Leveraging admixture analysis to resolve missing and crosspopulation. Noah Zaitlen

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1 Leveraging admixture analysis to resolve missing and crosspopulation heritability. Noah Zaitlen

2 Outline Background Yes, those three slides again. Local-ancestry based heritability estimation Cross-Population Heritability This abstract was not previously published elsewhere.

3 Total Number of Publications We have performed A LOT of GWAS Published GWA Reports, 005 9/ Calendar Quarter Through 9/30/10 postings

4 And have identified 1000s of variants associated with 100s of phenotypes NHGRI GWA Catalog,

5 Silventoinen et al, 003 Twin Research An estimated 80% of variation in height driven is driven by genetics

6 But GWAS explain only 10% of the variation in height h GWAS : The narrow-sense heritability explained by summing the effects of GWAS identified SNPs. Lango Allen et al, 010 Nature

7 GWAS have the potential to explain 45% of the variation in height h g : The narrow-sense heritability explained by all genotyped SNPs. Yang et al, 010 Nature Genetics

8 Where is the missing heritability? Rare Variants Weak effects Gene-Environment & Gene-Gene Interactions Structural Variants Parent of Origin Effects Inflated heritability estimates Maher 008 Nature; Manolio et al. 009 Nature, Gibson 01 Nature Reviews Genetics

9 Where is the missing heritability? Rare Variants Weak effects Gene-Environment & Gene-Gene Interactions Structural Variants Parent of Origin Effects Inflated heritability estimates Zuk et al PNAS 01

10 H h Use of relatives in heritability estimation can cause inflation Non-Additive SNPs (Dominance, Over-,Under-) Epistasis: Even in MZ/DZ studies [Zuk et al PNAS 01] Gene-Environment Interactions Shared Environment: Average Heritability of 37 Phenotypes Zaitlen et al, 01 Under Revision PLoS Genetics

11 Use of relatives does cause inflation: H h in yeast for many phenotypes Bloom et al arxiv 01

12 Outline Background Local-ancestry based heritability estimation Using unrelated individuals!!! Cross-Population Heritability

13 Admixed individuals have mosaic genomes from multiple distinct populations Europeans Africans After generation 10 Seldin etal. 011 Nat Rev Genet.

14 We can estimate the heritability explained by genotyped SNPs: Haplotype Haplotype Genotype 1 0 Copies of ref allele h g : The heritability explained by genotyped SNPs Yang et al, 010 Nature Genetics

15 We can also estimate the heritability explained by variation in local-ancestry: Haplotype Haplotype Local-ancestry 0 1 Copies of red ancestry h : The heritability explained by local-ancestry Genotype 1 0 Copies of ref allele h g : The heritability explained by genotyped SNPs

16 h unlike h g is driven by all causal variants not just those on the genotyping platform Haplotype Haplotype Local-ancestry 0 1 Copies of red ancestry h : The heritability explained by local-ancestry Genotype 1 0 Copies of ref allele h g : The heritability explained by genotyped SNPs

17 h is driven by, F st, and the admixture proportion h Height Increasing Alleles P EUR P AFR Height with Afr Alleles Height with Eur Alleles SNP Lower Higher SNP Average Average Under the model assumptions: Polygenic trait No selection at causal variants h h ** Fst * *(1) Estimated from data via variance components. Estimated from reference panels. Estimated from data.

18 Simulated Genotypes and Phenotypes Global ancestry drawn uniformly ( ) Local ancestry drawn from Binomial with mean = global ancestry Ancestral MAF = p Current MAF drawn from N(p,Fst*p(1-p)) One SNP per ancestry segment Infinitesimal model of disease Result: Under all parameter settings we converge to the correct heritability.

19 Real Genotypes and Simulated Phenotypes Multiple variants per ancestry block and LD Errors in local ancestry estimation Real distribution of admixture proportion 5,040 unrelated African-Americans (CARe) Local-Ancestry calls via HapMix Polygenic and Infinitesimal models Under all parameter settings, our estimates of h are within 1 sd (0.001) of the true h after 10,000 iterations. from h

20 Local-ancestry based heritability estimates are lower than twin based estimates Phenotype h g h (via h ) h (via rels) HDL 0. (0.07) (0.11) 0.47, 0.48 LDL 0.16 (0.07) (0.09) 0.37 Height 0.31 (0.07) 0.55 (0.13) 0.80 Yang et al 010 Nat Gen: Height Vattikuti et al 01 PloS Gen: HDL Pilia et al PLoS Gen 006 Silventoinen et al, 003 Twin Research

21 Multiple drivers of difference between twin based and local-ancestry based estimates Phenotype h g h (via h ) h (via rels) HDL 0. (0.07) (0.11) 0.47, 0.48 LDL 0.16 (0.07) (0.09) 0.37 Height 0.31 (0.07) 0.55 (0.13) 0.80 If twin studies are right: Selection: Lower Fst at causals local < true Non-polygenic model.

22 Multiple drivers of difference between twin based and local-ancestry based estimates Phenotype h g h (via h ) h (via rels) HDL 0. (0.07) (0.11) 0.47, 0.48 LDL 0.16 (0.07) (0.09) 0.37 Height 0.31 (0.07) 0.55 (0.13) 0.80 If local-ancestry studies are right: Shared Environment. Significant differences between H and h : Epistasis, G-E interactions, Non-additive models

23 Outline Background Local-ancestry based heritability estimation Cross-Population Heritability

24 What do GWAS in Europeans tell us about other populations? Population 1 Population Environment Environment Phenotype Phenotype Genes Genes rs7188 P-value=3.14x10-15 OR = 1.??????????

25 Ancestral heritability estimation model A A A Individual 1 Haplotype 1 G G G Individual Haplotype 1 K Af K X K Eu Ancestral African relatedness Cross-Population relatedness Ancestral European relatedness

26 Ancestral heritability estimation model Af X Eu K Af K X K Eu Ancestral African relatedness Cross-Population relatedness Ancestral European relatedness h Af Eu Af Eu Heritability is variance explained across European and African variation. x Af Eu Cross-population genetic variation Is a function of shared genetic model. It determines how much genetic variation form European studies can be transferred into African individuals

27 Ancestral heritability estimation model Af X Eu K Af K X K Eu Ancestral African relatedness Cross-Population relatedness Ancestral European relatedness h Af Eu Af Eu Heritability is variance explained across European and African variation. x Af Eu Cross-population genetic variation Is a function of shared genetic model. It determines how much genetic variation form European studies can be transferred into African individuals

28 Ancestral Heritability Simulations 500 Individuals Ancestry Uniform( ) Ancestral MAF = 0. Fst = iterations x Af Eu 1 TRUE Observed Af X Eu e

29 Future Work Extended simulations to real data sets Examine the relationship between crosspopulations heritability and cross-population risk prediction Look for evidence of GxG and/or GxE interactions

30 Acknowledgements HSPH Alkes Price Bogdan Pasaniuc Gaurav Bhatia Samuela Pollack Peter Kraft Hugues Aschard Sasha Gusev Bjarni Vilhjalmsson HMS David Reich Sriram Sankararaman Arti Tandon Eli Stahl Ron Do UCSF Esteban Burchard Chris Gignoux Joshua Galanter WHI Hua Tang Alex Reiner Postdoctoral positions available: Broad Institute Nick Patterson Taylor Young CARe Guillaume Lettre James G Wilson Ermeg L. Akylbekova Adrienne Cupples Myriam Fornage W.H. Linda Kao Leslie A. Lange Solomon Musani George Papanicolaou Jerome I. Rotter Ingo Ruczinski David Siscovick Xiaofeng Zhu Steve McCarroll Joel Hirschhorn Sek Kathiresan CARe Analysis Core