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