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 (Endogeneity) Reverse causation Alcohol consumption Heart disease Socio-economic status ? Associated with both exposure and outcome Not on causal pathway from exposure to outcome Well-beingBodyweight ? ?

Observation vs Randomisation 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

Mendelian Randomisation 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 Gene that influences alcohol consumption Heart disease Socio-economic status ? X X

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%

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%

Intervention trial Randomisation to judge causality RCT Sample Randomisation InterventionControl Event rate lower Event rate higher Mendelian randomisation Population Random allocation of alleles Genotype aaGenotype AA Event rate lower Event rate higher Genetics

Mendelian Randomisation technique Instrumental variable analysis MR relies upon three key assumptions 1.The gene Z is associated with exposure of interest X 2.The gene Z is independent of confounding factors U (that confound X-Y association) 3.The gene Z is related to the outcome Y only via its association with the modifiable exposure X Modifiable Exposure Outcome Genotype Confounders U Y X Z

Alcohol and Cardiovascular disease Corrao et al., 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

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) acetaldehydealcohol acetate water ALCOHOL DEHYDROGENASE (ADH) ALDEHYDE DEHYDROGENASE-2 (ALDH2) More active ADH variants / less active ALDH2 variants associated with higher acetaldehyde concentration  unpleasant side effects  lower alcohol intake “Flushing” response Caroline Dale

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 Alcohol intake Markers for CVD ADH1B Genotype SES, diet etc U Y X Z

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

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

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

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

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

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

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