The MR-Base platform supports systematic causal inference across the human phenome

A global reference for human genetic variation

The 1000 Genomes Project Consortium, authors, C., Auton, A., Abecasis, G. R., Steering committee, Altshuler, D. M., Durbin, R. M., Abecasis, G. R., Bentley, D. R., Chakravarti, A., et al. (2015) · Nature · doi:10.1038/nature15393 · Cited by 18,247 · see citing works

Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression

Bowden, J., Davey Smith, G., & Burgess, S. (2015) · International Journal of Epidemiology · doi:10.1093/ije/dyv080 · Cited by 9,816 · see citing works

Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator

Bowden, J., Davey Smith, G., Haycock, P. C., & Burgess, S. (2016) · Genetic Epidemiology · doi:10.1002/gepi.21965 · Cited by 8,922 · see citing works

Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases

Verbanck, M., Chen, C.-Y., Neale, B., & Do, R. (2018) · Nature Genetics · doi:10.1038/s41588-018-0099-7 · Cited by 8,591 · see citing works

Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials

Sterne, J. A. C., Sutton, A. J., Ioannidis, J. P. A., Terrin, N., Jones, D. R., Lau, J., Carpenter, J., Rucker, G., Harbord, R. M., Schmid, C. H., et al. (2011) · BMJ · doi:10.1136/bmj.d4002 · Cited by 7,709 · see citing works

‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease?*

Davey Smith, G., & Ebrahim, S. (2003) · International Journal of Epidemiology · doi:10.1093/ije/dyg070 · Cited by 5,882 · see citing works

The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans

The GTEx Consortium, Ardlie, K. G., Deluca, D. S., Segrè, A. V., Sullivan, T. J., Young, T. R., Gelfand, E. T., Trowbridge, C. A., Maller, J. B., Tukiainen, T., et al. (2015) · Science · doi:10.1126/science.1262110 · Cited by 5,062 · see citing works

Mendelian randomization: genetic anchors for causal inference in epidemiological studies

Davey Smith, G., & Hemani, G. (2014) · Human Molecular Genetics · doi:10.1093/hmg/ddu328 · Cited by 4,677 · see citing works

Mendelian randomization: Using genes as instruments for making causal inferences in epidemiology

Lawlor, D. A., Harbord, R. M., Sterne, J. A. C., Timpson, N., & Davey Smith, G. (2008) · Statistics in Medicine · doi:10.1002/sim.3034 · Cited by 4,618 · see citing works

Bayesian Test for Colocalisation between Pairs of Genetic Association Studies Using Summary Statistics

Giambartolomei, C., Vukcevic, D., Schadt, E. E., Franke, L., Hingorani, A. D., Wallace, C., & Plagnol, V. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004383 · Cited by 4,261 · see citing works

An atlas of genetic correlations across human diseases and traits

ReproGen Consortium, Bulik-Sullivan, B., Psychiatric Genomics Consortium, Genetic Consortium for Anorexia Nervosa of the Wellcome Trust Case Control Consortium 3, Finucane, H. K., Anttila, V., Gusev, A., Day, F. R., Loh, P.-R., Duncan, L., et al. (2015) · Nature Genetics · doi:10.1038/ng.3406 · Cited by 4,255 · see citing works

Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt

Durinck, S., Spellman, P. T., Birney, E., & Huber, W. K. (2009) · Nature Protocols · doi:10.1038/nprot.2009.97 · Cited by 4,081 · see citing works

Avoiding bias from weak instruments in Mendelian randomization studies

Burgess, S., Thompson, S. G., & CRP CHD Genetics Collaboration (2011) · International Journal of Epidemiology · doi:10.1093/ije/dyr036 · Cited by 3,952 · see citing works

10 Years of GWAS Discovery: Biology, Function, and Translation

Visscher, P. M., Wray, N. R., Zhang, Q., Sklar, P., McCarthy, M. I., Brown, M. A., & Yang, J. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.06.005 · Cited by 3,719 · see citing works

Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumption

Hartwig, F. P., Davey Smith, G., & Bowden, J. (2017) · International Journal of Epidemiology · doi:10.1093/ije/dyx102 · Cited by 3,485 · see citing works

Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets

Zhu, Z., Zhang, F., Hu, H., Bakshi, A., Robinson, M. R., Powell, J. E., Montgomery, G. W., Goddard, M. E., Wray, N. R., Visscher, P. M., et al. (2016) · Nature Genetics · doi:10.1038/ng.3538 · Cited by 3,352 · see citing works

Untitled work

Willer (2013) · doi:10.1038/ng.2797 · Cited by 2,983 · see citing works

Major lipids, apolipoproteins, and risk of vascular disease

The Emerging Risk Factors Collaboration* (2009) · JAMA · doi:10.1001/jama.2009.1619 · Cited by 2,731 · see citing works

The NHGRI GWAS Catalog, a curated resource of SNP-trait associations

Welter, D., MacArthur, J., Morales, J., Burdett, T., Hall, P., Junkins, H., Klemm, A., Flicek, P., Manolio, T., Hindorff, L., et al. (2014) · Nucleic Acids Research · doi:10.1093/nar/gkt1229 · Cited by 2,707 · see citing works

Orienting the causal relationship between imprecisely measured traits using GWAS summary data.

Hemani, G., Tilling, K., & Davey Smith, G. (2017) · PLoS Genetics · doi:10.1371/journal.pgen.1007081 · Cited by 2,607 · see citing works

Integrative approaches for large-scale transcriptome-wide association studies

Gusev, A., Ko, A., Shi, H., Bhatia, G., Chung, W., Penninx, B. W. J. H., Jansen, R., de Geus, E. J. C., Boomsma, D. I., Wright, F. A., et al. (2016) · Nature Genetics · doi:10.1038/ng.3506 · Cited by 2,479 · see citing works

A comprehensive 1000 Genomes–based genome-wide association meta-analysis of coronary artery disease

the CARDIoGRAMplusC4D Consortium (2015) · Nature Genetics · doi:10.1038/ng.3396 · Cited by 2,447 · see citing works

Statins and risk of incident diabetes: A collaborative meta-analysis of randomised statin trials

Sattar, N., Preiss, D., Murray, H. M., Welsh, P., Buckley, B. M., de Craen, A. J., Seshasai, S. R. K., McMurray, J. J., Freeman, D. J., Jukema, J. W., et al. (2010) · The Lancet · doi:10.1016/s0140-6736(09)61965-6 · Cited by 2,436 · see citing works

Five Years of GWAS Discovery

Visscher, P. M., Brown, M. A., McCarthy, M. I., & Yang, J. (2012) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2011.11.029 · Cited by 2,425 · see citing works

MendelianRandomization: an R package for performing Mendelian randomization analyses using summarized data

Yavorska, O. O., & Burgess, S. (2017) · International Journal of Epidemiology · doi:10.1093/ije/dyx034 · Cited by 2,072 · see citing works

A framework for the investigation of pleiotropy in two‐sample summary data Mendelian randomization

Bowden, J., Del Greco M, F., Minelli, C., Davey Smith, G., Sheehan, N., & Thompson, J. (2017) · Statistics in Medicine · doi:10.1002/sim.7221 · Cited by 1,887 · see citing works

Assessing the suitability of summary data for two-sample Mendelian randomization analyses using MR-Egger regression: the role of the I2 statistic

Bowden, J., Fabiola Del Greco, M., Minelli, C., Smith, G. D., Sheehan, N. A., & Thompson, J. R. (2016) · International Journal of Epidemiology · doi:10.1093/ije/dyw220 · Cited by 1,572 · see citing works

An atlas of genetic influences on human blood metabolites

The Multiple Tissue Human Expression Resource (MuTHER) Consortium, Shin, S.-Y., Fauman, E. B., Petersen, A.-K., Krumsiek, J., Santos, R., Huang, J., Arnold, M., Erte, I., Forgetta, V., et al. (2014) · Nature Genetics · doi:10.1038/ng.2982 · Cited by 1,515 · see citing works

Power and predictive accuracy of polygenic risk scores

Dudbridge, F. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003348 · Cited by 1,509 · cited 1× · see citing works

Association Between Lowering LDL-C and Cardiovascular Risk Reduction Among Different Therapeutic Interventions: A Systematic Review and Meta-analysis

Silverman, M. G., Ference, B. A., Im, K., Wiviott, S. D., Giugliano, R. P., Grundy, S. M., Braunwald, E., & Sabatine, M. S. (2016) · JAMA · doi:10.1001/jama.2016.13985 · Cited by 1,483 · cited 1× · see citing works

PhenoScanner: a database of human genotype-phenotype associations.

Staley, J. R., Blackshaw, J., Kamat, M. A., Ellis, S., Surendran, P., Sun, B. B., Paul, D. S., Freitag, D., Burgess, S., Danesh, J., et al. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw373 · Cited by 1,479 · see citing works

Efficient design for Mendelian randomization studies: subsample and 2-sample instrumental variable estimators.

Pierce, B. L., & Burgess, S. (2013) · American Journal of Epidemiology · doi:10.1093/aje/kwt084 · Cited by 1,389 · see citing works

PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene–disease associations

Denny, J. C., Ritchie, M. D., Basford, M. A., Pulley, J. M., Bastarache, L., Brown-Gentry, K., Wang, D., Masys, D. R., Roden, D. M., & Crawford, D. C. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq126 · Cited by 1,219 · see citing works

Detection and interpretation of shared genetic influences on 42 human traits

Pickrell, J. K., Berisa, T., Liu, J. Z., Ségurel, L., Tung, J. Y., & Hinds, D. A. (2016) · Nature Genetics · doi:10.1038/ng.3570 · Cited by 1,151 · see citing works

PRSice: Polygenic Risk Score software

Euesden, J., Lewis, C. M., & O’Reilly, P. F. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu848 · Cited by 1,149 · see citing works

Recent Developments in Mendelian Randomization Studies

Zheng, J., Baird, D. A., Borges, M. C., Bowden, J., Hemani, G., Haycock, P., Evans, D. M., & Smith, G. D. (2017) · Current Epidemiology Reports · doi:10.1007/s40471-017-0128-6 · Cited by 1,132 · see citing works

Triangulation in aetiological epidemiology

Lawlor, D. A., Tilling, K., & Davey Smith, G. (2017) · International Journal of Epidemiology · doi:10.1093/ije/dyw314 · Cited by 1,129 · see citing works

LD Hub: a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis

Zheng, J., Erzurumluoglu, A. M., Elsworth, B. L., Kemp, J. P., Howe, L., Haycock, P. C., Hemani, G., Tansey, K., Laurin, C., Early Genetics and Lifecourse Epidemiology (EAGLE) Eczema Consortium, et al. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btw613 · Cited by 869 · see citing works

Common variants associated with plasma triglycerides and risk for coronary artery disease

Do, R., Willer, C. J., Schmidt, E. M., Sengupta, S., Gao, C., Peloso, G. M., Gustafsson, S., Kanoni, S., Ganna, A., Chen, J., et al. (2013) · Nature Genetics · doi:10.1038/ng.2795 · Cited by 862 · see citing works

Two-sample Mendelian randomization: avoiding the downsides of a powerful, widely applicable but potentially fallible technique.

Hartwig, F. P., Davies, N. M., Hemani, G., & Davey Smith, G. (2016) · International Journal of Epidemiology · doi:10.1093/ije/dyx028 · Cited by 860 · see citing works

FINEMAP: efficient variable selection using summary data from genome-wide association studies

Benner, C., Spencer, C. C. A., Havulinna, A. S., Salomaa, V., Ripatti, S., & Pirinen, M. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw018 · Cited by 815 · see citing works

Genome-wide study for circulating metabolites identifies 62 loci and reveals novel systemic effects of LPA

Kettunen, J., Demirkan, A., Würtz, P., Draisma, H. H. M., Haller, T., Rawal, R., Vaarhorst, A., Kangas, A. J., Lyytikäinen, L.-P., Pirinen, M., et al. (2016) · Nature Communications · doi:10.1038/ncomms11122 · Cited by 738 · see citing works

HMG-coenzyme A reductase inhibition, type 2 diabetes, and bodyweight: evidence from genetic analysis and randomised trials

Swerdlow, D. I., Preiss, D., Kuchenbaecker, K. B., Holmes, M. V., Engmann, J. E. L., Shah, T., Sofat, R., Stender, S., Johnson, P. C. D., Scott, R. A., et al. (2015) · The Lancet · doi:10.1016/s0140-6736(14)61183-1 · Cited by 680 · see citing works

Mendelian randomization in cardiometabolic disease: challenges in evaluating causality

Holmes, M. V., Ala-Korpela, M., & Smith, G. D. (2017) · Nature Reviews Cardiology · doi:10.1038/nrcardio.2017.78 · Cited by 679 · see citing works

Robust research needs many lines of evidence

Munafò, M. R., & Davey Smith, G. (2018) · Nature · doi:10.1038/d41586-018-01023-3 · Cited by 666 · see citing works

Genome-wide genetic data on ~500,000 UK Biobank participantsPreprint

Bycroft, C., Freeman, C., Petkova, D., Band, G., Elliott, L. T., Sharp, K., Motyer, A., Vukcevic, D., Delaneau, O., O’Connell, J., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/166298 · Cited by 606 · see citing works

Best (but oft-forgotten) practices: the design, analysis, and interpretation of Mendelian randomization studies

Haycock, P., Burgess, S., Wade, K. H., Bowden, J., Relton, C. L., & Smith, G. D. (2016) · American Journal of Clinical Nutrition · doi:10.3945/ajcn.115.118216 · Cited by 602 · see citing works

Systematic identification of genetic influences on methylation across the human life course

Gaunt, T. R., Shihab, H. A., Hemani, G., Min, J. L., Woodward, G., Lyttleton, O., Zheng, J., Duggirala, A., McArdle, W. L., Ho, K., et al. (2016) · Genome Biology · doi:10.1186/s13059-016-0926-z · Cited by 598 · see citing works

A comprehensive 1000 Genomes-based genome-wide association meta-analysis of coronary artery disease

Nikpay, M., Goel, A., Won, H., Hall, L. M., Willenborg, C., Kanoni, S., Saleheen, D., Kyriakou, T., Nelson, C. P., Hopewell, J. C., et al. (2015) · EUR Research Repository (Erasmus University Rotterdam) · Cited by 581 · see citing works

Methodological Challenges in Mendelian Randomization

VanderWeele, T. J., Tchetgen Tchetgen, E. J., Cornelis, M., & Kraft, P. (2014) · Epidemiology · doi:10.1097/ede.0000000000000081 · Cited by 555 · see citing works

Association Between Telomere Length and Risk of Cancer and Non-Neoplastic Diseases

Haycock, P., Burgess, S., Nounu, A., Zheng, J., Okoli, G. N., Bowden, J., Wade, K. H., Timpson, N. J., Evans, D. M., Willeit, P., et al. (2017) · JAMA Oncology · doi:10.1001/jamaoncol.2016.5945 · Cited by 510 · see citing works

Dissecting the genetics of complex traits using summary association statistics

Paşaniuc, B., & Price, A. L. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2016.142 · Cited by 443 · see citing works

Split-Sample Instrumental Variables Estimates of the Return to Schooling

Angrist, J. D., & Krueger, A. B. (1995) · Journal of Business and Economic Statistics · doi:10.1080/07350015.1995.10524597 · Cited by 391 · see citing works

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 · doi:10.1371/journal.pgen.1006125 · Cited by 388 · see citing works

Selecting instruments for Mendelian randomization in the wake of genome-wide association studies.

Swerdlow, D. I., Kuchenbaecker, K. B., Shah, S., Sofat, R., Holmes, M. V., White, J., Mindell, J. S., Kivimaki, M., Brunner, E. J., Whittaker, J. C., et al. (2016) · International Journal of Epidemiology · doi:10.1093/ije/dyw088 · Cited by 387 · see citing works

Overcoming the Winner’s Curse: Estimating Penetrance Parameters from Case-Control Data

Zöllner, S. K., & Pritchard, J. K. (2007) · The American Journal of Human Genetics · doi:10.1086/512821 · Cited by 382 · see citing works

PCSK9 genetic variants and risk of type 2 diabetes: a mendelian randomisation study

Schmidt, A. F., Swerdlow, D. I., Holmes, M. V., Patel, R. S., Fairhurst-Hunter, Z., Lyall, D. M., Hartwig, F. P., Horta, B. L., Hyppönen, E., Power, C., et al. (2017) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(16)30396-5 · Cited by 380 · see citing works

Inflammatory Biomarkers and Risk of Schizophrenia

Hartwig, F. P., Borges, M. C., Horta, B. L., Bowden, J., & Smith, G. D. (2017) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2017.3191 · Cited by 304 · see citing works

The Genetic Architecture of the Human Immune System: A Bioresource for Autoimmunity and Disease Pathogenesis

Roederer, M., Quaye, L., Mangino, M., Beddall, M. H., Mahnke, Y., Chattopadhyay, P., Tosi, I., Napolitano, L., Terranova Barberio, M., Menni, C., et al. (2015) · Cell · doi:10.1016/j.cell.2015.02.046 · Cited by 296 · see citing works

Association of Lipid Fractions With Risks for Coronary Artery Disease and Diabetes

White, J., Swerdlow, D. I., Preiss, D., Fairhurst-Hunter, Z., Keating, B. J., Asselbergs, F. W., Sattar, N., Humphries, S. E., Hingorani, A. D., & Holmes, M. V. (2016) · JAMA Cardiology · doi:10.1001/jamacardio.2016.1884 · Cited by 293 · see citing works

Instrumental Variables Estimation With Some Invalid Instruments and its Application to Mendelian Randomization.

Kang, H., Zhang, A., Cai, T. T., & Small, D. S. (2016) · Journal of the American Statistical Association · doi:10.1080/01621459.2014.994705 · Cited by 265 · see citing works

Statistical inference in two-sample summary-data Mendelian randomization using robust adjusted profile scorePreprint

Zhao, Q., Wang, J., Hemani, G., et al. (2018) · Bristol Research (University of Bristol) · doi:10.48550/arxiv.1801.09652 · Cited by 258 · see citing works

Software Application Profile: PHESANT: a tool for performing automated phenome scans in UK Biobank

Millard, L. A. C., Davies, N. M., Gaunt, T. R., Smith, G. D., & Tilling, K. M. (2017) · International Journal of Epidemiology · doi:10.1093/ije/dyx204 · Cited by 228 · see citing works

Epidemiology—is it time to call it a day?

Smith, G. D., & Ebrahim, S. B. J. (2001) · International Journal of Epidemiology · doi:10.1093/ije/30.1.1 · Cited by 212 · see citing works

GWASdb v2: an update database for human genetic variants identified by genome-wide association studies

Li, M. J., Liu, Z., Wang, P., Wong, M. P., Nelson, M. R., Kocher, J., Yeager, M., Sham, P. C., Chanock, S. J., Xia, Z., et al. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1317 · Cited by 186 · see citing works

GWAS Central: a comprehensive resource for the comparison and interrogation of genome-wide association studies

Beck, T., Hastings, R. K., Hesketh, S., Free, R. C., & Brookes, A. J. (2013) · European Journal of Human Genetics · doi:10.1038/ejhg.2013.274 · Cited by 166 · see citing works

Human longevity is influenced by many genetic variants: evidence from 75,000 UK Biobank participants

Pilling, L. C., Atkins, J. L., Bowman, K., Jones, S. E., Tyrrell, J., Beaumont, R. N., Ruth, K. S., Tuke, M. A., Yaghootkar, H., Wood, A. R., et al. (2016) · Aging · doi:10.18632/aging.100930 · Cited by 141 · see citing works

Estimating the Payoff to Schooling Using the Vietnam-Era Draft Lottery

Angrist, J. D., & Krueger, A. B. (1992) · National Bureau of Economic Research · doi:10.3386/w4067 · Cited by 128 · see citing works

MR-PheWAS: hypothesis prioritization among potential causal effects of body mass index on many outcomes, using Mendelian randomization

Millard, L. A. C., Davies, N. M., Timpson, N. J., Tilling, K. M., Flach, P. A., & Smith, G. D. (2015) · Scientific Reports · doi:10.1038/srep16645 · Cited by 99 · see citing works

Using Multivariable Mendelian Randomization to Disentangle the Causal Effects of Lipid Fractions

Burgess, S., Freitag, D. F., Khan, H., Gorman, D. N., & Thompson, S. G. (2014) · PLoS ONE · doi:10.1371/journal.pone.0108891 · Cited by 95 · see citing works

Beyond Mendelian randomization: how to interpret evidence of shared genetic predictors

Burgess, S., Butterworth, A. S., & Thompson, J. R. (2015) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2015.08.001 · Cited by 92 · see citing works

Pleiotropic Effects of Trait-Associated Genetic Variation on DNA Methylation: Utility for Refining GWAS Loci

Hannon, E. J., Weedon, M., Bray, N. J., O’Donovan, M. C., & Mill, J. S. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.04.013 · Cited by 89 · see citing works

Automating Mendelian randomization through machine learning to construct a putative causal map of the human phenome

Hemani, G., Bowden, J., Haycock, P., Zheng, J., Davis, O., Flach, P., Gaunt, T., & Smith, G. D. (2017) · doi:10.1101/173682 · Cited by 85 · see citing works

Variants in the FTO and CDKAL1 loci have recessive effects on risk of obesity and type 2 diabetes, respectively

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., et al. (2016) · Diabetologia · doi:10.1007/s00125-016-3908-5 · Cited by 74 · see citing works

JAM: A Scalable Bayesian Framework for Joint Analysis of Marginal SNP Effects

Newcombe, P. J., Conti, D. V., & Richardson, S. T. (2016) · Genetic Epidemiology · doi:10.1002/gepi.21953 · Cited by 72 · see citing works

Mendelian Randomization Analysis Identifies CpG Sites as Putative Mediators for Genetic Influences on Cardiovascular Disease Risk

Richardson, T. G., Zheng, J., Smith, G. D., Timpson, N. J., Gaunt, T. R., Relton, C. L., & Hemani, G. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.09.003 · Cited by 68 · see citing works

Unbiased estimation of odds ratios: combining genomewide association scans with replication studies

Bowden, J., & Dudbridge, F. (2009) · Genetic Epidemiology · doi:10.1002/gepi.20394 · Cited by 62 · see citing works

Genetic studies of plasma analytes identify novel potential biomarkers for several complex traits

Deming, Y., Xia, J., Cai, Y., Lord, J., Del-Aguila, J. L., Fernandez, M. V., Carrell, D., Black, K., Budde, J., Ma, S., et al. (2016) · Scientific Reports · doi:10.1038/srep18092 · Cited by 28 · see citing works

Improving the visualisation, interpretation and analysis of two-sample summary data Mendelian randomization via the radial plot and radial regressionPreprint

Bowden, J., Spiller, W., Fabiola Del Greco, M., Sheehan, N. A., Thompson, J. R., Minelli, C., & Smith, G. D. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/200378 · Cited by 10 · see citing works

Instrumental Variables Estimation with Some Invalid Instruments and its Application to Mendelian RandomizationPreprint

Kang, H., Zhang, A. R., Cai, T., et al. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1401.5755 · Cited by 2 · see citing works

Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians

Davies, N. M., Holmes, M. V., & Davey Smith, G. (2018) · BMJ · doi:10.1136/bmj.k601 · Cited by 4,404 · see citing works

Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions

Howard, D. M., Adams, M. J., Clarke, T.-K., Hafferty, J. D., Gibson, J., Shirali, M., Coleman, J. R. I., Hagenaars, S. P., Ward, J., Wigmore, E. M., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-018-0326-7 · Cited by 2,565 · see citing works

Large-scale association analyses identify host factors influencing human gut microbiome composition

Kurilshikov, A., Medina-Gomez, C., Bacigalupe, R., Radjabzadeh, D., Wang, J., Demirkan, A., Le Roy, C. I., Raygoza Garay, J. A., Finnicum, C. T., Liu, X., et al. (2021) · Nature Genetics · doi:10.1038/s41588-020-00763-1 · Cited by 1,786 · see citing works

Plasma proteomic associations with genetics and health in the UK Biobank

Sun, B. B., Chiou, J., Traylor, M., Benner, C., Hsu, Y.-H., Richardson, T. G., Surendran, P., Mahajan, A., Robins, C., Vasquez-Grinnell, S. G., et al. (2023) · Nature · doi:10.1038/s41586-023-06592-6 · Cited by 1,740 · see citing works

Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomisation (STROBE-MR): explanation and elaboration.

Skrivankova, V. W., Richmond, R. C., Woolf, B. A. R., Davies, N. M., Swanson, S. A., VanderWeele, T. J., Timpson, N. J., Higgins, J. P. T., Dimou, N., Langenberg, C., et al. (2021) · BMJ · doi:10.1136/bmj.n2233 · Cited by 1,648 · see citing works

Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology

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Evaluating the potential role of pleiotropy in Mendelian randomization studies

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Coffee Consumption and Cardiovascular Diseases: A Mendelian Randomization Study

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Genome-Wide Association Studies of Coffee Intake in UK/US Participants of European Ancestry Uncover Gene-Cohort InfluencesPreprint

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