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Towards personalized
medicine in Estonia
Erkki Leego
IT adviser
Estonian Genome Center,
University of Tartu
Biobanks
ā€¢ Biobank
ā€“ An organized collection of human biological
material and associated information stored for one
or more research purposes
ā€¢ Population biobank
ā€“ The collection has a population basis
ā€“ To supply biological materials or data derived
therefrom for multiple future research projects
ā€“ It contains biological materials and associated
personal data
Genetic research
ā€¢ Most complex diseases are caused by a large
number of combined effects from genes,
lifestyle, and the environment
ā€¢ New discoveries and development of tools
depend on studies of large collections of well-
documented, up-to-date epidemiological and
clinical data accompanied by biological
material from individuals
Estonian Biobank
ā€¢ Estonian Genome Center,
University of Tartu
ā€¢ A prospective, longitudinal,
population biobank with
health record and biological
materials
ā€¢ Established in 2000
ā€¢ 52,000 gene donors recruited
-5% of the adult population
ā€¢ Supported directly by the
government
ā€¢ Estonian Human Genes
Research Act
Population pyramid (50155 participants)
02680536080401072013400
0100200300400500600700
18
20
22
24
26
28
30
32
34
36
38
40
42
44
46
48
50
52
54
56
58
60
62
64
66
68
70
72
74
76
78
80
82
84
Count EGCUT
Age
Female
EGCUT
Estonia 2007
0 2680 5360 8040 10720 13400
0 100 200 300 400 500 600 700
18
20
22
24
26
28
30
32
34
36
38
40
42
44
46
48
50
52
54
56
58
60
62
64
66
68
70
72
74
76
78
80
82
84
Count EGCUT
Male
EGCUT
Estonia 2007
Count Estonia Count Estonia
Data ā€œinfrastructureā€ for
research
ā€¢ Good quality data collection
ā€“ Biomedical data (DNA, plasma, WBC)
ā€“ Phenotype
ā€“ Genealogy
ā€“ Epidemiology data
ā€“ Genotypes
ā€¢ Open to various research projects
ā€¢ Well defined procedures for data release
ā€¢ Usable next 30 years
Questionnaire of
EGCUT
Personal data
Place of birth
Place of residence
Nationality
Education
Occupation
Genealogy
Parents
Children
Siblings
Grandparents
Health behavior
Smoking and
alcohol
Personality
inventory NEO-
PI-3
Physical activity
EQ-5D
Nutrition
Health self-
assessment
Chronotype
questionnaire
MCTQ
Diseases
Diagnosis
ICD ā€“ 10
Treatment
ATC
Psychiatry module
M.I.N.I. and SSP
Questions about
diabetes
Questions
about c/v diseases
Objective data
Height & weight
Blood pressure
Pulse
Handedness
Waist
Hip
Diagnoses in the database
(50155 participants)
64245
8928
3106
12677
10766
11833
19918
13833
40209
60778
39490
12585
37322
21170
3352
134
1405
3202
5710
1610
619
0 10000 20000 30000 40000 50000 60000 70000
Certain Infectious And Parasitic Diseases A00-B99
Neoplasms C00-D48
Diseases Of Blood And Blood-Forming Organs And Certainā€¦
Endocrine, Nutritional And Metabolic Diseases E00-E90
Mental, Behavioural Disorders F00-F99
Diseases Of The Nervous System G00-G99
Diseases Of The Eye And Adnexa H00-H59
Diseases Of The Ear And Mastoid Process H60-H95
Diseases Of The Circulatory System I00-I99
Diseases Of The Respiratory System J00-J99
Diseases Of The Digestive System K00-K93
Diseases Of The Skin And Subcutaneous Tissue L00-L99
Diseases Of The Musculoskeletal System And Connective Tissueā€¦
Diseases Of The Genitourinary System N00-N99
Pregnancy, Childbirth And The Puerperium O00-O99
Certain Conditions Originating In The Perinatal Period P00-P96
Congenital Malformations, Deformations, And Chromosomalā€¦
Symptoms, Signs And Abnormal Clinical And Laboratory Findings,ā€¦
Injury, Poisoning And Certain Other Consequences Of Externalā€¦
Factors Influencing Health Status And Contact With Health Servicesā€¦
External Causes Of Morbidity And Mortality V01-Y98
ā€¢In average a participant has
reported 7.8 different diagnoses
ā€¢98.3% of participants have
reported at least one disease
Education: the Estonian population vs. EGCUT
(50155 participants)
0 10 20 30
Education unknown
No elementary education
Elementary education
Basic education
Secondary education
Professional secondary
education
Higher education
Scientific degree
%
Estonian population EGCUT
Using data
ā€¢ Todayā€™s focus is on Genome
Wide Association Studies
(GWAS)
ā€“ "Genetic variants in novel
pathways influence blood
pressure and cardiovascular
disease riskā€ž
ā€“ "Complement Factor H
Polymorphism in Age-Related
Macular Degeneration"
ā€“ ā€¦
ā€¢ Next focus on rich phenotype,
including health behavior and
sensor data
ā€¢ Then personalized medicine
solutions
Example. Coffee drinking habits
1: 2002-2005; 2: 2007-2008; 3: 2009-2010
Example of science project
ā€¢ Genetic map of Europe (link)
Genetic ā€žmapā€œ of Estonia
-0,03
-0,02
-0,01
0
0,01
0,02
0,03
0,04
-0,02 -0,01 0 0,01 0,02 0,03
PC2
PC1
PƵhja-Eesti
LƵuna-Eesti
PƵhja
LƵuna
Secure data handling
Courier
Filled questionnaires
Personal data, health data, genealogy data.
Consent. Transportation code.
Information encrypted.
Consent(paperform).
Biologicalsamples.
Coding center
Memory stick
Consent forms. Questionnaires.
Receptionist
New barcode
High security area Access to database
Scientists
Health data.
No identification
data.
Health data and
identification
data
National Digital Health
Record DB & registries
Operative database
Phenotype database
Data collector IS
Communication server
Laboratory IS
Cryo Preservation ā€“ MAPI
Coding center IS
Coding challenges
EXTERNAL DATABASES
data collecting
BIOSAMPLES DATA
management
PERSONAL-, GENEALOGY-,
HEALTH DATA
Formatting for integration,
deindentification
DKOOD
I U T L
I
HEALTH DATA
data collecting
I T
PHENOTYPES
integration, quality control,
analysis
U L
CODING CENTRE
H
GENOTYPES
raw data, , quality control,
analysis
U L
PROJECT-BASED RESEARCH
L
CODE RELATIONS
U D L V
genotypes, fenotypes,
biosamples, analysis
D V
BIOSAMPLES DATA
analysis
L
IKOOD UKOOD TKOOD LKOOD VKOOD
FOLLOW UP
coordination
D
FEEDBACK
PERSONALIZED MEDICINE
genotypes, fenotypes,
biosamples, analysis
DATA REALEASE
BIOSAMPLES DATA
logistics
LT
H
HKOOD
D V
D V
National Digital Health
Record DB
Online access to
database
Scientists
Health data.
No identification
data
Phenotype database
Patient Portal
National DHR
Cancer Registry
Citizen Registry
Causes of Death Registry
Participant
Participant
Participant
Participant
Participant
Participant
Participant
EGCUT database
Personal health
information
Additional
questions.
Timeline data
Updated
phenotype
data
Participant
Data
release
EGCUT IS 2011-2015
Primary care physician
...
Ver. 5.0
Public opinion and awareness of the EGCUT 2001-
2013
Illumina
Genome
Analyser
10 Gbit Network10 Gbit Network
EGCUT Network High Perfomance Computing Centre
10Gbit
Coding Centre
Infrastructure
Servers
DATABASES
Data Colletor
Phenotype Database
Laboratory IS
Infrastructure
Servers
24 Core,
192GB RAM,
1,76TB HDD
System Storage
System Storage
Tape Library
1,2PB storage
Coding
Centre IS
Analyser servers
184 Core, 2048GB RAM
Backup Server
16 Core
1,2TB HDD
24GB RAM
EGCUT servers and storage
April 2013
Ā· 15 servers
Ā· Datastorage 1,1 PB harddrives
Ā· 1,2 PB system storage tape library
MAPI
Hamilton ASM
ASM Store
ASM Server
Datastorage
with servers
1,1 PB HDD
19 2318 2217 2116 2011 159 13 10 148 123 71 5 2 6402498-B24
System x3650 M3
1 2
3 4
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
System x3650 M3
1 2
3 4
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
19 2318 2217 2116 2011 159 13 10 148 123 71 5 2 6402498-B24
Computing power
Ā· 3260 processor core
Ā· 8,2 TB RAM
Operative
Database
HPC Cluster
ā€žAurumasinā€œ
52 node,
512 Core,
2,3TB RAM,
50TB HDD
HPC Cluster
ā€žVedurā€œ
80 node,
2560 Core,
3,75TB RAM,
110TB HDD
Example of
personal genetic
information
Ref: https://www.23andme.com/you/
Risk dependence on age
ā€¢ Men ages 0-79 ā€¢ Men ages 40-49
What can I do?
Ancestery and relatives
ā€¢ Ancestery ā€¢ DNA relatives
Towards more
personalized
medicine
Calculating personal genetic
risks
Person
DNA
Personal disease
risks
Personal variants
Database of known risk markers
Conditions for feedback
ā€¢ Treatable health conditions with genetic
factors
ā€“ Melanoma
ā€“ Prostate cancer
ā€“ Type I and II Diabetes
ā€“ Lupus
ā€“ Age-Related Macular Degeneration
ā€“ Iron Overload/Hemochromatosis
Pharmacogenomics
ā€¢ How genetic makeup affects an individualā€™s
response to drugs
ā€¢ Aim is to ensure maximum efficacy with
minimal adverse effects
ā€¢ Drugs and drug combinations can be
optimized for each individual's unique genetic
makeup
ā€¢ Reduces cost of healthcare
New devices for self monitoring
ā€¢ ECG adaptor for
smartphone
ā€¢ Blood clucose sensors
ā€¢ Sleep monitoring
ā€¢ Ultrasound device Vscan
Ref: E. Topol. http://www.ted.com/talks/eric_topol_the_wireless_future_of_medicine.html
Challenges and issues
ā€¢ Awareness doctors and patients
ā€¢ New technologies and data empower patient with
more possibilities to manage own health
ā€¢ Ethical issues
ā€“ Right to know and right not to know
ā€“ Treatable and non-treatable conditions
ā€¢ Not enough knowledge about associations
between DNA variants and diseases
ā€¢ Large work-load to keep database of known risk
markers updated
Estoniaā€™s unique
starting point
Estonian E-services
ā€¢ 99% of bank
transfers are
performed
electronically
ā€¢ 94% of income tax
declarations made
via the e-Tax Board
ā€¢ 24% of votes were
cast over the
internet on 2011
ā€¢ 62% persons have
completed the e-
census 2012
ā€¢ 2000: Launch of e-Tax Board
ā€¢ 2000: Launch of m-Parking
ā€¢ 2002 : Introduction of national
electronic ID-Card
ā€¢ 2005: i-Voting was introduced
ā€¢ 2007: Introduction of m-ID
ā€¢ 2007: Launch of e-Police
system
ā€¢ 2008: Launch of e-Health
system
ā€¢ 2010: Launch of e-Prescription
ā€¢ 2012: e-census
Tools and enablers of
information exchange
ā€¢ One universal national identification code
ā€“ Registries and databases use same code to uniquely
identify persons
ā€¢ National PKI infrastructure
ā€¢ The Estonian ID card
ā€“ Smartcard with two digital certificates
ā€¢ National Data Exchange Layer X-Road
ā€¢ Obligatory national data security framework
ā€¢ High public acceptance and trust
ā€“ No public incidents or misuses (10 years)
Estonian information system
PHARMACIES AND
FAMILY DOCTORS
2009
X-Road, ID-card, State IS Service Register
HEALTHCAREBOARD
-Healthcareproviders
-Healthprofessionals
-Dispensingchemists
STATEAGENCYOFMEDICINES
-CodingCentre
-Handlersofmedicines
POPULATIONREGISTER
PHARMACIS
2010january
BUSINESSREGISTER
HOSPITALS
2009
FAMILYDOCTORS
2009
SCHOOLNURSES
2010september
EMERGENCYMEDICALSERVICE
2011
NATION- WIDE
HEALTH
INFORMATION
EXCHANGE PLATFORM
2008 december
PRESCRIPTION
CENTRE
2010 january
PATIENT PORTAL
2009
X-ROAD
GATEWAY
SERVICE
2009
The Estonian ID card
ā€¢ The ID card is a mandatory ID document for all
Estonian residents from the age of 15
ā€¢ Enables secure digital authentication and signing
ā€¢ A digital signature has the same legal
consequences as a hand-written signature
ā€¢ Does not have any additional information
ā€“ No bank account, no health information etc.
ā€¢ Active cards: 1 209 594 (13.09.2013)
ā€“ Estonian Population 1 286 540 (01.01.2013)
ā€“ Estonia has been issuing electronic ID cards from
January 1st 2002
Public Key Infrastructure PKI
ā€¢ PKI or the public key infrastructure enables
secure digital authentication and signing
ā€¢ The infrastructure also allows forwarding data
by using an encrypting key pair: a public
encryption key and a private decryption key
ā€¢ In Estonia, this technology is used in relation
with electronic identity (ID card, mobile ID,
digital ID)
ā€¢ Certification Service and Time-stamping
Service provider is non-governmetal
Data Exchange Layer X-Road
ā€¢ Technical and organizational environment,
which enables secure Internet-based data
exchange between the stateā€™s information
systems
Conclusions
ā€¢ Estonia has great potential to implement state
level personalized medicine solutions
ā€“ Genetic research with 5% of population genetic
and continuously updated phenotype information
ā€“ Nation wide Health Information Exchange platform
ā€“ 10 years of experience of national level e-services
(PKI, X-Road, ID-card, security framework)
ā€“ High level public trust and acceptance
Thank you!
Erkki Leego
www.geenivaramu.ee
Erkki.Leego@ut.ee

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Towards Personalized Medicine in Estonia

  • 1. Towards personalized medicine in Estonia Erkki Leego IT adviser Estonian Genome Center, University of Tartu
  • 2. Biobanks ā€¢ Biobank ā€“ An organized collection of human biological material and associated information stored for one or more research purposes ā€¢ Population biobank ā€“ The collection has a population basis ā€“ To supply biological materials or data derived therefrom for multiple future research projects ā€“ It contains biological materials and associated personal data
  • 3. Genetic research ā€¢ Most complex diseases are caused by a large number of combined effects from genes, lifestyle, and the environment ā€¢ New discoveries and development of tools depend on studies of large collections of well- documented, up-to-date epidemiological and clinical data accompanied by biological material from individuals
  • 4. Estonian Biobank ā€¢ Estonian Genome Center, University of Tartu ā€¢ A prospective, longitudinal, population biobank with health record and biological materials ā€¢ Established in 2000 ā€¢ 52,000 gene donors recruited -5% of the adult population ā€¢ Supported directly by the government ā€¢ Estonian Human Genes Research Act
  • 5. Population pyramid (50155 participants) 02680536080401072013400 0100200300400500600700 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64 66 68 70 72 74 76 78 80 82 84 Count EGCUT Age Female EGCUT Estonia 2007 0 2680 5360 8040 10720 13400 0 100 200 300 400 500 600 700 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64 66 68 70 72 74 76 78 80 82 84 Count EGCUT Male EGCUT Estonia 2007 Count Estonia Count Estonia
  • 6. Data ā€œinfrastructureā€ for research ā€¢ Good quality data collection ā€“ Biomedical data (DNA, plasma, WBC) ā€“ Phenotype ā€“ Genealogy ā€“ Epidemiology data ā€“ Genotypes ā€¢ Open to various research projects ā€¢ Well defined procedures for data release ā€¢ Usable next 30 years
  • 7. Questionnaire of EGCUT Personal data Place of birth Place of residence Nationality Education Occupation Genealogy Parents Children Siblings Grandparents Health behavior Smoking and alcohol Personality inventory NEO- PI-3 Physical activity EQ-5D Nutrition Health self- assessment Chronotype questionnaire MCTQ Diseases Diagnosis ICD ā€“ 10 Treatment ATC Psychiatry module M.I.N.I. and SSP Questions about diabetes Questions about c/v diseases Objective data Height & weight Blood pressure Pulse Handedness Waist Hip
  • 8. Diagnoses in the database (50155 participants) 64245 8928 3106 12677 10766 11833 19918 13833 40209 60778 39490 12585 37322 21170 3352 134 1405 3202 5710 1610 619 0 10000 20000 30000 40000 50000 60000 70000 Certain Infectious And Parasitic Diseases A00-B99 Neoplasms C00-D48 Diseases Of Blood And Blood-Forming Organs And Certainā€¦ Endocrine, Nutritional And Metabolic Diseases E00-E90 Mental, Behavioural Disorders F00-F99 Diseases Of The Nervous System G00-G99 Diseases Of The Eye And Adnexa H00-H59 Diseases Of The Ear And Mastoid Process H60-H95 Diseases Of The Circulatory System I00-I99 Diseases Of The Respiratory System J00-J99 Diseases Of The Digestive System K00-K93 Diseases Of The Skin And Subcutaneous Tissue L00-L99 Diseases Of The Musculoskeletal System And Connective Tissueā€¦ Diseases Of The Genitourinary System N00-N99 Pregnancy, Childbirth And The Puerperium O00-O99 Certain Conditions Originating In The Perinatal Period P00-P96 Congenital Malformations, Deformations, And Chromosomalā€¦ Symptoms, Signs And Abnormal Clinical And Laboratory Findings,ā€¦ Injury, Poisoning And Certain Other Consequences Of Externalā€¦ Factors Influencing Health Status And Contact With Health Servicesā€¦ External Causes Of Morbidity And Mortality V01-Y98 ā€¢In average a participant has reported 7.8 different diagnoses ā€¢98.3% of participants have reported at least one disease
  • 9. Education: the Estonian population vs. EGCUT (50155 participants) 0 10 20 30 Education unknown No elementary education Elementary education Basic education Secondary education Professional secondary education Higher education Scientific degree % Estonian population EGCUT
  • 10. Using data ā€¢ Todayā€™s focus is on Genome Wide Association Studies (GWAS) ā€“ "Genetic variants in novel pathways influence blood pressure and cardiovascular disease riskā€ž ā€“ "Complement Factor H Polymorphism in Age-Related Macular Degeneration" ā€“ ā€¦ ā€¢ Next focus on rich phenotype, including health behavior and sensor data ā€¢ Then personalized medicine solutions
  • 11. Example. Coffee drinking habits 1: 2002-2005; 2: 2007-2008; 3: 2009-2010
  • 12. Example of science project ā€¢ Genetic map of Europe (link)
  • 13. Genetic ā€žmapā€œ of Estonia -0,03 -0,02 -0,01 0 0,01 0,02 0,03 0,04 -0,02 -0,01 0 0,01 0,02 0,03 PC2 PC1 PƵhja-Eesti LƵuna-Eesti PƵhja LƵuna
  • 14. Secure data handling Courier Filled questionnaires Personal data, health data, genealogy data. Consent. Transportation code. Information encrypted. Consent(paperform). Biologicalsamples. Coding center Memory stick Consent forms. Questionnaires. Receptionist New barcode High security area Access to database Scientists Health data. No identification data. Health data and identification data National Digital Health Record DB & registries Operative database Phenotype database Data collector IS Communication server Laboratory IS Cryo Preservation ā€“ MAPI Coding center IS
  • 15. Coding challenges EXTERNAL DATABASES data collecting BIOSAMPLES DATA management PERSONAL-, GENEALOGY-, HEALTH DATA Formatting for integration, deindentification DKOOD I U T L I HEALTH DATA data collecting I T PHENOTYPES integration, quality control, analysis U L CODING CENTRE H GENOTYPES raw data, , quality control, analysis U L PROJECT-BASED RESEARCH L CODE RELATIONS U D L V genotypes, fenotypes, biosamples, analysis D V BIOSAMPLES DATA analysis L IKOOD UKOOD TKOOD LKOOD VKOOD FOLLOW UP coordination D FEEDBACK PERSONALIZED MEDICINE genotypes, fenotypes, biosamples, analysis DATA REALEASE BIOSAMPLES DATA logistics LT H HKOOD D V D V
  • 16. National Digital Health Record DB Online access to database Scientists Health data. No identification data Phenotype database Patient Portal National DHR Cancer Registry Citizen Registry Causes of Death Registry Participant Participant Participant Participant Participant Participant Participant EGCUT database Personal health information Additional questions. Timeline data Updated phenotype data Participant Data release EGCUT IS 2011-2015 Primary care physician ... Ver. 5.0
  • 17. Public opinion and awareness of the EGCUT 2001- 2013
  • 18. Illumina Genome Analyser 10 Gbit Network10 Gbit Network EGCUT Network High Perfomance Computing Centre 10Gbit Coding Centre Infrastructure Servers DATABASES Data Colletor Phenotype Database Laboratory IS Infrastructure Servers 24 Core, 192GB RAM, 1,76TB HDD System Storage System Storage Tape Library 1,2PB storage Coding Centre IS Analyser servers 184 Core, 2048GB RAM Backup Server 16 Core 1,2TB HDD 24GB RAM EGCUT servers and storage April 2013 Ā· 15 servers Ā· Datastorage 1,1 PB harddrives Ā· 1,2 PB system storage tape library MAPI Hamilton ASM ASM Store ASM Server Datastorage with servers 1,1 PB HDD 19 2318 2217 2116 2011 159 13 10 148 123 71 5 2 6402498-B24 System x3650 M3 1 2 3 4 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 System x3650 M3 1 2 3 4 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 19 2318 2217 2116 2011 159 13 10 148 123 71 5 2 6402498-B24 Computing power Ā· 3260 processor core Ā· 8,2 TB RAM Operative Database HPC Cluster ā€žAurumasinā€œ 52 node, 512 Core, 2,3TB RAM, 50TB HDD HPC Cluster ā€žVedurā€œ 80 node, 2560 Core, 3,75TB RAM, 110TB HDD
  • 19. Example of personal genetic information Ref: https://www.23andme.com/you/
  • 20.
  • 21. Risk dependence on age ā€¢ Men ages 0-79 ā€¢ Men ages 40-49
  • 22. What can I do?
  • 23. Ancestery and relatives ā€¢ Ancestery ā€¢ DNA relatives
  • 25. Calculating personal genetic risks Person DNA Personal disease risks Personal variants Database of known risk markers
  • 26. Conditions for feedback ā€¢ Treatable health conditions with genetic factors ā€“ Melanoma ā€“ Prostate cancer ā€“ Type I and II Diabetes ā€“ Lupus ā€“ Age-Related Macular Degeneration ā€“ Iron Overload/Hemochromatosis
  • 27. Pharmacogenomics ā€¢ How genetic makeup affects an individualā€™s response to drugs ā€¢ Aim is to ensure maximum efficacy with minimal adverse effects ā€¢ Drugs and drug combinations can be optimized for each individual's unique genetic makeup ā€¢ Reduces cost of healthcare
  • 28. New devices for self monitoring ā€¢ ECG adaptor for smartphone ā€¢ Blood clucose sensors ā€¢ Sleep monitoring ā€¢ Ultrasound device Vscan Ref: E. Topol. http://www.ted.com/talks/eric_topol_the_wireless_future_of_medicine.html
  • 29. Challenges and issues ā€¢ Awareness doctors and patients ā€¢ New technologies and data empower patient with more possibilities to manage own health ā€¢ Ethical issues ā€“ Right to know and right not to know ā€“ Treatable and non-treatable conditions ā€¢ Not enough knowledge about associations between DNA variants and diseases ā€¢ Large work-load to keep database of known risk markers updated
  • 31. Estonian E-services ā€¢ 99% of bank transfers are performed electronically ā€¢ 94% of income tax declarations made via the e-Tax Board ā€¢ 24% of votes were cast over the internet on 2011 ā€¢ 62% persons have completed the e- census 2012 ā€¢ 2000: Launch of e-Tax Board ā€¢ 2000: Launch of m-Parking ā€¢ 2002 : Introduction of national electronic ID-Card ā€¢ 2005: i-Voting was introduced ā€¢ 2007: Introduction of m-ID ā€¢ 2007: Launch of e-Police system ā€¢ 2008: Launch of e-Health system ā€¢ 2010: Launch of e-Prescription ā€¢ 2012: e-census
  • 32. Tools and enablers of information exchange ā€¢ One universal national identification code ā€“ Registries and databases use same code to uniquely identify persons ā€¢ National PKI infrastructure ā€¢ The Estonian ID card ā€“ Smartcard with two digital certificates ā€¢ National Data Exchange Layer X-Road ā€¢ Obligatory national data security framework ā€¢ High public acceptance and trust ā€“ No public incidents or misuses (10 years)
  • 34. PHARMACIES AND FAMILY DOCTORS 2009 X-Road, ID-card, State IS Service Register HEALTHCAREBOARD -Healthcareproviders -Healthprofessionals -Dispensingchemists STATEAGENCYOFMEDICINES -CodingCentre -Handlersofmedicines POPULATIONREGISTER PHARMACIS 2010january BUSINESSREGISTER HOSPITALS 2009 FAMILYDOCTORS 2009 SCHOOLNURSES 2010september EMERGENCYMEDICALSERVICE 2011 NATION- WIDE HEALTH INFORMATION EXCHANGE PLATFORM 2008 december PRESCRIPTION CENTRE 2010 january PATIENT PORTAL 2009 X-ROAD GATEWAY SERVICE 2009
  • 35. The Estonian ID card ā€¢ The ID card is a mandatory ID document for all Estonian residents from the age of 15 ā€¢ Enables secure digital authentication and signing ā€¢ A digital signature has the same legal consequences as a hand-written signature ā€¢ Does not have any additional information ā€“ No bank account, no health information etc. ā€¢ Active cards: 1 209 594 (13.09.2013) ā€“ Estonian Population 1 286 540 (01.01.2013) ā€“ Estonia has been issuing electronic ID cards from January 1st 2002
  • 36. Public Key Infrastructure PKI ā€¢ PKI or the public key infrastructure enables secure digital authentication and signing ā€¢ The infrastructure also allows forwarding data by using an encrypting key pair: a public encryption key and a private decryption key ā€¢ In Estonia, this technology is used in relation with electronic identity (ID card, mobile ID, digital ID) ā€¢ Certification Service and Time-stamping Service provider is non-governmetal
  • 37. Data Exchange Layer X-Road ā€¢ Technical and organizational environment, which enables secure Internet-based data exchange between the stateā€™s information systems
  • 38. Conclusions ā€¢ Estonia has great potential to implement state level personalized medicine solutions ā€“ Genetic research with 5% of population genetic and continuously updated phenotype information ā€“ Nation wide Health Information Exchange platform ā€“ 10 years of experience of national level e-services (PKI, X-Road, ID-card, security framework) ā€“ High level public trust and acceptance

Editor's Notes

  1. Most complex diseases do not stem from a single genetic defect, but are caused by a large number of effects from genetic predisposition, lifestyle, and the environmentThese studies are necessary to work towards improvement of quality of life, more precise disease diagnostics to make progress in personalized medicine.
  2. The following illustrative analyses are made based on the data of 50 155 individuals.
  3. 52,000 participants withhealth dataContinuously being updated through follow-up projects and linking to national health registriesOver 1 millionbiologicalsamplesļ¾ 20,000 participants are genotypedwithIlluminamicroarrays120 fullgenomesplus 100 exomes are sequencedNumbersincreasecontinuously
  4. This slide shows the main subsets of the questionnaire. Besidesthe comprehensive health records and objective data alsothe DNA, plasma and WBC samples of each gene donor are deposited in the biobank. 30-50 ml of venous blood are obtained into EDTA Vacutainers which are transported to the central laboratory of EGCUT at +4-6 C within the next 6 to 48h where DNA, plasma and WBC are immediately isolated and kept in aliquots in MAPI straws in liquid N2 for further use.NEO-PI-R TheRevised NEO PersonalityInventory (neopi ai aar)Anatomical Therapeutic Chemical (ATC) Classification System MCTQ Munichchronotypequestionnaire.EQ-5Dā„¢ is a standardised instrument for use as a measure of health outcome.The Mini-International NeuropsychiatricInterview (M.I.N.I.) , SSP SwedishUniversitiesScalesofPersonality
  5. In this section of questionnaire, questions about all diseases the donor may suffer will be asked. 45 000 GD andmed: 1.3% (599) of gene donors have confirmed that they donā€™t have any diseases. 0.4% (167) of donors are neither aware of the diseases he/she might have and nor confirm not having it. 98.3% of individuals have suffered or suffers from different diseases. Altogether, 44 354 GDs have 344Ā 187 diagnoses, in average 7.8 diagnoses per donor.In average, a GD hasreported ca 8 different diagnoses. Mostfrequently infectious diseases, diseases of respiratory system and circulatory system are mentioned.
  6. Several essential changes occurred in the education of Estonia since the 20s and till the end of the last century. The duration of programs, names and contents of levels of study changed. They were divided according to the detailed classification of educational sublevels as follows:higher educationprofessional secondary education after secondary educationprofessional secondary education after basic educationvocational secondary education after secondary educationvocational secondary educationgeneral secondary educationbasic educationelementary educationno elementary educationAmong GDs, there are more individuals with higher (18%) and professional secondary (33.3%) education. Fewer individuals have elementary (15.8%) and no elementary (2.8%) education. In the whole population, there are more females with higher and more males with elementary education. The same ratio is represented among GDsAnaveragegenedonorisquitewell-educated and has at leastgraduatedfromhighschool (gymnasium) orvocationalschool.
  7. Erinevaid haiguseid on enam kui 12 000, samas kindlaid seoseid DNA mustrite ja haiguste vahel teada veel suhteliselt vƤhe.
  8. Projekti ENGAGE raamesEesti doonoreid 1026
  9. Ongoing linking on a regular basisMedical registries (Causes of Death, Cancer, TBC, Population Register) 2372 participants have died as of August 2013 Linking approved by the Ethics Committee and the Data Protection InspectionEstonian e-health database Estonian Health Insurance Fund databaseinc. digital prescriptions database Databases of the two largest 3rd level hospitals (currently we have two: Tartu University Hospital and North Estonia Medical Centre in Tallinn) Estonia has good solutions to update phenotype data from various national registriries and databases.Additionally is EGCUT actively collecting additional information from previously recruited participants.In 2013 there will be first solutions to feedback personal health information (primarly related to genetic information) to patient and primary care physicians.
  10. Personalized medicineĀ orĀ PMĀ is aĀ medical modelĀ that proposes the customization of healthcare - with medical decisions, practices, and/or products being tailored to the individual patient. The use of genetic information has played a major role in certain aspects of personalized medicine, and the term was even first coined in the context of genetics (though it has since broadened to encompass all sorts of personalization measures). To distinguish from the sense in which medicine has always been inherently "personal" to each patient,Ā PMĀ commonly denotes the use of some kind of technology or discovery enabling a level of personalization not previously feasible or practical.
  11. Electrocardiography (ECG or EKG from Greek: kardia, meaning heart) is a transthoracic (across the thorax or chest) interpretation of the electrical activity of the heart over a period of time, as detected by electrodes attached to the surface of the skin and recorded by a device external to the body.[1] The recording produced by this noninvasive procedure is termed an electrocardiogram (also ECG or EKG).