1. The Nest Generation in Personalized Medicine Discoveries: New methods and new populations
Chris Gignoux
Colorado Center for Personalized Medicine
Department of Biostatistics and Informatics
University of Colorado, Anschutz Medical Campus
@popgenepi

2. Background
Genetics has paved the way forward to large-scale personalized medicine
Genome-wide data is:
Cheap
Bioinformatically simple
Applicable across a broad range of traits, from Mendelian to complex
Current landscape: > 1/1000 people worldwide has genome-wide data
Ancestry, 23andMe
Health Systems (Geisinger, Colorado, UK NHS)

3. Human Genetic History
Henn, Cavalli-Sforza, Feldman, PNAS 2012

4. Human Genetic History is Complex!
And has changed dramatically recently:
Henn, Cavalli-Sforza, Feldman, PNAS 2012

5. Background
Disease or traits are largely influenced by a subset of sites
Even in an omnigenic model
Ancestry influences all sites on the genome
Genetics tells us about both

6. Discussion lately, improvement, but not quite there.

7. Precision Medicine shares this same danger!
Discussion lately, improvement, but not quite there.

8. Courtesy Alicia Martin, ATGU MGH

9. Courtesy Alicia Martin, ATGU MGH

10. Alicia Martin, ATGU MGH

11. Alicia Martin, ATGU MGH

12. Polygenic risks across populations
Trans-ethnic polygenic risk in complex traits
Simulate based on inferred population history:
Gravel et al, PNAS 2011

13. Alicia Martin, ATGU MGH

14. Alicia Martin, ATGU MGH

15. Polygenic risks across populations
Trans-ethnic polygenic risk in complex traits are unpredictably biased when ascertained in a single population
Coalescent-based simulation of polygenic architecture
Martin et al, AJHG 2017

16. Genomic prediction improves with sample size, albeit slowly…
Wray et al. Nat Rev Genet 2013

17. Genomic prediction improves with sample size, albeit slowly…
*this is for one population
Wray et al. Nat Rev Genet 2013

18. Today Investigating common diseases in diverse populations
Gaining a better understanding of architecture in complex traits
New methods to leverage existing data for improved power for discovery