The DOI matches its Crossref record; 217 of the 218 references it cites were found in a registry or an index.
Five Years of GWAS Discovery
Open accessAbstract
The past five years have seen many scientific and biological discoveries made through the experimental design of genome-wide association studies (GWASs). These studies were aimed at detecting variants at genomic loci that are associated with complex traits in the population and, in particular, at detecting associations between common single-nucleotide polymorphisms (SNPs) and common diseases such as heart disease, diabetes, auto-immune diseases, and psychiatric disorders. We start by giving a number of quotes from scientists and journalists about perceived problems with GWASs. We will then briefly give the history of GWASs and focus on the discoveries made through this experimental design, what those discoveries tell us and do not tell us about the genetics and biology of complex traits, and what immediate utility has come out of these studies. Rather than giving an exhaustive review of all reported findings for all diseases and other complex traits, we focus on the results for auto-immune diseases and metabolic diseases. We return to the perceived failure or disappointment about GWASs in the concluding section.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
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?
In the citing paper
“This lack of positive results from GWAS is most likely due to low statistical power to detect small effects”
From Genome-Wide Association Studies of a Broad Spectrum of Antisocial Behavior (2017) · cites this paper as Visscher, Brown, McCarthy, & Yang, 2012
In the citing paper
“Many of the gene variants identified in GWAS are located in non-coding regions of DNA [92].”
From Polycystic Ovary Syndrome: An Evolutionary Adaptation to Lifestyle and the Environment (2022) · cites this paper as [92]
In the citing paper
“The genes or functional DNA elements through which these variants exert their effects are often unknown.”
From Polycystic Ovary Syndrome: An Evolutionary Adaptation to Lifestyle and the Environment (2022) · cites this paper as [92]
In the citing paper
“Indeed, the large-scale impact of large numbers of common variants may be a general feature of human complex traits 70–77”
From Genetic architectures of psychiatric disorders: the emerging picture and its implications (2012) · cites this paper as [71]
In the citing paper
“Hypothesized genetic architectures consisting entirely of rare variants are inconsistent with the data for AD, ASD, BIP, and SCZ (as well as for multiple other complex biomedical diseases). 70–77”
From Genetic architectures of psychiatric disorders: the emerging picture and its implications (2012) · cites this paper as [71]
In the citing paper
“Evidence from many complex traits show that the number of variants discovered is strongly correlated with experimental sample size.51”
From Defining Future Directions for Endometriosis Research: Workshop Report From the 2011 World Congress of Endometriosis in Montpellier, France (2013) · cites this paper as [51]
In the citing paper
“Above a given threshold for each disease, doubling study size doubles the number of genes or regions identified.”
From Defining Future Directions for Endometriosis Research: Workshop Report From the 2011 World Congress of Endometriosis in Montpellier, France (2013) · cites this paper as [51]
Citations
Cites
PLINK: a tool set for whole-genome association and population-based linkage analyses.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089
Model-based Analysis of ChIP-Seq (MACS)
Zhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., Nusbaum, C., Myers, R. M., Brown, M., Li, W., et al. (2008) · Genome Biology · doi:10.1186/gb-2008-9-9-r137 · Cited by 18,386
Self-citationGenome-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
Self-citationFinding the missing heritability of complex diseases
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., et al. (2009) · Nature · doi:10.1038/nature08494 · Cited by 8,336
Self-citationA map of human genome variation from population-scale sequencing.
The 1000 Genomes Project Consortium (2010) · Nature · doi:10.1038/nature09534 · Cited by 7,877
Effectiveness of Antipsychotic Drugs in Patients with Chronic Schizophrenia
Lieberman, J. A., Stroup, T. S., McEvoy, J. P., Swartz, M. S., Rosenheck, R. A., Perkins, D. O., Keefe, R. S. E., Davis, S. M., Davis, C. E., Lebowitz, B. D., et al. (2005) · New England Journal of Medicine · doi:10.1056/nejmoa051688 · Cited by 5,892
A haplotype map of the human genome
The International HapMap Consortium (2005) · Nature · doi:10.1038/nature04226 · Cited by 5,858
The Future of Genetic Studies of Complex Human Diseases
Risch, N., & Merikangas, K. (1996) · Science · doi:10.1126/science.273.5281.1516 · Cited by 5,355
Principles of Population Genetics.
Cormack, R. M., Hartl, D. L., & Clark, A. G. (1990) · Biometrics · doi:10.2307/2531471 · Cited by 5,283
Common polygenic variation contributes to risk of schizophrenia and bipolar disorder
The International Schizophrenia Consortium (2009) · Nature · doi:10.1038/nature08185 · Cited by 4,821
Research works printed but not linked: 1
- Danoy, 2010, Association of variants at 1q32 and STAT3 with ankylosing spondylitis suggests genetic overlap with Crohn's disease, PLoS Genet., 6, e1001195, 10.1371/journal.pgen.1001195 · DOI
Cited by
Sorted by citations
Items 801–900 of 1,007
Carress, H., Lawson, D. J., & Elhaik, E. (2021) · BMC Genomics · doi:10.1186/s12864-021-07618-x · Cited by 35
Shin, J., & Lee, S. (2021) · Genome biology · doi:10.1186/s13059-021-02403-1 · Cited by 32
Challenging Sustainable and Innovative Technologies in Cheese Production: A Review
Oštarić, F., Antunac, N., Čubrić-Ćurik, V., Čurik, I., Jurić, S., Kazazić, S., Kiš, M., Vinceković, M., Zdolec, N., Špoljarić, J., et al. (2022) · Processes · doi:10.3390/pr10030529 · Cited by 31
Functional characterization of human genomic variation linked to polygenic diseases
Fabo, T., & Khavari, P. A. (2023) · Trends in Genetics · doi:10.1016/j.tig.2023.02.014 · Cited by 32
Ilan, Y. (2023) · Progress in Biophysics and Molecular Biology · doi:10.1016/j.pbiomolbio.2023.04.003 · Cited by 31
Findlay, J. M., Middleton, M. R., & Tomlinson, I. P. M. (2015) · Digestive Diseases and Sciences · doi:10.1007/s10620-015-3884-5 · Cited by 31
Liu, H., Li, Y., & Guo, G. (2014) · Social Forces · doi:10.1093/sf/sou086 · Cited by 33
Bakır-Güngör, B., Egemen, E., & Sezerman, O. U. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btt743 · Cited by 32
Schmit, S. L., Schumacher, F. R., Edlund, C. K., Conti, D. V., Raskin, L., Lejbkowicz, F., Pinchev, M., Rennert, H. S., Jenkins, M. A., Hopper, J. L., et al. (2014) · Carcinogenesis · doi:10.1093/carcin/bgu148 · Cited by 32
Endler, L., Betancourt, A. J., Nolte, V., & Schlötterer, C. (2015) · Genetics · doi:10.1534/genetics.115.183376 · Cited by 34
Human Genetic Variation, Shared and Private
Casals, F., & Bertranpetit, J. (2012) · Science · doi:10.1126/science.1224528 · Cited by 32
Large-scale genome-wide analyses of stuttering
Polikowsky, H. G., Scartozzi, A., Shaw, D. M., Pruett, D. G., Chen, H., Petty, L. E., Petty, A. S., Lowther, E., Cho, S.-H., Yu, Y., et al. (2025) · Nature Genetics · doi:10.1038/s41588-025-02267-2 · Cited by 30
Somatic Variation of T-Cell Receptor Genes Strongly Associate with HLA Class Restriction
Klarenbeek, P. L., Doorenspleet, M. E., Esveldt, R. E., van Schaik, B. D. C., Lardy, N. M., van Kampen, A. H. C., Tak, P. P., Plenge, R. M., Baas, F., de Bakker, P. I. W., et al. (2015) · PLoS ONE · doi:10.1371/journal.pone.0140815 · Cited by 30
Zhang, C., Hu, F. B., Olsen, S. F., Vaag, A. A., Gore‐Langton, R. E., Chavarro, J. E., Bao, W., Yeung, E. H., Bowers, K. A., Grunnet, L. G., et al. (2014) · Acta Obstetricia Et Gynecologica Scandinavica · doi:10.1111/aogs.12425 · Cited by 30
Incorporating prior information into association studies
Darnell, G., Duong, D., Han, B., & Eskin, E. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts235 · Cited by 30
Varga, T. V., Sonestedt, E., Shungin, D., Koivula, R. W., Hallmans, G., Escher, S. A., Barroso, I., Nilsson, P. M., Melander, O., Orho‐Melander, M., et al. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004388 · Cited by 30
Dickinson, A. M., & Norden, J. (2015) · International Journal of Immunogenetics · doi:10.1111/iji.12202 · Cited by 30
Luo, C., Liu, J., Dey, D. K., & Chen, K. (2016) · Biostatistics · doi:10.1093/biostatistics/kxw001 · Cited by 30
Myneni, V. D., Mousa, A., & Kaartinen, M. T. (2016) · Scientific Reports · doi:10.1038/srep35574 · Cited by 32
Fryett, J. J., Inshaw, J. R. J., Morris, A. P., & Cordell, H. J. (2018) · European Journal of Human Genetics · doi:10.1038/s41431-018-0176-5 · Cited by 31
Established and emerging strategies to crack the genetic code of obesity
Tam, V., Turcotte, M., & Meyre, D. (2018) · Obesity Reviews · doi:10.1111/obr.12770 · Cited by 31
Genome-wide association studies of cardiac electrical phenotypes
Glinge, C., Lahrouchi, N., Jabbari, R., Tfelt‐Hansen, J., & Bezzina, C. R. (2020) · Cardiovascular Research · doi:10.1093/cvr/cvaa144 · Cited by 31
Detection of breeding signatures in wheat using a linkage disequilibrium-corrected mapping approach
Dadshani, S., Mathew, B., Ballvora, A., Mason, A. S., & Léon, J. (2021) · Scientific Reports · doi:10.1038/s41598-021-85226-1 · Cited by 30
Gut microbiota is associated with bone mineral density
Cheng, B., Wen, Y. F., Yang, X., Cheng, S., Liu, L., Chu, X., Ye, J., Liang, C., Yao, Y., Jia, Y., et al. (2021) · Bone and Joint Research · doi:10.1302/2046-3758.1011.bjr-2021-0181.r1 · Cited by 30
Review of Mendelian Randomization Studies on Endometrial Cancer
Guo, J.-Z., Wu, Q., Liu, F.-H., Gao, C., Gong, T., & Li, G. (2022) · Frontiers in Endocrinology · doi:10.3389/fendo.2022.783150 · Cited by 31
Zhang, Q., Meng, X., Qiu, C., Shen, H., Zhao, Q., Zhao, L., Tian, Q., Sun, C., & Deng, H.-W. (2022) · Human Genomics · doi:10.1186/s40246-022-00388-x · Cited by 30
Estimation of Epistatic Variance Components and Heritability in Founder Populations and Crosses
Young, A. I., & Durbin, R. M. (2014) · Genetics · doi:10.1534/genetics.114.170795 · Cited by 31
Associations between the FKBP5 haplotype, exposure to violence and anxiety in females
Isaksson, J., Comasco, E., Åslund, C., Rehn, M., Tuvblad, C., Andershed, H., & Nilsson, K. W. (2016) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2016.07.206 · Cited by 30
A epigenética como nova hipótese etiológica no campo psiquiátrico contemporâneo
Freitas-Silva, L. R., & Ortega, F. (2014) · Physis Revista de Saúde Coletiva · doi:10.1590/s0103-73312014000300006 · Cited by 29
Analysis of genome-wide significant bipolar disorder genes in borderline personality disorder
Witt, S. H., Kleindienst, N., Frank, J., Treutlein, J., Mühleisen, T. W., Degenhardt, F., Jungkunz, M., Krumm, B., Cichon, S., Tadić, A., et al. (2014) · Psychiatric Genetics · doi:10.1097/ypg.0000000000000060 · Cited by 29
Embracing Complex Associations in Common Traits: Critical Considerations for Precision Medicine
Hall, M. A., Moore, J. H., & Ritchie, M. D. (2016) · Trends in Genetics · doi:10.1016/j.tig.2016.06.001 · Cited by 30
Dissolving the Missing Heritability Problem
Bourrat, P., & Lu, Q. (2017) · Philosophy of Science · doi:10.1086/694007 · Cited by 30
Li, J., Jew, B., Zhan, L., Hwang, S., Coppola, G., Freimer, N. B., & Sul, J. H. (2019) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1007556 · Cited by 29
Giacopuzzi, E., Popitsch, N. P., & Taylor, J. C. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac130 · Cited by 31
Xin, J., Gu, D., Chen, S., Ben, S., Li, H., Zhang, Z., Du, M., & Wang, M. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac677 · Cited by 30
Cebecí, Z., Bayraktar, M., & Gökçe, G. (2023) · Small Ruminant Research · doi:10.1016/j.smallrumres.2023.107053 · Cited by 29
The Dopaminergic Reward System and Leisure Time Exercise Behavior: A Candidate Allele Study
Huppertz, C., Bartels, M., Groen‐Blokhuis, M. M., Dolan, C. V., de Moor, M. H. M., Abdellaoui, A., van Beijsterveldt, C. E. M., Ehli, E. A., Hottenga, J., Willemsen, G. A. H. M., et al. (2014) · BioMed Research International · doi:10.1155/2014/591717 · Cited by 29
Ge, T., Nichols, T. E., Ghosh, D., Mormino, E. C., Smoller, J. W., & Sabuncu, M. R. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.01.029 · Cited by 31
Wei, W., Guo, Y., Kindt, A. S. D., Merriman, T. R., Semple, C. A. M., Wang, K., & Haley, C. (2014) · Human Molecular Genetics · doi:10.1093/hmg/ddu227 · Cited by 30
Hill, A., Loh, P., Bharadwaj, R., Pons, P., Shang, J., Guinan, E. C., Lakhani, K. R., Kilty, I., & Jelinsky, S. A. (2017) · GigaScience · doi:10.1093/gigascience/gix009 · Cited by 29
Interplay Between Genetic and Epigenetic Mechanisms in Rheumatoid Arthritis
Frank‐Bertoncelj, M., Klein, K., & Gay, S. (2017) · Epigenomics · doi:10.2217/epi-2016-0142 · Cited by 29
Identifying disease associated genes by network propagation
Qian, Y., Besenbacher, S., Mailund, T., & Schierup, M. H. (2014) · BMC Systems Biology · doi:10.1186/1752-0509-8-s1-s6 · Cited by 29
Genomes and phenomes of a population of outbred rats and its progenitors
Baud, A., Guryev, V., Hummel, O., Johannesson, M., Baud, A., Guryev, V., Hummel, O., Johannesson, M., Hermsen, R., Stridh, P., et al. (2014) · Scientific Data · doi:10.1038/sdata.2014.11 · Cited by 29
Ruchay, A. N., Kolpakov, V., Kosyan, D. B., Rusakova, E., Dorofeev, K., Guo, H., Ferrari, G., & Pezzuolo, A. (2022) · Animals · doi:10.3390/ani12162128 · Cited by 28
Križanac, A.-M., Reimer, C., Heise, J., Liu, Z., Pryce, J. E., Bennewitz, J., Thaller, G., Falker‐Gieske, C., & Tetens, J. (2025) · Genetics Selection Evolution · doi:10.1186/s12711-025-00951-9 · Cited by 31
Vrieze, S. I., Malone, S. M., Vaidyanathan, U., Kwong, A. M., Kang, H. M., Zhan, X., Flickinger, M., Irons, D. E., Jun, G., Locke, A. E., et al. (2014) · Psychophysiology · doi:10.1111/psyp.12350 · Cited by 30
Cellular Reprogramming Using Defined Factors and MicroRNAs
Eguchi, T., & Kuboki, T. (2016) · Stem Cells International · doi:10.1155/2016/7530942 · Cited by 30
Current Scope and Challenges in Phenome-Wide Association Studies
Verma, A., & Ritchie, M. D. (2017) · Current Epidemiology Reports · doi:10.1007/s40471-017-0127-7 · Cited by 30
Atrial Fibrillation Genetics Update: Toward Clinical Implementation
Kalstø, S. M., Siland, J. E., Rienstra, M., & Christophersen, I. E. (2019) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2019.00127 · Cited by 28
Abdollahi-Arpanahi, R., Carvalho, M. R., Ribeiro, E. S., & Peñagaricano, F. (2019) · Journal of Dairy Science · doi:10.3168/jds.2019-17068 · Cited by 28
GWAS for resistance against black point caused by Bipolaris sorokiniana in wheat
Li, Q., Niu, H., Xu, K., Xu, Q., Wang, S., Liang, X., Jiang, Y., & Niu, J. (2019) · Journal of Cereal Science · doi:10.1016/j.jcs.2019.102859 · Cited by 28
Ndungu, A., Payne, A., Torres, J., van de Bunt, M., & McCarthy, M. I. (2020) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2020.01.003 · Cited by 28
Self-citationTranslational biomarkers in the era of precision medicine
Bravo-Merodio, L., Acharjee, A., Russ, D., Bisht, V., Williams, J. A., Tsaprouni, L., & Gkoutos, G. V. (2020) · Advances in clinical chemistry · doi:10.1016/bs.acc.2020.08.002 · Cited by 28
Multi-scale inference of genetic trait architecture using biologically annotated neural networks
Demetçi, P., Cheng, W., Darnell, G., Zhou, X., Ramachandran, S., & Crawford, L. A. (2021) · PLoS Genetics · doi:10.1371/journal.pgen.1009754 · Cited by 30
Yang, Y., Wilson, L. T., Li, T., Paleari, L., Confalonieri, R., Zhu, Y. P., Tang, L. R., Qiu, X., Tao, F., Chen, Y., et al. (2021) · Field Crops Research · doi:10.1016/j.fcr.2021.108394 · Cited by 28
The prospects of precision psychiatry
Tabb, K., & Lemoine, M. (2021) · Metamedicine · doi:10.1007/s11017-022-09558-3 · Cited by 29
Exome-wide screening identifies novel rare risk variants for major depression disorder
Cheng, S., Cheng, B., Liu, L., Yang, X., Meng, P., Yao, Y., Pan, C., Zhang, J., Li, C., Zhang, H., et al. (2022) · Molecular Psychiatry · doi:10.1038/s41380-022-01536-4 · Cited by 28
Guo, C. C., Chiesa, P. A., de Moor, C., Fazeli, M. S., Schofield, T., Hofer, K., Belachew, S. M., & Scotland, A. (2022) · Journal of Medical Internet Research · doi:10.2196/37683 · Cited by 28
Bakır-Güngör, B., Remmers, E. F., Meguro, A., Mizuki, N., Kastner, D. L., Gül, A., & Sezerman, O. U. (2014) · European Journal of Human Genetics · doi:10.1038/ejhg.2014.158 · Cited by 28
Can Genetic Pleiotropy Replicate Common Clinical Constellations of Cardiovascular Disease and Risk?
Gottesman, O., Drill, E. N., Lotay, V., Böttinger, E. P., & Peter, I. (2012) · PLoS ONE · doi:10.1371/journal.pone.0046419 · Cited by 28
Taylor, D. L., Gough, A., Schurdak, M. E., Vernetti, L. A., Chennubhotla, C. S., Lefever, D. E., Pei, F., Faeder, J. R., Lezon, T. R., Stern, A. M., et al. (2019) · Handbook of experimental pharmacology · doi:10.1007/164_2019_239 · Cited by 28
Narrow-sense heritability estimation of complex traits using identity-by-descent information
Evans, L. M., Tahmasbi, R., Jones, M., Vrieze, S. I., Abecasis, G. R., Das, S., Bjelland, D. W., de Candia, T. R., Abecasis, G., Altshuler, D., et al. (2018) · Heredity · doi:10.1038/s41437-018-0067-0 · Cited by 29
Self-citationA Positive Causal Influence of IL-18 Levels on the Risk of T2DM: A Mendelian Randomization Study
Zhuang, H., Han, J., Cheng, L., & Liu, S. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00295 · Cited by 28
Donati, G., Dumontheil, I., & Meaburn, E. L. (2019) · Mind Brain and Education · doi:10.1111/mbe.12198 · Cited by 29
Su, S., Bouzoualegh, R., He, X., Cai, N., Li, X., Yu, J., Li, J., Yu, F. D., Wang, M., & Tang, Y. (2020) · Scientific Reports · doi:10.1038/s41598-020-64037-w · Cited by 28
Salvatore, M., Beesley, L. J., Fritsche, L. G., Hanauer, D. A., Shi, X., Mondul, A. M., Pearce, C. L., & Mukherjee, B. (2020) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2020.103652 · Cited by 27
Han, C., Yu, T., Qin, W., Liao, X., Huang, J., Liu, Z., Yu, L., Liu, X., Chen, Z., Yang, C., et al. (2020) · Journal of Gastrointestinal Oncology · doi:10.21037/jgo-20-510 · Cited by 27
Lupu, V. V., Jechel, E., Mihai, C. M., Mitrofan, E. C., Lupu, A., Stârcea, I. M., Fotea, S., Mocanu, A., Ghica, D. C., Mitrofan, C., et al. (2023) · Nutrients · doi:10.3390/nu15112535 · Cited by 30
Sweeny, A. R., Lemon, H., Ibrahim, A., Watt, K., Wilson, K. L., Childs, D. Z., Nussey, D. H., Free, A., & McNally, L. (2023) · mSystems · doi:10.1128/msystems.00040-23 · Cited by 27
Wittkowski, K. M., Sonakya, V., Bigio, B., Tonn, M. K., Shic, F., Ascano, M., Nasca, C., & Simson, G. G. (2014) · Translational Psychiatry · doi:10.1038/tp.2013.124 · Cited by 26
New Components of Drosophila Leg Development Identified through Genome Wide Association Studies
Grubbs, N., Leach, M., Su, X. B., Petrisko, T. J., Rosario, J. B., & Mahaffey, J. W. (2013) · PLoS ONE · doi:10.1371/journal.pone.0060261 · Cited by 27
The Role and Sources of Individual Differences in Critical-Analytic Thinking: a Capsule Overview
Bolger, D. J., Mackey, A. P., Wang, M., & Grigorenko, E. L. (2014) · Educational Psychology Review · doi:10.1007/s10648-014-9279-x · Cited by 30
Monogenic Models: What Have the Single Gene Disorders Taught Us?
Klupa, T., SKUPIEN, J. K., & Malecki, M. T. (2012) · Current Diabetes Reports · doi:10.1007/s11892-012-0325-0 · Cited by 30
Li, X., Yang, M., Wang, H., Jia, Y., Yan, P., Boden, G. H., Yang, G., & Li, L. (2014) · International Journal of Cardiology · doi:10.1016/j.ijcard.2014.09.007 · Cited by 27
Steinberg, K. M., Ramachandran, D., Patel, V. C., Shetty, A. C., Cutler, D. J., & Zwick, M. E. (2012) · Molecular Autism · doi:10.1186/2040-2392-3-8 · Cited by 30
Comprehensive evaluation of the neuropeptide-Y gene variants in the risk of obesity
Zain, S. M., Mohamed, Z., Jalaludin, M. Y., Fauzi, F. H., Hamidi, A., & Zaharan, N. L. (2015) · Pharmacogenetics and Genomics · doi:10.1097/fpc.0000000000000164 · Cited by 27
Vaez, A., Jansen, R., Prins, B. P., Hottenga, J., de Geus, E. J. C., Boomsma, D. I., Penninx, B. W. J. H., Nolte, I. M., Snieder, H., & Alizadeh, B. Z. (2015) · Circulation Cardiovascular Genetics · doi:10.1161/circgenetics.114.000714 · Cited by 27
Genetic Insights Into Frailty: Association of 9p21-23 Locus With Frailty
Sathyan, S., Barzilai, N., Atzmon, G., Milman, S., Ayers, E. I., & Verghese, J. (2018) · Frontiers in Medicine · doi:10.3389/fmed.2018.00105 · Cited by 28
Eriksson, D., Bianchi, M., Landegren, N., Dalin, F., Skov, J., Hultin‐Rosenberg, L., Mathioudaki, A., Nordin, J., Hallgren, Å., Andersson, G., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-26842-2 · Cited by 28
The contribution of rare genetic variants to the pathogenesis of polycystic ovary syndrome
Dapas, M., & Dunaif, A. E. (2020) · Current Opinion in Endocrine and Metabolic Research · doi:10.1016/j.coemr.2020.02.011 · Cited by 28
No Genes for Intelligence in the Fluid Genome
Ho, M. (2013) · Advances in child development and behavior · doi:10.1016/b978-0-12-397946-9.00004-x · Cited by 26
Precision Dentistry in Early Childhood
Divaris, K. (2017) · Dental Clinics of North America · doi:10.1016/j.cden.2017.02.008 · Cited by 26
Ruiz‐Pinto, S., Pita, G., Patiño‐García, A., Alonso, J., Pérez‐Martínez, A., Cartón, A. J., Gutiérrez‐Larraya, F., Alonso, M. R., Barnes, D. R., Dennis, J., et al. (2017) · Pharmacogenetics and Genomics · doi:10.1097/fpc.0000000000000309 · Cited by 27
Genome‐wide association study of shared liability to anxiety disorders in Army STARRS
Hettema, J. M., Verhulst, B., Chatzinakos, C., Bacanu, S., Chen, C., Ursano, R. J., Kessler, R. C., Gelernter, J. E., Smoller, J. W., He, F., et al. (2019) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32776 · Cited by 29
SNP‐based heritability and selection analyses: Improved models and new results
Speed, D., Kaphle, A., & Balding, D. J. (2022) · BioEssays · doi:10.1002/bies.202100170 · Cited by 26
Devereux-Cooke, A., Leary, S., McGrath, S. J., Northwood, E., Redshaw, A., Shepherd, C., Stacey, P., Tripp, C., Wilson, J., Mar, M., et al. (2022) · BMC Neurology · doi:10.1186/s12883-022-02763-6 · Cited by 26
Wenger, M., Grosse-Kathoefer, S., Kraiem, A., Pelamatti, E., Nunes, N. N. D. S., Pointner, L., & Aglas, L. (2023) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2023.1204025 · Cited by 31
Henning, J. A., Gent, D. H., Twomey, M. C., Townsend, M. S., Pitra, N. J., & Matthews, P. D. (2015) · Euphytica · doi:10.1007/s10681-015-1600-3 · Cited by 26
OpenMendel: a cooperative programming project for statistical genetics
Zhou, H., Sinsheimer, J. S., Bates, D. M., Chu, B. B., German, C., Ji, S. S., Keys, K. L., Kim, J., Ko, S., Mosher, G., et al. (2019) · Human Genetics · doi:10.1007/s00439-019-02001-z · Cited by 28
Gain-of-function variant of the human epithelial sodium channel
Chen, J., Kleyman, T. R., & Sheng, S. (2012) · American Journal of Physiology-Renal Physiology · doi:10.1152/ajprenal.00563.2012 · Cited by 26
Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline
Feldman, K., Faust, L. J., Wu, X., Huang, C., & Chawla, N. V. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-69775-8_9 · Cited by 27
scELMo: Embeddings from Language Models are Good Learners for Single-cell Data Analysis
Liu, T., Chen, T., Zheng, W., Luo, X., Chen, Y., & Zhao, H. (2023) · doi:10.1101/2023.12.07.569910 · Cited by 30
Antontseva, E. V., Degtyareva, A. O., Korbolina, E. E., Damarov, I. S., & Merkulova, T. I. (2023) · Vavilov Journal of Genetics and Breeding · doi:10.18699/vjgb-23-77 · Cited by 28
Uddin, M. J., Codner, D., Hasan, S. M. M., Scherer, S. W., O’Rielly, D. D., & Rahman, P. (2015) · Scientific Reports · doi:10.1038/srep10314 · Cited by 25
Performance of epistasis detection methods in semi-simulated GWAS
Chatelain, C., Durand, G., Thuillier, V., & Augé, F. (2018) · BMC Bioinformatics · doi:10.1186/s12859-018-2229-8 · Cited by 26
Psychiatric genetics researchers' views on offering return of results to individual participants
Kostick, K. M., Brannan, C., Pereira, S., & Lázaro‐Muñoz, G. (2018) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32682 · Cited by 25
Data Integration in Poplar: ‘Omics Layers and Integration Strategies
Weighill, D. A., Tschaplinski, T. J., Tuskan, G. A., & Jacobson, D. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00874 · Cited by 26
Monnot, S., Desaint, H., Mary‐Huard, T., Moreau, L., Schurdi‐Levraud, V., & Boissot, N. (2021) · Cells · doi:10.3390/cells10113080 · Cited by 26
Mittag, F., Römer, M., & Zell, A. (2015) · PLoS ONE · doi:10.1371/journal.pone.0135832 · Cited by 25
Connolly, S., & Heron, E. A. (2014) · Briefings in Bioinformatics · doi:10.1093/bib/bbu017 · Cited by 26
Metadata
- Authors
- Visscher, P. M., Brown, M. A., McCarthy, M. I., & Yang, J.
- Affiliations
- The University of Queensland (AU)
- Centre for Human Genetics (GB)
- QIMR Berghofer Medical Research Institute (AU)
- Corresponding author
- Visscher, Peter M.
- Venue
- The American Journal of Human Genetics
- Publisher
- Elsevier BV
- Published
- 2012-01
- Volume
- 90
- Issue
- 1
- Pages
- 7-24
- ISSN
- 0002-9297 (ISSN-L)
- PMC
- PMC3257326
- OpenAlex
- W2163924952
- Cited by
- 2,425
- References
- 218
- Citations by year
- 2026: 52 · 2025: 97 · 2024: 120 · 2023: 130 · 2022: 133 · 2021: 154 · 2020: 176 · 2019: 166 · 2018: 181 · 2017: 246 · 2016: 259 · 2015: 250 · 2014: 196 · 2013: 178 · 2012: 81
- FWCI
- 27.66
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- The American Journal of Human Genetics (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- QUT ePrints (Queensland University of Technology) (submittedVersion)
- Funders
- Wellcome Trust (090532)
- Australian Research Council
- National Health and Medical Research Council
- National Medical Research Council
- 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, single nucleotide polymorphisms, complex traits, autoimmune disease, metabolic disorders, heart disease, diabetes mellitus, mental illness, genetic association
- MeSH terms
- Autoimmune Diseases, Female, Humans, Genetic Linkage, Male, Metabolic Diseases, Genetic Predisposition to Disease, History, 21st Century, Genome-Wide Association Study, Genetic Loci, Translational Research, Biomedical
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