Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

Keynote webinar | Spotlight on medication adherence

LIVE: Thursday 27th June 2024, 18:00-19:30 (CEST)
Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.
ADVANCED SEARCH
Log in
Top
European Journal of Epidemiology
Published in: European Journal of Epidemiology 2/2020

Open Access 01-02-2020 | Coronary Heart Disease | COMMENTARY

Mendel’s laws, Mendelian randomization and causal inference in observational data: substantive and nomenclatural issues

Authors: George Davey Smith, Michael V. Holmes, Neil M. Davies, Shah Ebrahim

Published in: European Journal of Epidemiology | Issue 2/2020

Login to get access

Abstract

We respond to criticisms of Mendelian randomization (MR) by Mukamal, Stampfer and Rimm (MSR). MSR consider that MR is receiving too much attention and should be renamed. We explain how MR links to Mendel’s laws, the origin of the name and our lack of concern regarding nomenclature. We address MSR’s substantive points regarding MR of alcohol and cardiovascular disease, an issue on which they dispute the MR findings. We demonstrate that their strictures with respect to population stratification, confounding, weak instrument bias, pleiotropy and confounding have been addressed, and summarise how the field has advanced in relation to the issues they raise. We agree with MSR that “the hard problem of conducting high-quality, reproducible epidemiology” should be addressed by epidemiologists. However we see more evidence of confrontation of this issue within MR, as opposed to conventional observational epidemiology, within which the same methods that have demonstrably failed in the past are simply rolled out into new areas, leaving their previous failures unexamined.
Literature
1.
2.
Davey Smith G, Ebrahim S. ‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease? Int J Epidemiol. 2003;32(1):1–22.
3.
Burgess S, Foley CN, Zuber V. Inferring causal relationships between risk factors and outcomes from genome-wide association study data. Annu Rev Genom Hum G. 2018;19(1):303–27.
4.
Holmes MV, Ala-Korpela M, Davey Smith G. Mendelian randomization in cardiometabolic disease: challenges in evaluating causality. Nat Rev Cardiol. 2017;14(10):577–90.PubMedPubMedCentral
5.
Davies NM, Holmes MV, Davey Smith G. Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians. BMJ. 2018;362:k601.PubMedPubMedCentral
6.
Burgess S, Davey Smith G, Davies N, Dudbridge F, Gill D, Glymour M et al. Guidelines for performing Mendelian randomization investigations. Wellcome Open Res. 2019;4(186):186.
7.
Krieger N, Davey Smith G. The tale wagged by the DAG: broadening the scope of causal inference and explanation for epidemiology. Int J Epidemiol. 2016;45(6):1787–808.PubMed
8.
Robins JM, Hernán M, Brumback B. Marginal structural models and causal inference in epidemiology. Epidemiology. 2000;11(5):550–60.PubMed
9.
Rimm EB, Stampfer MJ, Ascherio A, Giovannucci E, Colditz GA, Willett WC. Vitamin E consumption and the risk of coronary heart disease in men. New Eng J Med. 1993;328(20):1450–6.PubMed
10.
Stampfer MJ, Hennekens CH, Manson JE, Colditz GA, Rosner B, Willett WC. Vitamin E consumption and the risk of coronary disease in women. New Eng J Med. 1993;328(20):1444–9.PubMed
11.
Stampfer MJ, Colditz GA, Willett WC, Manson JE, Rosner B, Speizer FE et al. Postmenopausal estrogen therapy and cardiovascular disease. New Eng J Med. 1991;325(11):756–62.PubMed
12.
Le Fanu J. The rise and fall of modern medicine. New York: Little Brown; 1999.
13.
Skrabanek P. False premises, false promises. Whithorn: Tarragon Press for the Skrabanek Foundation; 2000.
14.
Taubes G. Epidemiology faces its limits. 1995;269(5221):164–9.
15.
Davey Smith G, Ebrahim S. Epidemiology—is it time to call it a day? Int J Epidemiol. 2001;30(1):1–11.PubMed
16.
Li H, Stampfer MJ, Giovannucci EL, Morris JS, Willett WC, Gaziano JM et al. A prospective study of plasma selenium levels and prostate cancer risk. JNCI. 2004;96(9):696–703.PubMed
17.
Giovannucci E, Liu Y, Hollis BW, Rimm EB. 25-hydroxyvitamin D and risk of myocardial infarction in men: a prospective study. Arch Intern Med. 2008;168(11):1174–80.PubMedPubMedCentral
18.
Lippman SM, Klein EA, Goodman PJ, Lucia MS, Thompson IM, Ford LG et al. Effect of selenium and vitamin E on risk of prostate cancer and other cancers: the selenium and vitamin E cancer prevention trial (SELECT). JAMA. 2009;301(1):39–51.PubMed
19.
Manson JE, Cook NR, Lee IM, Christen W, Bassuk SS, Mora S et al. Vitamin D supplements and prevention of cancer and cardiovascular disease. New Eng J Med. 2018;380(1):33–44.PubMed
20.
Lawlor DA, Tilling K, Davey Smith G. Triangulation in aetiological epidemiology. Int J Epidemiol. 2016;45(6):1866–86.PubMed
21.
22.
Hernán M, Robins J. Causal inference: what if. Boca Raton: Chapman & Hall/CRC; 2020.
23.
Rosenbaum PR. Observation and experiment: an introduction to causal inference. Cambridge: Harvard University Press; 2017.
24.
Davey Smith G, Timpson N, Ebrahim S. Strengthening causal inference in cardiovascular epidemiology through Mendelian randomization. Ann Med. 2008;40(7):524–41.
25.
Rimm EB, Giovannucci EL, Willett WC, Colditz GA, Ascherio A, Rosner B, et al. Prospective study of alcohol consumption and risk of coronary disease in men. Lancet. 1991;338(8765):464–8.PubMed
26.
Rimm EB, Klatsky A, Grobbee D, Stampfer MJ. Review of moderate alcohol consumption and reduced risk of coronary heart disease: is the effect due to beer, wine, or spirits. BMJ. 1996;312(7033):731–6.PubMedPubMedCentral
27.
Rimm EB, Williams P, Fosher K, Criqui M, Stampfer MJ. Moderate alcohol intake and lower risk of coronary heart disease: meta-analysis of effects on lipids and haemostatic factors. BMJ. 1999;319(7224):1523–8.PubMedPubMedCentral
28.
Rimm EB, Willett WC, Hu FB, Sampson L, Colditz GA, Manson JE et al. Folate and vitamin B6 from diet and supplements in relation to risk of coronary heart disease among women. JAMA. 1998;279(5):359–64.PubMed
29.
Osganian SK, Stampfer MJ, Rimm E, Spiegelman D, Hu FB, Manson JE, et al. Vitamin C and risk of coronary heart disease in women. JACC. 2003;42(2):246–52.PubMed
30.
Voight BF, Peloso GM, Orho-Melander M, Frikke-Schmidt R, Barbalic M, Jensen MK, et al. Plasma HDL cholesterol and risk of myocardial infarction: a mendelian randomisation study. Lancet. 2012;380(9841):572–80.PubMedPubMedCentral
31.
Riaz H, Khan SU, Rahman H, Shah NP, Kaluski E, Lincoff AM, et al. Effects of high-density lipoprotein targeting treatments on cardiovascular outcomes: A systematic review and meta-analysis. Eur J Prev Cardiol. 2019;26(5):533–43.PubMed
32.
Davey Smith G, Phillips AN. Correlation without a cause: an epidemiological odyssey. Int J Epidemiol. 2020 (in press).
33.
Rimm EB, Moats C. Alcohol and coronary heart disease: drinking patterns and mediators of effect. Ann Epidemiol. 2007;17(5):S3-7.
34.
Mukamal KJ, Rimm EB. Alcohol consumption: risks and benefits. Curr Atheroscler Rep. 2008;10(6):536–43.PubMed
35.
Grodstein F, Stampfer MJ. Epidemiologic studies on ERT and cardioprotection: state of the art on HRT and cardiovascular disease. In: Crosignani PG, Paoletti R, Sarrel PM, Wenger NK, Meschia M, Soma M. editors. Women’s health in menopause. Medical Science Symposia Series, vol 7. Dordrecht: Springer; 1994.
36.
Hartwig FP, Davies NM, Hemani G, Davey Smith G. Two-sample Mendelian randomization: avoiding the downsides of a powerful, widely applicable but potentially fallible technique. Int J Epidemiol. 2016;45(6):1717–26.PubMed
37.
Ioannidis JPA, Chang CQ, Lam TK, Schully SD, Khoury MJ. The geometric increase in meta-analyses from China in the genomic era. PLOS ONE. 2013;8(6):e65602.PubMedPubMedCentral
38.
Wehby GL, Ohsfeldt RL, Murray JC. ‘Mendelian randomization’ equals instrumental variable analysis with genetic instruments. Stat Med. 2008;27(15):2745–9.PubMedPubMedCentral
39.
Lawlor DA, Windmeijer F, Davey Smith G. Is Mendelian randomization ‘lost in translation?’: Comments on ‘Mendelian randomization equals instrumental variable analysis with genetic instruments’ by Wehby et al. Stat Med. 2008;27(15):2750–5.PubMed
40.
Fisher RA. Statistical methods in genetics. Heredity. 1952;6(1):1–12 ((reprinted in the Int J Epidemiol 2010;39:329–335)).
41.
Fisher Box J, Commentary. On RA Fisher’s Bateson lecture on statistical methods in genetics. Int J Epidemiol. 2010;39(2):335–9.PubMed
42.
Davies NM, Howe LJ, Brumpton B, Havdahl A, Evans DM, Davey Smith G. Within family Mendelian randomization studies. Hum Mol Gen. 2019;28(R2):R170-R9.
43.
Tobin MD, Minelli C, Burton PR, Thompson JR. Commentary: development of Mendelian randomization: from hypothesis test to ‘Mendelian deconfounding’. Int J Epidemiol. 2004;33(1):26–9.PubMed
44.
DiPrete TA, Burik CAP, Koellinger PD. Genetic instrumental variable regression: Explaining socioeconomic and health outcomes in nonexperimental data. PNAS. 2018;115(22):E4970-E9.
45.
Gray R, Wheatley K. How to avoid bias when comparing bone marrow transplantation with chemotherapy. Bone Marrow Transplant. 1991;7:9–12.PubMed
46.
47.
48.
Davey Smith G. Mendelian randomization for strengthening causal inference in observational studies: application to gene x environment interactions. Perspect Psychol Sci. 2010;5(5):527–45.
49.
Beulens JWJ, Rimm EB, Ascherio A, Spiegelman D, Hendriks HFJ, Mukamal KJ. Alcohol consumption and risk for coronary heart disease among men with hypertension. Ann Intern Med. 2007;146(1):10–9.PubMed
50.
Solomon C, Hu F, Stampfer M, Colditz G, Speizer F, Rimm E et al. Moderate alcohol consumption and risk of coronary heart disease among women with type 2 diabetes mellitus. Circulation. 2000;102(5):494–9.PubMed
51.
Millwood IY, Walters RG, Mei XW, Guo Y, Yang L, Bian Z, et al. Conventional and genetic evidence on alcohol and vascular disease aetiology: a prospective study of 500,000 men and women in China. The Lancet. 2019;393(10183):1831–42.
52.
Chen L, Davey Smith G, Harbord RM, Lewis SJ. Alcohol intake and blood pressure: a systematic review implementing a mendelian randomization approach. PLOS Medicine. 2008;5(3):e52.PubMedPubMedCentral
53.
Cho Y, Kwak S, Lewis SJ, Wade KH, Relton CL, Davey Smith G, et al. Exploring the utility of alcohol flushing as an instrumental variable for alcohol intake in Koreans. Sci Rep. 2018;8(1):458.PubMedPubMedCentral
54.
Davey Smith G, Hemani G. Mendelian randomization: genetic anchors for causal inference in epidemiological studies. Hum Mol Genet. 2014;23(R1):R89–98.PubMedPubMedCentral
55.
Brumpton B, Sanderson E, Hartwig FP, Harrison S, Vie G, Cho Y, et al. Within-family studies for Mendelian randomization: avoiding dynastic, assortative mating, and population stratification biases. BioRxiv. 2019:602516.
56.
Haworth S, Mitchell R, Corbin L, Wade KH, Dudding T, Budu-Aggrey A et al. Apparent latent structure within the UK Biobank sample has implications for epidemiological analysis. Nature Commun. 2019;10(1):333.
57.
Lawson DJ, Davies NM, Haworth S, Ashraf B, Howe L, Crawford A, et al. Is population structure in the genetic biobank era irrelevant, a challenge, or an opportunity? Hum Genet. 2020;139(1):23–41.PubMed
58.
Munafo MR, Tilling K, Taylor AE, Evans DM, Davey Smith G. Collider scope: when selection bias can substantially influence observed associations. Int J Epidemiol. 2018;47(1):226–35.PubMed
59.
Taylor AE, Jones HJ, Sallis H, Euesden J, Stergiakouli E, Davies NM, et al. Exploring the association of genetic factors with participation in the Avon Longitudinal Study of Parents and Children. Int J Epidemiol. 2018;47(4):1207–16.PubMedPubMedCentral
60.
Tyrrell J, Zheng J, Beaumont R, Hinton K, Richardson TG, Wood AR, et al. Genetic predictors of participation in optional components of UK Biobank. BioRxiv. 2020:2020.02.10.941328.
61.
Hughes RA, Davies NM, Davey Smith G, Tilling K. Selection bias when estimating average treatment effects using one-sample instrumental variable analysis. Epidemiology. 2019;30(3):350–7.PubMed
62.
Davey Smith G, Ebrahim S. Mendelian randomization: prospects, potentials, and limitations. Int J Epidemiol. 2004;33(1):30–42.
63.
Holmes MV, Dale CE, Zuccolo L, Silverwood RJ, Guo Y, Ye Z et al. Association between alcohol and cardiovascular disease: Mendelian randomisation analysis based on individual participant data. BMJ. 2014;349:g4164.PubMedPubMedCentral
64.
Kong A, Thorleifsson G, Frigge ML, Vilhjalmsson BJ, Young AI, Thorgeirsson TE et al. The nature of nurture: effects of parental genotypes. Science. 2018;359(6374):424–8.PubMed
65.
Warrington NM, Beaumont RN, Horikoshi M, Day FR, Helgeland O, Laurin C, et al. Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors. Nat Genet. 2019;51(5):804–14.PubMedPubMedCentral
66.
Lawlor D, Richmond R, Warrington N, McMahon G, Davey Smith G, Bowden J, et al. Using Mendelian randomization to determine causal effects of maternal pregnancy (intrauterine) exposures on offspring outcomes: Sources of bias and methods for assessing them. Wellcome Open Res. 2017;2:11.PubMedPubMedCentral
67.
Zuccolo L, Lewis SJ, Davey Smith G, Sayal K, Draper ES, Fraser R, et al. Prenatal alcohol exposure and offspring cognition and school performance. A ‘Mendelian randomization’ natural experiment. Int J Epidemiol. 2013;42(5):1358–70.PubMedPubMedCentral
68.
Howe LJ, Lawson DJ, Davies NM, St. Pourcain B, Lewis SJ, Davey Smith G, et al. Genetic evidence for assortative mating on alcohol consumption in the UK Biobank. Nature Comms. 2019;10(1):5039.
69.
Carreras-Torres R, Johansson M, Haycock PC, Wade KH, Relton CL, Martin RM et al. Obesity, metabolic factors and risk of different histological types of lung cancer: a Mendelian randomization study. PLoS One. 2017;12(6):e0177875.PubMedPubMedCentral
70.
Haycock PC, Burgess S, Wade KH, Bowden J, Relton C, Davey Smith G. Best (but oft-forgotten) practices: the design, analysis, and interpretation of Mendelian randomization studies. Am J Clin Nutr. 2016;103(4):965–78.PubMedPubMedCentral
71.
Stock J, Yogo M. Testing for weak instruments in linear IV regression. In: Andrews D, Stock J, Rothenberg T, editors. Identification and inference for econometric models: essays in Honor of Thomas Rothenberg. Cambridge: Cambridge University Press; 2005.
72.
Lawlor DA, Nordestgaard BG, Benn M, Zuccolo L, Tybjaerg-Hansen A, Davey Smith G. Exploring causal associations between alcohol and coronary heart disease risk factors: findings from a Mendelian randomization study in the Copenhagen General Population Study. Eur Heart J. 2013;34(32):2519–28.PubMed
73.
Greene W. Econometric Analysis. Prentice Hall. 1993;2nd edition:284-6.
74.
Hemani G, Bowden J, Davey Smith G. Evaluating the potential role of pleiotropy in Mendelian randomization studies. Hum Mol Genet. 2018;27(R2):R195-r208.PubMedPubMedCentral
75.
Wagner GP, Zhang J. The pleiotropic structure of the genotype-phenotype map: the evolvability of complex organisms. Nat Rev Genet. 2011;12(3):204–13.PubMed
76.
77.
Lewis SJ, Davey Smith G. Alcohol ALDH2, and esophageal cancer: a meta-analysis which illustrates the potentials and limitations of a Mendelian randomization approach. Cancer Epidemiol Biomarkers Prev. 2005;14(8):1967–71.PubMed
78.
Boccia S, Hashibe M, Gallì P, De Feo E, Asakage T, Hashimoto T et al. Aldehyde dehydrogenase 2 and head and neck cancer: a meta-analysis implementing a mendelian randomization approach. Cancer Epidemiol Biomarkers Prev. 2009;18(1):248–54.
79.
Burgess S, Davies NM, Thompson SG, Consortium EP-I. Instrumental variable analysis with a nonlinear exposure-outcome relationship. Epidemiology (Cambridge Mass). 2014;25(6):877–85.
80.
Davey Smith G. Epidemiology, epigenetics and the ‘Gloomy Prospect’: embracing randomness in population health research and practice. Int J Epidemiol. 2011;40(3):537–62.
81.
Sanderson E, Davey Smith G, Windmeijer F, Bowden J. An examination of multivariable Mendelian randomization in the single-sample and two-sample summary data settings. Int J Epidemiol. 2018;48(3):713–27.PubMedCentral
82.
Rosoff DB, Davey Smith G, Mehta N, Clarke T-K, Lohoff FW. Evaluating the effects of alcohol and tobacco use on cardiovascular disease using multivariable Mendelian randomization. bioRxiv. 2019:757146.
83.
Richardson TG, Sanderson E, Elsworth B, Tilling K, Davey Smith G. Harnessing genetic variation to separate the effects of early and later life adiposity on disease risk: mendelian randomization study. BMJ 2020 (in press).
84.
Rimm E, Alcohol. Can we learn more? Epidemiology. 2001;12(4):380–2.PubMed
85.
Keavney B, Danesh J, Parish S, Palmer A, Clark S, Youngman L, et al. Fibrinogen and coronary heart disease: test of causality by ‘Mendelian randomization’. Int J Epidemiol. 2006;35(4):935–43.PubMed
86.
87.
Michaels D. The Triumph of doubt: dark money and the science of deception. New York: Oxford University Press; 2020.
88.
89.
Mitchell G, Lesch M, McCambridge J. Alcohol industry involvement in the moderate alcohol and cardiovascular health trial. Am J Public Health. 2020;110 (4):485–88.
90.
Stampfer MJ, Malinow MR, Willett WC, Newcomer LM, Upson B, Ullmann D et al. A prospective study of plasma homocyst(e)ine and risk of myocardial infarction in US physicians. JAMA. 1992;268(7):877–81.PubMed
91.
Lewis SJ, Ebrahim S, Davey Smith G. Meta-analysis of MTHFR 677C→ T polymorphism and coronary heart disease: does totality of evidence support causal role for homocysteine and preventive potential of folate? BMJ. 2005;331(7524):1053.PubMedPubMedCentral
92.
Clarke R, Bennett DA, Parish S, Verhoef P, Dötsch-Klerk M, Lathrop M, et al. Homocysteine and coronary heart disease: meta-analysis of MTHFR case-control studies, avoiding publication bias. PLoS Med. 2012;9(2):e1001177-e.
93.
Marti-Carvajal AJ, Sola I, Lathyris D, Dayer M. Homocysteine-lowering interventions for preventing cardiovascular events. Cochrane Database Syst Rev. 2017;8:Cd006612.PubMed
94.
Forman JP, Rimm EB, Stampfer MJ, Curhan GC. Folate Intake and the risk of incident hypertension among US women. JAMA. 2005;293(3):320–9.PubMed
95.
Hines LM, Stampfer MJ, Ma J, Gaziano JM, Ridker PM, Hankinson SE, et al. Genetic variation in alcohol dehydrogenase and the beneficial effect of moderate alcohol consumption on myocardial infarction. N Engl J Med. 2001;344(8):549–55.PubMed
96.
Colhoun HM, McKeigue PM, Davey Smith G. Problems of reporting genetic associations with complex outcomes. Lancet. 2003;361(9360):865–72.PubMed
97.
Jensen MK, Mukamal KJ, Overvad K, Rimm EB. Alcohol consumption, TaqIB polymorphism of cholesteryl ester transfer protein, high-density lipoprotein cholesterol, and risk of coronary heart disease in men and women. Eur Heart J. 2008;29(1):104–12.PubMed
98.
Ference BA, Kastelein JJP, Ginsberg HN, Chapman MJ, Nicholls SJ, Ray KK et al. Association of Genetic variants related to CETP inhibitors and statins with lipoprotein levels and cardiovascular risk. JAMA. 2017;318(10):947–56.PubMedPubMedCentral
99.
Holmes MV, Davey Smith G, Dyslipidaemia. Revealing the effect of CETP inhibition in cardiovascular disease. Nat Rev Cardiol. 2017;14(11):635–6.PubMedPubMedCentral
100.
Kalin S, Rimm E. Folate and vascular disease: epidemiological perspective. In: Bailey L, editor. Folate in health and disease. 2nd ed. Boca Raton: CRC Press; 2009. pp 263–90.
101.
Munafo MR, Davey Smith G. Robust research needs many lines of evidence. Nature. 2018;553(7689):399–401.PubMed
102.
Davey Smith G, Ebrahim S. Folate supplementation and cardiovascular disease. Lancet. 2005;366(9498):1679–81.PubMed
103.
Davey Smith G, Ebrahim S. Folate supplementation and cardiovascular disease—Authors’ reply. Lancet. 2006;367(9518):1238–9.
104.
Inoshita M, Numata S, Tajima A, Kinoshita M, Umehara H, Nakataki M et al. Retraction: A significant causal association between C-reactive protein levels and schizophrenia. Sci Rep. 2018;8:46947.PubMedPubMedCentral
105.
Davey Smith G. Increasing the accessibility of data. BMJ. 1994;308(6943):1519–20.
106.
Manousaki D, Mokry LE, Ross S, Goltzman D, Richards B. Mendelian randomization studies do not support a role for vitamin D in coronary artery disease. Circ Cardiovascular Genetics. 2016;9(4):349–56.PubMed
107.
Yoshizawa K, Willett WC, Morris SJ, Stampfer MJ, Spiegelman D, Rimm EB et al. Study of prediagnostic selenium level in toenails and the risk of advanced prostate cancer. JNCI. 1998;90(16):1219–24.PubMed
108.
Yarmolinsky J, Bonilla C, Haycock PC, Langdon RJQ, Lotta LA, Langenberg C et al. Circulating selenium and prostate cancer risk: a mendelian randomization analysis. JNCI. 2018;110(9):1035–8.PubMed
109.
Millen AE, Dodd KW, Subar AF. Use of vitamin, mineral, nonvitamin, and nonmineral supplements in the United States: the 1987, 1992, and 2000 National Health Interview Survey results. J Am Diet Assoc. 2004;104(6):942–50.PubMed
110.
Kantor ED, Rehm CD, Du M, White E, Giovannucci EL. Trends in dietary supplement use among US adults from 1999–2012. JAMA. 2016;316(14):1464–74.PubMedPubMedCentral
111.
Eidelman RS, Hollar D, Hebert PR, Lamas GA, Hennekens CH. Randomized trials of vitamin E in the treatment and prevention of cardiovascular disease. Arch Intern Med. 2004;164(14):1552–6.PubMed
Metadata
Title
Mendel’s laws, Mendelian randomization and causal inference in observational data: substantive and nomenclatural issues
Authors
George Davey Smith
Michael V. Holmes
Neil M. Davies
Shah Ebrahim
Publication date
01-02-2020
Publisher
Springer Netherlands
Published in
European Journal of Epidemiology / Issue 2/2020
Print ISSN: 0393-2990
Electronic ISSN: 1573-7284
DOI
https://doi.org/10.1007/s10654-020-00622-7

Other articles of this Issue 2/2020

European Journal of Epidemiology 2/2020 Go to the issue

CARDIOVASCULAR DISEASE

Serum albumin and atrial fibrillation: insights from epidemiological and mendelian randomization studies

NEW STUDY

Rationale and Design of the Hamburg City Health Study

CORRESPONDENCE

Authors’ reply to ‘Multiple comparisons controversies are about context and costs, not frequentism versus Bayesianism’

NEURO-EPIDEMIOLOGY

Observational and genetic studies of short telomeres and Alzheimer’s disease in 67,000 and 152,000 individuals: a Mendelian randomization study

CORRESPONDENCE

On the relationship of machine learning with causal inference

COHORT PROFILE

Lifelines NEXT: a prospective birth cohort adding the next generation to the three-generation Lifelines cohort study