Frayling, Timothy M.

A saturated map of common genetic variants associated with human height

Yengo, L., Vedantam, S., Marouli, E., Sidorenko, J., Bartell, E., Sakaue, S., Graff, M., Eliasen, A. U., Jiang, Y., Raghavan, S., et al. (2022) · Nature

Genetic Associations and EpidemiologyGenetics and Physical Performance

Cited by 825

Large-Scale Association Studies of Variants in Genes Encoding the Pancreatic β-Cell KATP Channel Subunits Kir6.2 (KCNJ11) and SUR1 (ABCC8) Confirm That the KCNJ11 E23K Variant Is Associated With Type 2 Diabetes

Gloyn, A. L., Weedon, M. N., Owen, K. R., Turner, M. J., Knight, B. A., Hitman, G., Walker, M., Levy, J. C., Sampson, M., Halford, S., et al. (2003) · Diabetes

Pancreatic function and diabetesGenetic Associations and Epidemiology

Cited by 754

Using human genetics to understand the disease impacts of testosterone in men and women

The Endometrial Cancer Association Consortium, Ruth, K. S., Day, F. R., Tyrrell, J., Thompson, D. J., Wood, A. R., Mahajan, A., Beaumont, R. N., Wittemans, L., Martin, S., et al. (2020) · Nature Medicine

Hormonal and reproductive studiesGenetic Associations and Epidemiology

Cited by 720

Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation

Mahajan, A., Spracklen, C. N., Zhang, W., Ng, M. C. Y., Petty, L. E., Kitajima, H., Yu, G. Z., Rüeger, S., Speidel, L., Kim, Y. J., et al. (2022) · Nature Genetics

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 704

Genome-wide association analyses of chronotype in 697,828 individuals provides insights into circadian rhythms

Jones, S. E., Lane, J. M., Wood, A. R., van Hees, V. T., Tyrrell, J., Beaumont, R. N., Jeffries, A. R., Dashti, H. S., Hillsdon, M., Ruth, K. S., et al. (2019) · Nature Communications

Circadian rhythm and melatoninGenetic Associations and Epidemiology

Cited by 691

Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture

Berndt, S. I., Gustafsson, S., Mägi, R., Ganna, A., Wheeler, E., Feitosa, M. F., Justice, A. E., Monda, K. L., Croteau-Chonka, D. C., Day, F. R., et al. (2013) · Nature Genetics

Genetic Associations and EpidemiologyGenetics and Physical Performance

Cited by 646

GWAS in 446,118 European adults identifies 78 genetic loci for self-reported habitual sleep duration supported by accelerometer-derived estimates

Dashti, H. S., Jones, S. E., Wood, A. R., Lane, J. M., van Hees, V. T., Wang, H., Rhodes, J. A., Song, Y., Patel, K., Anderson, S. G., et al. (2018) · Nature Communications

Sleep and related disordersGenetic Associations and Epidemiology

Cited by 614

Rare and low-frequency coding variants alter human adult height

Marouli, E., Graff, M., Medina-Gomez, C., Lo, K. S., Wood, A. R., Kjaer, T. R., Fine, R. S., Lu, Y., Schurmann, C., Highland, H. M., et al. (2017) · Nature

Genetic Associations and EpidemiologyGenetics and Physical Performance

Cited by 610

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Suzuki, K., Hatzikotoulas, K., Southam, L., Taylor, H. J., Yin, X., Lorenz, K. M., Mandla, R., Huerta-Chagoya, A., Melloni, G. E. M., Kanoni, S., et al. (2024) · Nature

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 606

A genome-wide association study identifies protein quantitative trait loci (pQTLs)

Melzer, D., Perry, J. R. B., Hernandez, D., Corsi, A.-M., Stevens, K., Rafferty, I., Lauretani, F., Murray, A., Gibbs, J. R., Paolisso, G., et al. (2008) · PLoS Genetics

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 480

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes

Mahajan, A., Wessel, J., Willems, S. M., Zhao, W., Robertson, N. R., Chu, A. Y., Gan, W., Kitajima, H., Taliun, D., Rayner, N. W., et al. (2018) · Nature Genetics

Genetic Associations and EpidemiologyGenomics and Rare Diseases

Cited by 442

Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood

Qi, T., Wu, Y., Zeng, J., Zhang, F., Xue, A., Jiang, L., Zhu, Z., Kemper, K., Yengo, L., Zheng, Z., et al. (2018) · Nature Communications

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 427

Biomarkers for Type 2 Diabetes and Impaired Fasting Glucose Using a Nontargeted Metabolomics Approach

Menni, C., Fauman, E., Erte, I., Perry, J. R. B., Kastenmüller, G., Shin, S.-Y., Petersen, A.-K., Hyde, C., Psatha, M., Ward, K. J., et al. (2013) · Diabetes

Metabolomics and Mass Spectrometry StudiesDiabetes, Cardiovascular Risks, and Lipoproteins

Cited by 416

Genome-Wide Association Analyses in 128,266 Individuals Identifies New Morningness and Sleep Duration Loci

Jones, S. E., Tyrrell, J., Wood, A. R., Beaumont, R. N., Ruth, K. S., Tuke, M. A., Yaghootkar, H., Hu, Y., Teder-Laving, M., Hayward, C., et al. (2016) · PLOS Genetics

Circadian rhythm and melatoninGenetic Associations and Epidemiology

Cited by 388

Height, body mass index, and socioeconomic status: mendelian randomisation study in UK Biobank

Tyrrell, J., Jones, S. E., Beaumont, R., Astley, C. M., Lovell, R., Yaghootkar, H., Tuke, M., Ruth, K. S., Freathy, R. M., Hirschhorn, J. N., et al. (2016) · BMJ

Genetic Associations and EpidemiologyIntergenerational and Educational Inequality Studies

Cited by 372

Genome-Wide Association Identifies Nine Common Variants Associated With Fasting Proinsulin Levels and Provides New Insights Into the Pathophysiology of Type 2 Diabetes

Strawbridge, R. J., Dupuis, J., Prokopenko, I., Barker, A., Ahlqvist, E., Rybin, D., Petrie, J. R., Travers, M. E., Bouatia-Naji, N., Dimas, A. S., et al. (2011) · Diabetes

Genetic Associations and EpidemiologyDiabetes and associated disorders

Cited by 356

Phantasia–The psychological significance of lifelong visual imagery vividness extremes

Zeman, A., Milton, F., Della Sala, S., Dewar, M., Frayling, T., Gaddum, J., Hattersley, A., Heuerman-Williamson, B., Jones, K., MacKisack, M., et al. (2020) · Cortex

Visual perception and processing mechanismsHallucinations in medical conditions

Cited by 336

Common Variation in the DIO2 Gene Predicts Baseline Psychological Well-Being and Response to Combination Thyroxine Plus Triiodothyronine Therapy in Hypothyroid Patients

Panicker, V., Saravanan, P., Vaidya, B., Evans, J., Hattersley, A. T., Frayling, T. M., & Dayan, C. M. (2009) · The Journal of Clinical Endocrinology & Metabolism

Thyroid Disorders and TreatmentsThyroid and Parathyroid Surgery

Cited by 327

Genetic evidence of assortative mating in humans

Robinson, M. R., Kleinman, A., Graff, M., Vinkhuyzen, A. A. E., Couper, D., Miller, M. B., Peyrot, W. J., Abdellaoui, A., Zietsch, B. P., Nolte, I. M., et al. (2017) · Nature Human Behaviour

Genetic Associations and EpidemiologyGenetic and phenotypic traits in livestock

Cited by 326

Mendelian randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits.

Porcu, E., Rüeger, S., Lepik, K., eQTLGen Consortium, Agbessi, M., Ahsan, H., Alves, I., Andiappan, A., Arindrarto, W., Awadalla, P., et al. (2019) · Nature Communications

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 322

C-reactive protein levels and body mass index: elucidating direction of causation through reciprocal Mendelian randomization

Timpson, N. J., Nordestgaard, B. G., Harbord, R. M., Zacho, J., Frayling, T. M., Tybjærg-Hansen, A., & Davey Smith, G. (2011) · International Journal of Obesity

Genetic Associations and EpidemiologyAdipokines, Inflammation, and Metabolic Diseases

Cited by 310

Genetic studies of accelerometer-based sleep measures yield new insights into human sleep behaviour

Jones, S. E., van Hees, V. T., Mazzotti, D. R., Marques-Vidal, P., Sabia, S., van der Spek, A., Dashti, H. S., Engmann, J., Kocevska, D., Tyrrell, J., et al. (2019) · Nature Communications

Sleep and related disordersGenetic Associations and Epidemiology

Cited by 300

Genetic evidence for causal relationships between maternal obesity-related traits and birth weight

Tyrrell, J., Richmond, R. C., Palmer, T. M., Feenstra, B., Rangarajan, J., Metrustry, S., Cavadino, A., Paternoster, L., Armstrong, L. L., De Silva, N. M. G., et al. (2016) · JAMA

Birth, Development, and HealthGestational Diabetes Research and Management

Cited by 284

Genetic correlates of social stratification in Great Britain

Abdellaoui, A., Hugh-Jones, D., Yengo, L., Kemper, K. E., Nivard, M. G., Veul, L., Holtz, Y., Zietsch, B. P., Frayling, T. M., Wray, N. R., et al. (2019) · Nature Human Behaviour

Genetic Associations and EpidemiologyForensic and Genetic Research

Cited by 261