Genome-Wide Association Study
"Genome-Wide Association Study" is a descriptor in the National Library of Medicine's controlled vocabulary thesaurus,
MeSH (Medical Subject Headings). Descriptors are arranged in a hierarchical structure,
which enables searching at various levels of specificity.
An analysis comparing the allele frequencies of all available (or a whole GENOME representative set of) polymorphic markers in unrelated patients with a specific symptom or disease condition, and those of healthy controls to identify markers associated with a specific disease or condition.
| Descriptor ID |
D055106
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| MeSH Number(s) |
E05.318.416.249 E05.318.780.392 E05.393.385.500 E05.393.522.500 E05.393.760.640.500 N06.850.520.445.392 N06.850.520.470.500
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| Concept/Terms |
Genome-Wide Association Study- Genome-Wide Association Study
- Association Studies, Genome-Wide
- Association Study, Genome-Wide
- Genome-Wide Association Studies
- Studies, Genome-Wide Association
- Study, Genome-Wide Association
- Genome Wide Association Scan
- Genome Wide Association Studies
- GWA Study
- GWA Studies
- Studies, GWA
- Study, GWA
- Whole Genome Association Analysis
- Whole Genome Association Study
- Genome Wide Association Analysis
- Genome Wide Association Study
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Below are MeSH descriptors whose meaning is more general than "Genome-Wide Association Study".
Below are MeSH descriptors whose meaning is more specific than "Genome-Wide Association Study".
This graph shows the total number of publications written about "Genome-Wide Association Study" by people in this website by year, and whether "Genome-Wide Association Study" was a major or minor topic of these publications.
To see the data from this visualization as text, click here.
| Year | Major Topic | Minor Topic | Total |
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| 2005 | 1 | 0 | 1 | | 2008 | 1 | 2 | 3 | | 2009 | 14 | 12 | 26 | | 2010 | 15 | 29 | 44 | | 2011 | 11 | 27 | 38 | | 2012 | 16 | 32 | 48 | | 2013 | 18 | 28 | 46 | | 2014 | 31 | 40 | 71 | | 2015 | 15 | 35 | 50 | | 2016 | 26 | 38 | 64 | | 2017 | 21 | 40 | 61 | | 2018 | 17 | 51 | 68 | | 2019 | 25 | 68 | 93 | | 2020 | 15 | 38 | 53 | | 2021 | 32 | 47 | 79 | | 2022 | 41 | 43 | 84 | | 2023 | 17 | 44 | 61 | | 2024 | 27 | 30 | 57 | | 2025 | 14 | 56 | 70 | | 2026 | 16 | 27 | 43 |
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Below are the most recent publications written about "Genome-Wide Association Study" by people in Profiles.
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Sutton KJ, Gervis JE, Jatoi M, Hwang LD, Hendricks AE, Ghosh D, Westerman KE, Cole JB. Refining Genetic Instruments for Dietary Intake Mendelian Randomization Using Phenome-Wide Association Studies. Genet Epidemiol. 2026 Dec; 50(8):e70059.
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Gonzalez-Covarrubias V, Morales-Alfaro A, Bonilla-Jimenez O, Rodríguez-Dorantes M, Frías-Jimenez E, Soto-Perez-de-Celis E. Characterization of DPYD pharmacogenetic variation in Mexican patients with gastrointestinal malignancies. Cancer Chemother Pharmacol. 2026 Sep 17; 96(1).
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Schwaba T, Clapp Sullivan ML, Akingbuwa WA, Ilves K, Tanksley PT, Williams CM, Dragostinov Y, Mallard TT, Tubbs JD, Liao W, Ackerman LS, Fealy JCM, Hemani G, de la Fuente J, Smith GD, Gupta P, Stein MB, Gelernter J, Levey DF, Võsa U, Ausmees L, Realo A, Vaht M, Allik J, Esko T, Mõttus R, Vainik U, Jonsdottir GA, Thorleifsson G, Gunnarsson ÁF, Bjornsdottir G, Thorgeirsson TE, Stefansson H, Stefansson K, Cheesman R, Qin Q, Corfield EC, Ask H, Torvik FA, Ystrom E, Tesli M, Boomsma DI, de Geus EJC, Hottenga JJ, Melo DC, Snieder H, Hartman CA, Xia C, Campbell A, Luciano M, Deary IJ, Hill WD, Jang SK, Vrieze SI, Abecasis G, Lupton MK, Mitchell BL, Viher PV, Colodro-Conde L, Martin NG, Medland SE, Derks EM, Wormington B, Kaprio J, Silventoinen K, Palviainen T, Musial A, Rimfeld K, Plomin R, Malanchini M, Dick DM, Aliev F, Wesseldijk LW, Ullén F, Mosing MA, Kranzler HR, Nunez Y, Beck S, Polimanti R, Edwards T, Giannelis A, Willoughby EA, Lee JJ, McGue M, Terracciano A, Marongiu M, Fiorillo E, Cucca F, Sutin AR, van der Most PJ, Oldehinkel AJ, Kretschmer T, Shabalin AA, Docherty AR, Krueger RF, Freilich CD, Mishra BH, Lehtimäki T, Raitakari OT, Kähönen M, Saarinen A, Dobewall H, Keltikangas-Järvinen L, Berger K, Herrera-Rivero M, Streit F, Awasthi S, Witt SH, Tuhkanen J, Räikkönen K, Eriksson JG, Lahti J, Davies G, Redmond P, Taylor A, Corley J, Russ TC, Ciullo M, Nutile T, Ding J, Qian Y, Tanaka T, Ferrucci L, Zillich L, Sirignano L, Harden KP, Genç E, Gajewski PD, Getzmann S, Fraenz C, Schneider Peñate JE, Lis S, Hall ASM, Schmahl C, Herpertz SC, Abdellaoui A, Nivard MG, Tucker-Drob EM. Robust inference and correlates from genetic associations with personality. Nature. 2026 Oct; 658(8138):1226-1236.
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Peyrot WJ, Panagiotaropoulou G, Olde Loohuis LM, Adams MJ, Andreassen OA, Awasthi S, Forstner AJ, Ge T, McIntosh AM, Mitchell BL, Mullins N, O'Connell KS, Penninx BWJH, Posthuma D, Ripke S, Ruderfer DM, Uffelmann E, Vilhjalmsson BJ, Zhu Z, Smoller JW, Price AL. Distinguishing different psychiatric disorders using DDx-PRS. Nat Genet. 2026 Sep; 58(9):2371-2380.
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Sadeeq SA, Leaton LA, Kichula KM, Farias TDJ, Font-Porterias N, Pollock NR, Collora CE, Castelli EC, Gignoux CR, Norman PJ. PONG 2.0: allele imputation for the killer cell immunoglobulin-like receptors. Hum Mol Genet. 2026 Aug 10; 35(17).
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McKim A, Mancuso CA, Krishnan A. A module-based approach for post-omics, post-GWAS network-based gene classification. Bioinformatics. 2026 08 03; 42(8).
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Wang N, DiCorpo DA, Zhang Y, Kleinbrink E, Arnett DK, Barnard J, Blangero J, Bowden DW, Carson AP, Chen YI, Chung MK, Curran JE, Darbar D, Duggirala R, Ellinor PT, Fatkin D, Fornage M, Heard-Costa N, He J, Hou L, Kardia SLR, Kooperberg C, Loos RJF, McManus DD, Mitchell BD, Minster RL, North KE, Psaty BM, Raffield LM, Redline S, Rich SS, Roden D, Rotter JI, Shoemaker MB, Smith JD, Van Wagoner DR, Aguet F, Ardlie K, Bis JC, Brody JA, Cade BE, Clish CB, de Vries PS, Floyd JS, Freedman BI, Gabriel S, Gerzsten RE, Goodarzi MO, Gu C, Guo X, Gupta N, Heckbert SR, Hsu S, Hung YJ, Kalyani RR, Kelly TN, Kinney GL, Li C, Liu S, Liu Y, Lloyd-Jones DM, Manson JE, Mathias RA, Mercader JM, Morrison AC, Naseri T, Onengut S, Palmer ND, Peyser PA, Qi Q, Raghavan S, Reiner AP, Rooney MR, Sevilla-Gonzalez M, Sarnowski C, Smith JD, Smith JA, Spartano NL, Tahir U, Taylor KD, Tobias DK, Tracy RP, Viali S, Wang H, Wood AC, Yanek LR, Zhao W, Zheng Y, Dupuis J, Liu CT, Sladek R, Wessel J, Meigs JB, Manning AK. Colocalization of eQTLs With Type 2 Diabetes and Glycemic Traits Using Whole-Genome Sequences in Diverse Populations From the NHLBI Trans-Omics in Precision Medicine (TOPMed) Program. Diabetes. 2026 Aug 01; 75(8):1477-1491.
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Palmieri L, Dowle EJ, Nadachowska-Brzyska K, Schopf A, Dobart N, Stauffer C, Schuler H, Ragland GJ, Schebeck M. Genomic Predictors of Diapause Polymorphism in the Bark Beetle Ips typographus With Implications for Voltinism Potential and Outbreak Dynamics. Mol Ecol. 2026 08; 35(16):e70532.
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Bright U, Beck S, Levey DF, Deak JD, Gaziano JM, Stein MB, Gelernter J. The genetics of fibromyalgia and its relationships to psychiatric and medical traits. Nat Commun. 2026 Jul 28; 17(1).
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Irvin MR, Srinivasasainagendra V, Armstrong ND, Patki A, Broeckel U, Wang Z, Lange LA, Limdi NA, Huerta-Chagoya A, Kim J, Ng MCY, Mercader JM, Tiwari HK. Improving performance of polygenic risk scores for hypertension across two ancestry groups. PLoS One. 2026; 21(7):e0353311.
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