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A HapMap harvest of insights into the genetics of common disease
Open accessAbstract
The International HapMap Project was designed to create a genome-wide database of patterns of human genetic variation, with the expectation that these patterns would be useful for genetic association studies of common diseases. This expectation has been amply fulfilled with just the initial output of genome-wide association studies, identifying nearly 100 loci for nearly 40 common diseases and traits. These associations provided new insights into pathophysiology, suggesting previously unsuspected etiologic pathways for common diseases that will be of use in identifying new therapeutic targets and developing targeted interventions based on genetically defined risk. In addition, HapMap-based discoveries have shed new light on the impact of evolutionary pressures on the human genome, suggesting multiple loci important for adapting to disease-causing pathogens and new environments. In this review we examine the origin, development, and current status of the HapMap; its prospects for continued evolution; and its current and potential future impact on biomedical science.
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“A relevant example is evident in genomics research, in which data pooling has, e.g., enabled knowledge of disease-related loci to be expanded substantially [e.g.Lambert et al. (2013); Manolio et al. (2008); Schizophrenia Working Group of the Psychiatric Genomics (2014)], findings which would not have been possible without the sample sizes offered through data-sharing.”
From New directions in hypnosis research: strategies for advancing the cognitive and clinical neuroscience of hypnosis (2017) · cites this paper as Manolio et al. 2008
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“Research in other fields has benefited substantially from datasharing initiatives.”
From New directions in hypnosis research: strategies for advancing the cognitive and clinical neuroscience of hypnosis (2017) · cites this paper as Manolio et al. 2008
In the citing paper
“GWAS has successfully identified thousands of common variants99”
From Rare and common variants: twenty arguments (2012) · cites this paper as [99]
In the citing paper
“As of June 2011, the NHGRI GWAS catalog lists 1,449 genome-wide significant associations with 237 traits and diseases, spread across all chromosome except the Y99.”
From Rare and common variants: twenty arguments (2012) · cites this paper as [99]
In the citing paper
“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 [1]
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Cites
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“In the past few years genome-wide association studies (GWAS) have become increasingly popular and the approach has identified robust associations of many common genetic variants with more than 80 diseases [Manolio et al., 2008]. However, it has also been noted that the established common variants from GWAS generally a…”
BackgroundWu, H., Zheng, J., Deng, J., Zhang, L., Li, N., li, W., Li, F., Lü, J., & Zhou, Y. (2014) · Oncogene · doi:10.1038/onc.2014.400 · Cited by 70
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“Most often this is the additive (per-allele or codominant) model, because of statistical power considerations, and thus most associations derived from genomewide association studies are usually presented as per-allele risks (9).”
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BackgroundMicroRNAs: Potential biomarkers in cancer
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“An integrinbeta4 (ITGB4) SNP may influence breast tumor aggressiveness and survival, and it may have prognostic value in the clinic (45).”
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Being More Realistic about the Public Health Impact of Genomic Medicine
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The Genomic Applications in Practice and Prevention Network
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“In brief, GAPPNet will develop a process that links ongoing collection of information on candidate genomic applications to four crucial domains: (1) knowledge synthesis and dissemination for new and existing technologies, and the identification of knowledge gaps, (2) a robust evidence-based recommendation development…”
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“Genome Wide Association Studies (GWAS) have uncovered many susceptible loci underlying common genetic disorders, and provided new insights into disease aetiology (1).”
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“Furthermore, advancements in technologies and analytics, such as genomewide association studies, further enabled the discovery of hundreds of disease-associated genes (7).”
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“Genome-wide association studies (GWAS) have identified common susceptibility variants for numerous disorders [1], [2].”
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METTL14 Gene Polymorphisms Confer Neuroblastoma Susceptibility: An Eight-Center Case-Control Study
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“…have successfully identified numerous genetic risk factors for many common diseases, however, only single nucleotide polymorphisms (SNPs) with the strongest p values are generally declared significant due to issues arising from multiple testing and type I error concerns (Manolio et al. 2008).”
CDH13is associated with working memory performance in attention deficit/hyperactivity disorder
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“These techniques have paved the way for numerous genomewide association studies, which aimed to further define the genetic basis of many common diseases, including cancer (5).”
Navigating the nuances of clinical sequence variant interpretation in Mendelian disease
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“The enhancement in SNP genotyping methodologies and progress in the human genome sequence project ( 41 ) have facilitated genome-wide SNP association and linkage studies for identification of novel genetic associations between SNPs and variation in markers of immunity to pathogens (42).”
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Matarín, M., Singleton, A., Hardy, J., & Meschia, J. F. (2009) · Journal of Internal Medicine · doi:10.1111/j.1365-2796.2009.02202.x · Cited by 54
Genome-Wide Association Studies for Atherosclerotic Vascular Disease and Its Risk Factors
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“variant [CDCV]) hypothesis.(17,18) This theory attributes the origin of complex diseases to the additive effects of many common variants with modest but real functional consequences, acting in concert and with concurrent environmental influences.”
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“This expectation has been fulfilled with just the initial output of genome-wide association analyses, identifying nearly 500 loci for over 80 common diseases and traits [2,3].”
MethodThe Handbook of Neuropsychiatric Biomarkers, Endophenotypes and Genes
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Human Genetics of Diabetic Retinopathy: Current Perspectives
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“Extrapolating from the collective GWAS experience [51, 52], one can nevertheless anticipate that for any DR gene found through GWAS, the implicated risk alleles will have limited effect sizes with OR <1.”
BackgroundLaparoscopic Colectomy Survival Benefit for Colon Cancer: Is Evidence From a Randomized Trial True?
Ziogas, D. E., Polychronidis, A., Kanellos, I., & Roukos, D. H. (2009) · Annals of Surgery · doi:10.1097/sla.0b013e31819f26e9 · Cited by 51
Personalized Genetic Prediction: Too Limited, Too Expensive, or Too Soon?
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A Knowledge-Based Weighting Framework to Boost the Power of Genome-Wide Association Studies
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“for complex diseases [2].”
Genetics of Patent Ductus Arteriosus Susceptibility and Treatment
Hajj, H., & Dagle, J. M. (2012) · Seminars in Perinatology · doi:10.1053/j.semperi.2011.09.019 · Cited by 52
Overview of personalized medicine in the disease genomic era
Hong, K., & Oh, B. (2010) · BMB Reports · doi:10.3858/bmbrep.2010.43.10.643 · Cited by 50
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“Single-nucleotide polymorphisms (SNPs) are sites in the genome sequence where individuals differ by a single base [70].”
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Miki, D., Ochi, H., Hayes, C. N., Aikata, H., & Chayama, K. (2012) · Cancer Science · doi:10.1111/j.1349-7006.2012.02242.x · Cited by 50
The Road from Next-Generation Sequencing to Personalized Medicine
Gonzalez‐Garay, M. L. (2014) · Personalized Medicine · doi:10.2217/pme.14.34 · Cited by 49
Manolio, T. A. (2009) · Pharmacogenomics · doi:10.2217/14622416.10.2.235 · Cited by 48
Self-citationPiriyapongsa, J., Ngamphiw, C., Intarapanich, A., Kulawonganunchai, S., Assawamakin, A., Bootchai, C., Shaw, P. J., & Tongsima, S. (2012) · BMC Genomics · doi:10.1186/1471-2164-13-s7-s2 · Cited by 48
Liu, X., & Yu, L. (2017) · Frontiers in Plant Science · doi:10.3389/fpls.2017.00853 · Cited by 51
“It has been used with success in both humans (Cardon and Abecasis, 2003; Manolio et al., 2008) and plants.”
New Genetic Insights from Autoimmune Thyroid Disease
Davies, T. F., Latif, R., & Yin, X. (2012) · Journal of Thyroid Research · doi:10.1155/2012/623852 · Cited by 48
“Results are now available for a variety of autoimmune diseases including rheumatoid arthritis and type 1 diabetes mellitus [18] and most recently for AITD [19].”
BackgroundRepertoires of the Nucleosome-Positioning Dinucleotides
Bettecken, T., & Trifonov, E. N. (2009) · PLoS ONE · doi:10.1371/journal.pone.0007654 · Cited by 48
“have the potential to help in interpretation of genetic association studies results, when associations are found with SNPs mapping to ‘‘gene deserts’’ [24].”
BackgroundChang, S., Gao, L., Zhao, L., Zhang, W., Du, Y., & Wang, J. (2013) · Biological Psychiatry · doi:10.1016/j.biopsych.2013.04.016 · Cited by 49
“The traditional association approach examines individual SNPs/genes and ignores their combined effects (21).”
BackgroundGenome‐wide SNP association–based localization of a dwarfism gene in Friesian dwarf horses
Orr, N., Back, W., Gu, J., Leegwater, P. A. J., Govindarajan, P., Conroy, J., Ducro, B. J., van Arendonk, J. A. M., MacHugh, D. E., Ennis, S., et al. (2010) · Animal Genetics · doi:10.1111/j.1365-2052.2010.02091.x · Cited by 48
“High-density SNP-based genotyping arrays have been successfully used to identify genetic variants contributing to both common and rare diseases in humans and animals (Charlier et al. 2008; Manolio et al. 2008).”
BackgroundRNA Biology Provides New Therapeutic Targets for Human Disease
Harries, L. W. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00205 · Cited by 53
“Similarly miR-33a and miR-33 have been associated with metabolic disease and atherosclerosis (Marquart et al., 2010; Rayner et al., 2011) and miR-155 has links with inflammatory diseases (Dorsett et al., 2008).”
SNP model development for the prediction of eye colour in New Zealand
Allwood, J. S., & Harbison, S. (2013) · Forensic Science International Genetics · doi:10.1016/j.fsigen.2013.03.005 · Cited by 46
“height [4,5]; eye colour [6,7] and many medical conditions [8,9]), often with the intent of utilising the SNPs contributing the greatest effect for eventual prediction of phenotype.”
BackgroundBailey, J. N. C., Yaspan, B. L., Pasquale, L. R., Hauser, M. A., Kang, J. H., Loomis, S. J., Brilliant, M. H., Budenz, D. L., Christen, W. G., Fingert, J. H., et al. (2014) · Human Genetics · doi:10.1007/s00439-014-1468-7 · Cited by 47
Genomics and bioinformatics capacity in Africa: no continent is left behind
Mboowa, G., Sserwadda, I., & Aruhomukama, D. (2021) · Genome · doi:10.1139/gen-2020-0013 · Cited by 48
Weissglas‐Volkov, D., Aguilar-Salinas, C. A., Sinsheimer, J. S., Riba, L., Huertas‐Vázquez, A., Ordóñez-Sánchez, M. L., Rodríguez-Guillén, R., Cantor, R. M., Tusié‐Luna, T., & Pajukanta, P. (2009) · Circulation Cardiovascular Genetics · doi:10.1161/circgenetics.109.908004 · Cited by 47
Inflammatory priming predisposes mice to age-related retinal degeneration
Mustafi, D., Maeda, T., Kohno, H., Nadeau, J. H., & Palczewski, K. (2012) · Journal of Clinical Investigation · doi:10.1172/jci64427 · Cited by 46
“ciation studies — having identified the vast majority of variations in noncoding regions (59) and the recent identification of large intervening noncoding RNAs implicated in controlling a diverse set of biological processes (60, 61), including differentiation of the murine retina (62), a discovery accelerated by appli…”
Pharmacogenomic Characterization of US FDA-approved Cytotoxic Drugs
Peters, E. J., Motsinger‐Reif, A. A., Havener, T. M., Everitt, L., Hardison, N. E., Watson, V. G., Wagner, M. J., Richards, K. L., Province, M. A., & McLeod, H. L. (2011) · Pharmacogenomics · doi:10.2217/pgs.11.92 · Cited by 46
Genetics and Genomics of Chronic Obstructive Pulmonary Disease
Silverman, E. K., Spira, A. E., & Paré, P. D. (2009) · Proceedings of the American Thoracic Society · doi:10.1513/pats.200904-021ds · Cited by 47
“Nonetheless, GWA studies have unequivocally identified genome-wide significant associations in a rapidly growing number of complex diseases, including age-related macular degeneration, diabetes mellitus, Crohn’s disease, and asthma ( 10 ).”
BackgroundWang, M., Liu, F., Hsing, A. W., Wang, X., Shao, Q., Qi, J., Ye, Y., Wang, Z., Chen, H., Gao, X., et al. (2011) · Carcinogenesis · doi:10.1093/carcin/bgr279 · Cited by 45
“The three well-established risk factors for prostate cancer are age, race, and family history [4], although recent genome-wide association studies (GWAS) mostly in Caucasian populations have identified over 30 risk-conferring loci, providing strong support for a genetic component for this disease [5-7].”
BackgroundGenetic susceptibility in Parkinson's disease
Brás, J., & Singleton, A. (2008) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2008.11.008 · Cited by 47
Analyzing complex traits with congenic strains
Shao, H., Sinasac, D. S., Burrage, L. C., Hodges, C. A., Supelak, P. J., Palmert, M. R., Moreno, C., Cowley, A. W., Jacob, H. J., & Nadeau, J. H. (2010) · Mammalian Genome · doi:10.1007/s00335-010-9267-5 · Cited by 44
“functions, regulatory controls, and the associated systems networks and pathways (Altschuler et al. 2008; Hirschhorn 2009; Manolio et al. 2008; Zhu et al. 2008).”
Using genetics to predict the natural history of asthma?
Holloway, J. W., Arshad, S. H., & Holgate, S. T. (2010) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2010.06.006 · Cited by 47
“5.(39) For example, for the first loci identified for asthma susceptibility using a GWAS approach, ORM1-like protein 3 (ORMDL3)/Gasdermin B (GSDMB) on chromosome 17q21, a meta-analysis of 5 published studies on rs7216389 in 9 populations resulted in an odds ratio for asthma of 1.”
MethodAdvances in the genetics of endometriosis
Dun, E. C., Taylor, R. N., & Wieser, F. (2010) · Genome Medicine · doi:10.1186/gm196 · Cited by 42
“GWASs have been performed successfully in the discovery of new genomic regions that are associated with multifactorial diseases [51,52].”
BackgroundRecent Advances in the Genetics of Fractures in Osteoporosis
Koromani, F., Trajanoska, K., Rivadeneira, F., & Oei, L. (2019) · Frontiers in Endocrinology · doi:10.3389/fendo.2019.00337 · Cited by 43
“On the other hand, genome-wide genotyping is unbiased in the sense that by surveying the whole genome in a hypothesis-free manner, involvement of unexpected candidates or even loci with unknown function could be revealed (27).”
BackgroundRealizing the promise of population biobanks: a new model for translation
Murtagh, M. J., Demir, İ., Harris, J. R., & Burton, P. R. (2011) · Human Genetics · doi:10.1007/s00439-011-1036-3 · Cited by 42
“This new challenge demands a comprehensive exploration of gene networks, of much weaker main eVects (Manolio et al. 2008; Merikangas and Risch 2003; Wellcome Trust Case Control Consortium 2007) and of interactions between genetic, environmental, behavioural and social factors (Manolio et al. 2006).”
BackgroundAn Exponential Combination Procedure for Set-Based Association Tests in Sequencing Studies
Chen, L., Hsu, L., Gamazon, E. R., Cox, N. J., & Nicolae, D. L. (2012) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2012.09.017 · Cited by 42
Visualization of Shared Genomic Regions and Meiotic Recombination in High-Density SNP Data
Roberson, E. D. O., & Pevsner, J. (2009) · PLoS ONE · doi:10.1371/journal.pone.0006711 · Cited by 42
“SNP data are also useful for the analysis of homozygosity and copy number alterations in individuals, and inheritance patterns in pedigrees [9].”
Harrill, A. H., & McAllister, K. A. (2017) · Environmental Health Perspectives · doi:10.1289/ehp1274 · Cited by 42
“Extensive research in recent years, including the Human Genome and HapMap projects, has led to a wealth of information on genetic polymorphisms in human populations (Manolio et al. 2008).”
BackgroundGenome-wide association studies of maximum number of drinks
Pan, Y., Luο, X., Liu, X., Wu, L.-Y., Zhang, Q., Wang, L., Wang, W., Zuo, L., & Wang, K.-S. (2013) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2013.07.013 · Cited by 41
“This approach has provided new insights into pathophysiology and suggested previously unsuspected etiologic pathways for common diseases that could be of use in identifying new therapeutic targets and in developing targeted interventions based on genetically defined risk (Manolio et al., 2008).”
Combined analysis of exon splicing and genome wide polymorphism data predict schizophrenia risk loci
Oldmeadow, C. J., Mossman, D., Evans, T., Holliday, E. G., Tooney, P. A., Cairns, M. J., Wu, J. Q., Carr, V. J., Attia, J., & Scott, R. J. (2014) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2014.01.011 · Cited by 44
“, 2011) supporting the notion that the combination of numerous variants, each of small effect size, contribute to disease etiology (Manolio et al., 2008).”
BackgroundInsights into the Genetic Architecture of Diabetic Nephropathy
Palmer, N. D., & Freedman, B. I. (2012) · Current Diabetes Reports · doi:10.1007/s11892-012-0279-2 · Cited by 41
Genetic Epidemiology of Type 2 Diabetes and Cardiovascular Diseases in Africa
Ayele, F. T., Adeyemo, A., & Rotimi, C. N. (2013) · Progress in Cardiovascular Diseases · doi:10.1016/j.pcad.2013.09.013 · Cited by 40
Winkler, C. A., Nelson, G. W., Oleksyk, T. K., Nava, M. B., & Kopp, J. B. (2010) · Seminars in Nephrology · doi:10.1016/j.semnephrol.2010.01.003 · Cited by 40
Quantifying the Underestimation of Relative Risks from Genome-Wide Association Studies
Spencer, C. C. A., Hechter, E., Vukcevic, D., & Donnelly, P. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1001337 · Cited by 39
“Genome-wide association studies (GWAS) have been extremely successful across many diseases in identifying loci harbouring genetic variants that affect disease susceptibility. Virtually all associated variants identified from GWAS to date have relatively small effects: each additional copy of the risk allele typically…”
Background
Metadata
- Authors
- Manolio, T. A., Brooks, L. D., & Collins, F. S.
- Affiliations
- National Human Genome Research Institute (US)
- Venue
- Journal of Clinical Investigation
- Published
- 2008-05-01
- Volume
- 118
- Issue
- 5
- Pages
- 1590-1605
- ISSN
- 0021-9738 (ISSN-L)
- PMC
- PMC2336881
- OpenAlex
- W2101983393
- Cited by
- 889
- References
- 136
- Citations by year
- 2026: 6 · 2025: 13 · 2024: 10 · 2023: 10 · 2022: 14 · 2021: 16 · 2020: 14 · 2019: 22 · 2018: 23 · 2017: 30 · 2016: 30 · 2015: 34 · 2014: 55 · 2013: 53 · 2012: 88
- FWCI
- 14.78
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- public-domain
- Locations
- Journal of Clinical Investigation (publishedVersion, public-domain)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- 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 › Forensic and Genetic Research
- Keywords
- HapMap, human genetic variation, genome-wide association study, disease pathophysiology, therapeutic target, genetic risk
- MeSH terms
- Chromosome Mapping, Genetics, Population, Haplotypes, Humans, Genetic Variation, Linkage Disequilibrium, Genome, Human, Evolution, Molecular, Genetic Predisposition to Disease, Databases, Genetic
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