Using genetic data to strengthen causal inference in observational research

Causality: Models, Reasoning, and Inference

Pearl, J. (2009) · doi:10.1017/cbo9780511803161 · Cited by 11,653 · 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

‘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

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

Identification of Causal Effects Using Instrumental Variables

Angrist, J. D., Imbens, G. W., & Rubin, D. B. (1996) · Journal of the American Statistical Association · doi:10.1080/01621459.1996.10476902 · Cited by 4,230 · see citing works

Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction

Imbens, G. W., & Rubin, D. B. (2015) · doi:10.1017/cbo9781139025751 · Cited by 4,210 · see citing works

Methodology for Genetic Studies of Twins and Families

Neale, M. C., & Cardon, L. R. (1992) · doi:10.1007/978-94-015-8018-2 · Cited by 4,005 · 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

Innovation in the pharmaceutical industry: New estimates of R&D costs

DiMasi, J. A., Grabowski, H. G., & Hansen, R. W. (2016) · Journal of Health Economics · doi:10.1016/j.jhealeco.2016.01.012 · Cited by 3,359 · 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

Power and predictive accuracy of polygenic risk scores

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

Clustered environments and randomized genes: a fundamental distinction between conventional and genetic epidemiology

Smith, G. D., Lawlor, D. A., Harbord, R., Timpson, N., Day, I., & Ebrahim, S. (2007) · PLoS Medicine · doi:10.1371/journal.pmed.0040352 · Cited by 569 · see citing works

What can mendelian randomisation tell us about modifiable behavioural and environmental exposures?

Smith, G. D., & Ebrahim, S. (2005) · BMJ · doi:10.1136/bmj.330.7499.1076 · Cited by 545 · see citing works

Causal Inference and Observational Research: The Utility of Twins

McGue, M., Osler, M., & Christensen, K. (2010) · Perspectives on Psychological Science · doi:10.1177/1745691610383511 · Cited by 529 · see citing works

Vitamin D and Risk of Multiple Sclerosis: A Mendelian Randomization Study

Mokry, L. E., Ross, S., Ahmad, O. S., Forgetta, V., Smith, G. D., Leong, A., Greenwood, C. M. T., Thanassoulis, G., & Richards, J. B. (2015) · PLOS Medicine · doi:10.1371/journal.pmed.1001866 · Cited by 445 · see citing works

Bias in causal estimates from Mendelian randomization studies with weak instruments

Burgess, S., & Thompson, S. G. (2011) · Statistics in Medicine · doi:10.1002/sim.4197 · Cited by 421 · see citing works

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 · doi:10.1001/jama.2016.1975 · Cited by 284 · see citing works

The heritability of human disease: estimation, uses and abuses.

Tenesa, A., & Haley, C. S. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3377 · Cited by 283 · see citing works

Use of vitamin, mineral, nonvitamin, and nonmineral supplements in the United States: the 1987, 1992, and 2000 National Health Interview Survey results

Millen, A. E., Dodd, K. W., & Subar, A. F. (2004) · Journal of the American Dietetic Association · doi:10.1016/j.jada.2004.03.022 · Cited by 217 · see citing works

Dependent Stressful Life Events and Prior Depressive Episodes in the Prediction of Major Depression

Kendler, K. S., & Gardner, C. O. (2010) · Archives of General Psychiatry · doi:10.1001/archgenpsychiatry.2010.136 · Cited by 156 · see citing works

Social Science Methods for Twins Data: Integrating Causality, Endowments, and Heritability

Kohler, H.-P., Behrman, J. R., & Schnittker, J. (2011) · Biodemography and Social Biology · doi:10.1080/19485565.2011.580619 · Cited by 116 · 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

Capitalizing on Mendelian randomization to assess the effects of treatments

Smith, G. D. (2007) · Journal of the Royal Society of Medicine · doi:10.1258/jrsm.100.9.432 · Cited by 60 · see citing works

Avoiding dynastic, assortative mating, and population stratification biases in Mendelian randomization through within-family analyses

Brumpton, B., Sanderson, E., Heilbron, K., Hartwig, F. P., Harrison, S., Vie, G. Å., Cho, Y., Howe, L. D., Hughes, A., Boomsma, D. I., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-17117-4 · Cited by 402 · see citing works

Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects

Howe, L. J., Nivard, M. G., Morris, T. T., Hansen, A. F., Rasheed, H., Cho, Y., Chittoor, G., Ahlskog, R., Lind, P. A., Palviainen, T., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01062-7 · Cited by 377 · see citing works

Comparing Within- and Between-Family Polygenic Score Prediction

Selzam, S., Ritchie, S. J., Pingault, J.-B., Reynolds, C. A., O’Reilly, P. F., & Plomin, R. (2019) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2019.06.006 · Cited by 289 · see citing works

Persistent depressive symptoms, HPA-axis hyperactivity, and inflammation: the role of cognitive-affective and somatic symptoms

Iob, E., Kirschbaum, C., & Steptoe, A. (2020) · Molecular Psychiatry · doi:10.1038/s41380-019-0501-6 · Cited by 305 · see citing works

Causal inference with observational data: the need for triangulation of evidence

Hammerton, G., & Munafò, M. R. (2021) · Psychological Medicine · doi:10.1017/s0033291720005127 · Cited by 262 · see citing works

Amyotrophic lateral sclerosis: translating genetic discoveries into therapies

Akçimen, F., Lopez, E. R., Landers, J. E., Nath, A., Chiò, A., Chia, R., & Traynor, B. J. (2023) · Nature Reviews Genetics · doi:10.1038/s41576-023-00592-y · Cited by 234 · see citing works

Genetics of circadian rhythms and sleep in human health and disease

Lane, J. M., Qian, J., Mignot, E., Redline, S., Scheer, F. A. J. L., & Saxena, R. (2023) · Nature Reviews Genetics · doi:10.1038/s41576-022-00519-z · Cited by 236 · see citing works

Mendelian randomization analysis using mixture models for robust and efficient estimation of causal effects.

Qi, G., & Chatterjee, N. (2019) · Nature Communications · doi:10.1038/s41467-019-09432-2 · Cited by 207 · see citing works

Protecting against researcher bias in secondary data analysis: challenges and potential solutions

Baldwin, J. R., Pingault, J.-B., Schoeler, T., Sallis, H. M., & Munafò, M. R. (2022) · European Journal of Epidemiology · doi:10.1007/s10654-021-00839-0 · Cited by 178 · see citing works

Triangulating Evidence through the Inclusion of Genetically Informed Designs

Munafò, M. R., Higgins, J. P. T., & Smith, G. D. (2021) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a040659 · Cited by 125 · see citing works

Multi-polygenic score approach to identifying individual vulnerabilities associated with the risk of exposure to bullying

Schoeler, T., Choi, S. W., Dudbridge, F., Baldwin, J., Duncan, L., Cecil, C. M., Walton, E., Viding, E., McCrory, E., & Pingault, J.-B. (2019) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2019.0310 · Cited by 105 · see citing works

A longitudinal twin study of victimization and loneliness from childhood to young adulthood

Matthews, T., Caspi, A., Danese, A., Fisher, H. L., Moffitt, T. E., & Arseneault, L. (2022) · Development and Psychopathology · doi:10.1017/s0954579420001005 · Cited by 93 · see citing works

Glucagon-like peptide-1 receptor agonists and diabetic retinopathy: nationwide cohort and Mendelian randomization studies

Zheng, D., Li, N., Hou, R., Zhang, X., Wu, L., Sundquist, J., Sundquist, K., & Ji, J. (2023) · BMC Medicine · doi:10.1186/s12916-023-02753-6 · Cited by 74 · see citing works

Does contact with the justice system deter or promote future delinquency? Results from a longitudinal study of British adolescent twins

Motz, R. T., Barnes, J. C., Caspi, A., Arseneault, L., Cullen, F. T., Houts, R., Wertz, J., & Moffitt, T. E. (2020) · Criminology · doi:10.1111/1745-9125.12236 · Cited by 62 · see citing works

Mendelian Randomization analysis of the causal effect of adiposity on hospital costs

Dixon, P., Hollingworth, W., Harrison, S., Davies, N. M., & Davey Smith, G. (2020) · Journal of Health Economics · doi:10.1016/j.jhealeco.2020.102300 · Cited by 48 · see citing works

Stressful life events increase the risk of major depressive episodes: A population-based twin study

Bjørndal, L. D., Kendler, K. S., Reichborn-Kjennerud, T., & Ystrom, E. (2023) · Psychological Medicine · doi:10.1017/s0033291722002227 · Cited by 35 · see citing works

Genetic nurturing, missing heritability, and causal analysis in genetic statistics

Shen, H., & Feldman, M. W. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2015869117 · Cited by 28 · see citing works

Assessment and visualization of phenome-wide causal relationships using genetic data: an application to dental caries and periodontitis

Haworth, S., Kho, P. F., Holgerson, P. L., Hwang, L.-D., Timpson, N. J., Rentería, M. E., Johansson, I., & Cuellar-Partida, G. (2021) · European Journal of Human Genetics · doi:10.1038/s41431-020-00734-4 · Cited by 29 · see citing works