Senior Director Meg Ehm, Human Genetics at GSK, at Genomics to Healthcare EU side event, 13 Sept 2019, THL, Helsinki

1. Fueling a genetics-
driven R&D
organization
Genomics to Healthcare
Helsinki, Finland
September 13, 2019
Meg Ehm
Senior Director,
Human Genetics

3. Drug Target Identification
3
DiseaseTarget
Mechanism
Molecule
G B D
C

4. Drugs with human genetic evidence >2x more likely to be successful
DiMasi JA et al. (2016) J Health Econ 47:20-33; Nelson et al. (2015) Nat Genet 47:846-60
The drug discovery dilemma
4

5. Our new approach to R&D
5
Science TechnologyX X Culture
= Next generation of medicines for patients
Human genetics
Functional genomics
Machine learning
“Shift our research and
development organization
to be ‘driven by genetics’”

6. What do we mean by genetic evidence?
Step 1: Measure genetic differences among people
DNA
Gene X
GCTATCAGTACT
ExonsIntrons
T
Single Nucleotide Polymorphism (SNP)

7. What do we mean by genetic evidence?
Step 2: Test relationship between genetic and phenotypic
differences
Figure modified from yourgenome.org
Genetic Association Analysis
Cases (n = 50,000)
People with asthma
Controls (n = 250,000)
People without asthma

8. What do we mean by genetic evidence?
Step 3: Repeat… over and over again
– Whole exome or genome
sequencing
– Virtually all genetic variants
– Modern genotyping panels can
measure
– >500,000 variants → Impute
>20M variants
– Genome-wide association studies
(GWAS) test them all

9. What do we mean by genetic evidence?
Step 4: Map significant associations to genes
Association of IL33 with asthma in UK Biobank
9
Genome-wide association studies
(GWAS) can yield tremendous insights
into the genes that influence disease
And suggest or prioritize fruitful drug targets

10. Sources of genetic evidence
12
Primary Sources
Pre-2018
New
Opportunities
Limited
DiseaseTarget
Mechanism
Molecule
G B D
C
Cross-biobank
Research
Pharma
Clinical Trials
Collaboration
Public
Databases
Other RWD-
linked data

11. Linkage of numerous data sources facilitates broad phenotypic exploration
UK Biobank – Unprecedented resource with 500K participants
13
Current
Data
Future
Data
Self-report
Data
Biomarkers
Imaging
Hospital Episode
Statistics (HES)
Death Registry
Genotype Data
(N=500,000)
Physical
Assessment
Adjudicated case
data (eg. Stroke,
MI)
Additional
assessments
Exome Sequencing
Whole Genome
Sequencing
‘Omics
Primary care
(GP) data
2019, 2020
Partial
2019?
Stroke/MI
2017 Q1
Unknown

12. GWAS Significance Threshold PheWAS Significance Threshold
Osteoporosis
IBS
Migraine
Angina
Back pain
Osteoarthritis
Asthma
UK Biobank UK Biobank
Assumptions
UKB case #s
MAF = 0.05, OR = 1.1
P = 5e-8 and 1e-4
Broad discovery power in population samples requires
very large numbers

13. – FinnGen is a consortium with 10 Finnish biobanks; access to
500K (by 2023)
– Whole genome data linked with Finnish registry information
– Collaboration with top tier geneticists: Aarno Palotie and Mark Daly
– Enables investigation of genetic effects on clinical endpoints
further informing clinical validity of discoveries made in other data
sources
– Provides Finnish-enriched variants for some genes
– Enables recall of participants by genetic or trait information
– Enables analysis of Nordic healthcare data with extensive and
long term record linkage.
– Enables collaboration with Finnish clinicians and epidemiologists
with years of experience.
https://www.finngen.fi/en
FinnGen Pharmaceutical Consortium

14. Finnish bottleneck boosts the frequency of a
subset of high impact variants
– Population history of Finland has lead to a bottleneck
– Reduction in variation overall but some variants will have a
high frequency
– Risk effects
– Tens of Mendelian diseases
– AKT2 knockouts ↑insulin level and ↑T2D risk
– TOP3B and SETD1A in schizophrenia and learning
disabilities
– Protective effects
– Knockouts of SLC30A8  T2D risk ↓ by 65%
– Knockouts of LPA  CAD risk ↓ by 20%
– RNF186 truncating variant with ulcerative colitis risk ↓ by
70%
POPULATION
ISOLATE
0
5000
10000
15000
0.1 1.0 10.0 100.0
Numberofvariants
●●
●
●
●
●
●
1.8
2.0
eleterious/
onymousratio
Variants in
both populations
“Enriched” variants

15. – UK Biobank analysis:
– Variant (rs28991009-MAF = 0.8%) significantly lowers IOP and is associated with a 34% reduced
risk of glaucoma.
– FinnGen analysis:
– Variant (rs147660927; MAF = 4.1%) is associated with 30% lower glaucoma risk
Rare protein-altering variants in ANGPTL7 lower
intraocular pressure (IOP) and protect against glaucoma

16. Rare protein-altering variants in ANGPTL7 lower
intraocular pressure (IOP) and protect against glaucoma
– PheWAS of R220C did not find any severe medical consequences

17. Order Spit Send Discover

18. 2008 2010 2012 2014 2016 2018 2019
1M
Kits Sold
10 M
Kits Sold
Customer growth is accelerating
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European73%
Latino12%
African American4%
East Asian and
South Asian
4%
Other7%
80%
consent to
research
2.5B+
survey
questions
answered

19. Data Resource Characteristics
Criteria/
Resources
Health information Family history,
ongoing surveys
Family history, baseline
assessment, HES, imaging,
biomarkers, death & cancer
registries
HES, disease registries, national
medicine reimbursement, cause of
death, surgical & population
registries
Genetic information GWAS GWAS, exome sequencing GWAS (potentially FFPE, RNA)
Sample Size 8.5M+ genotypes 500K 150K
(up to 500K)
Disease Representation Overall health
assessment
Overall health assessment Overall health assessment
Resurvey/
Recall
Resurvey & some
recall
Limited resurvey & recall Recall
Population description US, outbred UK, outbred Bottled necked European
Distinguishing feature Size & ability to survey Baseline assessment and
biomarkers
Finnish enriched variants, recall,
access to medication info
HES-hospital episode statistics
GWAS-Genome Wide Association Scan

20. The discovery of genetic contributions to complex traits
is just getting started
22
Case/Control & Anthropometrics Subtypes & Trajectories

21. Insert your date / confidentiality text here16x9 core template 23

22. Special thanks
24
Laura Yerges-
Armstrong
Dawn Waterworth Matt Nelson Robert Scott Jonathan Davitte Kirsi Auro Sam St Laurent