What isMendelian Randomisation?

Frank Dudbridge

Short answer

• Instrumental Variable Analysiswith 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% 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% 25% 25% 25%

Intervention trial

Randomisation to judge causality

RCT

Sample

Randomisation

Intervention Control

Event ratelower

Event ratehigher

Mendelian randomisation

Population

Random allocation of alleles

Genotype aa Genotype AA

Event ratelower

Event ratehigher

Genetics

Mendelian Randomisation techniqueInstrumental variable analysis

MR relies upon three key assumptions1. The gene Z is associated with exposure of interest X2. 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 OutcomeGenotype

Confounders

U

YXZ

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

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

ALCOHOLDEHYDROGENASE (ADH)

ALDEHYDEDEHYDROGENASE-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 CVDADH1B Genotype

SES, diet etc

U

YXZ

Objective 1:Association with alcohol phenotypes

Alcohol Markers for CVDADH1B

U

YXZ

SES, diet etc

Objective 2: No association with potential confounders

Alcohol Markers for CVDADH1B

U

YXZ

SES, diet etc

X

Objective 3:Association with CVD biomarkers

Alcohol Markers for CVDADH1B

U

YXZ

SES, diet etc

X

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

Alcohol intake Systolic BPADH1B Genotype

SES, diet etc

U

YXZ-0.16

-1.19

1.19/0.16

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