Estonian Biobank- from basic
research to public health
Tõnu Esko
Deputy Director of Research – Estonian Genome Center, University of Tartu
Visiting Reserach Fellow – Broad Institute of MIT and Harvard, USA
[email protected]
Estonian Biobank
• Prospective, longitudinal, volunteer-based
• 52,000 participants - 5% of the adult
population of Estonia
• Health records, diet, physical activity, etc.
• DNA, plasma and cell samples
• Estonian Human Genes Research Act
• Broad informed consent
• Open for research: Clear access rules
Legal background
HumanGenomeResearchAct(HGRA)
• ApprovedbyGovernmentonAug8,2000
• PassedbyParliamentonDec13,2000(42yes,3no)
• EnforcesinceJanuary08,2001
HGRAregulates
• scienGficresearchonhumangeneGcs
• theestablishmentandmaintenanceoftheBiobank
• theuseofgeneGcinformaGon(informedconsent,basedonprincipleof
openconsent)
HGRAprotects
• theconfidenGalityofgenedonor
• thepublicfromthemisuseofgeneGcinformaGon
• thegenedonorfromgeneGcdiscriminaGon
Diagnoses in database – 380,000
Estonia’suniquestar8ngpoint
Estonian E-services
• MandatoryIDdocumentforallEstonianresidents
• EnablessecuredigitalauthenGcaGonandsigning
• AcGvecards:1209594(95%ofciGzens)[13Sept2013]
X-Road, ID-card, State IS Service Register
PATIENT
PORTAL
2009
X-ROAD
GATEWAY
SERVICE
2009
PHARMACIES
AND FAMILY
DOCTORS
2009
NATION- WIDE
HEALTH
INFORMATION
EXCHANGE PLATFORM
2008 december
PRESCRIPTION
CENTRE
2010 january
EMERGENCY MEDICAL SERVICE
2011
SCHOOL NURSES
2010 september
PHARMACIeS
2010 january
FAMILY DOCTORS
2009
HOSPITALS
2009
BUSINESS REGISTER
POPULATION REGISTER
HEALTH CARE BOARD
- Health care providers
- Health professionals
- Dispensing chemists
- Coding Centre
- Handlers of medicines
• ElectonicHealthInforma7onSystem
STATE AGENCY OF MEDICINES
• Publice-services
From questionnaires to the national registries
Registries
Hospitals
Health Insurance
Coding center High security area.
Data collector:
baseline phenotype data
The broad informed consent.
Phenotype data
Phenotype database
Timeline: linking to registries
Pop
reg
Pop
Reg
Pop
reg
Pop
reg
10/2011 4/2012
03/2010 11/2010
Pop
reg
Pop
reg
1/2013
3/2014
Death
Reg
Death
Reg
Death
Reg
Death
Reg
Death
Reg
Death
Reg
9/2010
5/2011
1/2012
12/2012 8/2013
6/2014
NDHRD HIF
2/2014 6/2014
2002
2007
2008
2009
2010
2011
2012
2013
Cancer
Reg
Cancer
Reg
12/2010
6/2012
University NorthEstonia
MedicalCenter
Hospital
8/2013
Tub
Reg
12/2012
Baseline
2014
5/2014
MI
Reg
2/2014
2ndvisit
01/2002-31/2010
1/2011-6/2014
Electronicfollow-up
1/2003-...
8
Cancer Registry
Disease trajectories
• Diagnoseddiseases
K85&
P15.9&
• HealthInsurancebills
Agreement&
Z25.1&
J06.9&
J45.1&
E84.8_2&
G25.2_2&
J18.9&
J20&
J15.9&
R73.9&
J30.4&
K73.9&
K02.9&
F06.32&
G47.9&
Z02&
M06.9&
F84.8&
K04.0&F33.1&
H66.9&
D22.5&
S60.0&
H91.9&
W01.41&
K74&
B00.9&
F43.21&
K21.9&
B33&
2013%
2012%
2011%
2010%
2009%
2008%
2007%
2006%
2005%
2004%
2003%
2002%
2001%
2000%
1999%
1998%
1997%
1996%
1995%
1994%
1993%
1992%
1991%
1990%
1989%
1988%
1987%
1986%
Z11.3&
• ClinicalLabsmeasures
• E-HealthEHRsummaries
Male,#born#1986#
90.00#
400.00#
ALAT$
80.00#
ASAT$
CRP$
ALP$
350.00#
70.00#
300.00#
200.00#
40.00#
150.00#
30.00#
100.00#
20.00#
50.00#
3/2/14#
11/22/13#
8/14/13#
5/6/13#
1/26/13#
10/18/12#
7/10/12#
4/1/12#
12/23/11#
9/14/11#
6/6/11#
2/26/11#
11/18/10#
8/10/10#
5/2/10#
1/22/10#
10/14/09#
7/6/09#
3/28/09#
12/18/08#
9/9/08#
6/1/08#
2/22/08#
11/14/07#
8/6/07#
0.00#
4/28/07#
10.00#
0.00#
ALP$
250.00#
50.00#
1/18/07#
ALAT,$ASAT,$CRP$
60.00#
National EHR – eHealth
What tools & data in each process
generates
DS Engine
(executes rules)
Patient
Application
DS
report
Tools for data gathering, extracting, harmonizing, consolidating
X-Road
Rules
Consents
Genomic data
DNA
Cancer
tissue
DNA
Other
-omics
(e.g virus
RNA)
Hospital
IS
Phenotype data
Registries
DS
reports
Health
declarations
Prescriptions
Lab
results
ENHIS
epicrises
Tools for pseudonymization and data gathering
(R&D of) tools for data extracting, harmonizing, linking,
consolidating, mining, designing new rules etc.
Patient
Portal
are available via
Was the DS report
being used and how?
Report
tracking service
Clinician’s decision,
treatment of the
patient
Clinical trajectory – eHealth
What tools & data in each process
generates
DS Engine
(executes rules)
Patient
Application
DS
report
X-Road
Rules
Tools for data gathering, extracting, harmonizing, consolidating
Consents
Genomic data
DNA
Cancer
tissue
DNA
Other
-omics
(e.g virus
RNA)
Hospital
IS
Phenotype data
Registries
Health
declarations
Prescriptions
Lab
results
Patient
Portal
DS
reports
are available via
ENHIS
epicrises
Tools for pseudonymization and data gathering
(R&D of) tools for data extracting, harmonizing, linking,
consolidating, mining, designing new rules etc.
Tarkvara TAK (STACC)
Was the DS report
being used and how?
Report
tracking service
Clinician’s decision,
treatment of the
patient
Dataforresearch
• Ques7onnaireandelectronic
healthrecords
Na0onal(
Health(
Insurance(DB(
Omics(profiles(
Research(
>99%%
>99%%
Na0onal(
Medical(
Imaging(DB(
>99%%
Na0onal(
Cancer(Registry(
Na0onal(Health(
Insurance(DB(
Estonian(Biobank(
Baseline(
quess0onnaire(
52,000%%
Causes(of(
Death(Registry(
Hospitals(
electronic(
records(
75%+%
Na0onal(
Electronic(
Health(Records(
75%%
• Omicsprofiles
Method
Sample
Whole&genome*sequencing*(30X|PCRfree)
Exome*sequencing*(on&going)
Genome&wide*genotyping*arrays
Genome&wide*methylaGon*arrays
Genome&wide*expression*arrays
mRNA*sequencing*(on&going)
Total*RNA*sequencing
Metabolomics*(NMR)
Metabolomics*(MS/MS)
Telomere*length
Clinical*biochemistry*
Glycomics*(IgG)*
2,500
2,500
20,000
500
1,100
800
50
11*000
1,100
5,200
2,700*
1,000*
Personal risks
Age
Genetics risk
Geneetiline
Environment, lifestyle, comorbidities
Vanus
Disease
!!!! !
Age
Knownriskfactorsformanycommoncomplex
diseases
•
•
•
•
•
•
BMI
AlreadyexisGngdiseases
Familyhistory
AlcoholconsumGon
Smoking
Biomarkers
Chow et al 2015
Genetic risk for heart attacks
CAD genetic risk score quintiles in cases of premature
CVD mortality vs 85+ CAD-free individuals
CAD GRS
30
Proportion (%)
25
20
Lowest
genetic
risk score
quintile
(<20%)
madalaim
geneetilise
riski kvintiil
(<20%)
20-40%
40-60%
60-80%
kõrgeim
kvintiil
(>80%)
Highest geneetilise
genetic riskriski
score
quintile
(>80%)
15
10
5
0
CVD death 30-69
CAD-free
85+
OR=4.4, p=2.3*10-10
(highest vs lowest quintile)
Beyond evidence-based medicine
