1 / 19

What is Mendelian Randomisation?

What is Mendelian Randomisation?. Frank Dudbridge. Short answer. Instrumental Variable Analysis with a gene as the instrument A method for making causal statements from observational data. Association is not causation. Two major problems in observational data are: Confounding

gella
Télécharger la présentation

What is Mendelian Randomisation?

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. What isMendelian Randomisation? Frank Dudbridge

  2. Short answer • Instrumental Variable Analysis with a gene as the instrument • A method for making causal statements from observational data

  3. Association is not causation • Two major problems in observational data are: • Confounding (Endogeneity) • Reverse causation • Associated with both exposure and outcome • Not on causal pathway from exposure to outcome Socio-economic status ? Alcohol consumption Heart disease ? Bodyweight Well-being ?

  4. Observation vsRandomisation • In randomised intervention studies, confounding and reverse causation are reduced or even eliminated • Groups differ only in the intervention received, and by no other characteristics • Events that follow treatment (in time) are more likely to be caused by the treatment • But randomisation is not always possible • Effects of smoking or alcohol • Socio-economic effects • Observational studies are the only ethical option

  5. MendelianRandomisation principle • Genes are randomly allocated, independent of confounders • Genes cause phenotypes, but phenotypes do not cause genes • Therefore, a gene that causes the exposure of interest can be a proxy for that exposure Socio-economic status X ? Gene that influences alcohol consumption Heart disease X

  6. Mendel’s first law • Law of segregation: Two copies of a gene have an equal probability of being transmitted to an offspring • “Random allocation at conception” 50% 50%

  7. Mendel’s second law • Law of independent assortment: each gene is distributed randomly and independently from genes for other characteristics • “Random allocation at conception” independent of confounders 25% 25% 25% 25%

  8. Randomisation to judge causality Genetics Intervention trial RCT Mendelian randomisation Sample Population Randomisation Random allocation of alleles Intervention Control Genotype aa Genotype AA Event rate lower Event rate higher Event rate lower Event rate higher

  9. MendelianRandomisation techniqueInstrumental variable analysis MR relies upon three key assumptions • The gene Z is associated with exposure of interest X • The gene Z is independent of confounding factors U (that confound X-Y association) • The gene Z is related to the outcome Yonly via its association with the modifiable exposure X Confounders U Y X Z Outcome Modifiable Exposure Genotype

  10. Alcohol and Cardiovascular disease Corrao et al., 2000 • 1 UK alcohol unit = 8g ethanol • UK recommended limits = 3-4 units per day for men; 2-3 units per day women Slide by Caroline Dale

  11. Alcohol metabolising genes • Heritability of alcoholism estimated at 40-60% (Goldman et al., 2005) • Many genes influence propensity to drink • Alcohol metabolising enzymes (ALDH2, ADH1B, ADH1C) • Neurotransmitter receptors (GABRA2, DRD4, DRD2) acetate ALCOHOL DEHYDROGENASE (ADH) ALDEHYDE alcohol acetaldehyde DEHYDROGENASE - 2 (ALDH2) water “Flushing” response • More active ADH variants / less active ALDH2 variants associated with higher acetaldehyde concentration  unpleasant side effects  lower alcohol intake Caroline Dale

  12. ADH1B – CVD collaboration Large collaborative effort to describe causal effects of alcohol intake on cardiovasular markers • >16 studies with >56,000 subjects and >45 measurements SES, diet etc U Y X Z Markers for CVD Alcohol intake ADH1B Genotype

  13. Objective 1:Association with alcohol phenotypes SES, diet etc U Y X Z Markers for CVD Alcohol ADH1B

  14. Objective 2: No association with potential confounders SES, diet etc U X Y X Z Markers for CVD Alcohol ADH1B

  15. Objective 3:Association with CVD biomarkers SES, diet etc U Y X Z Markers for CVD Alcohol ADH1B X

  16. Causal effect of alcohol on blood pressure • Effect of gene on systolic BP = -1.19 mmHg • Effect of gene on log weekly units of alcohol = -0.16 units • Therefore, effect on SBP of increasing alcohol by one log unit is -1.19/-0.16 = 7.4375 mmHG • Equivalent to multiplying alcohol intake by 2.72 units SES, diet etc U -1.19 Y -0.16 X Z Systolic BP 1.19/0.16 Alcohol intake ADH1B Genotype

  17. Issues in Mendelian randomisation Among many other issues, two important ones are • Pleiotropy • Gene affects traits other than the phenotype in question • This can invalidate the MR assumptions • Weak instrument bias • If the gene predicts the phenotype poorly, then the MR estimate is biased and unstable • Most genes have very weak effects on modifiable exposures • Both problems can be reduced by combining multiple genes into a composite instrument

  18. Multiple genes used for Mendelian Randomisation Among many other issues, two important ones are • Pleiotropy • Gene affects traits other than the exposure in question • This can invalidate the MR assumptions • Weak instrument bias • If the gene predicts the exposure poorly, the MR estimate becomes biased and unstable • Most genes have very weak effects on complex traits • Both problems can be reduced by combining multiple genes into a composite instrument Juan-Pablo Casas

  19. Thanks • LSHTM • Caroline Dale • Michael Holmes • Richard Silverwood • Juan Pablo Casas • Dave Leon • Bristol • Tom Palmer • Debbie Lawlor

More Related