Variants in the FTO and CDKAL1 loci have recessive effects on risk of obesity and type 2 diabetes, respectively
Open accessPublished version of a preprint
Abstract
AIMS/HYPOTHESIS: Genome-wide association (GWA) studies have identified hundreds of common genetic variants associated with obesity and type 2 diabetes. These studies have usually focused on additive association tests. Identifying deviations from additivity may provide new biological insights and explain some of the missing heritability for these diseases. METHODS: We performed a GWA study using a dominance deviation model for BMI, obesity (29,925 cases) and type 2 diabetes (4,040 cases) in 120,286 individuals of British ancestry from the UK Biobank study. We also investigated whether single nucleotide polymorphisms previously shown to be associated with these traits showed any enrichment for departures from additivity. RESULTS: Known obesity-associated variants in FTO showed strong evidence of deviation from additivity (p DOMDEV = 3 × 10(-5)) through a recessive effect of the allele associated with higher BMI. The average BMI of individuals carrying zero, one or two BMI-raising alleles was 27.27 (95% CI 27.22, 27.31) kg/m(2), 27.54 (95% CI 27.50, 27.58) kg/m(2) and 28.07 (95% CI 28.00, 28.14) kg/m(2), respectively. A similar effect was observed in 105,643 individuals from the GIANT Consortium (p DOMDEV = 0.003; meta-analysis p DOMDEV = 1 × 10(-7)). For type 2 diabetes, we detected a recessive effect (p DOMDEV = 5 × 10(-4)) at CDKAL1. Relative to homozygous non-risk allele carriers, homozygous risk allele carriers had an OR of 1.48 (95% CI 1.32, 1.65), while the heterozygous group had an OR of 1.06 (95% CI 0.99, 1.14), a result consistent with that of a previous study. We did not identify any novel associations at genome-wide significance. CONCLUSIONS/INTERPRETATION: Although we found no evidence of widespread non-additive genetic effects contributing to obesity and type 2 diabetes risk, we did find robust examples of recessive effects at the FTO and CDKAL1 loci. ACCESS TO RESEARCH MATERIALS: Summary statistics are available at www.t2diabetesgenes.org and by request (a.r.wood@exeter.ac.uk). All underlying data are available on application from the UK Biobank.
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
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?
Analyses aimed at genes which influence disease in a non-additive fashion have identified novel candidate genes for obesity and type 2 diabetes.
“Analyses aimed at genes which influence disease in a non-additive fashion have identified novel candidate genes for obesity and type 2 diabetes [267]”
From Genetic architecture of Alzheimer's disease (2020) · cites this paper as [267]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Sudlow, C., Gallacher, J., Allen, N., Beral, V., Burton, P., Danesh, J., Downey, P., Elliott, P., Green, J., Landray, M., et al. (2015) · PLOS Medicine · doi:10.1371/journal.pmed.1001779 · Cited by 12,728 · see citing works
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 · see citing works
Genetic studies of body mass index yield new insights for obesity biology
Study, T. L. C., Locke, A. E., The ADIPOGen Consortium, The AGEN-BMI Working Group, The CARDIOGRAMplusC4D Consortium, The CKDGen Consortium, The, G. L. G. C., The, I. C. B. P., The MAGIC Investigators, The MuTHER Consortium, et al. (2015) · Nature · doi:10.1038/nature14177 · Cited by 4,534 · see citing works
Self-citationFrayling, 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 · see citing works
Self-citationAssociation analyses of 249,796 individuals reveal 18 new loci associated with body mass index
MAGIC, Speliotes, E. K., on behalf of Procardis Consortium, Willer, C. J., Berndt, S. I., Monda, K. L., Thorleifsson, G., Jackson, A. U., Allen, H. L., Lindgren, C. M., et al. (2010) · Nature Genetics · doi:10.1038/ng.686 · Cited by 2,912 · see citing works
Self-citationGenome-wide association studies for complex traits: consensus, uncertainty and challenges
McCarthy, M. I., Abecasis, G. R., Cardon, L. R., Goldstein, D. B., Little, J., Ioannidis, J. P. A., & Hirschhorn, J. N. (2008) · Nature Reviews Genetics · doi:10.1038/nrg2344 · Cited by 2,891 · see citing works
the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Morris, A. P., Voight, B. F., Teslovich, T. M., Ferreira, T., Segrè, A. V., Steinthorsdottir, V., Strawbridge, R. J., Khan, H., Grallert, H., et al. (2012) · Nature Genetics · doi:10.1038/ng.2383 · Cited by 1,912 · see citing works
Self-citationWellcome Trust Case Control Consortium, Zeggini, E., Scott, L. J., Saxena, R., Voight, B. F., Marchini, J. L., Hu, T., de Bakker, P. I., Abecasis, G. R., Almgren, P., et al. (2008) · Nature Genetics · doi:10.1038/ng.120 · Cited by 1,864 · see citing works
Self-citationTwelve type 2 diabetes susceptibility loci identified through large-scale association analysis
The MAGIC investigators, Voight, B. F., The GIANT Consortium, Scott, L. J., Steinthorsdottir, V., Morris, A. P., Dina, C., Welch, R. P., Zeggini, E., Huth, C., et al. (2010) · Nature Genetics · doi:10.1038/ng.609 · Cited by 1,761 · see citing works
the GIANT Consortium (2009) · Nature Genetics · doi:10.1038/ng.287 · Cited by 1,720 · see citing works
Self-citation<i>FTO</i> Obesity Variant Circuitry and Adipocyte Browning in Humans
Claussnitzer, M., Dankel, S. N., Kim, K.-H., Quon, G., Meuleman, W., Haugen, C., Glunk, V., Sousa, I. S., Beaudry, J. L., Puviindran, V., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1502214 · Cited by 1,332 · see citing works
A variant in CDKAL1 influences insulin response and risk of type 2 diabetes
Steinthorsdottir, V., Thorleifsson, G., Reynisdottir, I., Benediktsson, R., Jonsdottir, T., Walters, G. B., Styrkarsdottir, U., Gretarsdottir, S., Emilsson, V., Ghosh, S., et al. (2007) · Nature Genetics · doi:10.1038/ng2043 · Cited by 1,072 · see citing works
DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Mahajan, A., Asian Genetic Epidemiology Network Type 2 Diabetes (AGEN-T2D) Consortium, South Asian Type 2 Diabetes (SAT2D) Consortium, Mexican American Type 2 Diabetes (MAT2D) Consortium, Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples (T2D-GENES) Consortium, Go, M. J., Zhang, W., Below, J. E., Gaulton, K. J., et al. (2014) · Nature Genetics · doi:10.1038/ng.2897 · Cited by 1,034 · see citing works
Self-citationGauderman, W. J., Morrison, J., & Morrison, W. M. (2006) · Medical Entomology and Zoology · Cited by 599 · see citing works
FTO genotype is associated with phenotypic variability of body mass index
Yang, J., Loos, R., Powell, J. E., Medland, S., Speliotes, E. K., Chasman, D., Rose, L., Thorleifsson, G., Steinthorsdottir, V., Mägi, R., et al. (2012) · Nature · doi:10.1038/nature11401 · Cited by 457 · see citing works
Self-citationDominance Genetic Variation Contributes Little to the Missing Heritability for Human Complex Traits
Zhu, Z., Bakshi, A., Vinkhuyzen, A. A. E., Hemani, G., Lee, S. H., Nolte, I. M., van Vliet-Ostaptchouk, J. V., Snieder, H., Esko, T., Milani, L., et al. (2015) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.01.001 · Cited by 224 · see citing works
Lenz, T. L., Deutsch, A. J., Han, B., Hu, X., Okada, Y., Eyre, S., Knapp, M., Zhernakova, A., Huizinga, T. W. J., Abecasis, G. R., et al. (2015) · Nature Genetics · doi:10.1038/ng.3379 · Cited by 195 · see citing works
Yang, Q., Wu, H., Guo, C., & Fox, C. S. (2010) · Genetic Epidemiology · doi:10.1002/gepi.20497 · Cited by 142 · see citing works
Another explanation for apparent epistasis
Wood, A. R., Tuke, M. A., Nalls, M. A., Hernandez, D. G., Bandinelli, S., Singleton, A., Melzer, D. R., Ferrucci, L., Frayling, T. M., & Weedon, M. N. (2014) · Nature · doi:10.1038/nature13691 · Cited by 115 · see citing works
Self-citationWojciechowski, P., Lipowska, A. M., Rys, P., Ewens, K. G., Franks, S., Tan, S., Lerchbaum, E., Včelák, J., Attaoua, R., Strączkowski, M., et al. (2012) · Diabetologia · doi:10.1007/s00125-012-2638-6 · Cited by 105 · see citing works
Yang, J., Wray, N. R., & Visscher, P. M. (2009) · Genetic Epidemiology · doi:10.1002/gepi.20456 · Cited by 99 · see citing works
Wood, A. R., Hernandez, D. G., Nalls, M. A., Yaghootkar, H., Gibbs, J. R., Harries, L. W., Chong, S., Moore, M., Weedon, M. N., Guralnik, J. M., et al. (2011) · Human Molecular Genetics · doi:10.1093/hmg/ddr328 · Cited by 65 · see citing works
Self-citation
Flagged first, then by citations
1 of the 24 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
The MR-Base platform supports systematic causal inference across the human phenome
Hemani, G., Zheng, J., Elsworth, B., Wade, K. H., Haberland, V., Baird, D., Laurin, C., Burgess, S., Bowden, J., Langdon, R., et al. (2018) · eLife · doi:10.7554/elife.34408 · Cited by 7,959 · see citing works
Benefits and limitations of genome-wide association studies
Tam, V., Patel, N. K., Turcotte, M., Bossé, Y., Paré, G., & Meyre, D. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-019-0127-1 · Cited by 2,092 · see citing works
Genetic Insights Into Biological Mechanisms Governing Human Ovarian Ageing
Ruth, K. S., Day, F. R., Hussain, J., Martínez-Marchal, A., Aiken, C., Azad, A., Thompson, D. J., Knoblochová, L., Abe, H., Tarry‐Adkins, J. L., et al. (2021) · Nature · doi:10.1038/s41586-021-03779-7 · Cited by 436 · see citing works
Self-citationGenetic architecture of human thinness compared to severe obesity
Riveros-Mckay, F., Mistry, V., Bounds, R., Hendricks, A. E., Keogh, J. M., Thomas, H., Henning, E., Corbin, L. J., Understanding Society Scientific Group, O’Rahilly, S., et al. (2019) · PLoS Genetics · doi:10.1371/journal.pgen.1007603 · Cited by 138 · see citing works
Genetic architecture of Alzheimer's disease
Neuner, S. M., TCW, J., & Goate, A. M. (2020) · Neurobiology of Disease · doi:10.1016/j.nbd.2020.104976 · Cited by 126 · see citing works
“Analyses aimed at identifying genes which influence disease in a non-additive fashion have nominated novel candidate genes for obesity and type 2 diabetes (Wood et al., 2016), suggesting these approaches may be useful in identifying recessive mutations that modify an individual's risk for AD.”
BackgroundThe impact of non-additive genetic associations on age-related complex diseases
Guindo-Martínez, M., Amela, R., Bonàs‐Guarch, S., Puiggròs, M., Salvoro, C., Miguel-Escalada, I., Carey, C. E., Cole, J. B., Rüeger, S., Atkinson, E. G., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-21952-4 · Cited by 116 · see citing works
Genetic risk for obesity predicts nucleus accumbens size and responsivity to real-world food cues
Rapuano, K. M., Zieselman, A. L., Kelley, W. M., Sargent, J. D., Heatherton, T. F., & Gilbert-Diamond, D. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1605548113 · Cited by 96 · see citing works
Nutter, C. A., & Kuyumcu‐Martinez, M. N. (2017) · Wiley Interdisciplinary Reviews - RNA · doi:10.1002/wrna.1459 · Cited by 64 · see citing works
di Renzo, L., Cioccoloni, G., Falcó, S., Abenavoli, L., Moia, A., Sinibaldi-Salimei, P., & Lorenzo, A. D. (2018) · Journal of Translational Medicine · doi:10.1186/s12967-018-1680-7 · Cited by 52 · see citing works
Recent Advances in Human Genetics and Epigenetics of Adiposity: Pathway to Precision Medicine?
Fall, T., Mendelson, M., & Speliotes, E. K. (2017) · Gastroenterology · doi:10.1053/j.gastro.2017.01.054 · Cited by 48 · see citing works
Genetics of Obesity in East Asians
Sun, C., Kovacs, P. L., & Guiu‐Jurado, E. (2020) · Frontiers in Genetics · doi:10.3389/fgene.2020.575049 · Cited by 45 · see citing works
Genome sequence analyses identify novel risk loci for multiple system atrophy
Chia, R., Ray, A., Shah, Z., Ding, J., Ruffo, P., Fujita, M., Menon, V., Sáez-Atiénzar, S., Reho, P., Kaivola, K., et al. (2024) · Neuron · doi:10.1016/j.neuron.2024.04.002 · Cited by 45 · see citing works
Posttranscriptional Regulation of Insulin Resistance: Implications for Metabolic Diseases
Pérez-García, A., Torrecilla-Parra, M., Frutos, M. F.-D., Martín-Martín, Y., Pardo, V., & Ramírez, C. M. (2022) · Biomolecules · doi:10.3390/biom12020208 · Cited by 44 · see citing works
Recessive/dominant model: Alternative choice in case-control-based genome-wide association studies
Liu, H.-M., Zheng, J.-P., Yang, D., Liu, Z.-F., Li, Z., Hu, Z.-Z., & Li, Z.-N. (2021) · PLoS ONE · doi:10.1371/journal.pone.0254947 · Cited by 36 · see citing works
Genetic insights into the biological mechanisms governing human ovarian ageingPreprint
Ruth, K. S., Day, F. R., Hussain, J., Martínez-Marchal, A., Aiken, C., Azad, A., Thompson, D. J., Abe, H., Tarry‐Adkins, J. L., Gonzalez, J. M., et al. (2021) · medRxiv · doi:10.1101/2021.01.11.20248322 · Cited by 34 · see citing works
Self-citationEstablished 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 30 · see citing works
Obesity genetics: insights from the Pakistani population
Pigeyre, M., Saqlain, M., Turcotte, M., Raja, G. K., & Meyre, D. (2017) · Obesity Reviews · doi:10.1111/obr.12644 · Cited by 29 · see citing works
tRNA Biology in the Pathogenesis of Diabetes: Role of Genetic and Environmental Factors
Arroyo, M. N., Green, J. A., Cnop, M., & Igoillo‐Esteve, M. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22020496 · Cited by 27 · see citing works
mRNA Processing: An Emerging Frontier in the Regulation of Pancreatic β Cell Function
Moss, N. D., & Sussel, L. (2020) · Frontiers in Genetics · doi:10.3389/fgene.2020.00983 · Cited by 24 · see citing works
Genome-wide association study identifies genetic risk loci for adiposity in a Taiwanese population
Wong, H. S.-C., Tsai, S.-Y., Chu, H., Lin, M., Lin, G.-H., Tai, Y., Shen, C., & Chang, W. (2022) · PLoS Genetics · doi:10.1371/journal.pgen.1009952 · Cited by 26 · see citing works
Genetics of metabolic traits in Greenlanders: lessons from an isolated population
Andersen, M. K., & Hansen, T. F. (2018) · Journal of Internal Medicine · doi:10.1111/joim.12814 · Cited by 27 · see citing works
Ward-Caviness, C. K., de Vries, P. S., Wiggins, K. L., Huffman, J. E., Huffman, J. E., Yanek, L. R., Bielak, L. F., Giulianini, F., Guo, X., Kleber, M. E., et al. (2019) · PLoS ONE · doi:10.1371/journal.pone.0216222 · Cited by 25 · see citing works
Li, X., & Zhao, H. (2020) · PLoS Genetics · doi:10.1371/journal.pgen.1009089 · Cited by 24 · see citing works
Recessive Genome-Wide Meta-analysis Illuminates Genetic Architecture of Type 2 Diabetes
O’Connor, M. J., Schroeder, P. H., Huerta‐Chagoya, A., Cortés-Sánchez, P., Bonàs‐Guarch, S., Guindo-Martínez, M., Cole, J. B., Kaur, V., Torrents, D., Veerapen, K., et al. (2021) · Diabetes · doi:10.2337/db21-0545 · Cited by 24 · see citing works
Tan, Y., He, Q., & Chan, K. H. K. (2023) · Frontiers in Endocrinology · doi:10.3389/fendo.2023.1050049 · Cited by 23 · see citing works
Juvinao-Quintero, D., Sharp, G., Sanderson, E., Relton, C., & Elliott, H. (2023) · Diabetologia · doi:10.1007/s00125-023-05914-7 · Cited by 22 · see citing works
Lubberding, A., Juhl, C., Skovhøj, E. Z., Kanters, J., Mandrup-Poulsen, T., & Torekov, S. (2022) · Acta Physiologica · doi:10.1111/apha.13781 · Cited by 18 · see citing works
Grarup, N., Moltke, I., Andersen, M. K., Bjerregaard, P., Larsen, C. V. L., Dahl‐Petersen, I. K., Jørsboe, E., Tiwari, H. K., Hopkins, S. E., Wiener, H. W., et al. (2018) · Diabetologia · doi:10.1007/s00125-018-4659-2 · Cited by 20 · see citing works
Pan, C., Dong, X., Lança, C., Wang, Y., Saw, S., He, X., Hu, D., Fan, Q., Grzybowski, A. E., & Ohno‐Matsui, K. (2025) · Progress in Retinal and Eye Research · doi:10.1016/j.preteyeres.2025.101415 · Cited by 18 · see citing works
Causality of particulate matter on cardiovascular diseases and cardiovascular biomarkers
Wang, Q., Wang, Z., Chen, M., Mu, W., Xu, Z., & Xue, M. (2023) · Frontiers in Public Health · doi:10.3389/fpubh.2023.1201479 · Cited by 17 · see citing works
Fine-mapping of 98 obesity loci in Mexican children
Liu, H. Y., Alyass, A., Abadi, A., Peralta‐Romero, J., Suarez, F., Gómez-Zamudio, J. H., Audirac-Chalifour, A., Parra, E. J., Cruz, M., & Meyre, D. (2018) · International Journal of Obesity · doi:10.1038/s41366-018-0056-7 · Cited by 17 · see citing works
Non-additive (dominance) effects of genetic variants associated with refractive error and myopia
Pozarickij, A., Williams, C., & Guggenheim, J. A. (2020) · Molecular Genetics and Genomics · doi:10.1007/s00438-020-01666-w · Cited by 16 · see citing works
Xu, K., Kosoy, R., Shameer, K., Kumar, S., Liu, L., Readhead, B., Belbin, G. M., Lee, H.-C., Chen, R., & Dudley, J. T. (2019) · BMC Genetics · doi:10.1186/s12863-019-0758-4 · Cited by 17 · see citing works
Genome-Wide Association Study: A Powerful Approach to Map QTLs in Crop Plants
Desaint, H., Héreil, A., & Causse, M. (2023) · Springer eBooks · doi:10.1007/978-3-031-28146-4_15 · Cited by 14 · see citing works
Lim, A. M. W., Lim, E. U., Chen, P., & Fann, C. S. J. (2024) · iScience · doi:10.1016/j.isci.2024.109815 · Cited by 14 · see citing works
Yang, Y., Wu, J., Li, S.-S., Yu, W.-K., Zhu, H., Wang, Y., & Li, Y. (2023) · Current Neurovascular Research · doi:10.2174/1567202620666230627145908 · Cited by 14 · see citing works
Chen, W., Zeng, H., Zhong, Z., Cai, X., Teng, J., Liu, Y., Zhao, Y., Wu, X., Li, J., & Zhang, Z. (2023) · animal · doi:10.1016/j.animal.2023.100817 · Cited by 13 · see citing works
Li, Q. S., Tian, C., Hinds, D. A., & Seabrook, G. R. (2020) · PLoS ONE · doi:10.1371/journal.pone.0241552 · Cited by 12 · see citing works
Type 1 diabetes, glycemic traits, and risk of dental caries: a Mendelian randomization study
Tan, L., Zhong, M., Zhao, Y., Zhao, J., Dusenge, M. A., Feng, Y., Ye, Q., Hu, J., Ou-Yang, Z.-Y., Chen, N.-X., et al. (2023) · Frontiers in Genetics · doi:10.3389/fgene.2023.1230113 · Cited by 11 · see citing works
Cui, Z.-Y., Feng, H., He, B.-C., He, J.-L., Tian, H., & Tian, Y. (2023) · Osteoarthritis and Cartilage · doi:10.1016/j.joca.2023.04.005 · Cited by 11 · see citing works
Inflammatory bowel disease and allergic diseases: A Mendelian randomization study
Li, J., Wang, L., Ma, Y., & Liu, Y. (2024) · Pediatric Allergy and Immunology · doi:10.1111/pai.14147 · Cited by 10 · see citing works
Wang, J. T., Liu, F.-Y., Mo, J., Gong, D., Zheng, F., Su, J., Ding, S., Yang, W., & Guo, P. (2024) · Frontiers in Medicine · doi:10.3389/fmed.2024.1402108 · Cited by 9 · see citing works
How much do we know about the heritability of BMI?
Feng, R. (2016) · American Journal of Clinical Nutrition · doi:10.3945/ajcn.116.139451 · Cited by 9 · see citing works
Variable expression quantitative trait loci analysis of breast cancer risk variants
Wiggins, G. A. R., Black, M. A., Dunbier, A. K., Merriman, T. R., Pearson, J. F., & Walker, L. C. (2021) · Scientific Reports · doi:10.1038/s41598-021-86690-5 · Cited by 9 · see citing works
Wang, T., Qiao, J., Zhang, S., Wei, Y., & Zeng, P. (2022) · Briefings in Bioinformatics · doi:10.1093/bib/bbac038 · Cited by 9 · see citing works
Genetic Insights Into Biological Mechanisms Governing Human Ovarian Ageing
Ruth, K. S., Day, F. R., & Hussain, J. (2021) · Obstetrical & Gynecological Survey · doi:10.1097/01.ogx.0000800176.90737.65 · Cited by 9 · see citing works
Self-citationGenome-Wide Interaction and Pathway Association Studies for Body Mass Index
Jiao, H., Zang, Y., Zhang, M., Zhang, Y., Wang, Y., Wang, K., Price, R. A., & Li, W. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00404 · Cited by 7 · see citing works
Yu, X., Zhang, Y., Lin, Y., Zou, S., Zhu, P., Song, M., Fu, F., & Yang, H. (2023) · Frontiers in Genetics · doi:10.3389/fgene.2022.1004931 · Cited by 6 · see citing works
Genetic effect of metformin use on risk of cancers: evidence from Mendelian randomization analysis
Chen, Y., Bai, B., Ye, S., Gao, X. H., Zheng, X., Ying, K., Pan, H., & Xie, B. (2023) · Diabetology & Metabolic Syndrome · doi:10.1186/s13098-023-01218-3 · Cited by 5 · see citing works
Causal relationship between affect disorders and endometrial cancer: a Mendelian randomisation study
Sun, Y., Geng, S., Fu, C., Song, X., Lin, H., & Xu, Y. (2024) · Journal of Obstetrics and Gynaecology · doi:10.1080/01443615.2024.2321321 · Cited by 5 · see citing works
Wuni, R., Curi-Quinto, K., Liu, L., Espinoza, D., Aquino, A. I., del Valle-Mendoza, J., Aguilar-Luis, M. Á., Murray, C. B., Nunes, R. J., Methven, L., et al. (2025) · Clinical Nutrition ESPEN · doi:10.1016/j.clnesp.2024.12.027 · Cited by 4 · see citing works
Integrating genetic and transcriptomic data to identify genes underlying obesity risk loci
Xu, H., Gupta, S., Dinsmore, I. R., Kollu, A., Cawley, A. M., Anwar, M. Y., Chen, H., Petty, L. E., Seshadri, S. S., Graff, M., et al. (2025) · International Journal of Obesity · doi:10.1038/s41366-025-01898-z · Cited by 4 · see citing works
The Decay of Disease Association with Declining Linkage Disequilibrium: A Fine Mapping Theorem
Maadooliat, M., Bansal, N. K., Upadhya, J., Farazi, M. R., Li, X., He, M. M., Hebbring, S. J., Ye, Z., & Schrodi, S. J. (2016) · Frontiers in Genetics · doi:10.3389/fgene.2016.00217 · Cited by 4 · see citing works
Mazo-Lopera, M. A., Coombes, B. J., & de Andrade, M. (2017) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph14101134 · Cited by 4 · see citing works
Sánchez‐Maldonado, J. M., Cabrera-Serrano, A. J., Chattopadhyay, S., Campa, D., Garrido, M. D. P., Macauda, A., ter Horst, R., Jerez, A., Netea, M. G., Li, Y., et al. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24076029 · Cited by 4 · see citing works
Molecular Effects of Physical Activity and Body Composition: A Systematic Review and Meta-Analysis
Chambers, J., Roscoe, C. M. P., Chidley, C., Lovett, A., & Duggirala, A. (2025) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph22040637 · Cited by 4 · see citing works
pgainsim: an R-package to assess the mode of inheritance for quantitative trait loci in GWAS
Scherer, N., Sekula, P., Pfaffelhuber, P., & Schlosser, P. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab150 · Cited by 3 · see citing works
Zhang, W., Sun, J., Yu, H., Shi, M., Hu, H., & Yuan, H. (2024) · Frontiers in Endocrinology · doi:10.3389/fendo.2024.1405517 · Cited by 3 · see citing works
Andersen, M. K., Grarup, N., Moltke, I., Albrechtsen, A., & Hansen, T. F. (2018) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2018.02.010 · Cited by 3 · see citing works
Wu, Q., Klinkhammer, H., Kunwar, K., Staerk, C., Maj, C., & Mayr, A. J. (2026) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2529164123 · Cited by 2 · see citing works
Semiparametric efficient estimation of small genetic effects in large-scale population cohorts
Labayle, O., Roskams-Hieter, B., Slaughter, J., Tetley-Campbell, K., van der Laan, M. J., Ponting, C. P., Beentjes, S. V., & Khamseh, A. (2024) · Biostatistics · doi:10.1093/biostatistics/kxaf030 · Cited by 2 · see citing works
Genetic architecture of human thinness compared to severe obesity
Riveros-Mckay, F., Mistry, V., Bounds, R., Hendricks, A. E., Keogh, J. M., Thomas, H., Henning, E., Corbin, L. J., Society Scientific Group Understanding, O’Rahilly, S., et al. (2019) · Yearbook of pediatric endocrinology · doi:10.1530/ey.16.11.1 · Cited by 3 · see citing works
The CRTh2 polymorphism rs533116 G > A associates with asthma severity in older females
Palikhe, N. S., Mackenzie, C. A., Licskai, C. J., Kim, R. B., Vliagoftis, H., & Cameron, L. (2022) · Frontiers in Medicine · doi:10.3389/fmed.2022.970495 · Cited by 2 · see citing works
Alipour, N., Farsi, F., Bioky, A. A., Tavasoli, N., Bidkhori, M., Sehatpour, F., Khalagi, K., Fahimfar, N., Ebrahimpur, M., Ostovar, A., et al. (2025) · Journal of Diabetes & Metabolic Disorders · doi:10.1007/s40200-025-01721-6 · Cited by 1 · see citing works
Genetic insights into biological mechanisms governing human ovarian ageing
Ruth, K. S., Day, F. R., Hussain, J., Martínez-Marchal, A., Aiken, C. E., Azad, A., & Thompson, D. J. (2022) · Yearbook of pediatric endocrinology · doi:10.1530/ey.19.15.9 · Cited by 1 · see citing works
Emerging role of mRNA and RNA binding proteins in Diabetes
Aamir, K., & Arya, A. (2023) · Elsevier eBooks · doi:10.1016/b978-0-323-99521-4.00019-2 · Cited by 1 · see citing works
Bivariate traits association analysis using generalized estimating equations in family data
de Andrade, M., Mazo-Lopera, M. A., & Duarte, N. E. (2020) · Statistical Applications in Genetics and Molecular Biology · doi:10.1515/sagmb-2019-0030
EFFECT OF FTO rs9939609 POLIMORPHISM ON OBESITY IN TURKISH POPULATION
Hız, M. M., Kiliç, S. O., & Elmas, L. (2020) · Health Sciences Quarterly · doi:10.26900/jsp.4.022
Juvinao-Quintero, D., Sharp, G., Sanderson, E., Relton, C., & Elliott, H. (2022) · medRxiv · doi:10.1101/2022.07.20.22277870
Dispensing with unnecessary assumptions in population genetics analysisPreprint
Labayle, O., Tetley-Campbell, K., van der Laan, M. J., Ponting, C. P., Beentjes, S. V., & Khamseh, A. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.09.12.507656
Cluster Analysis Identified Clinically Relevant Metabolic Syndrome EndophenotypesPreprint
Lim, A. M. W., Lim, E. U., Chen, P., & Fann, C. S. J. (2022) · medRxiv · doi:10.1101/2022.11.04.22281926
Air Pollution as a Risk Factor Affecting Human Health and Economic Costs
(2024) · Frontiers research topics · doi:10.3389/978-2-8325-4914-8
Chen, Y., Bai, B., Ye, S., Gao, X., Zheng, X., Ying, K., Pan, H., & Xie, B. (2023) · Figshare · doi:10.6084/m9.figshare.24761496
Combining Association and Haplotype Studies Towards the Improvement of Fruit Quality in Tomato
Zhao, J. (2019) · theses.fr (ABES) · doi:10.70675/998b4925z8633z4ddcz9bc0z4fb6ad557530
- Authors
- The GIANT consortium, Wood, A. R., Tyrrell, J., Beaumont, R., Jones, S. E., Tuke, M. A., Ruth, K. S., Yaghootkar, H., Freathy, R. M., Murray, A., Frayling, T. M., & Weedon, M. N.
- Affiliations
- University of Exeter (GB)
- Corresponding author
- Wood, Andrew R.
- ORCID
- Venue
- Diabetologia
- Published
- 2016-03-10
- Volume
- 59
- Issue
- 6
- Pages
- 1214-1221
- ISSN
- 0012-186X (ISSN-L)
- 1432-0428
- PMC
- PMC4869698
- OpenAlex
- W2293647101
- Cited by
- 74
- References
- 24
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 8 · 2023: 13 · 2022: 9 · 2021: 9 · 2020: 8 · 2019: 7 · 2018: 7 · 2017: 4 · 2016: 3
- FWCI
- 5.66
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Diabetologia (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Open Research Exeter (University of Exeter) (publishedVersion)
- Figshare (submittedVersion, cc-by)
- Figshare (submittedVersion)
- Site cant be reached (submittedVersion, cc-by)
- Royal Devon and Exeter Research Repository (Royal Devon and Exeter) (submittedVersion, cc-by)
- Funders
- Wellcome Trust (WT097835MF)
- Medical Research Council (MR/M005070/1)
- European Research Council (323195: SZ-245 50371-GLUCOSEGENES-FP7-IDEAS-ERC)
- Royal Society (104150/Z/14/Z)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Physical Performance
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- type 2 diabetes, FTO, dominance deviation, non-additive genetic effects, body mass index, genetic risk variants, missing heritability, gene-environment interaction, heterozygous carriers, homozygous carriers
- MeSH terms
- Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Alleles, Diabetes Mellitus, Type 2, Genotype, Humans, Obesity, tRNA Methyltransferases, Models, Statistical, Body Mass Index, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Principal Component Analysis, Genome-Wide Association Study
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
