distinguishing genetic correlation from causation among 52 ... · distinguishing genetic...
TRANSCRIPT
![Page 1: Distinguishing genetic correlation from causation among 52 ... · Distinguishing genetic correlation from causation among 52 diseases and complex traits Luke J O'Connor Harvard T.H](https://reader031.vdocuments.us/reader031/viewer/2022040717/5e223fda61979861aa361cd7/html5/thumbnails/1.jpg)
Distinguishing genetic correlation from causationamong 52 diseases and complex traits
Luke J O'ConnorHarvard T.H. Chan School of Public Health
Pre-print on biorxiv
![Page 2: Distinguishing genetic correlation from causation among 52 ... · Distinguishing genetic correlation from causation among 52 diseases and complex traits Luke J O'Connor Harvard T.H](https://reader031.vdocuments.us/reader031/viewer/2022040717/5e223fda61979861aa361cd7/html5/thumbnails/2.jpg)
What is a genetic correlation?
Psychiatric Genomics Consortium 2013 Nat Genet; Bulik-Sullivan et al. 2015b Nat Genet
Correlation across SNPs Correlation across Individuals
![Page 3: Distinguishing genetic correlation from causation among 52 ... · Distinguishing genetic correlation from causation among 52 diseases and complex traits Luke J O'Connor Harvard T.H](https://reader031.vdocuments.us/reader031/viewer/2022040717/5e223fda61979861aa361cd7/html5/thumbnails/3.jpg)
What is Mendelian Randomization?
Primary motivation: modifiable exposures to reduce disease risk
If LDL causes CAD: (Voight et al. 2012 Lancet)
– SNPs associated high LDL are associated with higher CAD risk– Individuals with high LDL alleles have higher CAD risk
If LDL does not cause CAD, and no genetic correlation due topleiotropy:– SNPs associated high LDL are not associated with CAD– Individuals with high LDL alleles have equal CAD risk
![Page 4: Distinguishing genetic correlation from causation among 52 ... · Distinguishing genetic correlation from causation among 52 diseases and complex traits Luke J O'Connor Harvard T.H](https://reader031.vdocuments.us/reader031/viewer/2022040717/5e223fda61979861aa361cd7/html5/thumbnails/4.jpg)
Mendelian randomization is geneticcorrelation restricted to top SNPs
Davey Smith and Hemani 2014 Hum Mol Genet; Bulik-Sullivan et al. 2015b Nat Genet
Regress SNP effects Regress genetic values
![Page 5: Distinguishing genetic correlation from causation among 52 ... · Distinguishing genetic correlation from causation among 52 diseases and complex traits Luke J O'Connor Harvard T.H](https://reader031.vdocuments.us/reader031/viewer/2022040717/5e223fda61979861aa361cd7/html5/thumbnails/5.jpg)
Pleiotropy is common
Pickrell et al 2016 Nat Genet
Pleiotropy: same variantaffects multiple traits
– Effects may or maynot be correlated
– May or may not bedue to causalrelationship betweentraits
![Page 6: Distinguishing genetic correlation from causation among 52 ... · Distinguishing genetic correlation from causation among 52 diseases and complex traits Luke J O'Connor Harvard T.H](https://reader031.vdocuments.us/reader031/viewer/2022040717/5e223fda61979861aa361cd7/html5/thumbnails/6.jpg)
Genetic Correlations are common
Bulik-Sullivan et al 2015b Nat Genet
![Page 7: Distinguishing genetic correlation from causation among 52 ... · Distinguishing genetic correlation from causation among 52 diseases and complex traits Luke J O'Connor Harvard T.H](https://reader031.vdocuments.us/reader031/viewer/2022040717/5e223fda61979861aa361cd7/html5/thumbnails/7.jpg)
Bidirectional MR distinguishes correlationfrom causation?
If A has a causal effect on B, then:
Pickrell et al 2016 Nat Genet
– Most variants ascertainedfor B do not affect A
– All variants ascertainedfor A do affect B
![Page 8: Distinguishing genetic correlation from causation among 52 ... · Distinguishing genetic correlation from causation among 52 diseases and complex traits Luke J O'Connor Harvard T.H](https://reader031.vdocuments.us/reader031/viewer/2022040717/5e223fda61979861aa361cd7/html5/thumbnails/8.jpg)
Outline
1. Latent Causal Variable model to distinguishcorrelation from causation
2. Comparison with MR in simulations
3. Application to MI and other traits
![Page 9: Distinguishing genetic correlation from causation among 52 ... · Distinguishing genetic correlation from causation among 52 diseases and complex traits Luke J O'Connor Harvard T.H](https://reader031.vdocuments.us/reader031/viewer/2022040717/5e223fda61979861aa361cd7/html5/thumbnails/9.jpg)
Latent causal variable model
Value of trait kEffect of on
Latent causal variable
![Page 10: Distinguishing genetic correlation from causation among 52 ... · Distinguishing genetic correlation from causation among 52 diseases and complex traits Luke J O'Connor Harvard T.H](https://reader031.vdocuments.us/reader031/viewer/2022040717/5e223fda61979861aa361cd7/html5/thumbnails/10.jpg)
Latent causal variable model
Genotype
Value of trait kEffect of on
Latent causal variable
Effect of on Effect of on not mediated by
![Page 11: Distinguishing genetic correlation from causation among 52 ... · Distinguishing genetic correlation from causation among 52 diseases and complex traits Luke J O'Connor Harvard T.H](https://reader031.vdocuments.us/reader031/viewer/2022040717/5e223fda61979861aa361cd7/html5/thumbnails/11.jpg)
When
Special case: full genetic causality
Genotype
Value of trait kEffect of on
Latent causal variable
Effect of on Effect of on not mediated by
![Page 12: Distinguishing genetic correlation from causation among 52 ... · Distinguishing genetic correlation from causation among 52 diseases and complex traits Luke J O'Connor Harvard T.H](https://reader031.vdocuments.us/reader031/viewer/2022040717/5e223fda61979861aa361cd7/html5/thumbnails/12.jpg)
Genetic causality proportion measuresdegree of partial causality
Genetic causality proportion (gcp): number x such that
gcp=1: trait 1 fully genetically causal for trait 2
gcp=-1: trait 2 fully genetically causal for trait 1
gcp=0: no partial causality
![Page 13: Distinguishing genetic correlation from causation among 52 ... · Distinguishing genetic correlation from causation among 52 diseases and complex traits Luke J O'Connor Harvard T.H](https://reader031.vdocuments.us/reader031/viewer/2022040717/5e223fda61979861aa361cd7/html5/thumbnails/13.jpg)
Key intuition: if trait 1 causal, then SNPsaffecting trait 1 have proportional effects ontrait 2, but not vice versaKey equation: relates mixed fourth momentswith q under the LCV model
Inference using mixed fourth moments
![Page 14: Distinguishing genetic correlation from causation among 52 ... · Distinguishing genetic correlation from causation among 52 diseases and complex traits Luke J O'Connor Harvard T.H](https://reader031.vdocuments.us/reader031/viewer/2022040717/5e223fda61979861aa361cd7/html5/thumbnails/14.jpg)
Key equation relates mixed fourth momentswith q
Excess kurtosis (zerowhen Gaussian)
Estimate fromsummary statistics
Genetic correlation(estimate using LDSC)Want
![Page 15: Distinguishing genetic correlation from causation among 52 ... · Distinguishing genetic correlation from causation among 52 diseases and complex traits Luke J O'Connor Harvard T.H](https://reader031.vdocuments.us/reader031/viewer/2022040717/5e223fda61979861aa361cd7/html5/thumbnails/15.jpg)
Posterior estimation of gcp
Mixed 4th moments, block jackknife →approximate likelihood
Uniform prior → posterior mean, standard error
Hypothesis testing: does gcp = 0?
![Page 16: Distinguishing genetic correlation from causation among 52 ... · Distinguishing genetic correlation from causation among 52 diseases and complex traits Luke J O'Connor Harvard T.H](https://reader031.vdocuments.us/reader031/viewer/2022040717/5e223fda61979861aa361cd7/html5/thumbnails/16.jpg)
Outline
1. Latent Causal Variable model to distinguishcorrelation from causation
2. Comparison with MR in simulations
3. Application to MI and other traits
![Page 17: Distinguishing genetic correlation from causation among 52 ... · Distinguishing genetic correlation from causation among 52 diseases and complex traits Luke J O'Connor Harvard T.H](https://reader031.vdocuments.us/reader031/viewer/2022040717/5e223fda61979861aa361cd7/html5/thumbnails/17.jpg)
Simulations: comparison with MR methods
● Comparison with:– Two-sample MR (Burgess et al. 2013 Genet Epidemiol)
– MR-Egger (Bowden et al. 2015 Int J Epidemiol)
– Bidirectional MR (Pickrell et al. 2016 Nat Genet)
● M=50k no LD● N=100k disjoint cohorts
● h2g = 0.3, h2
GWAS ~ 0.15
![Page 18: Distinguishing genetic correlation from causation among 52 ... · Distinguishing genetic correlation from causation among 52 diseases and complex traits Luke J O'Connor Harvard T.H](https://reader031.vdocuments.us/reader031/viewer/2022040717/5e223fda61979861aa361cd7/html5/thumbnails/18.jpg)
Uncorrelated pleiotropic effects: all methodswell calibrated
● Pleiotropic SNPs explaining 20%of heritability for both traits
● Zero genetic correlation
![Page 19: Distinguishing genetic correlation from causation among 52 ... · Distinguishing genetic correlation from causation among 52 diseases and complex traits Luke J O'Connor Harvard T.H](https://reader031.vdocuments.us/reader031/viewer/2022040717/5e223fda61979861aa361cd7/html5/thumbnails/19.jpg)
Nonzero genetic correlation: MRconfounded
● SNPs with correlated pleiotropiceffects explaining 20% ofheritability for both traits
● Genetic correlation: 0.2
![Page 20: Distinguishing genetic correlation from causation among 52 ... · Distinguishing genetic correlation from causation among 52 diseases and complex traits Luke J O'Connor Harvard T.H](https://reader031.vdocuments.us/reader031/viewer/2022040717/5e223fda61979861aa361cd7/html5/thumbnails/20.jpg)
Unequal polygenicity between traits: Bi-MR(and MR) confounded
● SNPs affecting trait 1 only: highper-SNP heritability
● SNPs affecting trait 2 only: lowper-SNP heritability (4x difference)
● Genetic correlation: 0.2● Similar results for unequal power
![Page 21: Distinguishing genetic correlation from causation among 52 ... · Distinguishing genetic correlation from causation among 52 diseases and complex traits Luke J O'Connor Harvard T.H](https://reader031.vdocuments.us/reader031/viewer/2022040717/5e223fda61979861aa361cd7/html5/thumbnails/21.jpg)
Full genetic causality: all methods (exceptMR-Egger) well powered
● All SNPs affecting trait 1 alsoaffect trait 2
● Genetic correlation: 0.2● High power in more challenging
simulations as well
![Page 22: Distinguishing genetic correlation from causation among 52 ... · Distinguishing genetic correlation from causation among 52 diseases and complex traits Luke J O'Connor Harvard T.H](https://reader031.vdocuments.us/reader031/viewer/2022040717/5e223fda61979861aa361cd7/html5/thumbnails/22.jpg)
Unbiased posterior estimates in simulationswith LD
● Real LD patterns● gcp values drawn from
prior distribution● Unequal polygenicity and
power● Unbiasedness:
![Page 23: Distinguishing genetic correlation from causation among 52 ... · Distinguishing genetic correlation from causation among 52 diseases and complex traits Luke J O'Connor Harvard T.H](https://reader031.vdocuments.us/reader031/viewer/2022040717/5e223fda61979861aa361cd7/html5/thumbnails/23.jpg)
Outline
1. Latent Causal Variable model to distinguishcorrelation from causation
2. Comparison with MR in simulations
3. Application to MI and other traits
![Page 24: Distinguishing genetic correlation from causation among 52 ... · Distinguishing genetic correlation from causation among 52 diseases and complex traits Luke J O'Connor Harvard T.H](https://reader031.vdocuments.us/reader031/viewer/2022040717/5e223fda61979861aa361cd7/html5/thumbnails/24.jpg)
Application to 52 traits
● Summary statistic data:– 37 UK Biobank traits including MI (N=460k)– 16 other traits (average N=43k)
● Nominally significant genetic correlation: 430 trait pairs● Significant partial causality: 63 trait pairs (1% FDR)
– Many have low gcp estimates: probably not fullgenetic causality
![Page 25: Distinguishing genetic correlation from causation among 52 ... · Distinguishing genetic correlation from causation among 52 diseases and complex traits Luke J O'Connor Harvard T.H](https://reader031.vdocuments.us/reader031/viewer/2022040717/5e223fda61979861aa361cd7/html5/thumbnails/25.jpg)
Trait 1 Gen corr LCV p-val gcp est MR Ref
BMI 0.34 (0.09) 5x10-9 0.94 (0.11) Holmes 2014
Triglycerides 0.30 (0.06) 2x10-31 0.90 (0.08) Do 2013
LDL 0.17 (.08) 4x10-31 0.73 (.13) Voight 2012
Hypothyroidism 0.26 (0.05) 1x10-11 0.72 (0.16) Zhao 2017(null)
High cholesterol 0.52 (0.12) 2x10-4 0.71 (0.19) Voight 2012
Fasting glucose 0.19 (0.07) 4x10-4 0.62 (0.23) Ahmad 2015(T2D)
Traits affecting myocardial infarction:consistent with known biology
![Page 26: Distinguishing genetic correlation from causation among 52 ... · Distinguishing genetic correlation from causation among 52 diseases and complex traits Luke J O'Connor Harvard T.H](https://reader031.vdocuments.us/reader031/viewer/2022040717/5e223fda61979861aa361cd7/html5/thumbnails/26.jpg)
Effect of LDL on BMD consistent with RCTs
Trait 1 Trait 2 Gen corr LCV p-val gcp est MR ref
LDL BMD -0.12 (.05) 7x10-34 0.80 (.12)
● Familial defective apolipoprotein B-100: leads to highLDL and low BMD (Yerges-Armstrong et al. 2013 J Endocrinol Metab)
● Effect of statins on BMD in 7 trial meta-analysis (Wang etal. 2016 Medicine)
– Not interpreted specifically as evidence for an effect of LDL
– Modest effect size concordant with modest genetic correlation
![Page 27: Distinguishing genetic correlation from causation among 52 ... · Distinguishing genetic correlation from causation among 52 diseases and complex traits Luke J O'Connor Harvard T.H](https://reader031.vdocuments.us/reader031/viewer/2022040717/5e223fda61979861aa361cd7/html5/thumbnails/27.jpg)
Summary
● MR methods can be confounded by geneticcorrelations
● Partial genetic causality measured by genetic causalityproportion (gcp)
● LCV produces unbiased estimates of gcp and well-calibrated p-values
● LCV recapitulates known biology and identifies novelputative causal relationships
![Page 28: Distinguishing genetic correlation from causation among 52 ... · Distinguishing genetic correlation from causation among 52 diseases and complex traits Luke J O'Connor Harvard T.H](https://reader031.vdocuments.us/reader031/viewer/2022040717/5e223fda61979861aa361cd7/html5/thumbnails/28.jpg)
Acknowledgements
Alkes Price
Soumya Raychaudhuri
Ben Neale
Chirag Patel
Members of the Price lab
UK Biobank
Pre-print on biorxiv
Related work at ASHG2017: Morrison et al. poster 3004W