.pone.0013929 · Cited by 142 · see citing works
Genetic architecture of Alzheimer's disease
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“In addition, most GWAS are conducted using a standard additive model [266], where it is hypothesized heterozygous variant carriers exhibit a phenotype approximately intermediate in severity relative to each homozygous genotype.”
MethodTherapy‐related myeloid neoplasms: pathobiology and clinical characteristics
Sill, H., Olipitz, W., Zebisch, A., Schulz, E., & Wölfler, A. (2010) · British Journal of Pharmacology · doi:10.1111/j.1476-5381.2010.01100.x · Cited by 123 · see citing works
Kendler, K. S., Kalsi, G., Holmans, P. A., Sanders, A. R., Aggen, S. H., Dick, D. M., Aliev, F., Shi, J., Levinson, D. F., & Gejman, P. V. (2011) · Alcoholism: Clinical and Experimental Research · doi:10.1111/j.1530-0277.2010.01427.x · Cited by 121 · see citing works
Predictive data mining in clinical medicine: a focus on selected methods and applications
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Genetic and Environmental Risk Factors for Adolescent-Onset Substance Use Disorders
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Hebbel, R. P., Vercellotti, G. M., & Nath, K. A. (2009) · Cardiovascular & Haematological Disorders - Drug Targets · doi:10.2174/1871529x10909040271 · Cited by 89 · see citing works
Hall, F. S., Drgonová, J., Jain, S., & Uhl, G. R. (2013) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2013.07.006 · Cited by 71 · see citing works
Toward a Road Map for Global -Omics: A Primer on -Omic Technologies
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Genetic risk sum score comprised of common polygenic variation is associated with body mass index
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Genome-wide association studies and susceptibility to infectious diseases
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Unravelling the complex genetics of common kidney diseases: from variants to mechanisms
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Vohra, M., Sharma, A. R., Prabhu, N. B., & Padmalatha, S. (2020) · Public Health Genomics · doi:10.1159/000510253 · Cited by 46 · see citing works
SEVERE SICKLE CELL ANEMIA IS ASSOCIATED WITH INCREASED PLASMA LEVELS OF TNF-R1 AND VCAM-1
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Single nucleotide polymorphisms in colorectal cancer: associations with tumor site and TNM stage.
Mateș, I. N., Jinga, V., Csiki, I. E., Mateș, D., Dinu, D., Constantin, A., & Jinga, M. (2012) · PubMed · Cited by 40 · see citing works
Making the right connections: Network biology and plant immune system dynamics
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Lindquist, K. J., Jorgenson, E., Hoffmann, T. J., & Witte, J. S. (2013) · Genetic Epidemiology · doi:10.1002/gepi.21724 · Cited by 23 · see citing works
Nuclear Receptor Co-regulators
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The genetics of depression: what information can new methodologic approaches provide?
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Whole genome sequencing of an ethnic Pathan (Pakhtun) from the north-west of Pakistan
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Krithika, S., Valladares‐Salgado, A., Peralta‐Romero, J., Escobedo, J., Kumate-Rodríguez, J., Cruz, M., & Parra, E. J. (2012) · BMC Medical Genomics · doi:10.1186/1755-8794-5-12 · Cited by 14 · see citing works
Mathur, S. K., Jain, P., & Mathur, P. (2011) · Journal of Obesity · doi:10.1155/2011/587495 · Cited by 15 · see citing works
Kuo, K. H. M. (2017) · Genomics Insights · doi:10.1177/1178631017721178 · Cited by 14 · see citing works
Genetic predisposition to tinnitus in the UK Biobank population
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Dhiman, A., Mehan, S., Khan, Z., Tiwari, A., Gupta, G. D., & Narula, A. S. (2024) · Current Gene Therapy · doi:10.2174/0115665232316708240828063527 · Cited by 11 · see citing works
Smoking and Atherosclerotic Cardiovascular Disease: Part IV: Genetic Markers Associated With Smoking
Winkelmann, B. R., von Holt, K., & Unverdorben, M. (2010) · Biomarkers in Medicine · doi:10.2217/bmm.10.10 · Cited by 9 · see citing works
Bayesian Polynomial Regression Models to Fit Multiple Genetic Models for Quantitative Traits
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Huang, Z., Su, G., Bi, X., Zhang, L., Xu, Z., & Wang, G. (2021) · Bioengineered · doi:10.1080/21655979.2021.1975016 · Cited by 8 · see citing works
Pharmacogenetic Variation in Over 100 Genes in Patients Receiving Acenocumarol
González-Covarrubias, V., Ureña-Carrión, J., Villegas-Torres, B. E., Cossío-Aranda, J. E., Trevethan-Cravioto, S., Izaguirre-Ávila, R., Fiscal-López, Ó. J., & Soberón, X. (2017) · Frontiers in Pharmacology · doi:10.3389/fphar.2017.00863 · Cited by 8 · see citing works
Amanullah, A., Mirbod, M., Pandey, A., Singh, S. B., Gandhi, O. H., & Ayubcha, C. (2025) · Journal of Imaging · doi:10.3390/jimaging11080280 · Cited by 5 · see citing works
Hall, F. S., Chen, Y., & Resendiz-Gutierrez, F. (2020) · Brain Behavior and Evolution · doi:10.1159/000516169 · Cited by 7 · see citing works
Vyshnavi, A. M. H., & Namboori, P. K. K. (2023) · Research in Pharmaceutical Sciences · doi:10.4103/1735-5362.367792 · Cited by 6 · see citing works
Reverse Translational Implications of Genome-Wide Association Studies for Addiction Genetics
Hall, F. S. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-800634-4.00016-0 · Cited by 6 · see citing works
Butković, A., & Elena, S. F. (2022) · Frontiers in Systems Biology · doi:10.3389/fsysb.2022.1005758 · Cited by 5 · see citing works
Phenotypic characterisation and associations of leg ulcers in adult sickle cell patients
Madu, A. J., Madu, K. A., Anigbogu, I. O., Ugwu, A. O., Okwulehie, V. A., Ololo, U., Ugwu, C., & Chikezie, K. (2021) · Wound Repair and Regeneration · doi:10.1111/wrr.12970 · Cited by 5 · see citing works
Anand, V., Rosenman, M. B., & Downs, S. M. (2013) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2013.05.003 · Cited by 3 · see citing works
Yamamoto, A., & Shibuya, T. (2022) · IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) · doi:10.1109/trustcom56396.2022.00078 · Cited by 3 · see citing works
Genome Wide Association Studies
Paola Sebastiani, B., & Solovieff, N. (2010) · Springer eBooks · doi:10.1007/978-0-387-09760-2_8 · Cited by 3 · see citing works
Multiomics Approaches with Advanced Breeding Tools for Crop Improvement
Aggarwal, G., Kumari, S., Kumari, N., Mehra, K., Tiwari, M., Singh, M. K., & Kumar, B. (2025) · CABI eBooks · doi:10.1079/9781800628717.0006 · Cited by 2 · see citing works
Li, F., Grzybowski, M., Roston, R., & Schnable, J. C. (2025) · Frontiers in Plant Science · doi:10.3389/fpls.2025.1595339 · Cited by 1 · see citing works
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- Authors
- Sebastiani, P., Timofeev, N., Dworkis, D. A., Perls, T. T., & Steinberg, M. H.
- Affiliations
- Boston University (US)
- Venue
- American Journal of Hematology
- Publisher
- Wiley
- Published
- 2009-06-29
- Volume
- 84
- Issue
- 8
- Pages
- 504-515
- ISSN
- 0361-8609 (ISSN-L)
- 1096-8652
- PMC
- PMC2895326
- OpenAlex
- W2036839871
- Cited by
- 67
- References
- 152
- Citations by year
- 2026: 3 · 2025: 3 · 2024: 1 · 2023: 1 · 2022: 3 · 2021: 4 · 2020: 6 · 2019: 1 · 2017: 4 · 2016: 1 · 2015: 4 · 2014: 3 · 2013: 4 · 2012: 7
- FWCI
- 0.91
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- American Journal of Hematology (publishedVersion, other-oa)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health
- National Heart, Lung, and Blood Institute (R01-HL87681, R01 HL70735, R01HL087681, R01HL068970, R01 HL 68970, HL87681, R01HL070735)
- 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
- genome-wide association study, complex traits, common genetic variants, common diseases, false negative rate, polygenic traits, sickle cell disease, genetic dissection
- MeSH terms
- Anemia, Sickle Cell, Animals, Humans, Genome, Human, Sequence Analysis, DNA, Quantitative Trait Loci, Genome-Wide Association Study
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