The DOI matches its Crossref record; 135 of the 136 references it cites were found in a registry or an index.
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“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]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Inference of Population Structure Using Multilocus Genotype Data
Pritchard, J. K., Stephens, M., & Donnelly, P. (2000) · Genetics · doi:10.1093/genetics/155.2.945 · Cited by 33,871
Initial sequencing and analysis of the human genome
International Human Genome Sequencing Consortium, Whitehead Institute for Biomedical Research, C. F. G. R., Lander, E. S., Linton, L. M., Birren, B., Nusbaum, C., Zody, M. C., Baldwin, J., Devon, K., Dewar, K., et al. (2001) · Nature · doi:10.1038/35057062 · Cited by 24,216
Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls
The Wellcome Trust Case Control Consortium, Management Committee, Burton, P. R., Clayton, D. G., Cardon, L. R., Craddock, N., Deloukas, P., Duncanson, A., Kwiatkowski, D. P., McCarthy, M. I., et al. (2007) · Nature · doi:10.1038/nature05911 · Cited by 9,442
The International HapMap Project
†The International HapMap Consortium, Genotyping centres: Baylor College of Medicine and ParAllele BioScience, Gibbs, R. A., Belmont, J. W., Hardenbol, P., Willis, T. D., Yu, F., Chinese HapMap Consortium, Yang, H., Ch'ang, L.-Y., et al. (2003) · Nature · doi:10.1038/nature02168 · Cited by 6,057
Self-citationThe Structure of Haplotype Blocks in the Human Genome
Gabriel, S. B., Schaffner, S. F., Nguyen, H., Moore, J. M., Roy, J., Blumenstiel, B., Higgins, J., DeFelice, M., Lochner, A., Faggart, M., et al. (2002) · Science · doi:10.1126/science.1069424 · Cited by 5,863
A haplotype map of the human genome
The International HapMap Consortium (2005) · Nature · doi:10.1038/nature04226 · Cited by 5,858
Population Structure and Eigenanalysis
Patterson, N., Price, A. L., & Reich, D. (2006) · PLoS Genetics · doi:10.1371/journal.pgen.0020190 · Cited by 5,280
Finishing the euchromatic sequence of the human genome
International Human Genome Sequencing Consortium (2004) · Nature · doi:10.1038/nature03001 · Cited by 4,971
Frayling, T. M., Timpson, N. J., Weedon, M. N., Zeggini, E., Freathy, R. M., Lindgren, C. M., Perry, J. R. B., Elliott, K. S., Lango, H., Rayner, N. W., et al. (2007) · Science · doi:10.1126/science.1141634 · Cited by 4,531
Complement factor H polymorphism in age-related macular degeneration
Klein, R. J., Zeiss, C., Chew, E. Y., Tsai, J.-Y., Sackler, R. S., Haynes, C., Henning, A. K., SanGiovanni, J. P., Mane, S. M., Mayne, S. T., et al. (2005) · Science · doi:10.1126/science.1109557 · Cited by 4,492
Flagged first, then by citations
1 of the 136 references couldn’t be matched to a known paper.
Research works printed but not linked: 3
- NCBI Reference Assembly. Single nucleotide polymorphism. http://www.ncbi.nlm.nih.gov/projects/SNP/ .
- 10.1126/science.1105436 · DOI
- Colca, 2007, Curr. Opin. Investig. Drugs., 8, 707
Cited by
Sorted by citations
Items 301–400 of 888
Informatics and clinical genome sequencing: opening the black box
Moorthie, S. A., Hall, A., & Wright, C. F. (2012) · Genetics in Medicine · doi:10.1038/gim.2012.116 · Cited by 40
“Projects such as ENCODE, the Encyclopedia of DNA Elements, 16,17 and the related GENCODE, encyclope-dia of genes and gene variants, 18,19 aim to identify all functional elements in the human genome sequence and will ultimately be used to annotate all evidence-based gene features in the entire human…”
BackgroundHuman longevity and common variations in the LMNA gene: a meta‐analysis
Conneely, K. N., Capell, B. C., Erdos, M. R., Sebastiani, P., Solovieff, N., Swift, A. J., Baldwin, C. T., Budagov, T., Barzilai, N., Atzmon, G., et al. (2012) · Aging Cell · doi:10.1111/j.1474-9726.2012.00808.x · Cited by 40
“With the completion of the International HapMap Project, power to detect common variants for common and complex diseases has increased (Manolio et al., 2008), and the search for genetic contributors to human aging and lifespan has been accelerated.”
BackgroundSelf-citationRecent Advances in Understanding the Role of Nutrition in Human Genome Evolution
Ye, K., & Gu, Z. (2011) · Advances in Nutrition · doi:10.3945/an.111.001024 · Cited by 40
Utility-preserving transaction data anonymization with low information loss
Loukides, G., & Gkoulalas-Divanis, A. (2012) · Expert Systems with Applications · doi:10.1016/j.eswa.2012.02.179 · Cited by 39
“Data utility in electronic medical record publishing We compared the effectiveness of UAR to that of COAT in a real-world scenario, which involves publishing VNEC in a way that allows genetic studies, related to 18 diseases [46], as well as accurate biomedical query answering, to be performed.”
MethodStatistical significance in genetic association studies
Qu, H., Tien, M. Z., & Polychronakos, C. (2010) · Clinical and investigative medicine · doi:10.25011/cim.v33i5.14351 · Cited by 39
Update in Endocrine Autoimmunity
Anderson, M. S. (2008) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2008-1251 · Cited by 38
“the haplotype map), affordable technologies for high-density/high-throughput genotyping, and adequately powered sample sizes of cases and controls (32, 33).”
BackgroundFast Association Tests for Genes with FAST
Chanda, P., Huang, H., Arking, D. E., & Bader, J. S. (2013) · PLoS ONE · doi:10.1371/journal.pone.0068585 · Cited by 38
“While single-SNP GWAS have been quite successful in identifying many genetic associations for human diseases [16,17], they can miss true associations arising from multiple independent associations within a single gene.”
BackgroundAre transgenic mice the ‘alkahest’ to understanding myocardial hypertrophy and failure?
Cook, S. A., Clerk, A., & Sugden, P. H. (2008) · Journal of Molecular and Cellular Cardiology · doi:10.1016/j.yjmcc.2008.11.005 · Cited by 38
Epistasis and immunity: the role of genetic interactions in autoimmune diseases
Rose, A. M., & Bell, L. C. K. (2012) · Immunology · doi:10.1111/j.1365-2567.2012.03623.x · Cited by 40
Systems Genetic Analysis in GeneNetwork.org
Parker, C. C., Dickson, P. E., Philip, V. M., Thomas, M., & Chesler, E. J. (2017) · Current Protocols in Neuroscience · doi:10.1002/cpns.23 · Cited by 37
“…decade, genome-wide association studies (GWAS) have emerged as a powerful tool to identify alleles and molecular pathways that influence susceptibility to psychiatric disorders (Manolio et al., 2008; Manolio et al., 2013; Schizophrenia Working Group of the Psychiatric Genomics Consortium, 2014).”
Enabling precision medicine via standard communication of HTS provenance, analysis, and results
Alterovitz, G., Dean, D. A., Goble, C., Crusoe, M. R., Soiland‐Reyes, S., Bell, A. L., Hayes, A., Suresh, A., Purkayastha, A., King, C. H., et al. (2018) · PLoS Biology · doi:10.1371/journal.pbio.3000099 · Cited by 34
“A BCO is designed to satisfy FAIR Data Principles (findable, accessible, interoperable and reusable)[12], ensuring that data and pipelines are available for evaluation, validation, and verification[11,13,14].”
MethodComputational analysis of functional single nucleotide polymorphisms associated with SLC26A4 gene
Hasnain, M. J. U., Shoaib, M., Qadri, S., Afzal, B., Anwar, T., Abbas, S. H., Sarwar, A., Malik, H. M. T., & Pervez, M. T. (2020) · PLoS ONE · doi:10.1371/journal.pone.0225368 · Cited by 37
“In last few years, genome-wide association studies (GWAS) tested a huge number of SNPs in thousands of people and highlighted reproducibly distinguished numerous relationships among the common genetic variants and diseases with their traits [1].”
BackgroundA two-SNP IL-6 promoter haplotype is associated with increased lung cancer risk
Chen, J., Liu, R., Yang, L., Zhao, J., Zhao, X., Lu, D., Yi, N., Han, B., Chen, X., Zhang, K., et al. (2012) · Journal of Cancer Research and Clinical Oncology · doi:10.1007/s00432-012-1314-z · Cited by 37
“Given the fact that association studies based on haplotypes of multiple markers instead of genotypes at single markers significantly improve the power of mapping and characterizing disease-causing genes (Akey et al. 2001; Johnson et al. 2001; Manolio et al. 2008), we sought to assess whether various haplotypes consist…”
BackgroundResultInfluentialKnowledge gaining by human genetic studies on tuberculosis susceptibility
Qu, H., Fisher‐Hoch, S. P., & McCormick, J. B. (2010) · Journal of Human Genetics · doi:10.1038/jhg.2010.164 · Cited by 35
“Because of the wide-spread of DNA polymorphisms, different individuals may have different susceptibility to a common disease”
Cardiovascular Genomics, Personalized Medicine, and the National Heart, Lung, and Blood Institute
O’Donnell, C. J., & Nabel, E. G. (2008) · Circulation Cardiovascular Genetics · doi:10.1161/circgenetics.108.813337 · Cited by 39
New findings from genetic association studies of schizophrenia
Williams, H. J., Owen, M. J., & O’Donovan, M. C. (2009) · Journal of Human Genetics · doi:10.1038/jhg.2008.7 · Cited by 35
Predicting Response to Short-Acting Bronchodilator Medication Using Bayesian Networks
Himes, B. E., Wu, A. C., Duan, Q., Klanderman, B. J., Litonjua, A. A., Tantisira, K. G., Ramoni, M. F., & Weiss, S. T. (2009) · Pharmacogenomics · doi:10.2217/pgs.09.93 · Cited by 37
Genomics for Disease Treatment and Prevention
Bloss, C. S., Jeste, D. V., & Schork, N. J. (2010) · Psychiatric Clinics of North America · doi:10.1016/j.psc.2010.11.005 · Cited by 38
“These differences are known as single nucleotide polymorphisms or “SNPs,” and they occur, on average, about one site per 300 bases [22].”
BackgroundCoassin, S., Kloss‐Brandstätter, A., & Kronenberg, F. (2009) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2009.10.026 · Cited by 35
Mohammed, J. P., Fusakio, M. E., Rainbow, D. B., Moule, C. L., Fraser, H. I., Clark, J., Todd, J. A., Peterson, L. B., Savage, P. B., Wills-Karp, M. A., et al. (2011) · The Journal of Immunology · doi:10.4049/jimmunol.1003525 · Cited by 35
Zhang, L., Prather, D. M., Eng, J. V., Crawford, S. B., Kariuki, S., ter Kuile, F. O., Terlouw, D. J., Nahlen, B. L., Lal, A. A., Slutsker, L., et al. (2010) · Malaria Journal · doi:10.1186/1475-2875-9-87 · Cited by 35
“Regulation of the protein products, rather than differences in the structure or function of the protein may be most important for disease risk [ 38 ].”
BackgroundZou, S., Teixeira, A. M., Kostadima, M. A., Astle, W. J., Radhakrishnan, A., Simon, L. M., Truman, L. A., Fang, J. S., Hwa, J., Zhang, P., et al. (2017) · PLoS ONE · doi:10.1371/journal.pone.0178095 · Cited by 35
The Genomic Architecture of Sporadic Heart Failure
Dorn, G. W. (2011) · Circulation Research · doi:10.1161/circresaha.110.229260 · Cited by 36
Effect of IL28B genotype on hepatitis B and C virus infection
Stättermayer, A. F., & Ferenci, P. (2015) · Current Opinion in Virology · doi:10.1016/j.coviro.2015.07.011 · Cited by 34
Cao, S., Wang, S.-G., Ma, H., Tang, S., Sun, C., Dai, J., Wang, C., Shu, Y., Xu, L., Yin, R. H., et al. (2015) · The Pharmacogenomics Journal · doi:10.1038/tpj.2015.22 · Cited by 34
Edelstein, L. C., Luna, E. J., Gibson, I. B., Bray, M. S., Jin, Y., Kondkar, A. A., Nagalla, S., Hadjout-Rabi, N., Smith, T. C., Covarrubias, D., et al. (2012) · Circulation · doi:10.1161/circulationaha.112.091462 · Cited by 34
From GWAS to the clinic: risk factors for intracranial aneurysms
Ruigrok, Y. M., & Rinkel, G. J. E. (2010) · Genome Medicine · doi:10.1186/gm182 · Cited by 32
“However, the variants identified so far by GWAS in relation to complex disease explain only a small proportion of the genetic risk for those conditions [16,17].”
Association studies in outbred mice in a new era of full-genome sequencing
Yalcin, B., & Flint, J. (2012) · Mammalian Genome · doi:10.1007/s00335-012-9409-z · Cited by 33
The Emergent Phenomenon of Aspirin Resistance: Insights from Genetic Association Studies
Ferreira, M., Freitas-Silva, M., Assis, J., Pinto, R., Nunes, J. P. L., & Medeiros, R. (2020) · Pharmacogenomics · doi:10.2217/pgs-2019-0133 · Cited by 36
Exploring genetic susceptibility to cancer in diverse populations
Haiman, C. A., & Stram, D. O. (2010) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2010.02.007 · Cited by 36
“Over the past 4-5 years, genome-wide association studies (GWAS) have emerged as a powerful approach to identify risk alleles for common diseases [4-6].”
BackgroundKim, D., Park, S., Kim, M., Ji, Y. I., Kang, M. Y., Jung, E. H., Ko, E., Kim, Y., Kim, S. H., Shim, Y. M., et al. (2011) · Cancer · doi:10.1002/cncr.25930 · Cited by 34
The A's, G's, C's, and T's of health disparities
Ramos, E., & Rotimi, C. N. (2009) · BMC Medical Genomics · doi:10.1186/1755-8794-2-29 · Cited by 33
“, genomewide association studies – GWAS) is rapidly shedding light on subsets of genetic variants that are associated with an increase risk of particular conditions[13,14].”
BackgroundDo Alterations in Mitochondrial DNA Play a Role in Breast Carcinogenesis?
Rohan, T. E., Wong, L.-J. C., Wang, T., Haines, J. L., & Kabat, G. C. (2010) · Journal of Oncology · doi:10.1155/2010/604304 · Cited by 33
“Genome-wide association studies (GWAS) represent one approach to the identification of such genes, and their conduct has been facilitated by the development of the HapMap, a genome-wide database of patterns of human genetic variation [99, 117].”
BackgroundGenome‐wide association studies (GWAS): impact on elucidating the aetiology of diabetes
Hakonarson, H. H., & Grant, S. F. A. (2011) · Diabetes/Metabolism Research and Reviews · doi:10.1002/dmrr.1221 · Cited by 34
Genetic Polymorphisms Affecting Drug Metabolism
Daly, A. K. (2012) · Advances in pharmacology · doi:10.1016/b978-0-12-398339-8.00004-5 · Cited by 33
Elliott, K. S., Zeggini, E., McCarthy, M. I., Guðmundsson, J., Sulem, P., Stacey, S., Thorlacius, S., Amundadottir, L. T., Grönberg, H., Xu, J., et al. (2010) · PLoS ONE · doi:10.1371/journal.pone.0010858 · Cited by 33
“Recently, with the advent of genome-wide association studies (GWAS), a large number of genetic variants have been identified that confer susceptibility to T2D or specific types of cancer[8].”
Backgroundvan Waas, M., Neggers, S. J. C. M. M., Uitterlinden, A. G., Blijdorp, K., van der Geest, I. M. M., Pieters, R., & van den Heuvel‐Eibrink, M. M. (2012) · European Journal of Cancer · doi:10.1016/j.ejca.2012.09.007 · Cited by 33
“Large-scale genome-wide association studies (GWAS), in which hundreds of thousands of common genetic variants are genotyped, identified genes associated with common diseases and traits.(8,9) The ATP2B1 gene appeared to be associated with systolic and diastolic blood pressure and hypertension.”
BackgroundIdentifying genetic relatives without compromising privacyPreprint
He, D., Furlotte, N. A., Hormozdiari, F., Joo, J. W. J., Wadia, A., Ostrovsky, R., Sahai, A., & Eskin, E. (2014) · Genome Research · doi:10.1101/gr.153346.112 · Cited by 32
“The development of these technologies was driven by the goal to perform genome-wide association studies (GWASs), where genetic variation information is collected from tens of thousands of individuals and correlated with disease status (Risch and Merikangas 1996; Manolio et al. 2008; Hardy and Singleton 2009).”
BackgroundMethodClimer, S., Yang, W., Fuentes, L. D. L., Dávila‐Román, V. G., & Gu, C. C. (2014) · Genetic Epidemiology · doi:10.1002/gepi.21833 · Cited by 32
“Introduction Genome-wide association (GWAS) studies have successfully identified numerous single nucleotide polymorphisms (SNPs) associated with human diseases [Manolio et al., 2008].”
Tavares, V., Pinto, R., Assis, J., Pereira, D., & Medeiros, R. (2019) · Biochimica et Biophysica Acta (BBA) - Reviews on Cancer · doi:10.1016/j.bbcan.2019.188331 · Cited by 32
Copy number variants on the X chromosome in women with primary ovarian insufficiency
Knauff, E. A. H., Blauw, H. M., Pearson, P. L., Kok, K., Wijmenga, C., Veldink, J. H., van den Berg, L. H., Bouchard, P., Fauser, B. C. J. M., & Franke, L. (2011) · Fertility and Sterility · doi:10.1016/j.fertnstert.2011.01.018 · Cited by 32
A Genome-Wide Association Study of Amygdala Activation in Youths With and Without Bipolar Disorder
Liu, X., Akula, N., Skup, M., Brotman, M. A., Leibenluft, E., & McMahon, F. J. (2010) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2009.10.006 · Cited by 32
Evaluation of genetic tests for susceptibility to common complex diseases: why, when and how?
Wright, C. F., & Kroese, M. (2009) · Human Genetics · doi:10.1007/s00439-009-0767-x · Cited by 32
“At the date of writing, a catalogue of the approximately 350 published GWAS contained around 1,600 single nucleotide polymorphisms (SNPs) associated with over 80 diseases and traits (HindorV et al. 2009a, b; Manolio et al. 2008).”
Comprehension and Data-Sharing Behavior of Direct-To-Consumer Genetic Test Customers
McGrath, S., Coleman, J. D., Najjar, L., Fruhling, A., & Bastola, D. R. (2016) · Public Health Genomics · doi:10.1159/000444477 · Cited by 31
Kitagaki, J., Miyauchi, S., Asano, Y., Imai, A., Kawai, S., Michikami, I., Yamashita, M., Yamada, S., Kitamura, M., & Murakami, S. (2016) · PLoS ONE · doi:10.1371/journal.pone.0160765 · Cited by 31
“Such genome-wide association studies (GWAS) are comprehensive and hypothesis-free [16], and have recently identified genes not previously known to be involved in the etiology of the target disease such as hypertension [17] and diabetes [16, 18].”
BackgroundGenetic variation in the hypothalamic pathways and its role on obesity
van Vliet‐Ostaptchouk, J. V., Hofker, M. H., van der Schouw, Y. T., Wijmenga, C., & Onland‐Moret, N. C. (2009) · Obesity Reviews · doi:10.1111/j.1467-789x.2009.00597.x · Cited by 32
“It is also important to remember that current-generation genome-wide association genotyping platforms are based on HapMap data, which is based on the ‘common disease, common variant’ hypothesis, and thus target SNPs with minor allele frequency 5% (141).”
BackgroundMethodSiblings With Ischemic Stroke Study
Meschia, J. F., Nalls, M. A., Matarín, M., Brott, T. G., Brown, R. D., Hardy, J., D, B. M. K. M., Rich, S. S., Singleton, A., Hernandez, D. G., et al. (2011) · Stroke · doi:10.1161/strokeaha.111.620484 · Cited by 32
“[13] It has since become less clear that the hypothesis holds for ischemic stroke.”
Liu, G., Zhu, H., Lagou, V., Gutin, B., Barbeau, P., Treiber, F. A., Dong, Y., & Snieder, H. (2010) · The Journal of Pediatrics · doi:10.1016/j.jpeds.2009.10.037 · Cited by 30
Systems-based candidate genes for human response to influenza infection
Zhang, L., Katz, J. M., GWINN, M. L., Dowling, N. F., & Khoury, M. J. (2009) · Infection Genetics and Evolution · doi:10.1016/j.meegid.2009.07.006 · Cited by 31
“studies need very large sample sizes and their findings require further replication (Manolio et al., 2008).”
Association of μ-opioid receptor gene (OPRM1) haplotypes with postoperative nausea and vomiting
Sugino, S., Hayase, T., Higuchi, M., Saito, K., Moriya, H., Kumeta, Y., Kurosawa, N., Namiki, A., & Janicki, P. K. (2014) · Experimental Brain Research · doi:10.1007/s00221-014-3987-9 · Cited by 28
“…only genetic variation but also environmental factors, such as female-specific epigenetic modifications resulting from hormones such as estrogen (Mccarthy et al. 2009). although such epigenetic modifications would reduce gene expression in specific brain regions, its involvement in PONV remains…”
BackgroundWang, M., Jiang, X., Wu, W., & Zhang, D. (2013) · PLoS ONE · doi:10.1371/journal.pone.0060472 · Cited by 29
“However, in the setting of an agnostic approach, most associations derived from genome-wide association studies are also usually presented as perallele risks (the codominant model) [54] because of statistical power considerations.”
BackgroundFast and Accurate Construction of Confidence Intervals for Heritability
Schweiger, R., Kaufman, S., Laaksonen, R., Kleber, M. E., März, W., Eskin, E., Rosset, S., & Halperin, E. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2016.04.016 · Cited by 30
Dozmorov, M. G. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx414 · Cited by 29
Complex Diseases, Complex Genes
Kraft, P. L., & Raychaudhuri, S. (2009) · Epidemiology · doi:10.1097/ede.0b013e3181a93b98 · Cited by 30
Lötsch, J., & Ultsch, A. (2013) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2013.07.010 · Cited by 29
“Especially in complex traits emerging from multifactorial mechanisms, single genetic variants often produce only small effect sizes [2].”
BackgroundHäge, A., Banaschewski, T., Buitelaar, J. K., Dijkhuizen, R. M., Franke, B., Lythgoe, D. J., Mechler, K., Williams, S., & Dittmann, R. (2016) · Trials · doi:10.1186/s13063-016-1266-8 · Cited by 32
“Compulsivity-related disorders such as OCD and ASD are assumed to be highly heritable but genetically complex, with multiple genetic variants of small effect contributing to disease in most patients [33].”
Lu, Z., Lin, V., May, A., Che, B., Xu, X., Shaw, D. H., Su, F., Wang, Z., Du, H., & Shaw, P. X. (2019) · PLoS ONE · doi:10.1371/journal.pone.0216808 · Cited by 29
Yan, Q., Tiwari, H. K., Yi, N., Gao, G., Zhang, K., Lin, W., Lou, X., Cui, X., & Liu, N. (2015) · Human Heredity · doi:10.1159/000375409 · Cited by 28
Genetics of Diabetic Nephropathy: Are There Clues to the Understanding of Common Kidney Diseases?
Conway, B. R., & Maxwell, A. P. (2009) · Nephron Clinical Practice · doi:10.1159/000224787 · Cited by 28
“Given the low prevalence of type 1 diabetic nephropathy as compared with type 2 diabetes, cohorts of this magnitude will be very difficult to assemble and replication studies may need to include patients with nephropathy due to type 2 diabetes. Secondly the extent of heritability of diabetic nephropathy is less than t…”
BackgroundA nonsynonymous variant of IL1A is associated with endometriosis in Japanese population
Hata, Y., Nakaoka, H., Yoshihara, K., Adachi, S., Haino, K., Yamaguchi, M., Nishikawa, N., Kashima, K., Yahata, T., Tajima, A., et al. (2013) · Journal of Human Genetics · doi:10.1038/jhg.2013.32 · Cited by 28
A practical guide to interpretation and clinical application of personal genomic screening
Edelman, E. A., & Eng, C. (2009) · BMJ · doi:10.1136/bmj.b4253 · Cited by 28
“Genome-wide association studies have identified SNPs associated with many common diseases such as type 1 and type 2 diabetes, cardiovascular disease, prostate cancer, breast cancer, colon cancer, asthma, Crohn’s disease, and rheumatoid arthritis.”
BackgroundFenstad, M. H., Johnson, M. P., Roten, L. T., Aas, P. A., Forsmo, S., Klepper, K., East, C. E., Abraham, L. J., Blangero, J., Brennecke, S. P., et al. (2010) · PLoS ONE · doi:10.1371/journal.pone.0012993 · Cited by 28
“This approach has provided new insight [81], but a notable knowledge ‘‘gap’’ of 90– 95% of the genetic liability to these diseases is left unaccounted for [80].”
BackgroundRole of MicroRNA in Pancreatic β-Cells
WALKER, M. D. (2008) · Diabetes · doi:10.2337/db08-0934 · Cited by 27
Evaluating the transferability of Hapmap SNPs to a Singapore Chinese population
Andiappan, A. K., Anantharaman, R., Parate, P. N., Wang, D. Y., & Chew, F. T. (2010) · BMC Genetics · doi:10.1186/1471-2156-11-36 · Cited by 29
“The Hapmap Consortium developed a human haplotype map by genotyping 270 samples from four populations with diverse geographic ancestry.”
BackgroundIwaya, C., Kitajima, H., Yamamoto, K., Maeda, Y., Sonoda, N., Shibata, H., & Inoguchi, T. (2018) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2017.12.104 · Cited by 26
Johnston, H. R., Keats, B. J. B., & Sherman, S. L. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-812537-3.00012-3 · Cited by 28
Genetic Scoring Analysis: a way forward in Genome Wide Association Studies?
Amin, N., van Duijn, C. M., & Janssens, A. C. J. W. (2009) · European Journal of Epidemiology · doi:10.1007/s10654-009-9387-y · Cited by 27
“Facilitated by technological developments in molecular biology, genetic epidemiologists have so far discovered many variants associated with several common diseases and traits such as Type 2 Diabetes, age-related macular degeneration and Crohn’s disease [1].”
BackgroundTesting Gene–Gene Interactions in Genome Wide Association Studies
Hu, J. K., Wang, X., & Wang, P. (2014) · Genetic Epidemiology · doi:10.1002/gepi.21786 · Cited by 27
Ivansson, E. L., Juko‐Pecirep, I., Erlich, H. A., & Gyllensten, U. B. (2011) · Genes and Immunity · doi:10.1038/gene.2011.40 · Cited by 28
New routes for transgenesis of the mouse
Belizário, J. E., Akamine, P. S., Wolf, P., Strauss, B. E., & Xavier‐Neto, J. (2012) · Journal of Applied Genetics · doi:10.1007/s13353-012-0096-y · Cited by 26
Gene- or region-based association study via kernel principal component analysis
Gao, Q., He, Y., Yuan, Z., Zhao, J., Zhang, B., & Xue, F. (2011) · BMC Genetics · doi:10.1186/1471-2156-12-75 · Cited by 26
“Specifically, we set five low levels of relative risks (1.1-1.5) because the great majority of the identified risk marker alleles conferred very small relative risks [46].”
BackgroundInfluentialCardiovascular diseases and genome-wide association studies
Ndiaye, N. C., Azimi–Nezhad, M., Shamieh, S. E., Stathopoulou, M. G., & Visvikis‐Siest, S. (2011) · Clinica Chimica Acta · doi:10.1016/j.cca.2011.05.035 · Cited by 26
Cao, S., Wang, C., Ma, H., Yin, R. H., Zhu, M., Shen, W., Dai, J., Shu, Y., Xu, L., Hu, Z., et al. (2015) · Scientific Reports · doi:10.1038/srep11556 · Cited by 26
Genome-wide association database developed in the Japanese Integrated Database Project
Koike, A., Nishida, N., Inoue, I., Tsuji, S., & Tokunaga, K. (2009) · Journal of Human Genetics · doi:10.1038/jhg.2009.68 · Cited by 26
Laboratory Mouse Models for the Human Genome-Wide Associations
Kitsios, G. D., Tangri, N., Castaldi, P. J., & Ioannidis, J. P. A. (2010) · PLoS ONE · doi:10.1371/journal.pone.0013782 · Cited by 26
“Genome-wide association studies (GWAS) have led to the discovery of hundreds of associations between genetic loci and complex human diseases or traits [1].”
BackgroundYatagai, Y., Sakamoto, T., Yamada, H., Masuko, H., Kaneko, Y., Iijima, H., Naito, T., Noguchi, E., Hirota, T., Tamari, M., et al. (2014) · Clinical & Experimental Allergy · doi:10.1111/cea.12415 · Cited by 26
Meng, X., Kou, C., Shi, J., Yu, Y., & Huang, Y. (2011) · Journal of Affective Disorders · doi:10.1016/j.jad.2011.01.005 · Cited by 27
“While the etiology of psychiatric disorders has long been recognized to include a number of interacting biological, psychological and social environmental elements, there is an emerging emphasis on social environmental and genetic factors (Engel, 1977; Manolio et al., 2008).”
BackgroundFinding a Place for Genomics in Health Disparities Research
Fullerton, S. M., Knerr, S. A., & Burke, W. (2012) · Public Health Genomics · doi:10.1159/000334717 · Cited by 26
Church, J. A., Grigorenko, E. L., & Fletcher, J. M. (2021) · Reading Research Quarterly · doi:10.1002/rrq.439 · Cited by 28
Novel mutations of ABCC6 gene in Japanese patients with Angioid streaks
Sato, N., Nakayama, T., Mizutani, Y., & Yuzawa, M. (2009) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2009.01.117 · Cited by 25
“Haplotype-based case-control studies have recently been devised in order to identify susceptibility genotypes for multifactorial genetic disorders [9].”
MethodThe emerging role for rat models in gene discovery
Dwinell, M. R., Lazar, J., & Geurts, A. M. (2011) · Mammalian Genome · doi:10.1007/s00335-011-9346-2 · Cited by 25
“testinal, pulmonary, and other diseases (Hindorff et al. 2011; Manolio et al. 2008).”
BackgroundChild and adolescent psychiatric genetics
Hebebrand, J., Scherag, A., SCHIMMELMANN, B. G., & Hinney, A. (2010) · European Child & Adolescent Psychiatry · doi:10.1007/s00787-010-0091-y · Cited by 25
“Furthermore, the construction of a haplotype map of the human genome has greatly facilitated comprehensive genetic association studies of human disease [48, 55, 103].”
BackgroundYoo, Y. J., Bull, S. B., Paterson, A. D., Waggott, D. M., & Sun, L. (2009) · Genetic Epidemiology · doi:10.1002/gepi.20438 · Cited by 25
“The Wellcome Trust Case Control Consortium (WTCCC), 2007; Manolio et al., 2008; Rodriguez-Murillo and Greenberg, 2008; Tenesa et al., 2008].”
InfluentialKenny, E. E., Gusev, A., Riegel, K., Lütjohann, D., Lowe, J. K., Salit, J., Maller, J., Stoffel, M., Daly, M. J., Altshuler, D., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0907336106 · Cited by 25
“Study participants (2,906) were successfully genotyped on the Affymetrix 500-K platform; data were generated at Affymetrix.”
MethodHu, Y., Zhong, D., Pang, F., Ning, Q., Zhang, Y. Y., Li, G., Wu, J. Z., & Mo, Z. (2013) · Genetics and Molecular Research · doi:10.4238/2013.april.25.4 · Cited by 25
“Genome-wide association (GWA) studies, characterized by high-throughput results, are useful for suggesting risk candidate genes associated with common diseases (Manolio et al., 2008).”
BackgroundLi, Q., Wacholder, S., Hunter, D. J., Hoover, R. N., Chanock, S. J., Thomas, G. D., & Yu, K. F. (2009) · Genetic Epidemiology · doi:10.1002/gepi.20396 · Cited by 25
“Genome-wide association studies (GWAS) have emerged as an effective approach to identify common polymorphisms underlying complex traits [Hunter et al., 2007; The Wellcome Trust Case Control Consortium, 2007; Yeager et al., 2007; Manolio et al., 2008; Pearson and Manolio, 2008].”
BackgroundChanock, S. J. (2009) · Nature Genetics · doi:10.1038/ng0709-765 · Cited by 25
Assessment of Improved Prediction Beyond Traditional Risk Factors
Janssens, A. C. J. W., & Khoury, M. J. (2010) · Circulation Cardiovascular Genetics · doi:10.1161/circgenetics.110.938092 · Cited by 25
Machine learning empowered next generation DNA sequencing: perspective and prospectus
Mittal, S., Jena, M. K., & Pathak, B. (2024) · Chemical Science · doi:10.1039/d4sc01714e · Cited by 24
Εvangelou, Ε., Fellay, J., Colombo, S. F., Martínez‐Picado, J., Obel, N., Goldstein, D. B., Telenti, A., & Ioannidis, J. P. A. (2011) · American Journal of Epidemiology · doi:10.1093/aje/kwr024 · Cited by 23
“Genome-wide association (GWA) studies have discovered many gene-phenotype associations with strong statistical support (1, 2).”
BackgroundSystems genetics in “-omics” era: current and future development
Li, H. (2012) · Theory in Biosciences · doi:10.1007/s12064-012-0168-x · Cited by 24
Genome-wide association studies in bladder cancer: first results and potential relevance
Kiemeney, L. A. L. M., Grotenhuis, A. J., Vermeulen, S. H. H. M., & Wu, X. (2009) · Current Opinion in Urology · doi:10.1097/mou.0b013e32832eb336 · Cited by 23
Human genome–guided identification of memory-modulating drugs
Papassotiropoulos, A., Gerhards, C., Heck, A., Ackermann, S., Aerni, A., Schicktanz, N., Auschra, B., Demougin, P., Mumme, E., Elbert, T. R., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1314478110 · Cited by 26
“Genomewide association studies (GWASs) using single-marker statistics have been very successful in identifying trait-associated single-gene loci (9).”
BackgroundUtility-guided Clustering-based Transaction Data Anonymization
Gkoulalas-Divanis, A., & Loukides, G. (2012) · ORCA Online Research @Cardiff (Cardiff University) · Cited by 24
Management of High-Throughput DNA Sequencing Projects: Alpheus
Andrew F, N. A. (2008) · Journal of Computer Science & Systems Biology · doi:10.4172/jcsb.1000013 · Cited by 75
“Keywords: Alpheus; sequencing-by-synthesis; pyrosequencing”
Zhou, D., Zhou, T., Tang, S., Li, Q., Li, W., Gan, G., Li, M., & Qiu, C. (2024) · Frontiers in Endocrinology · doi:10.3389/fendo.2024.1354950 · Cited by 27
From genes to therapeutic targets for psychiatric disorders – what to expect?
Muglia, P. (2011) · Current Opinion in Pharmacology · doi:10.1016/j.coph.2011.08.003 · Cited by 23
Kazma, R., Babron, M., & Génin, E. (2010) · American Journal of Epidemiology · doi:10.1093/aje/kwq352 · Cited by 23
“gov/), providing the distribution patterns of single nucleotide polymorphisms across the whole genome, a plethora of genomewide association scans have been conducted, leading to the successful identification of over 100 association signals (2).”
A Genome-wide Pleiotropy Scan for Prostate Cancer Risk
Panagiotou, O. A., Travis, R. C., Campa, D., Berndt, S. I., Lindström, S., Kraft, P. L., Schumacher, F. R., Siddiq, A., Papatheodorou, S., Stanford, J. L., et al. (2014) · European Urology · doi:10.1016/j.eururo.2014.09.020 · Cited by 23
“This is not uncommon in GWAS, for which the majority of the SNPs discovered have relatively small effect sizes [32].”
Statistical issues in the analysis of DNA Copy Number Variations
Wineinger, N. E., Kennedy, R., Erickson, S. W., Wojczynski, M. K., Bruder, C. E. G., & Tiwari, H. K. (2008) · International Journal of Computational Biology and Drug Design · doi:10.1504/ijcbdd.2008.022208 · Cited by 24
“The majority of genetic association studies to date have been case-control studies for both GWAS (Manolio et al., 2008) and CNV (Lachman et al.”
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
